From 90a81a1cb485c5be65594a3b992e75c8a9dd4509 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Fri, 29 Mar 2024 14:19:33 -0300 Subject: [PATCH 001/229] Fix unique constraints for id column (#1584) Fix unique constraints for id column (#1583) * Fix unique constraints for id column * Update version in pyproject.toml --- poetry.lock | 971 +++++++++--------- pyproject.toml | 3 +- .../006b3990db50_add_unique_constraints.py | 12 +- 3 files changed, 505 insertions(+), 481 deletions(-) diff --git a/poetry.lock b/poetry.lock index e5b91c6b8..f6dd53297 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. [[package]] name = "aiohttp" @@ -224,13 +224,13 @@ files = [ [[package]] name = "asgiref" -version = "3.8.0" +version = "3.8.1" description = "ASGI specs, helper code, and adapters" optional = false python-versions = ">=3.8" files = [ - {file = "asgiref-3.8.0-py3-none-any.whl", hash = "sha256:30fc07797ad71a0abb8fe34aa03c8043308a8389abc7942d797ea9911540bc28"}, - {file = "asgiref-3.8.0.tar.gz", hash = "sha256:ec75d9d0f04e2dbfedef1f20ee73a6594af80c333df47cdd31f37e6701f7c53a"}, + {file = "asgiref-3.8.1-py3-none-any.whl", hash = "sha256:3e1e3ecc849832fe52ccf2cb6686b7a55f82bb1d6aee72a58826471390335e47"}, + {file = "asgiref-3.8.1.tar.gz", hash = "sha256:c343bd80a0bec947a9860adb4c432ffa7db769836c64238fc34bdc3fec84d590"}, ] [package.dependencies] @@ -314,13 +314,13 @@ files = [ [[package]] name = "bce-python-sdk" -version = "0.9.5" +version = "0.9.6" description = "BCE SDK for python" optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, <4" +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,<4,>=2.7" files = [ - 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{file = "botocore-1.34.68-py3-none-any.whl", hash = "sha256:3ad0ec67f78beecc039c3c31c93a83181e30b6f789261bdbb9f5c8e8dc551812"}, - {file = "botocore-1.34.68.tar.gz", hash = "sha256:e7ae9d69cc3e7b31d926e6a1a9ae673ba02da263e35cf12ff2bae35a21755cc6"}, + {file = "botocore-1.34.73-py3-none-any.whl", hash = "sha256:88d660b711cc5b5b049e15d547cb09526f86e48c15b78dacad78522109502b91"}, + {file = "botocore-1.34.73.tar.gz", hash = "sha256:8df020b6682b9f1e9ee7b0554d5d0c14b7b23e3de070c85bcdf07fb20bfe4e2b"}, ] [package.dependencies] @@ -540,26 +540,27 @@ files = [ [[package]] name = "build" -version = "1.1.1" +version = "1.2.1" description = "A simple, correct Python build frontend" optional = false -python-versions = ">= 3.7" +python-versions = ">=3.8" files = [ - {file = "build-1.1.1-py3-none-any.whl", hash = "sha256:8ed0851ee76e6e38adce47e4bee3b51c771d86c64cf578d0c2245567ee200e73"}, - {file = "build-1.1.1.tar.gz", hash = "sha256:8eea65bb45b1aac2e734ba2cc8dad3a6d97d97901a395bd0ed3e7b46953d2a31"}, + {file = "build-1.2.1-py3-none-any.whl", hash = "sha256:75e10f767a433d9a86e50d83f418e83efc18ede923ee5ff7df93b6cb0306c5d4"}, + {file = "build-1.2.1.tar.gz", hash = "sha256:526263f4870c26f26c433545579475377b2b7588b6f1eac76a001e873ae3e19d"}, ] [package.dependencies] colorama = {version = "*", markers = "os_name == \"nt\""} importlib-metadata = {version = ">=4.6", markers = "python_full_version < \"3.10.2\""} -packaging = ">=19.0" +packaging = ">=19.1" pyproject_hooks = "*" tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""} [package.extras] docs = ["furo (>=2023.08.17)", "sphinx (>=7.0,<8.0)", "sphinx-argparse-cli (>=1.5)", "sphinx-autodoc-typehints (>=1.10)", "sphinx-issues (>=3.0.0)"] -test = ["filelock (>=3)", "pytest (>=6.2.4)", "pytest-cov (>=2.12)", "pytest-mock (>=2)", "pytest-rerunfailures (>=9.1)", "pytest-xdist (>=1.34)", "setuptools (>=42.0.0)", "setuptools (>=56.0.0)", "setuptools (>=56.0.0)", "setuptools (>=67.8.0)", "wheel (>=0.36.0)"] -typing = ["importlib-metadata (>=5.1)", "mypy (>=1.5.0,<1.6.0)", "tomli", "typing-extensions (>=3.7.4.3)"] +test = ["build[uv,virtualenv]", "filelock (>=3)", "pytest (>=6.2.4)", "pytest-cov (>=2.12)", "pytest-mock (>=2)", "pytest-rerunfailures (>=9.1)", "pytest-xdist (>=1.34)", "setuptools (>=42.0.0)", "setuptools (>=56.0.0)", "setuptools (>=56.0.0)", "setuptools (>=67.8.0)", "wheel (>=0.36.0)"] +typing = ["build[uv]", "importlib-metadata (>=5.1)", "mypy (>=1.9.0,<1.10.0)", "tomli", "typing-extensions (>=3.7.4.3)"] +uv = ["uv (>=0.1.18)"] virtualenv = ["virtualenv (>=20.0.35)"] [[package]] @@ -919,13 +920,13 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""} [[package]] name = "click-didyoumean" -version = "0.3.0" +version = "0.3.1" description = "Enables git-like *did-you-mean* feature in click" optional = true -python-versions = ">=3.6.2,<4.0.0" +python-versions = ">=3.6.2" files = [ - 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-version = "0.6.11" +version = "0.6.12" description = "A Python package with a built-in web application" authors = ["Logspace "] maintainers = [ "Carlos Coelho ", "Cristhian Zanforlin ", "Gabriel Almeida ", - "Gustavo Schaedler ", "Igor Carvalho ", "Lucas Eduoli ", "Otávio Anovazzi ", diff --git a/src/backend/langflow/alembic/versions/006b3990db50_add_unique_constraints.py b/src/backend/langflow/alembic/versions/006b3990db50_add_unique_constraints.py index e5958ab73..68b765160 100644 --- a/src/backend/langflow/alembic/versions/006b3990db50_add_unique_constraints.py +++ b/src/backend/langflow/alembic/versions/006b3990db50_add_unique_constraints.py @@ -26,20 +26,14 @@ def upgrade() -> None: flow_constraints = inspector.get_unique_constraints("flow") user_constraints = inspector.get_unique_constraints("user") try: - if not any( - constraint["name"] == "uq_apikey_id" for constraint in api_key_constraints - ): + if not any(constraint['column_names'] == ['id'] for constraint in api_key_constraints): with op.batch_alter_table("apikey", schema=None) as batch_op: batch_op.create_unique_constraint("uq_apikey_id", ["id"]) - if not any( - constraint["name"] == "uq_flow_id" for constraint in flow_constraints - ): + if not any(constraint["column_names"] == ["id"] for constraint in flow_constraints): with op.batch_alter_table("flow", schema=None) as batch_op: batch_op.create_unique_constraint("uq_flow_id", ["id"]) - if not any( - constraint["name"] == "uq_user_id" for constraint in user_constraints - ): + if not any(constraint["column_names"] == ["id"] for constraint in user_constraints): with op.batch_alter_table("user", schema=None) as batch_op: batch_op.create_unique_constraint("uq_user_id", ["id"]) except Exception as e: From 9120b91facafced93876bf60fc4368eb7db00f0f Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Thu, 4 Apr 2024 00:51:31 +0200 Subject: [PATCH 002/229] Added GTAG for Google Analytics --- docs/docusaurus.config.js | 4 + docs/package-lock.json | 369 +++++++++++++++++++++++++++++++++++++- docs/package.json | 3 +- 3 files changed, 369 insertions(+), 7 deletions(-) diff --git a/docs/docusaurus.config.js b/docs/docusaurus.config.js index 430aebcb0..35d6c1e5e 100644 --- a/docs/docusaurus.config.js +++ b/docs/docusaurus.config.js @@ -42,6 +42,10 @@ module.exports = { path: "docs", // sidebarPath: 'sidebars.js', }, + gtag: { + trackingID: 'G-SLQFLQ3KPT', + anonymizeIP: true, + }, theme: { customCss: [ require.resolve("@code-hike/mdx/styles.css"), diff --git a/docs/package-lock.json b/docs/package-lock.json index 6742b89e7..876120375 100644 --- a/docs/package-lock.json +++ b/docs/package-lock.json @@ -11,6 +11,7 @@ "@babel/preset-react": "^7.22.3", "@code-hike/mdx": "^0.9.0", "@docusaurus/core": "3.0.1", + "@docusaurus/plugin-google-gtag": "^3.2.0", "@docusaurus/plugin-ideal-image": "^3.0.1", "@docusaurus/preset-classic": "3.0.1", "@docusaurus/theme-classic": "^3.0.1", @@ -2573,13 +2574,13 @@ } }, "node_modules/@docusaurus/plugin-google-gtag": { - "version": "3.0.1", - "resolved": "https://registry.npmjs.org/@docusaurus/plugin-google-gtag/-/plugin-google-gtag-3.0.1.tgz", - "integrity": "sha512-UFTDvXniAWrajsulKUJ1DB6qplui1BlKLQZjX4F7qS/qfJ+qkKqSkhJ/F4VuGQ2JYeZstYb+KaUzUzvaPK1aRQ==", + "version": "3.2.0", + "resolved": "https://registry.npmjs.org/@docusaurus/plugin-google-gtag/-/plugin-google-gtag-3.2.0.tgz", + "integrity": "sha512-3s6zxlaMMb87MW2Rxy6EnSRDs0WDEQPuHilZZH402C8kOrUnIwlhlfjWZ4ZyLDziGl/Eec/DvD0PVqj0qHRomA==", "dependencies": { - "@docusaurus/core": "3.0.1", - "@docusaurus/types": "3.0.1", - "@docusaurus/utils-validation": "3.0.1", + "@docusaurus/core": "3.2.0", + "@docusaurus/types": "3.2.0", + "@docusaurus/utils-validation": "3.2.0", "@types/gtag.js": "^0.0.12", "tslib": "^2.6.0" }, @@ -2591,6 +2592,343 @@ "react-dom": "^18.0.0" } }, + "node_modules/@docusaurus/plugin-google-gtag/node_modules/@docusaurus/core": { + "version": "3.2.0", + "resolved": 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"node_modules/@docusaurus/plugin-google-tag-manager": { "version": "3.0.1", "resolved": "https://registry.npmjs.org/@docusaurus/plugin-google-tag-manager/-/plugin-google-tag-manager-3.0.1.tgz", @@ -2690,6 +3028,25 @@ "react-dom": "^18.0.0" } }, + "node_modules/@docusaurus/preset-classic/node_modules/@docusaurus/plugin-google-gtag": { + "version": "3.0.1", + "resolved": "https://registry.npmjs.org/@docusaurus/plugin-google-gtag/-/plugin-google-gtag-3.0.1.tgz", + "integrity": "sha512-UFTDvXniAWrajsulKUJ1DB6qplui1BlKLQZjX4F7qS/qfJ+qkKqSkhJ/F4VuGQ2JYeZstYb+KaUzUzvaPK1aRQ==", + "dependencies": { + "@docusaurus/core": "3.0.1", + "@docusaurus/types": "3.0.1", + "@docusaurus/utils-validation": "3.0.1", + "@types/gtag.js": "^0.0.12", + "tslib": "^2.6.0" + }, + "engines": { + "node": ">=18.0" + }, + "peerDependencies": { + "react": "^18.0.0", + "react-dom": "^18.0.0" + } + }, "node_modules/@docusaurus/react-loadable": { "version": "5.5.2", "resolved": "https://registry.npmjs.org/@docusaurus/react-loadable/-/react-loadable-5.5.2.tgz", diff --git a/docs/package.json b/docs/package.json index 35f38de59..599243e58 100644 --- a/docs/package.json +++ b/docs/package.json @@ -17,6 +17,7 @@ "@babel/preset-react": "^7.22.3", "@code-hike/mdx": "^0.9.0", "@docusaurus/core": "3.0.1", + "@docusaurus/plugin-google-gtag": "^3.2.0", "@docusaurus/plugin-ideal-image": "^3.0.1", "@docusaurus/preset-classic": "3.0.1", "@docusaurus/theme-classic": "^3.0.1", @@ -69,4 +70,4 @@ "engines": { "node": ">=16.14" } -} \ No newline at end of file +} From bb196944249147751d3fbf550b66405f1241565e Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Thu, 4 Apr 2024 00:52:57 +0200 Subject: [PATCH 003/229] Changed version --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 45661c562..d6ef0d5dc 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langflow" -version = "0.6.12" +version = "0.6.13" description = "A Python package with a built-in web application" authors = ["Logspace "] maintainers = [ From ed37228396e9fa2bb7fa99bfa7c07ef338639541 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Fri, 5 Apr 2024 12:15:37 -0300 Subject: [PATCH 004/229] Update Langflow documentation (#1618) --- docs/docs/index.mdx | 96 +++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 92 insertions(+), 4 deletions(-) diff --git a/docs/docs/index.mdx b/docs/docs/index.mdx index 840f10f10..377517353 100644 --- a/docs/docs/index.mdx +++ b/docs/docs/index.mdx @@ -1,10 +1,13 @@ -# 👋 Welcome to Langflow - -Langflow is an easy way to create flows. The drag-and-drop feature allows quick and effortless experimentation, while the built-in chat interface facilitates real-time interaction. It provides options to edit prompt parameters, create chains and agents, track thought processes, and export flows. - import ThemedImage from "@theme/ThemedImage"; import useBaseUrl from "@docusaurus/useBaseUrl"; import ZoomableImage from "/src/theme/ZoomableImage.js"; +import Admonition from "@theme/Admonition"; + +# 👋 Welcome to Langflow + +Langflow is an easy way to build from simple to complex AI applications. It is a low-code platform that allows you to integrate AI into everything you do. + +{" "} {" "} @@ -16,3 +19,88 @@ import ZoomableImage from "/src/theme/ZoomableImage.js"; }} style={{ width: "100%" }} /> + +## 🚀 First steps + +## Installation + +Make sure you have **Python 3.10** installed on your system. + +You can install **Langflow** with [pipx](https://pipx.pypa.io/stable/installation/) or with pip. + +Pipx can fetch the missing Python version for you, but you can also install it manually. + +```bash +pip install langflow -U +# or (since pipx 1.5.0) +pipx install langflow --python python3.10 --fetch-missing-python +``` + +Or you can install a pre-release version using: + +```bash +pip install langflow --pre --force-reinstall +# or (since pipx 1.5.0) +pipx install langflow --python python3.10 --fetch-missing-python --pip-args="--pre --force-reinstall" +``` + +We recommend using --force-reinstall to ensure you have the latest version of Langflow and its dependencies. + +### ⛓️ Running Langflow + +Langflow can be run in a variety of ways, including using the command-line interface (CLI) or HuggingFace Spaces. + +```bash +langflow run # or langflow --help +``` + +#### 🤗 HuggingFace Spaces + +Hugging Face provides a great alternative for running Langflow in their Spaces environment. This means you can run Langflow without any local installation required. + +The first step is to go to the [Langflow Space](https://huggingface.co/spaces/Langflow/Langflow?duplicate=true) or [Langflow 1.0 Preview Space](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) + +Remember to use a Chromium-based browser for the best experience. You'll be presented with the following screen: + + + +From here, just name your Space, define the visibility (Public or Private), and click on `Duplicate Space` to start the installation process. When that is done, you'll be redirected to the Space's main page to start using Langflow right away! + +Once you get Langflow running, click on New Project in the top right corner of the screen. Langflow provides a range of example flows to help you get started. + +To quickly try one of them, open a starter example, set up your API keys and click ⚡ Run, on the bottom right corner of the canvas. This will open up Langflow's Interaction Panel with the chat console, text inputs, and outputs. + +### 🖥️ Command Line Interface (CLI) + +Langflow provides a command-line interface (CLI) for easy management and configuration. + +#### Usage + +You can run the Langflow using the following command: + +```bash +langflow run [OPTIONS] +``` + +Find more information about the available options by running: + +```bash +langflow --help +``` + +## Find out more about 1.0 + + +

+ We are currently working on updating the documentation for Langflow 1.0. +

+ + +To get you learning more about what's new and why you should be excited about Langflow 1.0, go to [A new chapter for Langflow](https://pre-release.langflow.org/whats-new/a-new-chapter-langflow) and also come back often to check out our [migration guides](https://pre-release.langflow.org/whats-new/migrating-to-one-point-zero) as we release them. 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import in script.py.mako * Fix error handling during upgrade in alembic scripts * Bump version to 0.6.14 in pyproject.toml --- poetry.lock | 706 +++++++++--------- pyproject.toml | 2 +- src/backend/langflow/alembic/script.py.mako | 1 + .../alembic/versions/1ef9c4f3765d_.py | 2 + .../versions/7843803a87b5_store_updates.py | 2 + .../b2fa308044b5_add_unique_constraints.py | 13 +- 6 files changed, 366 insertions(+), 360 deletions(-) diff --git a/poetry.lock b/poetry.lock index f6dd53297..fc8999756 100644 --- a/poetry.lock +++ b/poetry.lock @@ -167,13 +167,13 @@ files = [ [[package]] name = "anthropic" -version = "0.21.3" +version = "0.23.1" description = "The official Python library for the anthropic API" optional = false python-versions = ">=3.7" files = [ - {file = "anthropic-0.21.3-py3-none-any.whl", hash = "sha256:5869115453b543a46ded6515c9f29b8d610b6e94bbba3230ad80ac947d2b0862"}, - {file = "anthropic-0.21.3.tar.gz", hash = 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signature library (pure python)" optional = false -python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*" +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.6" files = [ - {file = "ecdsa-0.18.0-py2.py3-none-any.whl", hash = "sha256:80600258e7ed2f16b9aa1d7c295bd70194109ad5a30fdee0eaeefef1d4c559dd"}, - {file = "ecdsa-0.18.0.tar.gz", hash = "sha256:190348041559e21b22a1d65cee485282ca11a6f81d503fddb84d5017e9ed1e49"}, + {file = "ecdsa-0.19.0-py2.py3-none-any.whl", hash = "sha256:2cea9b88407fdac7bbeca0833b189e4c9c53f2ef1e1eaa29f6224dbc809b707a"}, + {file = "ecdsa-0.19.0.tar.gz", hash = "sha256:60eaad1199659900dd0af521ed462b793bbdf867432b3948e87416ae4caf6bf8"}, ] [package.dependencies] @@ -1531,13 +1531,13 @@ test = ["pytest (>=6)"] [[package]] name = "execnet" -version = "2.0.2" +version = "2.1.1" description = "execnet: rapid multi-Python deployment" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" files = [ - {file = "execnet-2.0.2-py3-none-any.whl", hash = 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library." optional = false python-versions = ">=3.8" files = [ - {file = "werkzeug-3.0.1-py3-none-any.whl", hash = "sha256:90a285dc0e42ad56b34e696398b8122ee4c681833fb35b8334a095d82c56da10"}, - {file = "werkzeug-3.0.1.tar.gz", hash = "sha256:507e811ecea72b18a404947aded4b3390e1db8f826b494d76550ef45bb3b1dcc"}, + {file = "werkzeug-3.0.2-py3-none-any.whl", hash = "sha256:3aac3f5da756f93030740bc235d3e09449efcf65f2f55e3602e1d851b8f48795"}, + {file = "werkzeug-3.0.2.tar.gz", hash = "sha256:e39b645a6ac92822588e7b39a692e7828724ceae0b0d702ef96701f90e70128d"}, ] [package.dependencies] diff --git a/pyproject.toml b/pyproject.toml index d6ef0d5dc..edffd9644 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langflow" -version = "0.6.13" +version = "0.6.14" description = "A Python package with a built-in web application" authors = ["Logspace "] maintainers = [ diff --git a/src/backend/langflow/alembic/script.py.mako b/src/backend/langflow/alembic/script.py.mako index 2fbdc930d..59f3ae7e4 100644 --- a/src/backend/langflow/alembic/script.py.mako +++ b/src/backend/langflow/alembic/script.py.mako @@ -11,6 +11,7 @@ from alembic import op import sqlalchemy as sa import sqlmodel from sqlalchemy.engine.reflection import Inspector +from loguru import logger #noqa ${imports if imports else ""} # revision identifiers, used by Alembic. diff --git a/src/backend/langflow/alembic/versions/1ef9c4f3765d_.py b/src/backend/langflow/alembic/versions/1ef9c4f3765d_.py index df92f1f02..3ef39ee7d 100644 --- a/src/backend/langflow/alembic/versions/1ef9c4f3765d_.py +++ b/src/backend/langflow/alembic/versions/1ef9c4f3765d_.py @@ -28,6 +28,7 @@ def upgrade() -> None: "name", existing_type=sqlmodel.sql.sqltypes.AutoString(), nullable=True ) except Exception as e: + logger.exception(f"Error during upgrade: {e}") pass # ### end Alembic commands ### @@ -38,5 +39,6 @@ def downgrade() -> None: with op.batch_alter_table("apikey", schema=None) as batch_op: batch_op.alter_column("name", existing_type=sa.VARCHAR(), nullable=False) except Exception as e: + logger.exception(f"Error during upgrade: {e}") pass # ### end Alembic commands ### diff --git a/src/backend/langflow/alembic/versions/7843803a87b5_store_updates.py b/src/backend/langflow/alembic/versions/7843803a87b5_store_updates.py index b1565cd0f..26961d6b6 100644 --- a/src/backend/langflow/alembic/versions/7843803a87b5_store_updates.py +++ b/src/backend/langflow/alembic/versions/7843803a87b5_store_updates.py @@ -33,6 +33,7 @@ def upgrade() -> None: sa.Column("is_component", sa.Boolean(), nullable=True) ) except Exception as e: + logger.exception(f"Error during upgrade: {e}") pass try: if "store_api_key" not in user_columns: @@ -41,6 +42,7 @@ def upgrade() -> None: sa.Column("store_api_key", sqlmodel.AutoString(), nullable=True) ) except Exception as e: + logger.exception(f"Error during upgrade: {e}") pass # ### end Alembic commands ### diff --git a/src/backend/langflow/alembic/versions/b2fa308044b5_add_unique_constraints.py b/src/backend/langflow/alembic/versions/b2fa308044b5_add_unique_constraints.py index bb3c0c7cd..1ae34ce6b 100644 --- a/src/backend/langflow/alembic/versions/b2fa308044b5_add_unique_constraints.py +++ b/src/backend/langflow/alembic/versions/b2fa308044b5_add_unique_constraints.py @@ -11,6 +11,7 @@ from typing import Sequence, Union import sqlalchemy as sa import sqlmodel from alembic import op +from loguru import logger # noqa from sqlalchemy.engine.reflection import Inspector # revision identifiers, used by Alembic. @@ -55,15 +56,13 @@ def upgrade() -> None: batch_op.create_index( batch_op.f("ix_flow_user_id"), ["user_id"], unique=False ) - if "fk_flow_user_id_user" not in indices_names: - batch_op.create_foreign_key( - "fk_flow_user_id_user", "user", ["user_id"], ["id"] - ) + fk_names = [fk["name"] for fk in inspector.get_foreign_keys("flow")] + if "fk_flow_user_id_user" not in fk_names: + batch_op.create_foreign_key("fk_flow_user_id_user", "user", ["user_id"], ["id"]) - except Exception: + except Exception as e: + logger.exception(f"Error during upgrade: {e}") pass - # ### end Alembic commands ### - def downgrade() -> None: conn = op.get_bind() From e2172f4b9cdb1b96fbed2bfff72d5a59251452fd Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Tue, 9 Apr 2024 13:57:43 -0300 Subject: [PATCH 007/229] Update column types and bump version (#1653) * Add logger import in script.py.mako * Fix error handling during upgrade in alembic scripts * Bump version to 0.6.14 in pyproject.toml * Update column types in credential and api_key models * Bump version to 0.6.15 in pyproject.toml --- pyproject.toml | 2 +- .../versions/2ac71eb9c3ae_adds_credential_table.py | 2 +- .../langflow/services/database/models/api_key/model.py | 6 +++--- .../services/database/models/credential/model.py | 9 ++++++--- 4 files changed, 11 insertions(+), 8 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index edffd9644..417d4cdd7 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langflow" -version = "0.6.14" +version = "0.6.15" description = "A Python package with a built-in web application" authors = ["Logspace "] maintainers = [ diff --git a/src/backend/langflow/alembic/versions/2ac71eb9c3ae_adds_credential_table.py b/src/backend/langflow/alembic/versions/2ac71eb9c3ae_adds_credential_table.py index ce2d2cd76..367bf8118 100644 --- a/src/backend/langflow/alembic/versions/2ac71eb9c3ae_adds_credential_table.py +++ b/src/backend/langflow/alembic/versions/2ac71eb9c3ae_adds_credential_table.py @@ -36,7 +36,7 @@ def upgrade() -> None: ), sa.Column("user_id", sqlmodel.sql.sqltypes.GUID(), nullable=False), sa.Column("id", sqlmodel.sql.sqltypes.GUID(), nullable=False), - sa.Column("created_at", sa.DateTime(), nullable=False), + sa.Column("created_at", sqlmodel.sql.sqltypes.DateTime(), nullable=False), sa.Column("updated_at", sa.DateTime(), nullable=True), sa.PrimaryKeyConstraint("id"), ) diff --git a/src/backend/langflow/services/database/models/api_key/model.py b/src/backend/langflow/services/database/models/api_key/model.py index 226794cbe..776c4bb7e 100644 --- a/src/backend/langflow/services/database/models/api_key/model.py +++ b/src/backend/langflow/services/database/models/api_key/model.py @@ -3,7 +3,7 @@ from typing import TYPE_CHECKING, Optional from uuid import UUID, uuid4 from pydantic import validator -from sqlmodel import Field, Relationship, SQLModel +from sqlmodel import Field, Relationship, SQLModel, Field, Column, func, DateTime if TYPE_CHECKING: from langflow.services.database.models.user import User @@ -11,8 +11,8 @@ if TYPE_CHECKING: class ApiKeyBase(SQLModel): name: Optional[str] = Field(index=True, nullable=True, default=None) - created_at: datetime = Field(default_factory=datetime.utcnow) - last_used_at: Optional[datetime] = Field(default=None, nullable=True) + created_at: datetime = Field(sa_column=Column(DateTime(timezone=True), server_default=func.now())) + last_used_at: Optional[datetime] = Field(sa_column=Column(DateTime(timezone=True))) total_uses: int = Field(default=0) is_active: bool = Field(default=True) diff --git a/src/backend/langflow/services/database/models/credential/model.py b/src/backend/langflow/services/database/models/credential/model.py index 95bd4b829..1208560ad 100644 --- a/src/backend/langflow/services/database/models/credential/model.py +++ b/src/backend/langflow/services/database/models/credential/model.py @@ -2,7 +2,7 @@ from datetime import datetime from typing import TYPE_CHECKING, Optional from uuid import UUID, uuid4 -from sqlmodel import Field, Relationship, SQLModel +from sqlmodel import Field, Relationship, SQLModel, Column, func, DateTime from langflow.services.database.models.credential.schema import CredentialType @@ -19,8 +19,11 @@ class CredentialBase(SQLModel): class Credential(CredentialBase, table=True): id: Optional[UUID] = Field(default_factory=uuid4, primary_key=True, description="Unique ID for the credential") # name is unique per user - created_at: datetime = Field(default_factory=datetime.utcnow, description="Creation time of the credential") - updated_at: Optional[datetime] = Field(None, description="Last update time of the credential") + created_at: datetime = Field( + sa_column=Column(DateTime(timezone=True), server_default=func.now()), + description="Creation time of the credential", + ) + updated_at: Optional[datetime] = Field(None,sa_column=Column(DateTime(timezone=True)), description="Last update time of the credential") # foreign key to user table user_id: UUID = Field(description="User ID associated with this credential", foreign_key="user.id") user: "User" = Relationship(back_populates="credentials") From 4e4338f79e59b1941f0d1ae8d332b0d937a9d5b2 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 15 Apr 2024 09:30:10 -0300 Subject: [PATCH 008/229] Update API key creation and bump version to 0.6.16 (#1704) * Update API key creation with optional created_at field * Bump version to 0.6.16 in pyproject.toml * Update last_used_at field in ApiKeyBase model --- pyproject.toml | 2 +- .../langflow/services/database/models/api_key/crud.py | 1 + .../services/database/models/api_key/model.py | 11 +++++++++-- 3 files changed, 11 insertions(+), 3 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 417d4cdd7..8c38e2cd1 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langflow" -version = "0.6.15" +version = "0.6.16" description = "A Python package with a built-in web application" authors = ["Logspace "] maintainers = [ diff --git a/src/backend/langflow/services/database/models/api_key/crud.py b/src/backend/langflow/services/database/models/api_key/crud.py index 33bdc7579..37fe08cd1 100644 --- a/src/backend/langflow/services/database/models/api_key/crud.py +++ b/src/backend/langflow/services/database/models/api_key/crud.py @@ -24,6 +24,7 @@ def create_api_key(session: Session, api_key_create: ApiKeyCreate, user_id: UUID api_key=generated_api_key, name=api_key_create.name, user_id=user_id, + created_at=api_key_create.created_at or datetime.datetime.now(datetime.timezone.utc), ) session.add(api_key) diff --git a/src/backend/langflow/services/database/models/api_key/model.py b/src/backend/langflow/services/database/models/api_key/model.py index 776c4bb7e..d73f03b8b 100644 --- a/src/backend/langflow/services/database/models/api_key/model.py +++ b/src/backend/langflow/services/database/models/api_key/model.py @@ -3,16 +3,20 @@ from typing import TYPE_CHECKING, Optional from uuid import UUID, uuid4 from pydantic import validator -from sqlmodel import Field, Relationship, SQLModel, Field, Column, func, DateTime +from sqlmodel import Column, DateTime, Field, Relationship, SQLModel, func if TYPE_CHECKING: from langflow.services.database.models.user import User +def utcnow(): + return datetime.now() + + class ApiKeyBase(SQLModel): name: Optional[str] = Field(index=True, nullable=True, default=None) created_at: datetime = Field(sa_column=Column(DateTime(timezone=True), server_default=func.now())) - last_used_at: Optional[datetime] = Field(sa_column=Column(DateTime(timezone=True))) + last_used_at: Optional[datetime] = Field(None, sa_column=Column(DateTime(timezone=True))) total_uses: int = Field(default=0) is_active: bool = Field(default=True) @@ -32,6 +36,9 @@ class ApiKey(ApiKeyBase, table=True): class ApiKeyCreate(ApiKeyBase): api_key: Optional[str] = None user_id: Optional[UUID] = None + created_at: Optional[datetime] = Field( + default_factory=utcnow, description="The date and time the API key was created" + ) class UnmaskedApiKeyRead(ApiKeyBase): From 676021d2d3b090293e81699a3fe509b86861db10 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 22 Apr 2024 19:58:15 -0300 Subject: [PATCH 009/229] Fix unique constraints for id column and update API key creation (#1764) * Update .gitignore to ignore additional files and directories * Add migration to fix column types * Bump version to 0.6.17 in pyproject.toml --- .gitignore | 8 + poetry.lock | 2233 ++++++++--------- pyproject.toml | 2 +- .../versions/bc804d8e7a18_fix_types.py | 91 + 4 files changed, 1196 insertions(+), 1138 deletions(-) create mode 100644 src/backend/langflow/alembic/versions/bc804d8e7a18_fix_types.py diff --git a/.gitignore b/.gitignore index 744817491..7995b4739 100644 --- a/.gitignore +++ b/.gitignore @@ -260,3 +260,11 @@ langflow.db src/backend/langflow/frontend/ .docker scratchpad* +/tmp/* +src/backend/langflow/frontend/ +src/backend/base/langflow/frontend/ +.docker +scratchpad* +chroma*/* +stuff/* +src/frontend/playwright-report/index.html \ No newline at end of file diff --git a/poetry.lock b/poetry.lock index fc8999756..e7c0912e1 100644 --- a/poetry.lock +++ b/poetry.lock @@ -2,87 +2,87 @@ [[package]] name = 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description = "A Python package with a built-in web application" authors = ["Logspace "] maintainers = [ diff --git a/src/backend/langflow/alembic/versions/bc804d8e7a18_fix_types.py b/src/backend/langflow/alembic/versions/bc804d8e7a18_fix_types.py new file mode 100644 index 000000000..1b29b088f --- /dev/null +++ b/src/backend/langflow/alembic/versions/bc804d8e7a18_fix_types.py @@ -0,0 +1,91 @@ +"""Fix types + +Revision ID: bc804d8e7a18 +Revises: bc2f01c40e4a +Create Date: 2024-04-22 19:33:02.242116 + +""" +from typing import Sequence, Union + +import sqlalchemy as sa +from alembic import op +from sqlalchemy.dialects import postgresql +from sqlalchemy.engine.reflection import Inspector + +# revision identifiers, used by Alembic. +revision: str = 'bc804d8e7a18' +down_revision: Union[str, None] = 'bc2f01c40e4a' +branch_labels: Union[str, Sequence[str], None] = None +depends_on: Union[str, Sequence[str], None] = None + + +def upgrade() -> None: + conn = op.get_bind() + inspector = Inspector.from_engine(conn) # type: ignore + # ### commands auto generated by Alembic - please adjust! ### + table_names = inspector.get_table_names() + if "apikey" in table_names: + column_names = [col["name"] for col in inspector.get_columns("apikey")] + with op.batch_alter_table('apikey', schema=None) as batch_op: + if "created_at" in column_names: + batch_op.alter_column('created_at', + existing_type=postgresql.TIMESTAMP(), + type_=sa.DateTime(timezone=True), + nullable=True) + if "last_used_at" in column_names: + batch_op.alter_column('last_used_at', + existing_type=postgresql.TIMESTAMP(), + type_=sa.DateTime(timezone=True), + existing_nullable=True) + + if "credential" in table_names: + column_names = [col["name"] for col in inspector.get_columns("credential")] + with op.batch_alter_table('credential', schema=None) as batch_op: + if "created_at" in column_names: + batch_op.alter_column('created_at', + existing_type=postgresql.TIMESTAMP(), + type_=sa.DateTime(timezone=True), + nullable=True) + if "updated_at" in column_names: + batch_op.alter_column('updated_at', + existing_type=postgresql.TIMESTAMP(), + type_=sa.DateTime(timezone=True), + existing_nullable=True) + + # ### end Alembic commands ### + + +def downgrade() -> None: + conn = op.get_bind() + inspector = Inspector.from_engine(conn) # type: ignore + # ### commands auto generated by Alembic - please adjust! ### + table_names = inspector.get_table_names() + if "credential" in table_names: + column_names = [col["name"] for col in inspector.get_columns("credential")] + with op.batch_alter_table('credential', schema=None) as batch_op: + if "updated_at" in column_names: + batch_op.alter_column('updated_at', + existing_type=sa.DateTime(timezone=True), + type_=postgresql.TIMESTAMP(), + existing_nullable=True) + if "created_at" in column_names: + batch_op.alter_column('created_at', + existing_type=sa.DateTime(timezone=True), + type_=postgresql.TIMESTAMP(), + nullable=False) + + if "apikey" in table_names: + column_names = [col["name"] for col in inspector.get_columns("apikey")] + with op.batch_alter_table('apikey', schema=None) as batch_op: + if "last_used_at" in column_names: + batch_op.alter_column('last_used_at', + existing_type=sa.DateTime(timezone=True), + type_=postgresql.TIMESTAMP(), + existing_nullable=True) + if "created_at" in column_names: + batch_op.alter_column('created_at', + existing_type=sa.DateTime(timezone=True), + type_=postgresql.TIMESTAMP(), + nullable=False) + + # ### end Alembic commands ### From 83dfa4d16054d9f024a35d7257b20bdcd0ba5072 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 29 Apr 2024 15:41:26 -0300 Subject: [PATCH 010/229] Fix bugs and make improvements (#1794) * add ? to prevent bug when template has no value * Refactor determine_component_name function in utils.py to use file name * Bump version to 0.6.18 in pyproject.toml --------- Co-authored-by: anovazzi1 --- poetry.lock | 995 +++++++++--------- pyproject.toml | 2 +- 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a/src/backend/langflow/interface/custom/directory_reader/utils.py b/src/backend/langflow/interface/custom/directory_reader/utils.py index f1771b2d7..6f2723ba6 100644 --- a/src/backend/langflow/interface/custom/directory_reader/utils.py +++ b/src/backend/langflow/interface/custom/directory_reader/utils.py @@ -1,6 +1,7 @@ +from loguru import logger + from langflow.interface.custom.directory_reader import DirectoryReader from langflow.template.frontend_node.custom_components import CustomComponentFrontendNode -from loguru import logger def merge_nested_dicts_with_renaming(dict1, dict2): @@ -124,12 +125,8 @@ def get_new_key(dictionary, original_key): def determine_component_name(component): """Determine the name of the component.""" - component_output_types = component["output_types"] - if len(component_output_types) == 1: - return component_output_types[0] - else: - file_name = component.get("file").split(".")[0] - return "".join(word.capitalize() for word in file_name.split("_")) if "_" in file_name else file_name + file_name = component.get("file").split(".")[0] + return "".join(word.capitalize() for word in file_name.split("_")) if "_" in file_name else file_name def build_menu_items(menu_item): diff --git a/src/frontend/src/components/codeTabsComponent/index.tsx b/src/frontend/src/components/codeTabsComponent/index.tsx index 2bea4265f..2a502074b 100644 --- a/src/frontend/src/components/codeTabsComponent/index.tsx +++ b/src/frontend/src/components/codeTabsComponent/index.tsx @@ -733,7 +733,7 @@ export default function CodeTabsComponent({ value={ node.data.node!.template[ templateField - ].value.toString() === "{}" + ].value?.toString() === "{}" ? { yourkey: "value", } From 731eec3dc5dea649720341bc430791b3da7f9e66 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Tue, 7 May 2024 18:29:42 -0300 Subject: [PATCH 011/229] Fixes Pinecone implementation (#1856) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * ⬆️ 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"^0.1.0" [tool.poetry.group.dev.dependencies] pytest-asyncio = "^0.23.1" diff --git a/src/backend/langflow/components/vectorstores/Pinecone.py b/src/backend/langflow/components/vectorstores/Pinecone.py index 147af1df8..f886905f0 100644 --- a/src/backend/langflow/components/vectorstores/Pinecone.py +++ b/src/backend/langflow/components/vectorstores/Pinecone.py @@ -1,63 +1,145 @@ -import os from typing import List, Optional, Union -import pinecone # type: ignore from langchain.schema import BaseRetriever from langchain_community.vectorstores import VectorStore -from langchain_community.vectorstores.pinecone import Pinecone -from langflow import CustomComponent -from langflow.field_typing import Document, Embeddings +from langchain_core.documents import Document +from langchain_pinecone._utilities import DistanceStrategy +from langchain_pinecone.vectorstores import PineconeVectorStore + +from langflow.field_typing import Embeddings +from langflow.interface.custom.custom_component import CustomComponent class PineconeComponent(CustomComponent): display_name = "Pinecone" description = "Construct Pinecone wrapper from raw documents." + icon = "Pinecone" + field_order = ["index_name", "namespace", "distance_strategy", "pinecone_api_key", "documents", "embedding"] def build_config(self): + distance_options = [e.value.title().replace("_", " ") for e in DistanceStrategy] + distance_value = distance_options[0] return { - "documents": {"display_name": "Documents"}, + "inputs": {"display_name": "Input", "input_types": ["Document", "Record"]}, "embedding": {"display_name": "Embedding"}, "index_name": {"display_name": "Index Name"}, "namespace": {"display_name": "Namespace"}, - "pinecone_api_key": {"display_name": "Pinecone API Key", "default": "", "password": True, "required": True}, - "pinecone_env": {"display_name": "Pinecone Environment", "default": "", "required": True}, - "search_kwargs": {"display_name": "Search Kwargs", "default": "{}"}, - "pool_threads": {"display_name": "Pool Threads", "default": 1, "advanced": True}, + "text_key": {"display_name": "Text Key"}, + "distance_strategy": { + "display_name": "Distance Strategy", + # get values from enum + # and make them title case for display + "options": distance_options, + "advanced": True, + "value": distance_value, + }, + "pinecone_api_key": { + "display_name": "Pinecone API Key", + "default": "", + "password": True, + "required": True, + }, + "pool_threads": { + "display_name": "Pool Threads", + "default": 1, + "advanced": True, + }, } + def from_existing_index( + self, + index_name: str, + embedding: Embeddings, + pinecone_api_key: str | None, + text_key: str = "text", + namespace: Optional[str] = None, + distance_strategy: DistanceStrategy = DistanceStrategy.COSINE, + pool_threads: int = 4, + ) -> PineconeVectorStore: + """Load pinecone vectorstore from index name.""" + pinecone_index = PineconeVectorStore.get_pinecone_index( + index_name, pool_threads, pinecone_api_key=pinecone_api_key + ) + return PineconeVectorStore( + index=pinecone_index, + embedding=embedding, + text_key=text_key, + namespace=namespace, + distance_strategy=distance_strategy, + ) + + def from_documents( + self, + documents: List[Document], + embedding: Embeddings, + index_name: str, + pinecone_api_key: str | None, + text_key: str = "text", + namespace: Optional[str] = None, + pool_threads: int = 4, + distance_strategy: DistanceStrategy = DistanceStrategy.COSINE, + batch_size: int = 32, + upsert_kwargs: Optional[dict] = None, + embeddings_chunk_size: int = 1000, + ) -> PineconeVectorStore: + """Create a new pinecone vectorstore from documents.""" + texts = [d.page_content for d in documents] + metadatas = [d.metadata for d in documents] + pinecone = self.from_existing_index( + index_name=index_name, + embedding=embedding, + pinecone_api_key=pinecone_api_key, + text_key=text_key, + namespace=namespace, + distance_strategy=distance_strategy, + pool_threads=pool_threads, + ) + pinecone.add_texts( + texts, + metadatas=metadatas, + ids=None, + namespace=namespace, + batch_size=batch_size, + embedding_chunk_size=embeddings_chunk_size, + **(upsert_kwargs or {}), + ) + return pinecone + def build( self, embedding: Embeddings, - pinecone_env: str, - documents: List[Document], + distance_strategy: str, + documents: Optional[List[Document]] = None, text_key: str = "text", pool_threads: int = 4, index_name: Optional[str] = None, pinecone_api_key: Optional[str] = None, namespace: Optional[str] = "default", - ) -> Union[VectorStore, Pinecone, BaseRetriever]: - if pinecone_api_key is None or pinecone_env is None: - raise ValueError("Pinecone API Key and Environment are required.") - if os.getenv("PINECONE_API_KEY") is None and pinecone_api_key is None: - raise ValueError("Pinecone API Key is required.") - - pinecone.init(api_key=pinecone_api_key, environment=pinecone_env) # type: ignore + ) -> Union[VectorStore, BaseRetriever]: + # get distance strategy from string + distance_strategy = distance_strategy.replace(" ", "_").upper() + _distance_strategy = DistanceStrategy[distance_strategy] if not index_name: raise ValueError("Index Name is required.") + if documents: - return Pinecone.from_documents( + return self.from_documents( documents=documents, embedding=embedding, index_name=index_name, - pool_threads=pool_threads, - namespace=namespace, + pinecone_api_key=pinecone_api_key, text_key=text_key, + namespace=namespace, + distance_strategy=_distance_strategy, + pool_threads=pool_threads, ) - return Pinecone.from_existing_index( + return self.from_existing_index( index_name=index_name, embedding=embedding, + pinecone_api_key=pinecone_api_key, text_key=text_key, namespace=namespace, + distance_strategy=_distance_strategy, pool_threads=pool_threads, ) From de2a95d5aa4394ae1ab0de58042465d1fbd80959 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 08:13:10 -0300 Subject: [PATCH 012/229] chore: Update docker-build.yml to include pre_release option --- .github/workflows/docker-build.yml | 15 ++- .github/workflows/release.yml | 165 ++++++++++++++++++----------- 2 files changed, 117 insertions(+), 63 deletions(-) diff --git a/.github/workflows/docker-build.yml b/.github/workflows/docker-build.yml index 75c136202..1e1b00ed3 100644 --- a/.github/workflows/docker-build.yml +++ b/.github/workflows/docker-build.yml @@ -8,6 +8,11 @@ on: release_type: required: true type: string + pre_release: + required: false + type: boolean + default: true + workflow_dispatch: inputs: version: @@ -19,6 +24,10 @@ on: options: - base - main + pre_release: + required: false + type: boolean + default: true env: POETRY_VERSION: "1.8.2" TEST_TAG: "langflowai/langflow:test" @@ -38,7 +47,11 @@ jobs: echo "tags=langflowai/langflow:base-${{ inputs.version }}" >> $GITHUB_OUTPUT echo "file=./docker/build_and_push_base.Dockerfile" >> $GITHUB_OUTPUT else - echo "tags=langflowai/langflow:${{ inputs.version }},langflowai/langflow:1.0-alpha" >> $GITHUB_OUTPUT + if [[ "${{ inputs.pre_release }}" == "true" ]]; then + echo "tags=langflowai/langflow:${{ inputs.version }}-alpha,langflowai/langflow:alpha" >> $GITHUB_OUTPUT + else + echo "tags=langflowai/langflow:${{ inputs.version }},langflowai/langflow:latest" >> $GITHUB_OUTPUT + fi echo "file=./docker/build_and_push.Dockerfile" >> $GITHUB_OUTPUT fi build: diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml index e27836ee3..a764c6cae 100644 --- a/.github/workflows/release.yml +++ b/.github/workflows/release.yml @@ -1,21 +1,36 @@ -name: release - +name: Langflow Release +run-name: Langflow (${{inputs.release_type}}) Release by @${{ github.actor }} on: - pull_request: - types: - - closed - branches: - - main - paths: - - "pyproject.toml" + workflow_dispatch: + inputs: + release_package: + description: "Release package" + required: true + type: boolean + default: false + release_type: + description: "Type of release (base or main)" + required: true + type: choice + options: + - base + - main + pre_release: + description: "Pre-release" + required: false + type: boolean + default: true env: POETRY_VERSION: "1.8.2" jobs: - if_release: - if: ${{ (github.event.pull_request.merged == true) && contains(github.event.pull_request.labels.*.name, 'Release') }} + release: + name: Release Langflow + if: inputs.release_package == true runs-on: ubuntu-latest + outputs: + version: ${{ steps.check-version.outputs.version }} steps: - uses: actions/checkout@v4 - name: Install poetry @@ -25,64 +40,89 @@ jobs: with: python-version: "3.10" cache: "poetry" - - name: Build project for distribution - run: make build + - name: Set up Nodejs 20 + uses: actions/setup-node@v4 + with: + node-version: "20" - name: Check Version id: check-version run: | - echo version=$(poetry version --short) >> $GITHUB_OUTPUT + if [ "${{ inputs.release_type }}" == "base" ]; then + version=$(cd src/backend/base && poetry version --short) + last_released_version=$(curl -s "https://pypi.org/pypi/langflow-base/json" | jq -r '.releases | keys | .[]' | sort -V | tail -n 1) + else + version=$(poetry version --short) + last_released_version=$(curl -s "https://pypi.org/pypi/langflow/json" | jq -r '.releases | keys | .[]' | sort -V | tail -n 1) + fi + if [ "$version" = "$last_released_version" ]; then + echo "Version $version is already released. Skipping release." + exit 1 + else + echo version=$version >> $GITHUB_OUTPUT + fi + - name: Build project for distribution + run: | + if [ "${{ inputs.release_type }}" == "base" ]; then + make build base=true + else + make build main=true + fi + - name: Test CLI + run: | + if [ "${{ inputs.release_type }}" == "base" ]; then + python -m pip install src/backend/base/dist/*.whl + else + python -m pip install dist/*.whl + fi + python -m langflow run --host 127.0.0.1 --port 7860 & + SERVER_PID=$! + # Wait for the server to start + timeout 120 bash -c 'until curl -f http://127.0.0.1:7860/health; do sleep 2; done' || (echo "Server did not start in time" && kill $SERVER_PID && exit 1) + # Terminate the server + kill $SERVER_PID || (echo "Failed to terminate the server" && exit 1) + sleep 10 # give the server some time to terminate + # Check if the server is still running + if kill -0 $SERVER_PID 2>/dev/null; then + echo "Failed to terminate the server" + exit 1 + else + echo "Server terminated successfully" + fi - name: Publish to PyPI env: POETRY_PYPI_TOKEN_PYPI: ${{ secrets.PYPI_API_TOKEN }} run: | - poetry publish - - name: Set up QEMU - uses: docker/setup-qemu-action@v3 - id: qemu - - name: Set up Docker Buildx - uses: docker/setup-buildx-action@v3 - - name: Login to Docker Hub - uses: docker/login-action@v3 + if [ "${{ inputs.release_type }}" == "base" ]; then + make publish base=true + else + make publish main=true + fi + - name: Upload Artifact + uses: actions/upload-artifact@v4 with: - username: ${{ secrets.DOCKERHUB_USERNAME }} - password: ${{ secrets.DOCKERHUB_TOKEN }} - - name: Build and push - uses: docker/build-push-action@v5 + name: dist${{ inputs.release_type }} + path: ${{ inputs.release_type == 'base' && 'src/backend/base/dist' || 'dist' }} + + call_docker_build: + name: Call Docker Build Workflow + needs: release + uses: langflow-ai/langflow/.github/workflows/docker-build.yml@main + with: + version: ${{ needs.release.outputs.version }} + release_type: ${{ inputs.release_type }} + pre_release: ${{ inputs.pre_release }} + secrets: inherit + + create_release: + name: Create Release + runs-on: ubuntu-latest + needs: [release] + if: ${{ inputs.release_type == 'main' }} + steps: + - uses: actions/download-artifact@v4 with: - context: . - push: true - file: ./docker/build_and_push.Dockerfile - # provenance: false will result in a single manifest for all platforms which makes the image pullable from arm64 machines via the emulation (e.g. Apple Silicon machines) - provenance: false - tags: | - langflowai/langflow:${{ steps.check-version.outputs.version }} - langflowai/langflow:latest - - name: Wait for Docker Hub to propagate - run: sleep 120 - - name: Build and push (backend) - uses: docker/build-push-action@v5 - with: - context: . - push: true - file: ./docker/build_and_push_backend.Dockerfile - # provenance: false will result in a single manifest for all platforms which makes the image pullable from arm64 machines via the emulation (e.g. Apple Silicon machines) - provenance: false - build-args: | - LANGFLOW_IMAGE=langflowai/langflow:${{ steps.check-version.outputs.version }} - tags: | - langflowai/langflow-backend:${{ steps.check-version.outputs.version }} - langflowai/langflow-backend:latest - - name: Build and push (frontend) - uses: docker/build-push-action@v5 - with: - context: . - push: true - file: ./docker/frontend/build_and_push_frontend.Dockerfile - # provenance: false will result in a single manifest for all platforms which makes the image pullable from arm64 machines via the emulation (e.g. Apple Silicon machines) - provenance: false - tags: | - langflowai/langflow-frontend:${{ steps.check-version.outputs.version }} - langflowai/langflow-frontend:latest + name: dist${{ inputs.release_type }} + path: dist - name: Create Release uses: ncipollo/release-action@v1 with: @@ -90,5 +130,6 @@ jobs: token: ${{ secrets.GITHUB_TOKEN }} draft: false generateReleaseNotes: true - tag: v${{ steps.check-version.outputs.version }} - commit: main + prerelease: false + tag: v${{ needs.release.outputs.version }} + commit: dev From 7c35e29da266cdedf1b7ae40a90d4017c78c4fc3 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 08:17:28 -0300 Subject: [PATCH 013/229] chore: Update docker-build.yml to include pre_release option and base-latest tag --- .github/workflows/docker-build.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/docker-build.yml b/.github/workflows/docker-build.yml index 1e1b00ed3..45d2f38c7 100644 --- a/.github/workflows/docker-build.yml +++ b/.github/workflows/docker-build.yml @@ -44,7 +44,7 @@ jobs: id: set-vars run: | if [[ "${{ inputs.release_type }}" == "base" ]]; then - echo "tags=langflowai/langflow:base-${{ inputs.version }}" >> $GITHUB_OUTPUT + echo "tags=langflowai/langflow:base-${{ inputs.version }},langflowai/langflow:base-latest" >> $GITHUB_OUTPUT echo "file=./docker/build_and_push_base.Dockerfile" >> $GITHUB_OUTPUT else if [[ "${{ inputs.pre_release }}" == "true" ]]; then From f4ddc60d2a04c04d83ba810ea1a684076bf307ea Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 08:25:13 -0300 Subject: [PATCH 014/229] chore: Update docker-build.yml to include pre_release option and base-latest tag --- .github/workflows/docker-build.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/docker-build.yml b/.github/workflows/docker-build.yml index 45d2f38c7..266877611 100644 --- a/.github/workflows/docker-build.yml +++ b/.github/workflows/docker-build.yml @@ -48,7 +48,7 @@ jobs: echo "file=./docker/build_and_push_base.Dockerfile" >> $GITHUB_OUTPUT else if [[ "${{ inputs.pre_release }}" == "true" ]]; then - echo "tags=langflowai/langflow:${{ inputs.version }}-alpha,langflowai/langflow:alpha" >> $GITHUB_OUTPUT + echo "tags=langflowai/langflow:${{ inputs.version }}" >> $GITHUB_OUTPUT else echo "tags=langflowai/langflow:${{ inputs.version }},langflowai/langflow:latest" >> $GITHUB_OUTPUT fi From 07de1d6674d24f38a9cb9f8a65afd158c1a7273d Mon Sep 17 00:00:00 2001 From: anovazzi1 Date: Sun, 23 Jun 2024 18:05:11 -0300 Subject: [PATCH 015/229] add warning to components with old codes --- src/frontend/src/alerts/notice/index.tsx | 2 +- .../src/pages/FlowPage/components/PageComponent/index.tsx | 8 ++++++++ src/frontend/src/stores/flowStore.ts | 6 ++++++ src/frontend/src/utils/reactflowUtils.ts | 5 +++++ 4 files changed, 20 insertions(+), 1 deletion(-) diff --git a/src/frontend/src/alerts/notice/index.tsx b/src/frontend/src/alerts/notice/index.tsx index 7d2d4d987..49fb52759 100644 --- a/src/frontend/src/alerts/notice/index.tsx +++ b/src/frontend/src/alerts/notice/index.tsx @@ -47,7 +47,7 @@ export default function NoticeAlert({ />

-

+

{title}

diff --git a/src/frontend/src/pages/FlowPage/components/PageComponent/index.tsx b/src/frontend/src/pages/FlowPage/components/PageComponent/index.tsx index c3632cf6d..d5a18f261 100644 --- a/src/frontend/src/pages/FlowPage/components/PageComponent/index.tsx +++ b/src/frontend/src/pages/FlowPage/components/PageComponent/index.tsx @@ -34,6 +34,7 @@ import { useTypesStore } from "../../../../stores/typesStore"; import { APIClassType } from "../../../../types/api"; import { FlowType, NodeType } from "../../../../types/flow"; import { + checkOldComponents, generateFlow, generateNodeFromFlow, getNodeId, @@ -97,6 +98,7 @@ export default function Page({ const onConnect = useFlowStore((state) => state.onConnect); const currentFlowId = useFlowsManagerStore((state) => state.currentFlowId); const setErrorData = useAlertStore((state) => state.setErrorData); + const setNoticeData = useAlertStore((state) => state.setNoticeData); const [selectionMenuVisible, setSelectionMenuVisible] = useState(false); const edgeUpdateSuccessful = useRef(true); @@ -170,6 +172,12 @@ export default function Page({ } }, [currentFlowId, reactFlowInstance]); +useEffect(() => { + if(checkOldComponents({nodes:flow?.data?.nodes ?? []})){ + setNoticeData({title:"Components created before Langflow 1.0 may be unstable. Ensure components are up to date."}) + } +},[]) + useEffect(() => { return () => { cleanFlow(); diff --git a/src/frontend/src/stores/flowStore.ts b/src/frontend/src/stores/flowStore.ts index 24e3a83d3..05f5ff948 100644 --- a/src/frontend/src/stores/flowStore.ts +++ b/src/frontend/src/stores/flowStore.ts @@ -27,6 +27,7 @@ import { FlowStoreType, VertexLayerElementType } from "../types/zustand/flow"; import { buildVertices } from "../utils/buildUtils"; import { checkChatInput, + checkOldComponents, cleanEdges, getHandleId, getNodeId, @@ -240,6 +241,11 @@ const useFlowStore = create((set, get) => ({ }); return; } + if(selection.nodes){ + if(checkOldComponents({nodes:selection.nodes ?? []})){ + useAlertStore.getState().setNoticeData({title:"Components created before Langflow 1.0 may be unstable. Ensure components are up to date."}) + } + } let minimumX = Infinity; let minimumY = Infinity; let idsMap = {}; diff --git a/src/frontend/src/utils/reactflowUtils.ts b/src/frontend/src/utils/reactflowUtils.ts index ad9666201..34cefa4a1 100644 --- a/src/frontend/src/utils/reactflowUtils.ts +++ b/src/frontend/src/utils/reactflowUtils.ts @@ -1511,3 +1511,8 @@ export function getGroupOutputNodeId( } return { id: node.id, outputName: p_name }; } + +export function checkOldComponents({nodes}:{nodes:any[]}) { + return nodes.some((node) => node.data.node?.template.code && (node.data.node?.template.code.value as string).includes("(CustomComponent):")); + +} From 696c07991d3156046732a48eb90841158099e29b Mon Sep 17 00:00:00 2001 From: anovazzi1 Date: Sun, 23 Jun 2024 18:07:10 -0300 Subject: [PATCH 016/229] update liteLLM icon --- src/backend/base/langflow/components/models/ChatLiteLLMModel.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/backend/base/langflow/components/models/ChatLiteLLMModel.py b/src/backend/base/langflow/components/models/ChatLiteLLMModel.py index e43854bc7..cd487c4a0 100644 --- a/src/backend/base/langflow/components/models/ChatLiteLLMModel.py +++ b/src/backend/base/langflow/components/models/ChatLiteLLMModel.py @@ -22,7 +22,7 @@ class ChatLiteLLMModelComponent(LCModelComponent): display_name = "LiteLLM" description = "`LiteLLM` collection of large language models." documentation = "https://python.langchain.com/docs/integrations/chat/litellm" - icon = "LiteLLM" + icon = "🚄" inputs = [ MessageInput(name="input_value", display_name="Input"), From b8581581ea13f724bd8e2511c9640caa27888d3c Mon Sep 17 00:00:00 2001 From: anovazzi1 Date: Sun, 23 Jun 2024 21:09:00 +0000 Subject: [PATCH 017/229] Apply Prettier formatting --- .../FlowPage/components/PageComponent/index.tsx | 13 ++++++++----- src/frontend/src/stores/flowStore.ts | 11 ++++++++--- src/frontend/src/utils/reactflowUtils.ts | 11 ++++++++--- 3 files changed, 24 insertions(+), 11 deletions(-) diff --git a/src/frontend/src/pages/FlowPage/components/PageComponent/index.tsx b/src/frontend/src/pages/FlowPage/components/PageComponent/index.tsx index d5a18f261..f302c70e3 100644 --- a/src/frontend/src/pages/FlowPage/components/PageComponent/index.tsx +++ b/src/frontend/src/pages/FlowPage/components/PageComponent/index.tsx @@ -172,11 +172,14 @@ export default function Page({ } }, [currentFlowId, reactFlowInstance]); -useEffect(() => { - if(checkOldComponents({nodes:flow?.data?.nodes ?? []})){ - setNoticeData({title:"Components created before Langflow 1.0 may be unstable. Ensure components are up to date."}) - } -},[]) + useEffect(() => { + if (checkOldComponents({ nodes: flow?.data?.nodes ?? [] })) { + setNoticeData({ + title: + "Components created before Langflow 1.0 may be unstable. Ensure components are up to date.", + }); + } + }, []); useEffect(() => { return () => { diff --git a/src/frontend/src/stores/flowStore.ts b/src/frontend/src/stores/flowStore.ts index 05f5ff948..9167a6b05 100644 --- a/src/frontend/src/stores/flowStore.ts +++ b/src/frontend/src/stores/flowStore.ts @@ -241,9 +241,14 @@ const useFlowStore = create((set, get) => ({ }); return; } - if(selection.nodes){ - if(checkOldComponents({nodes:selection.nodes ?? []})){ - useAlertStore.getState().setNoticeData({title:"Components created before Langflow 1.0 may be unstable. Ensure components are up to date."}) + if (selection.nodes) { + if (checkOldComponents({ nodes: selection.nodes ?? [] })) { + useAlertStore + .getState() + .setNoticeData({ + title: + "Components created before Langflow 1.0 may be unstable. Ensure components are up to date.", + }); } } let minimumX = Infinity; diff --git a/src/frontend/src/utils/reactflowUtils.ts b/src/frontend/src/utils/reactflowUtils.ts index 34cefa4a1..9b62b2624 100644 --- a/src/frontend/src/utils/reactflowUtils.ts +++ b/src/frontend/src/utils/reactflowUtils.ts @@ -1512,7 +1512,12 @@ export function getGroupOutputNodeId( return { id: node.id, outputName: p_name }; } -export function checkOldComponents({nodes}:{nodes:any[]}) { - return nodes.some((node) => node.data.node?.template.code && (node.data.node?.template.code.value as string).includes("(CustomComponent):")); - +export function checkOldComponents({ nodes }: { nodes: any[] }) { + return nodes.some( + (node) => + node.data.node?.template.code && + (node.data.node?.template.code.value as string).includes( + "(CustomComponent):", + ), + ); } From 399a65153111a9c1b49560ff52cbd087bc9e7edb Mon Sep 17 00:00:00 2001 From: Rodrigo Date: Sat, 22 Jun 2024 21:05:43 -0300 Subject: [PATCH 018/229] feat: Update sidebar link to Langflow workspace --- README.PT.md | 2 +- README.md | 2 +- docs/docs/administration/playground.mdx | 3 +- docs/docs/components/custom.mdx | 4 +- docs/docs/getting-started/canvas.mdx | 89 ++++++++++++------- .../docs/getting-started/install-langflow.mdx | 42 ++++----- docs/docs/getting-started/quickstart.mdx | 40 +++++---- .../docs/getting-started/rag-with-astradb.mdx | 2 +- docs/docs/index.mdx | 2 +- docs/docs/integrations/notion/page-update.md | 2 +- .../migration/migrating-to-one-point-zero.mdx | 12 +-- .../tutorials/chatprompttemplate_guide.mdx | 2 +- docs/docs/tutorials/custom_components.mdx | 6 +- docs/docs/tutorials/loading_document.mdx | 2 +- docs/docs/tutorials/rag-with-astradb.mdx | 2 +- .../docs/whats-new/a-new-chapter-langflow.mdx | 2 +- docs/sidebars.js | 2 +- 17 files changed, 117 insertions(+), 99 deletions(-) diff --git a/README.PT.md b/README.PT.md index 8d3197dd7..6f7a93609 100644 --- a/README.PT.md +++ b/README.PT.md @@ -73,7 +73,7 @@ Você também pode visualizar o Langflow no [HuggingFace Spaces](https://hugging # 🎨 Criar Fluxos -Criar fluxos com Langflow é fácil. Basta arrastar componentes da barra lateral para o canvas e conectá-los para começar a construir sua aplicação. +Criar fluxos com Langflow é fácil. Basta arrastar componentes da barra lateral para o workspace e conectá-los para começar a construir sua aplicação. Explore editando os parâmetros do prompt, agrupando componentes e construindo seus próprios componentes personalizados (Custom Components). diff --git a/README.md b/README.md index 64fa185ea..765835b25 100644 --- a/README.md +++ b/README.md @@ -74,7 +74,7 @@ You can also preview Langflow in [HuggingFace Spaces](https://huggingface.co/spa # 🎨 Create Flows -Creating flows with Langflow is easy. Simply drag components from the sidebar onto the canvas and connect them to start building your application. +Creating flows with Langflow is easy. Simply drag components from the sidebar onto the workspace and connect them to start building your application. Explore by editing prompt parameters, grouping components into a single high-level component, and building your own Custom Components. diff --git a/docs/docs/administration/playground.mdx b/docs/docs/administration/playground.mdx index c3ed5c4b7..e1b235444 100644 --- a/docs/docs/administration/playground.mdx +++ b/docs/docs/administration/playground.mdx @@ -36,7 +36,7 @@ As long as you have a flow's environment variables set, you can run it by clicki ## Playground I/O -The Playground's appearance changes depending on what components are in your canvas. +The Playground's appearance changes depending on what components are in your workspace. Adding or removing any of the below components modifies your Playground so you can monitor the inputs and outputs. @@ -58,4 +58,3 @@ When you send a message, under **Memories**, you can view a table of previous in Langflow allows every chat message to be stored, and a single flow can have multiple memory sessions. This enables you to create multiple “memories” for agents to store and recall specific information as needed. You can edit and remove previous messages to inspect and validate a model’s response behavior. - diff --git a/docs/docs/components/custom.mdx b/docs/docs/components/custom.mdx index e17b9db8d..e7a23241f 100644 --- a/docs/docs/components/custom.mdx +++ b/docs/docs/components/custom.mdx @@ -28,7 +28,7 @@ This class is the foundation for creating custom components. It allows users to ### Methods -**build:** This method is essential in a `CustomComponent` class. It defines the component's functionality and how it processes input data. The build method is invoked when you click the **Build** button on the canvas. +**build:** This method is essential in a `CustomComponent` class. It defines the component's functionality and how it processes input data. The build method is invoked when you click the **Build** button on the workspace. The following types are supported in the build method: @@ -102,4 +102,4 @@ The `CustomComponent` class also provides helpful methods for specific tasks (e. - `status`: Shows values from the `build` method, useful for debugging. - `field_order`: Controls the display order of fields. -- `icon`: Sets the canvas display icon. +- `icon`: Sets the workspace display icon. diff --git a/docs/docs/getting-started/canvas.mdx b/docs/docs/getting-started/canvas.mdx index bfd71c63b..cb03768fb 100644 --- a/docs/docs/getting-started/canvas.mdx +++ b/docs/docs/getting-started/canvas.mdx @@ -4,33 +4,60 @@ import ZoomableImage from "/src/theme/ZoomableImage.js"; import ReactPlayer from "react-player"; import Admonition from "@theme/Admonition"; -# 🎨 Langflow Canvas +# 🖥️ Langflow Workspace -The **Langflow canvas** is the central hub of Langflow, where you'll assemble new flows from components, run them, and see the results. +# The Langflow Workspace Interface -To get a feel for the canvas, we'll examine a basic prompting flow. -You can either build this flow yourself, or select **New Project** > **Basic prompting** to open a canvas with the flow pre-built. +The Langflow Workspace interface is designed to facilitate the creation, management, and execution of flows. It features a minimalistic design with various menus and options that are accessible for building and customizing a chatbot. -## Flows, components, collections, and projects +### Sidebar Menu -A [flow](#flow) is a pipeline of components connected together in the Langflow canvas. +Located on the left, this menu includes several collapsible sections that categorize the different types of pre-built components available in Langflow. -A [component](#component) is a single building block within a flow. A component has inputs, outputs, and parameters that define its functionality. +### Workspace Area -A [collection](#collection) is a snapshot of the flows available in your database. Collections can be downloaded to local storage and uploaded for future use. +The large central area where users can visually assemble and connect components to create flows. -A [project](#project) can be a component or a flow. Projects are saved as part of your collection. +## Top Navigation Bar -For example, the **OpenAI LLM** is a **component** of the **Basic prompting** flow, and the **flow** is stored in a **collection**. +- **Project Options**: Indicates the name of the current project or document. Clicking here allows users to rename the project or access project settings. +- **My Collection**: Provides access to saved or user-defined collections of components or flows. +- **Store**: Opens the component store where users can browse and add new components to their workspace. + +## Control Panel + +- **Star**: Located in the top-right corner, allowing users to star or favorite the project for easy access. +- **Playground**: Button that executes the current flow in the workspace. +- **API**: Provides API access details and integration options for the current flow. +- **Share**: Allows users to share their project or flow with others, providing options for collaboration and review. + +## Footer + +- **Langflow DataStax**: Displays the branding, indicating that the workspace is part of the Langflow suite, maintained or developed by DataStax. + +## Utility Buttons + +- **Plus (+)**: Located at the bottom of the sidebar, used to add new components to the workspace. +- **Settings (gear icon)**: Provides access to settings for the Langflow Workspace, where users can customize their experience or manage account settings. + +The **Langflow Workspace** is where you assemble new flows by connecting components and run them. To get started, click on **New Project**. You can either build a flow from scratch (Blank Flow) or choose from pre-built starter examples. + +## Flows & Components + +A [flow](#flow) is a pipeline of components connected together in the Langflow Workspace. + +A [component](#component) is a single building block within a flow. It has inputs, outputs, and parameters that define its functionality. + +For example, the **OpenAI Model** is a **component** of the **Basic Prompting** flow. ## Flow -A **flow** is a pipeline of components connected together in the Langflow canvas. +A **Flow** is a sequence of components that are connected to perform a series of operations or tasks. Each flow is essentially a pipeline where data functions travel through various components, each modifying or analyzing the data according to its specific functionality. -For example, the [Basic prompting](../starter-projects/basic-prompting) flow is a pipeline of four components: +For example, the [Basic Prompting](../starter-projects/basic-prompting) flow is a pipeline of four components: -In this flow, the **OpenAI LLM component** receives input (left side) and produces output (right side) - in this case, receiving input from the **Chat Input** and **Prompt** components and producing output to the **Chat Output** component. +In this flow, the **OpenAI Model** receives input (left side) and produces output (right side) - in this case, receiving input from the **Chat Input** and **Prompt** components and passing the output to the **Chat Output** component. ## Component -Components are the building blocks of flows. They consist of inputs, outputs, and parameters that define their functionality. These elements provide a convenient and straightforward way to compose LLM-based applications. Learn more about components and how they work in the LangChain [documentation](https://python.langchain.com/docs/integrations/components). +Components are the building blocks of flows. They consist of inputs, outputs, and parameters that define their functionality. These elements provide a convenient and straightforward way to compose LLM-based applications. Learn more about components and how they work in the [Components Section](../components).

During the flow creation process, you will notice handles (colored circles) - attached to one or both sides of a component. These handles represent the - availability to connect to other components. Hover over a handle to see - connection details. + attached to one or both sides of a component. These handles use distinct + colors to indicate the types of inputs and outputs that can be interconnected. + Hover over a handle to see connection details.
-
- For example, if you select a ConversationChain component, you - will see orange o and purple{" "} +{/\*
+For example, if you select a ConversationChain component, you +will see orange o and purple{" "} + o input handles. They indicate that this component accepts an LLM and a Memory component as inputs. The red asterisk * means that at least one input @@ -69,11 +97,11 @@ Components are the building blocks of flows. They consist of inputs, outputs, an dark: useBaseUrl("img/single-component-dark.png"), }} style={{ width: "40%", margin: "20px auto" }} -/> +/> */}
In the top right corner of the component, you'll find the component status icon (![Status icon](/logos/playbutton.svg)). -Build the flow by clicking the **![Playground icon](/logos/botmessage.svg)Playground** at the bottom right of the canvas. +Build the flow by clicking the **![Playground icon](/logos/botmessage.svg)Playground** at the bottom right of the workspace. Once the validation is complete, the status of each validated component should turn green (![Status icon](/logos/greencheck.svg)). To debug, hover over the component status to see the outputs. @@ -107,7 +135,7 @@ Langflow components can be edited by clicking the component settings button.
-Hide parameters with the **SHOW** button to reduce complexity and keep the canvas clean and intuitive for experimentation. +Hide parameters with the **SHOW** button to reduce complexity and keep the workspace clean and intuitive for experimentation. Double-click the component name to rename it. @@ -162,7 +190,7 @@ This avoids spending tokens when consistent output is expected. ### Group multiple components Components without input or output nodes can be grouped into a single component for reuse. -This is useful for combining large flows into single components (like RAG with a vector database, for example) and saves space in the canvas. +This is useful for combining large flows into single components (like RAG with a vector database, for example) and saving space. 1. Hold **Shift** and drag to select the **Prompt** and **OpenAI** components. 2. Select **Group**. @@ -171,11 +199,11 @@ This is useful for combining large flows into single components (like RAG with a ### Update component version -Canvas component state is stored in a database, while sidebar components are like starter templates. +A component's state is stored in a database, while sidebar components are like starter templates. -As soon as you drag a component from the sidebar to the canvas, the two components are no longer in parity. +As soon as you drag a component from the sidebar to the workspace, the two components are no longer in parity. -The canvas component will keep the version number it was initilized to the canvas with. Click the **Update Component** icon to bring the component up to the `latest` version. +The component will keep the version number it was initilized to the workspace with. Click the **Update Component** icon to bring the component up to the `latest` version. ## Playground @@ -276,11 +304,11 @@ Select **Download Collection** to save your project to your local machine. This Select **Upload Collection** to upload a flow or component `.json` file from your local machine. -Select **New Project** to create a new project. In addition to a blank canvas, [starter projects](../starter-projects/basic-prompting) are also available. +Select **New Project** to create a new project. In addition to a blank workspace, [starter projects](../starter-projects/basic-prompting) are also available. ## Project options menu -To see options for your project, in the upper left corner of the canvas, select the dropdown menu. +To see options for your project, in the upper left corner of the workspace, select the dropdown menu. - Langflow **requires** Python version 3.10 or greater. + Langflow **requires** Python version 3.10 or greater and + [pip](https://pypi.org/project/pip/) or + [pipx](https://pipx.pypa.io/stable/installation/) to be installed on your + system. -Langflow **requires** [Python >=3.10](https://www.python.org/downloads/release/python-3100/) and [pip](https://pypi.org/project/pip/) or [pipx](https://pipx.pypa.io/stable/installation/) to be installed on your system. - Install Langflow with pip: ```bash @@ -23,25 +24,7 @@ Install Langflow with pipx: pipx install langflow --python python3.10 --fetch-missing-python ``` -Pipx can fetch the missing Python version for you with `--fetch-missing-python`, but you can also install the Python version manually. - -## Install Langflow pre-release - -To install a pre-release version of Langflow: - -pip: - -```bash -python -m pip install langflow --pre --force-reinstall -``` - -pipx: - -```bash -pipx install langflow --python python3.10 --fetch-missing-python --pip-args="--pre --force-reinstall" -``` - -Use `--force-reinstall` to ensure you have the latest version of Langflow and its dependencies. +Pipx can fetch the missing Python version for you with `--fetch-missing-python`, but you can also install the Python version manually. Use `--force-reinstall` to ensure you have the latest version of Langflow and its dependencies. ## Having a problem? @@ -74,14 +57,17 @@ python -m langflow run ## HuggingFace Spaces -HuggingFace provides a great alternative for running Langflow in their Spaces environment. This means you can run Langflow without any local installation required. +HuggingFace provides a great alternative for running Langflow in their Spaces environment. This means you can run Langflow in the cloud without any local installation required. Here's how you can get Langflow up and running on HuggingFace Spaces: -In a Chromium-based browser, go to the [Langflow Space](https://huggingface.co/spaces/Langflow/Langflow?duplicate=true) or [Langflow v1.0 alpha Preview Space](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true). +1. **Access Langflow Space**: Open a Chromium-based browser and navigate to the [Langflow Space](https://huggingface.co/spaces/Langflow/Langflow?duplicate=true). This link directs you to a pre-configured environment for Langflow. -You'll be presented with the following screen: +2. **Duplicate the Space**: Upon arrival, you'll encounter an option to duplicate the Langflow space. This step involves a few simple decisions: + - **Naming Your Space**: Assign a unique name to your new Space. + - **Visibility Settings**: Choose between Public or Private visibility for your Space. + - After setting these parameters, click on **Duplicate Space** to initiate the setup. -Name your Space, define the visibility (Public or Private), and click on **Duplicate Space** to start the installation process. When installation is finished, you'll be redirected to the Space's main page to start using Langflow right away! +3. **Complete Installation**: The duplication and setup process begins immediately after you click **Duplicate Space**. Once completed, you will be automatically redirected to the main page of your new Space. + +4. **Start Exploring Langflow**: With the setup complete, Langflow is now ready for use in your Space and you can start exploring its features and capabilities right away! diff --git a/docs/docs/getting-started/quickstart.mdx b/docs/docs/getting-started/quickstart.mdx index c64abdbc4..ca0b88b28 100644 --- a/docs/docs/getting-started/quickstart.mdx +++ b/docs/docs/getting-started/quickstart.mdx @@ -27,16 +27,17 @@ This guide demonstrates how to build a basic prompt flow and modify that prompt Let's start with a Prompt component to instruct an OpenAI Model. -Prompts serve as the inputs to a large language model (LLM), acting as the interface between human instructions and computational tasks. +Prompts serve as the inputs to a large language model (LLM), acting as the interface between human instructions and computational tasks. By submitting natural language requests in a prompt to an LLM, you can obtain answers, generate text, and solve problems. -By submitting natural language requests in a prompt to an LLM, you can obtain answers, generate text, and solve problems. +
1. From the Langflow dashboard, click **New Project**. 2. Select **Basic Prompting**. -3. The **Basic Prompting** flow is created. + +
-This flow allows you to chat with the **OpenAI** component via a **Prompt**. +This flow allows you to chat with the **OpenAI** model by using a **Prompt** to send instructions. + Examine the **Prompt** component. The **Template** field instructs the LLM to `Answer the user as if you were a pirate.` This should be interesting... -4. To create an environment variable for the **OpenAI** component, in the **OpenAI API Key** field, click the **Globe** button, and then click **Add New Variable**. - 1. In the **Variable Name** field, enter `openai_api_key`. - 2. In the **Value** field, paste your OpenAI API Key (`sk-...`). - 3. Click **Save Variable**. +To use the **OpenAI** component, you have two options for providing your OpenAI API Key: directly passing it to the component or creating an environment variable. For better security and manageability, creating an environment variable is recommended. Here's how to set it up: + +In the **OpenAI API Key** field, click the **Globe** button to access environment variables, and then click **Add New Variable**. + +1. In the **Variable Name** field, enter `openai_api_key`. +2. In the **Value** field, paste your OpenAI API Key (`sk-...`). +3. Click **Save Variable**. + +By creating an environment variable, you keep your API key secure and make it easier to manage across different components or projects. ## Run the basic prompting flow -1. Click the **Run** button. - The **Interaction Panel** opens, where you can chat with your bot. -2. Type a message and press Enter. +1. Click the **Playground** button. This where you can interact with your bot. +2. Type any message and press Enter. And... Ahoy! 🏴‍☠️ The bot responds in a piratical manner! @@ -73,10 +79,8 @@ This should be interesting... Well done! You've built your first prompt in Langflow. 🎉 -By adding Langflow components to your flow, you can create all sorts of interesting behaviors. +By adding Langflow components to your flow, you can create all sorts of interesting behaviors. Here are a couple of examples: -Here are a couple of examples: - -- [Memory chatbot](/starter-projects/memory-chatbot) -- [Blog writer](/starter-projects/blog-writer) -- [Document QA](/starter-projects/document-qa) \ No newline at end of file +- [Memory Chatbot](/starter-projects/memory-chatbot) +- [Blog Writer](/starter-projects/blog-writer) +- [Document QA](/starter-projects/document-qa) diff --git a/docs/docs/getting-started/rag-with-astradb.mdx b/docs/docs/getting-started/rag-with-astradb.mdx index d1766c57a..eff9973dc 100644 --- a/docs/docs/getting-started/rag-with-astradb.mdx +++ b/docs/docs/getting-started/rag-with-astradb.mdx @@ -22,7 +22,7 @@ TLDR; - Duplicate our [Langflow 1.0 Space](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) - Create a new database, get a **Token** and the **API Endpoint** - Click on the **New Project** button and look for Vector Store RAG. This will create a new project with the necessary components -- Import the project into Langflow by dropping it on the Canvas or My Collection page +- Import the project into Langflow by dropping it on the Workspace or My Collection page - Update the **Token** and **API Endpoint** in the **Astra DB** components - Update the OpenAI API key in the **OpenAI** components - Run the ingestion flow which is the one that uses the **Astra DB** component diff --git a/docs/docs/index.mdx b/docs/docs/index.mdx index e762142f0..64d55ec57 100644 --- a/docs/docs/index.mdx +++ b/docs/docs/index.mdx @@ -26,7 +26,7 @@ Its intuitive interface allows for easy manipulation of AI building blocks, enab - [Quickstart](/getting-started/quickstart) - Create a flow and run it. -- [Langflow Canvas](/getting-started/canvas) - Learn more about the Langflow canvas. +- [Langflow Workspace](/getting-started/workspace) - Learn more about the Langflow workspace. Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space diff --git a/docs/docs/integrations/notion/page-update.md b/docs/docs/integrations/notion/page-update.md index 3ed8f7740..ca88f547d 100644 --- a/docs/docs/integrations/notion/page-update.md +++ b/docs/docs/integrations/notion/page-update.md @@ -13,7 +13,7 @@ The `NotionPageUpdate` component updates the properties of a Notion page. It pro To use the `NotionPageUpdate` component in your Langflow flow: -1. Drag and drop the `NotionPageUpdate` component onto the canvas. +1. Drag and drop the `NotionPageUpdate` component onto the workspace. 2. Double-click the component to open its configuration. 3. Provide the required parameters as defined in the component's `build_config` method. 4. Connect the component to other nodes in your flow as needed. diff --git a/docs/docs/migration/migrating-to-one-point-zero.mdx b/docs/docs/migration/migrating-to-one-point-zero.mdx index 8ff848def..c6afa8ab2 100644 --- a/docs/docs/migration/migrating-to-one-point-zero.mdx +++ b/docs/docs/migration/migrating-to-one-point-zero.mdx @@ -19,7 +19,7 @@ We have a special channel in our Discord server dedicated to Langflow 1.0 migrat - Improved user experience with Text and Data modes - CustomComponent for all components - Compatibility with previous versions using Runnable Executor -- Multiple flows in the canvas +- Multiple flows in the workspace - Improved component status - Ability to connect Output components to any other Component - Rename and edit component descriptions @@ -76,9 +76,9 @@ To use flows built in previous versions of Langflow, you can utilize the experim [Learn more about Compatibility with Previous Versions](./compatibility) -## Multiple Flows in the Canvas +## Multiple Flows in the Workspace -Langflow 1.0 allows you to have more than one flow in the canvas and run them separately. Discover how to create and manage multiple flows within a single project. +Langflow 1.0 allows you to have more than one flow in the workspace and run them separately. Discover how to create and manage multiple flows within a single project. **Guide coming soon** @@ -86,7 +86,7 @@ Langflow 1.0 allows you to have more than one flow in the canvas and run them se Each component now displays its status more clearly, allowing you to quickly identify any issues or errors. Explore how to use the new component status feature to troubleshoot and optimize your flows. -[Learn more about Component Status](../getting-started/canvas#component) +[Learn more about Component Status](../getting-started/workspace#component) ## Connecting Output Components @@ -98,13 +98,13 @@ You can now connect Output components to any other component (that has a Text ou Langflow 1.0 allows you to rename and edit the description of each component, making it easier to understand and interact with the flow. Learn how to customize your component names and descriptions for improved clarity. -[Learn more about Component Descriptions](../getting-started/canvas#component-parameters) +[Learn more about Component Descriptions](../getting-started/workspace#component-parameters) ## Passing Tweaks and Inputs in the API Things got a whole lot easier. You can now pass tweaks and inputs in the API by referencing the Display Name of the component. Discover how to leverage this feature to dynamically control your flow's behavior. -[Learn more about Tweaks and API inputs](../getting-started/canvas#tweaks) +[Learn more about Tweaks and API inputs](../getting-started/workspace#tweaks) ## Global Variables for Text Fields diff --git a/docs/docs/tutorials/chatprompttemplate_guide.mdx b/docs/docs/tutorials/chatprompttemplate_guide.mdx index a01fec1ca..e19f95f4a 100644 --- a/docs/docs/tutorials/chatprompttemplate_guide.mdx +++ b/docs/docs/tutorials/chatprompttemplate_guide.mdx @@ -62,7 +62,7 @@ In this guide, we will modify the "Basic Chat with Prompt and History" example, 16. You should now be able to see and use the defined variables in the chat interface. -17. Click on 'role' to examine the variable you established in the canvas. +17. Click on 'role' to examine the variable you established in the workspace. 18. Now, let's define the 'behavior' variable. diff --git a/docs/docs/tutorials/custom_components.mdx b/docs/docs/tutorials/custom_components.mdx index b6a32d048..127337937 100644 --- a/docs/docs/tutorials/custom_components.mdx +++ b/docs/docs/tutorials/custom_components.mdx @@ -196,7 +196,7 @@ Let's create a custom component that processes a document (_`langchain.schema.Do ### Pick a display name -To start, let's choose a name for our component by adding a _`display_name`_ attribute. This name will appear on the canvas. The name of the class is not relevant, but let's call it _`DocumentProcessor`_. +To start, let's choose a name for our component by adding a _`display_name`_ attribute. This name will appear on the workspace. The name of the class is not relevant, but let's call it _`DocumentProcessor`_. ```python from langflow.custom import CustomComponent @@ -267,7 +267,7 @@ class DocumentProcessor(CustomComponent): Here, the build method takes two input parameters: _`document`_, representing the input document to be processed, and _`function`_, a string representing the selected text transformation to be applied (either "Uppercase," "Lowercase," or "Titlecase"). The method processes the text content of the input Document based on the selected function. -The attribute _`repr_value`_ is used to display the result of the component on the canvas. It is optional and can be used to display any string value. +The attribute _`repr_value`_ is used to display the result of the component on the workspace. It is optional and can be used to display any string value. The return type is _`Document`_. @@ -399,6 +399,6 @@ Langflow will attempt to load all of the components found in the specified direc ### Interact with Custom Components -Once your custom components have been loaded successfully, they will appear in Langflow's sidebar. From there, you can add them to your Langflow canvas for use. However, please note that components with errors will not be available for addition to the canvas. Always ensure your code is error-free before attempting to load components. +Once your custom components have been loaded successfully, they will appear in Langflow's sidebar. From there, you can add them to your Langflow workspace for use. However, please note that components with errors will not be available for addition to the workspace. Always ensure your code is error-free before attempting to load components. Remember, creating custom components allows you to extend the functionality of Langflow to better suit your unique needs. Happy coding! diff --git a/docs/docs/tutorials/loading_document.mdx b/docs/docs/tutorials/loading_document.mdx index c123624c1..3b1eca436 100644 --- a/docs/docs/tutorials/loading_document.mdx +++ b/docs/docs/tutorials/loading_document.mdx @@ -39,7 +39,7 @@ This guide takes you through the process of augmenting the "Basic Chat with Prom 6. Next, open the search bar and type "web". -7. Drag and drop a WebBaseLoader (or any other loader of your choice) onto the canvas. +7. Drag and drop a WebBaseLoader (or any other loader of your choice) onto the workspace. 8. Connect this loader to the `{context}` variable that we just added. diff --git a/docs/docs/tutorials/rag-with-astradb.mdx b/docs/docs/tutorials/rag-with-astradb.mdx index 8d0fbd41e..6cf5c172d 100644 --- a/docs/docs/tutorials/rag-with-astradb.mdx +++ b/docs/docs/tutorials/rag-with-astradb.mdx @@ -23,7 +23,7 @@ TLDR; - Duplicate our [Langflow 1.0 Space](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) - Create a new database, get a **Token** and the **API Endpoint** - Click on the **New Project** button and look for Vector Store RAG. This will create a new project with the necessary components -- Import the project into Langflow by dropping it on the Canvas or My Collection page +- Import the project into Langflow by dropping it on the Workspace or My Collection page - Update the **Token** and **API Endpoint** in the **Astra DB** components - Update the OpenAI API key in the **OpenAI** components - Run the ingestion flow which is the one that uses the **Astra DB** component diff --git a/docs/docs/whats-new/a-new-chapter-langflow.mdx b/docs/docs/whats-new/a-new-chapter-langflow.mdx index bdc0f178b..ccdaf8426 100644 --- a/docs/docs/whats-new/a-new-chapter-langflow.mdx +++ b/docs/docs/whats-new/a-new-chapter-langflow.mdx @@ -28,7 +28,7 @@ It allows you to define the structure of your conversation and the data that flo This makes it easier to understand and control your conversation. This change comes with a new way of visualizing your projects. Before 1.0 you would connect Components to ultimately build one final Component that was processed behind the scenes. -Now, each step of the process is defined by you, is visible on the canvas, and can be monitored and controlled by you. This makes it so that Composition is now just another way of building in Langflow. **Now data flows through your project more transparently**. +Now, each step of the process is defined by you, is visible on the workspace, and can be monitored and controlled by you. This makes it so that Composition is now just another way of building in Langflow. **Now data flows through your project more transparently**. The caveat is existing projects may need some new Components to get them back to their full functionality. [We've made this as easy as possible](../migration/compatibility), and there will be improvements to it as we get feedback in our Discord server and on GitHub. diff --git a/docs/sidebars.js b/docs/sidebars.js index 322a23050..c3aa4194e 100644 --- a/docs/sidebars.js +++ b/docs/sidebars.js @@ -14,7 +14,7 @@ module.exports = { "index", "getting-started/install-langflow", "getting-started/quickstart", - "getting-started/canvas", + "getting-started/workspace", "migration/possible-installation-issues", "getting-started/new-to-llms", ], From 4243bf7b5a78a7a0fa1ea9d029ce97b6205a75a3 Mon Sep 17 00:00:00 2001 From: Mendon Kissling <59585235+mendonk@users.noreply.github.com> Date: Sat, 22 Jun 2024 20:20:11 -0400 Subject: [PATCH 019/229] remove-extra-install-issues-page --- docs/docs/getting-started/{canvas.mdx => workspace.mdx} | 4 ++-- docs/sidebars.js | 1 - 2 files changed, 2 insertions(+), 3 deletions(-) rename docs/docs/getting-started/{canvas.mdx => workspace.mdx} (99%) diff --git a/docs/docs/getting-started/canvas.mdx b/docs/docs/getting-started/workspace.mdx similarity index 99% rename from docs/docs/getting-started/canvas.mdx rename to docs/docs/getting-started/workspace.mdx index cb03768fb..338ef840c 100644 --- a/docs/docs/getting-started/canvas.mdx +++ b/docs/docs/getting-started/workspace.mdx @@ -6,7 +6,7 @@ import Admonition from "@theme/Admonition"; # 🖥️ Langflow Workspace -# The Langflow Workspace Interface +## The Langflow Workspace Interface The Langflow Workspace interface is designed to facilitate the creation, management, and execution of flows. It features a minimalistic design with various menus and options that are accessible for building and customizing a chatbot. @@ -78,7 +78,7 @@ Components are the building blocks of flows. They consist of inputs, outputs, an Hover over a handle to see connection details.
-{/\*
+
For example, if you select a ConversationChain component, you will see orange o and purple{" "} diff --git a/docs/sidebars.js b/docs/sidebars.js index c3aa4194e..65ef4db24 100644 --- a/docs/sidebars.js +++ b/docs/sidebars.js @@ -95,7 +95,6 @@ module.exports = { label: "Migration", collapsed: false, items: [ - "migration/possible-installation-issues", "migration/migrating-to-one-point-zero", "migration/compatibility", ], From c5fe03fcd23bc3c0490e9575f7c0abfc4b76e1a6 Mon Sep 17 00:00:00 2001 From: Mendon Kissling <59585235+mendonk@users.noreply.github.com> Date: Sat, 22 Jun 2024 20:25:08 -0400 Subject: [PATCH 020/229] topnav --- docs/docs/getting-started/workspace.mdx | 26 +++++++++++++++++++----- docs/static/img/topnav.png | Bin 0 -> 76092 bytes 2 files changed, 21 insertions(+), 5 deletions(-) create mode 100644 docs/static/img/topnav.png diff --git a/docs/docs/getting-started/workspace.mdx b/docs/docs/getting-started/workspace.mdx index 338ef840c..0e8973072 100644 --- a/docs/docs/getting-started/workspace.mdx +++ b/docs/docs/getting-started/workspace.mdx @@ -24,6 +24,26 @@ The large central area where users can visually assemble and connect components - **My Collection**: Provides access to saved or user-defined collections of components or flows. - **Store**: Opens the component store where users can browse and add new components to their workspace. +In the top navigation bar, the dropdown menu labeled with the project name offers several management and customization options for the current flow in the Langflow Workspace. + + + +**New**: Create a new flow from scratch. +**Settings**: Adjust settings specific to the current flow, such as its Name, Description, and Endpoint Name. +**Logs**: View logs for the current project, including execution history, errors, and other runtime events. +**Import**: Import a flow or component from a JSON file into the Workspace. +**Export**: Export the current flow as a JSON file. +**Undo (⌘Z)**: Revert the last action taken in the project. +**Redo (⌘Y)**: Reapply a previously undone action. +**Refresh All**: Refresh all components and data within the Workspace. + ## Control Panel - **Star**: Located in the top-right corner, allowing users to star or favorite the project for easy access. @@ -31,10 +51,6 @@ The large central area where users can visually assemble and connect components - **API**: Provides API access details and integration options for the current flow. - **Share**: Allows users to share their project or flow with others, providing options for collaboration and review. -## Footer - -- **Langflow DataStax**: Displays the branding, indicating that the workspace is part of the Langflow suite, maintained or developed by DataStax. - ## Utility Buttons - **Plus (+)**: Located at the bottom of the sidebar, used to add new components to the workspace. @@ -97,7 +113,7 @@ will see orange o and purple{" "} dark: useBaseUrl("img/single-component-dark.png"), }} style={{ width: "40%", margin: "20px auto" }} -/> */} +/>
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[PATCH 021/229] bullets --- docs/docs/getting-started/workspace.mdx | 23 +++++++++++++++-------- 1 file changed, 15 insertions(+), 8 deletions(-) diff --git a/docs/docs/getting-started/workspace.mdx b/docs/docs/getting-started/workspace.mdx index 0e8973072..5a5bd5827 100644 --- a/docs/docs/getting-started/workspace.mdx +++ b/docs/docs/getting-started/workspace.mdx @@ -35,14 +35,21 @@ In the top navigation bar, the dropdown menu labeled with the project name offer style={{ width: "40%", margin: "20px auto" }} /> -**New**: Create a new flow from scratch. -**Settings**: Adjust settings specific to the current flow, such as its Name, Description, and Endpoint Name. -**Logs**: View logs for the current project, including execution history, errors, and other runtime events. -**Import**: Import a flow or component from a JSON file into the Workspace. -**Export**: Export the current flow as a JSON file. -**Undo (⌘Z)**: Revert the last action taken in the project. -**Redo (⌘Y)**: Reapply a previously undone action. -**Refresh All**: Refresh all components and data within the Workspace. +* **New**: Create a new flow from scratch. + +* **Settings**: Adjust settings specific to the current flow, such as its Name, Description, and Endpoint Name. + +* **Logs**: View logs for the current project, including execution history, errors, and other runtime events. + +* **Import**: Import a flow or component from a JSON file into the Workspace. + +* **Export**: Export the current flow as a JSON file. + +* **Undo (⌘Z)**: Revert the last action taken in the project. + +* **Redo (⌘Y)**: Reapply a previously undone action. + +* **Refresh All**: Refresh all components and data within the Workspace. ## Control Panel From 8401f18f7fa546c8669f7a8dd1d4f1ed024dc47a Mon Sep 17 00:00:00 2001 From: Mendon Kissling <59585235+mendonk@users.noreply.github.com> Date: Sat, 22 Jun 2024 20:47:23 -0400 Subject: [PATCH 022/229] collections-and-projetcs --- .../administration/collections-projects.mdx | 93 ++++++++++++++++++ docs/docs/getting-started/workspace.mdx | 65 +----------- docs/sidebars.js | 1 + docs/static/img/my-collection.png | Bin 0 -> 358047 bytes 4 files changed, 95 insertions(+), 64 deletions(-) create mode 100644 docs/docs/administration/collections-projects.mdx create mode 100644 docs/static/img/my-collection.png diff --git a/docs/docs/administration/collections-projects.mdx b/docs/docs/administration/collections-projects.mdx new file mode 100644 index 000000000..ccb57a61a --- /dev/null +++ b/docs/docs/administration/collections-projects.mdx @@ -0,0 +1,93 @@ +import ThemedImage from "@theme/ThemedImage"; +import useBaseUrl from "@docusaurus/useBaseUrl"; +import ZoomableImage from "/src/theme/ZoomableImage.js"; +import ReactPlayer from "react-player"; +import Admonition from "@theme/Admonition"; + +# Collections and Projects + +My Collection is a space in Langflow where users can manage, organize, and access their flows and components. +Flows and components are displayed as individual cards that provide relevant information. + + + +* **Folders**: Users can organize their projects into folders. Default folders include "My Projects" and the ability to create new folders. Hover over a folder to access options to download or delete it. + +* **Search Bar** Enables users to quickly search through their flows and components. + +* **Select All**: This feature allows users to select all projects displayed on the page for batch actions like moving, deleting, or exporting. + +Click on a flow card to open it in Langflow Workspace or use the **Playground Button** for direct access to execute and interact with the flow’s chatbot interface. + +## Collections + +Components created or imported by the user are also displayed in **My Collection** and can be directly removed from here. + +A collection is a snapshot of flows available in a database. + +Collections can be downloaded to local storage and uploaded for future use. + +
+ +
+ +## Project + +A **Project** can be a flow or a component. To view your saved projects, select **My Collection**. + +Your **Projects** are displayed. + +Click the **![Playground icon](/logos/botmessage.svg) Playground** button to run a flow from the **My Collection** screen. + +In the top left corner of the screen are options for **Download Collection**, **Upload Collection**, and **New Project**. + +Select **Download Collection** to save your project to your local machine. This downloads all flows and components as a `.json` file. + +Select **Upload Collection** to upload a flow or component `.json` file from your local machine. + +Select **New Project** to create a new project. In addition to a blank workspace, [starter projects](../starter-projects/basic-prompting) are also available. + +## Project options menu + +To see options for your project, in the upper left corner of the workspace, select the dropdown menu. + + + +* **New** - Start a new project. + +* **Duplicate** - Duplicate the current flow as a new project. + +* **Settings** - Modify the project's **Name** or **Description**. + +* **Import** - Upload a flow `.json` file from your local machine. + +* **Export** - Download your current project to your local machine as a `.json` file. + +* **Undo** or **Redo** - Undo or redo your last action. + +## Project folders + +As of Langflow 1.0 alpha, more options are available for storing projects with **folders**. + +Create new folders with the **New folder** button. One folder can store multiple projects (as the default My Projects folder does). + +You can download folders of projects as a single JSON file, and upload files and flows to your folder. + +Click the **Trash** icon to delete a folder. + diff --git a/docs/docs/getting-started/workspace.mdx b/docs/docs/getting-started/workspace.mdx index 5a5bd5827..eef951494 100644 --- a/docs/docs/getting-started/workspace.mdx +++ b/docs/docs/getting-started/workspace.mdx @@ -299,67 +299,4 @@ For example, changing the **Chat Input** component's `input_value` will change t style={{ marginBottom: "20px", display: "flex", justifyContent: "center" }} > -
- -## Collection - -A collection is a snapshot of flows available in a database. - -Collections can be downloaded to local storage and uploaded for future use. - -
- -
- -## Project - -A **Project** can be a flow or a component. To view your saved projects, select **My Collection**. - -Your **Projects** are displayed. - -Click the **![Playground icon](/logos/botmessage.svg) Playground** button to run a flow from the **My Collection** screen. - -In the top left corner of the screen are options for **Download Collection**, **Upload Collection**, and **New Project**. - -Select **Download Collection** to save your project to your local machine. This downloads all flows and components as a `.json` file. - -Select **Upload Collection** to upload a flow or component `.json` file from your local machine. - -Select **New Project** to create a new project. In addition to a blank workspace, [starter projects](../starter-projects/basic-prompting) are also available. - -## Project options menu - -To see options for your project, in the upper left corner of the workspace, select the dropdown menu. - - - -**New** - Start a new project. - -**Duplicate** - Duplicate the current flow as a new project. - -**Settings** - Modify the project's **Name** or **Description**. - -**Import** - Upload a flow `.json` file from your local machine. - -**Export** - Download your current project to your local machine as a `.json` file. - -**Undo** or **Redo** - Undo or redo your last action. - -## Project folders - -As of Langflow 1.0 alpha, more options are available for storing projects with **folders**. - -Create new folders with the **New folder** button. One folder can store multiple projects (as the default My Projects folder does). - -You can download folders of projects as a single JSON file, and upload files and flows to your folder. - -Click the **Trash** icon to delete a folder. +
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This makes it easier to find and access specific projects quickly. + +**My Projects** is a default folder where all new projects and components are initially stored unless specified otherwise. Users can create custom folders to better organize their work according to specific needs. + +Hovering over a folder in Langflow provides options to either remove or download the entire folder, allowing you to keep an offline copy or migrate projects between environments + Create new folders with the **New folder** button. One folder can store multiple projects (as the default My Projects folder does). You can download folders of projects as a single JSON file, and upload files and flows to your folder. Click the **Trash** icon to delete a folder. + + From 054bf256802981000eddf90d69fa631137505a47 Mon Sep 17 00:00:00 2001 From: Mendon Kissling <59585235+mendonk@users.noreply.github.com> Date: Sat, 22 Jun 2024 21:27:17 -0400 Subject: [PATCH 024/229] playground --- docs/docs/administration/playground.mdx | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) diff --git a/docs/docs/administration/playground.mdx b/docs/docs/administration/playground.mdx index e1b235444..bad4b8acb 100644 --- a/docs/docs/administration/playground.mdx +++ b/docs/docs/administration/playground.mdx @@ -6,13 +6,11 @@ import Admonition from "@theme/Admonition"; # Playground -In Langflow 1.0 alpha, the **Playground** replaces the **Interaction Panel**. - -The **Playground** provides an interface for interacting with flows without opening them in the flow editor. +The **Playground** is a dynamic interface designed for real-time interaction with agents, allowing users to access and manage memories and monitor the inputs and outputs. Here, users can directly prototype and experiment with their configured components or AI models, making adjustments and observing different outcomes in real-time. It even works for flows hosted on the Langflow store! -As long as you have a flow's environment variables set, you can run it by clicking the **Playground** button. +As long as you have a flow properly working, you can interact with it by clicking the Playground button. 1. From your **Collections** page, click the **![Playground icon](/logos/botmessage.svg)Playground** in one of your flows. The **Playground** window opens. @@ -34,6 +32,11 @@ As long as you have a flow's environment variables set, you can run it by clicki

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+ + From the "My Collection” page, just click the Playground button in one of your flow cards. + It will directly open up a window with that project's Playground, without even showing the flow (this also works for flows hosted on the Langflow Store!). + + ## Playground I/O The Playground's appearance changes depending on what components are in your workspace. From f4f5d2fc7fee2d7e07c11300499c0a2f2b4c5538 Mon Sep 17 00:00:00 2001 From: Mendon Kissling <59585235+mendonk@users.noreply.github.com> Date: Sat, 22 Jun 2024 21:28:08 -0400 Subject: [PATCH 025/229] playgounrd --- docs/docs/administration/playground.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/administration/playground.mdx b/docs/docs/administration/playground.mdx index bad4b8acb..f67193daa 100644 --- a/docs/docs/administration/playground.mdx +++ b/docs/docs/administration/playground.mdx @@ -39,7 +39,7 @@ As long as you have a flow properly working, you can interact with it by clickin ## Playground I/O -The Playground's appearance changes depending on what components are in your workspace. +The Playground's window arrangement changes depending on what components are being used. Adding or removing any of the below components modifies your Playground so you can monitor the inputs and outputs. From 5d786aa3206f53a1f5e1b072153594b15d732c43 Mon Sep 17 00:00:00 2001 From: Mendon Kissling <59585235+mendonk@users.noreply.github.com> Date: Sat, 22 Jun 2024 21:57:15 -0400 Subject: [PATCH 026/229] strip-v10-alpha --- docs/docs/administration/api.mdx | 2 +- docs/docs/administration/collections-projects.mdx | 2 +- docs/docs/contributing/contribute-component.md | 2 +- docs/docs/getting-started/quickstart.mdx | 2 +- docs/docs/index.mdx | 2 +- docs/docs/migration/possible-installation-issues.mdx | 2 +- docs/docs/starter-projects/basic-prompting.mdx | 2 +- docs/docs/starter-projects/blog-writer.mdx | 2 +- docs/docs/starter-projects/document-qa.mdx | 2 +- docs/docs/starter-projects/memory-chatbot.mdx | 2 +- docs/docs/starter-projects/vector-store-rag.mdx | 2 +- 11 files changed, 11 insertions(+), 11 deletions(-) diff --git a/docs/docs/administration/api.mdx b/docs/docs/administration/api.mdx index db279ed80..db74fa506 100644 --- a/docs/docs/administration/api.mdx +++ b/docs/docs/administration/api.mdx @@ -172,7 +172,7 @@ print(run_flow(inputs, flow_id=FLOW_ID, tweaks=TWEAKS, apiKey=api_key)) ## Custom API endpoint -As of Langflow v1.0 alpha, under **Project Settings** > **Endpoint Name**, you can pick a custom name for the endpoint used to call your flow from the API. +Under **Project Settings** > **Endpoint Name**, you can pick a custom name for the endpoint used to call your flow from the API. ## Revoke an API Key diff --git a/docs/docs/administration/collections-projects.mdx b/docs/docs/administration/collections-projects.mdx index f8e7cc7c8..c116050e1 100644 --- a/docs/docs/administration/collections-projects.mdx +++ b/docs/docs/administration/collections-projects.mdx @@ -83,7 +83,7 @@ To see options for your project, in the upper left corner of the workspace, sele ## Project folders -As of Langflow 1.0 alpha, more options are available for storing projects with **folders**. +Multiple projects can be stored in **folders**. Folders allow you to categorize flows and components into manageable groups. This makes it easier to find and access specific projects quickly. diff --git a/docs/docs/contributing/contribute-component.md b/docs/docs/contributing/contribute-component.md index d252a0929..7f628623b 100644 --- a/docs/docs/contributing/contribute-component.md +++ b/docs/docs/contributing/contribute-component.md @@ -2,7 +2,7 @@ import ZoomableImage from "/src/theme/ZoomableImage.js"; # How to Contribute Components? -As of Langflow 1.0 alpha, new components are added as objects of the [CustomComponent](https://github.com/langflow-ai/langflow/blob/dev/src/backend/base/langflow/interface/custom/custom_component/custom_component.py) class and any dependencies are added to the [pyproject.toml](https://github.com/langflow-ai/langflow/blob/dev/pyproject.toml#L27) file. +New components are added as objects of the [CustomComponent](https://github.com/langflow-ai/langflow/blob/dev/src/backend/base/langflow/interface/custom/custom_component/custom_component.py) class and any dependencies are added to the [pyproject.toml](https://github.com/langflow-ai/langflow/blob/dev/pyproject.toml#L27) file. ## Add an example component diff --git a/docs/docs/getting-started/quickstart.mdx b/docs/docs/getting-started/quickstart.mdx index ca0b88b28..0ec833e7c 100644 --- a/docs/docs/getting-started/quickstart.mdx +++ b/docs/docs/getting-started/quickstart.mdx @@ -17,7 +17,7 @@ This guide demonstrates how to build a basic prompt flow and modify that prompt - [OpenAI API key](https://platform.openai.com) - Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space + Langflow is also available in HuggingFace Spaces. [Clone the space using this link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) to create your own Langflow workspace in minutes. diff --git a/docs/docs/index.mdx b/docs/docs/index.mdx index 64d55ec57..8a9e18abe 100644 --- a/docs/docs/index.mdx +++ b/docs/docs/index.mdx @@ -29,7 +29,7 @@ Its intuitive interface allows for easy manipulation of AI building blocks, enab - [Langflow Workspace](/getting-started/workspace) - Learn more about the Langflow workspace. - Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space + Langflow is also available in HuggingFace Spaces. [Clone the space using this link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) to create your own Langflow workspace in minutes. diff --git a/docs/docs/migration/possible-installation-issues.mdx b/docs/docs/migration/possible-installation-issues.mdx index 203996f39..15e7ea382 100644 --- a/docs/docs/migration/possible-installation-issues.mdx +++ b/docs/docs/migration/possible-installation-issues.mdx @@ -1,6 +1,6 @@ # ❗️ Common Installation Issues -This is a list of possible issues that you may encounter when installing Langflow 1.0 alpha and how to solve them. +This is a list of possible issues that you may encounter when installing Langflow and how to solve them. ## _`No module named 'langflow.__main__'`_ diff --git a/docs/docs/starter-projects/basic-prompting.mdx b/docs/docs/starter-projects/basic-prompting.mdx index 59519c91d..4e01f2472 100644 --- a/docs/docs/starter-projects/basic-prompting.mdx +++ b/docs/docs/starter-projects/basic-prompting.mdx @@ -19,7 +19,7 @@ This article demonstrates how to use Langflow's prompt tools to issue basic prom - [OpenAI API key created](https://platform.openai.com) - Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space + Langflow is also available in HuggingFace Spaces. [Clone the space using this link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) to create your own Langflow workspace in minutes. diff --git a/docs/docs/starter-projects/blog-writer.mdx b/docs/docs/starter-projects/blog-writer.mdx index ab8a600b6..efaad8030 100644 --- a/docs/docs/starter-projects/blog-writer.mdx +++ b/docs/docs/starter-projects/blog-writer.mdx @@ -15,7 +15,7 @@ Build a blog writer with OpenAI that uses URLs for reference content. - [OpenAI API key created](https://platform.openai.com) - Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space + Langflow is also available in HuggingFace Spaces. [Clone the space using this link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) to create your own Langflow workspace in minutes. diff --git a/docs/docs/starter-projects/document-qa.mdx b/docs/docs/starter-projects/document-qa.mdx index 0d64ed515..952285cdb 100644 --- a/docs/docs/starter-projects/document-qa.mdx +++ b/docs/docs/starter-projects/document-qa.mdx @@ -15,7 +15,7 @@ Build a question-and-answer chatbot with a document loaded from local memory. - [OpenAI API key created](https://platform.openai.com) - Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space + Langflow is also available in HuggingFace Spaces. [Clone the space using this link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) to create your own Langflow workspace in minutes. diff --git a/docs/docs/starter-projects/memory-chatbot.mdx b/docs/docs/starter-projects/memory-chatbot.mdx index e980cc8a1..8997170f8 100644 --- a/docs/docs/starter-projects/memory-chatbot.mdx +++ b/docs/docs/starter-projects/memory-chatbot.mdx @@ -15,7 +15,7 @@ This flow extends the [basic prompting flow](./basic-prompting) to include chat - [OpenAI API key created](https://platform.openai.com) - Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space + Langflow is also available in HuggingFace Spaces. [Clone the space using this link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) to create your own Langflow workspace in minutes. diff --git a/docs/docs/starter-projects/vector-store-rag.mdx b/docs/docs/starter-projects/vector-store-rag.mdx index 7cc4b3691..120978439 100644 --- a/docs/docs/starter-projects/vector-store-rag.mdx +++ b/docs/docs/starter-projects/vector-store-rag.mdx @@ -17,7 +17,7 @@ We've chosen [Astra DB](https://astra.datastax.com/signup?utm_source=langflow-pr ## Prerequisites - Langflow v1.0 alpha is also available in HuggingFace Spaces. [Clone the space + Langflow is also available in HuggingFace Spaces. [Clone the space using this link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) to create your own Langflow workspace in minutes. From 85c1d79d3e6a43d6aa00f60357882ebc7b3d0190 Mon Sep 17 00:00:00 2001 From: Mendon Kissling <59585235+mendonk@users.noreply.github.com> Date: Sun, 23 Jun 2024 10:07:52 -0400 Subject: [PATCH 027/229] memories --- docs/docs/administration/memories.mdx | 34 ++++++++++++++++++++++ docs/docs/administration/settings.mdx | 1 + docs/docs/components/text-and-record.mdx | 2 +- docs/docs/getting-started/workspace.mdx | 3 +- docs/sidebars.js | 1 + docs/static/img/chat-memory-component.png | Bin 0 -> 109650 bytes docs/static/img/playground-memories.png | Bin 0 -> 427260 bytes 7 files changed, 39 insertions(+), 2 deletions(-) create mode 100644 docs/docs/administration/memories.mdx create mode 100644 docs/static/img/chat-memory-component.png create mode 100644 docs/static/img/playground-memories.png diff --git a/docs/docs/administration/memories.mdx b/docs/docs/administration/memories.mdx new file mode 100644 index 000000000..e0679afc7 --- /dev/null +++ b/docs/docs/administration/memories.mdx @@ -0,0 +1,34 @@ +import ThemedImage from "@theme/ThemedImage"; +import useBaseUrl from "@docusaurus/useBaseUrl"; +import ZoomableImage from "/src/theme/ZoomableImage.js"; +import Admonition from "@theme/Admonition"; + +# Chat Memory + +Langflow allows every chat message to be stored, and a single flow can have multiple memory sessions. This enables you to create multiple “memories” for agents to store and recall specific information as needed. You can edit and remove previous messages to inspect and validate a model’s response behavior. Control, explore, and manage conversation histories to get your models acting just right. + +The **Chat Memory** component retrieves message histories by session ID. Users can change the session ID in the advanced settings, with the default session ID set to match the flow ID. These memories are accessible and manageable directly from the Playground; modifications to them directly affect the behavior of chatbot responses. Users can remove or edit previous messages to manipulate and explore model responses further. + + + +By default, chat conversations store Message objects categorized by session ID. A a single flow can host multiple session IDs, and different flows can also share the same session ID. + +Memories can be visualized and managed directly from the Playground. Modifying these memories will influence the behavior of the chatbot responses, as long as an agent uses them. Here you have the ability to remove or edit previous messages, allowing them to manipulate and explore how these changes affect model responses. + + + +You can also display all messages stored across every flow in your workspace by going to **Settings** > **Messages**. \ No newline at end of file diff --git a/docs/docs/administration/settings.mdx b/docs/docs/administration/settings.mdx index 39c6081c7..3599e967e 100644 --- a/docs/docs/administration/settings.mdx +++ b/docs/docs/administration/settings.mdx @@ -1,5 +1,6 @@ # Settings +Change the **Project Settings** or **General Settings** for Langflow. ## Project Settings diff --git a/docs/docs/components/text-and-record.mdx b/docs/docs/components/text-and-record.mdx index fe2e61644..e1ece5069 100644 --- a/docs/docs/components/text-and-record.mdx +++ b/docs/docs/components/text-and-record.mdx @@ -1,6 +1,6 @@ # Text and Data -In Langflow 1.0, we added two main input and output types: `Text` and `Data`. +There are two main input and output types: `Text` and `Data`. `Text` is a simple string input and output type, while `Data` is a structure very similar to a dictionary in Python. It is a key-value pair data structure. diff --git a/docs/docs/getting-started/workspace.mdx b/docs/docs/getting-started/workspace.mdx index eef951494..2372d8420 100644 --- a/docs/docs/getting-started/workspace.mdx +++ b/docs/docs/getting-started/workspace.mdx @@ -123,6 +123,7 @@ will see orange o and purple{" "} /> - - From the "My Collection” page, just click the Playground button in one of your flow cards. - It will directly open up a window with that project's Playground, without even showing the flow (this also works for flows hosted on the Langflow Store!). - - ## Playground I/O The Playground's window arrangement changes depending on what components are being used. @@ -61,3 +61,5 @@ When you send a message, under **Memories**, you can view a table of previous in Langflow allows every chat message to be stored, and a single flow can have multiple memory sessions. This enables you to create multiple “memories” for agents to store and recall specific information as needed. 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+ In the top right corner of the component, you'll find the component status icon (![Status icon](/logos/playbutton.svg)). Build the flow by clicking the **![Playground icon](/logos/botmessage.svg)Playground** at the bottom right of the workspace. @@ -255,7 +256,7 @@ The **curl** tab displays sample code for posting a query to your flow. Modify the `input_value` to change your input message. Copy the code and run it to post a query to your flow and get the result. -```curl +```bash curl -X POST \ http://127.0.0.1:7863/api/v1/run/f2eefd80-bb91-4190-9279-0d6ffafeaac4\?stream\=false \ -H 'Content-Type: application/json'\ diff --git a/docs/sidebars.js b/docs/sidebars.js index 491b1ce6e..fb3bfd788 100644 --- a/docs/sidebars.js +++ b/docs/sidebars.js @@ -40,6 +40,7 @@ module.exports = { "administration/login", "administration/cli", "administration/playground", + "administration/memories", "administration/collections-projects", "administration/settings", "administration/global-env", diff --git a/docs/static/img/chat-memory-component.png b/docs/static/img/chat-memory-component.png new file mode 100644 index 0000000000000000000000000000000000000000..3c9c7c92d857a4f588e6652c43d95d5f8aada2a3 GIT binary patch literal 109650 zcmeFZXH-+&);1iPprT+wqzEXY0s;a8(ouRxPb@c z^Q_{T1!SJ5UA5iXAr{Vk!Vg_*N4Y>$1ixH(Tlm-s;`qvKYJov?|5g1>flOj@zbjpY 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z61nAxAbs)mk%O&ZB;6C0G<`2yk`0I99v45E&y)n6KnA8YQWuNIla5_O@hvJw-Gghe zL_R5!S86*^E;(h9&qrnwK|rQgY=Fz%ON)~BjRG3X93k|0KC85KXzHnW`gYC36xoV$ zcUA;Go8V43Rb$gIr0NYa3cWap4V$k&NLo7^aWWoY9RRgJPqC|5cI-tvMz2BqhAi0S zk~jG61&Qb8BCzlj4caSuWW7;qfHk2ZJxT9*cK?h~_VTkm-yYQfYyA(}gFT$ErO2kp zUR*Hkx}dR(=dg3~UD+jq_`1ub`BoH{$Zl)><=Q&AKX!P&v^UZ8QkQKa=yDl!uznwl z;o1~Itry~P?U(=c_hq4nNUmSM@=~&}$_wiNf9%qF>Ap^4D;FBA;8;<2xq=<3(myt4 zJAc&jaM;hn<&xj*G`ZIC)Ni?$N&G9-nx{w2Y#c9acC{Dw>jcrz3lmTrYKo$$N<9cc n9%`^2Fjp{q68u)(zTVxf= literal 0 HcmV?d00001 From 6c65cc3f25ab1cef30b234b14f12393fbda9df61 Mon Sep 17 00:00:00 2001 From: Mendon Kissling <59585235+mendonk@users.noreply.github.com> Date: Sun, 23 Jun 2024 10:29:49 -0400 Subject: [PATCH 028/229] logs --- docs/docs/administration/logs.mdx | 24 ++++++++++++++++++++++++ 1 file changed, 24 insertions(+) create mode 100644 docs/docs/administration/logs.mdx diff --git a/docs/docs/administration/logs.mdx b/docs/docs/administration/logs.mdx new file mode 100644 index 000000000..8f26d2f8a --- /dev/null +++ b/docs/docs/administration/logs.mdx @@ -0,0 +1,24 @@ +import ThemedImage from "@theme/ThemedImage"; +import useBaseUrl from "@docusaurus/useBaseUrl"; +import ZoomableImage from "/src/theme/ZoomableImage.js"; +import ReactPlayer from "react-player"; +import Admonition from "@theme/Admonition"; + +# Logs + +To view logs, go to **Project Options** > **Logs**. + +The **Logs** page provides a detailed record of all component executions within a workspace. + +It is designed to help you track actions, debug issues, and understand the flow of data through various components. + +Each log entry includes an execution with source and target components, and displays the data and parameters passed from one component to another. The status of each execution is indicated and errors encountered are easily detected. + + \ No newline at end of file From d8169ee1a233bd59d136a81ba1441103fc0b6f36 Mon Sep 17 00:00:00 2001 From: Mendon Kissling <59585235+mendonk@users.noreply.github.com> Date: Sun, 23 Jun 2024 10:29:57 -0400 Subject: [PATCH 029/229] playground --- docs/docs/administration/playground.mdx | 12 +++++++----- docs/static/img/playground-logs.png | Bin 0 -> 649432 bytes 2 files changed, 7 insertions(+), 5 deletions(-) create mode 100644 docs/static/img/playground-logs.png diff --git a/docs/docs/administration/playground.mdx b/docs/docs/administration/playground.mdx index f67193daa..dec2225c8 100644 --- a/docs/docs/administration/playground.mdx +++ b/docs/docs/administration/playground.mdx @@ -6,6 +6,11 @@ import Admonition from "@theme/Admonition"; # Playground + + From the **My Collection** page, click the Playground button in one of your flow cards. + It will directly open up a window with that project's Playground, without even showing the flow (this also works for flows hosted on the Langflow Store!). + + The **Playground** is a dynamic interface designed for real-time interaction with agents, allowing users to access and manage memories and monitor the inputs and outputs. Here, users can directly prototype and experiment with their configured components or AI models, making adjustments and observing different outcomes in real-time. It even works for flows hosted on the Langflow store! @@ -32,11 +37,6 @@ As long as you have a flow properly working, you can interact with it by clickin

\ No newline at end of file +
diff --git a/docs/docs/index.mdx b/docs/docs/index.mdx index 8a9e18abe..c6b6e0e71 100644 --- a/docs/docs/index.mdx +++ b/docs/docs/index.mdx @@ -5,14 +5,15 @@ import Admonition from "@theme/Admonition"; # 👋 Welcome to Langflow -Langflow is a new, visual way to build, iterate, and deploy AI applications. +Langflow is a new, visual framework for building multi-agent and RAG applications. It is open-source, Python-powered, fully customizable, LLM and vector store agnostic. Its intuitive interface allows for easy manipulation of AI building blocks, enabling developers to quickly prototype and turn their ideas into powerful, real-world solutions. {" "} +{/* rsn */} - Langflow is also available in HuggingFace Spaces. [Clone the space - using this + Langflow is also available in HuggingFace Spaces. [Clone the space using this link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) - to create your own Langflow workspace in minutes. + to run your own Langflow instance in minutes. ## Learn more about Langflow 1.0 Learn more about the exciting changes in Langflow 1.0, and how to migrate your existing Langflow projects. +{/* rsn */} + - [A new chapter for Langflow](/whats-new/a-new-chapter-langflow) - [Migration guides](/migration/migrating-to-one-point-zero) diff --git a/docs/static/img/basic-prompting.png b/docs/static/img/basic-prompting.png index 76d658a2dfb51248ab4f801c844782affe3fef4b..b56696f44e5a3ec8bc2813f5f0b3840446b002f0 100644 GIT binary patch literal 263804 zcmeF3XH-*L_wG@|hJuQMbQKkq5*6tsSipjSh|-%xKnW0v^b*mdNI$56)F>*51TY{S z5|rLWA(R9{4-f*Xl13xwv*zb8+zmZQlw$5qy&;170?H-MoB(E3aK_3jF7igV|L_eSNM|;Qe;4 zO=0)Bwy-w=KO*3Vi;Mg9CN6I9x{3YS>&^fE>yGNz-2Z;h6U5%|^w-;=TwK~*S1+Bv z<+o{OV8^SYQ|1RJaTPfg7ZV$T)1LnQT@ah*-r)LQHeY* 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They consist of inputs, outputs, an style={{ width: "100%", margin: "20px auto" }} /> -

*/} {/\* ### Multiple outputs diff --git a/docs/docs/integrations/langsmith/intro.mdx b/docs/docs/integrations/langsmith/intro.mdx new file mode 100644 index 000000000..68f28a891 --- /dev/null +++ b/docs/docs/integrations/langsmith/intro.mdx @@ -0,0 +1,46 @@ +import Admonition from "@theme/Admonition"; +import ThemedImage from "@theme/ThemedImage"; +import useBaseUrl from "@docusaurus/useBaseUrl"; +import ZoomableImage from "/src/theme/ZoomableImage.js"; + +# LangSmith + +LangSmith is a full-lifecycle DevOps service from LangChain that provides monitoring and observability. To integrate with Langflow, just add your LangChain API key as a Langflow environment variable and you are good to go! + +## Step-by-step Configuration + +1. Obtain your LangChain API key from https://smith.langchain.com +2. Add the following keys to Langflow .env file: + +```bash +LANGCHAIN_API_KEY="your-api-key" +LANGCHAIN_PROJECT="your-project-name" +``` + +or export the environment variables in your terminal: + +```bash +export LANGCHAIN_API_KEY="your-api-key" +export LANGCHAIN_PROJECT="your-project-name" +``` + +3. Restart Langflow using `langflow run --env-file .env` +4. Run any project and check the LangSmith dashboard for monitoring and observability. + + + + diff --git a/docs/sidebars.js b/docs/sidebars.js index 37ef65f14..20f5dafb9 100644 --- a/docs/sidebars.js +++ b/docs/sidebars.js @@ -141,6 +141,7 @@ module.exports = { label: "Integrations", collapsed: false, items: [ + "integrations/langsmith/intro", { type: "category", label: "Notion", @@ -157,6 +158,13 @@ module.exports = { "integrations/notion/page-content-viewer", ], }, + // { + // type: "category", + // label: "LangSmith", + // items: [ + // , + // ], + // }, ], }, ], diff --git a/docs/static/img/langsmith-flow.png b/docs/static/img/langsmith-flow.png new file mode 100644 index 0000000000000000000000000000000000000000..c7e44edd5443fa0df779599a417af4e81a6af58b GIT binary patch literal 305642 zcmeEuX3sh}cKqLLzzqM+h%misx+`<~zV@NS>;>3rB9RD}Cp!?o76?(2X3{}-_r zFIa8a2-&!5)v7J0Po1z`wQA$hRjbxEtp5ePgJWOR2Y-I@x3xO9s;FIQ6#R3-1AhAY z`SYs|g4gR;{SS+#1-^Pg6&0e^p5e((9}e}B61=<_xIe!aF~`NE@- 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docs/docs/examples/chat-memory.mdx | 2 +- docs/docs/examples/combine-text.mdx | 2 +- .../docs/getting-started/rag-with-astradb.mdx | 19 +++++++------------ docs/docs/index.mdx | 12 +++++++----- .../docs/starter-projects/basic-prompting.mdx | 9 +-------- docs/docs/starter-projects/blog-writer.mdx | 13 +++++++------ docs/docs/starter-projects/document-qa.mdx | 7 ------- docs/docs/starter-projects/memory-chatbot.mdx | 9 +-------- .../starter-projects/vector-store-rag.mdx | 7 ------- docs/docs/tutorials/rag-with-astradb.mdx | 3 +-- 10 files changed, 26 insertions(+), 57 deletions(-) diff --git a/docs/docs/examples/chat-memory.mdx b/docs/docs/examples/chat-memory.mdx index 88dbbca2b..174711ce8 100644 --- a/docs/docs/examples/chat-memory.mdx +++ b/docs/docs/examples/chat-memory.mdx @@ -8,7 +8,7 @@ import Admonition from "@theme/Admonition"; The **Chat Memory** component restores previous messages given a Session ID, which can be any string. -This component is available under the **Helpers** tab of the Langflow preview. +This component is available under the **Helpers** tab of the Langflow sidebar.

- Langflow is also available in HuggingFace Spaces. [Clone the space using this - link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) - to run your own Langflow instance in minutes. - +{/* Mentions wrong link */} +{/\* +Langflow is also available in HuggingFace Spaces. [Clone the space using this +link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) +to run your own Langflow instance in minutes. + + */} ## Learn more about Langflow 1.0 diff --git a/docs/docs/starter-projects/basic-prompting.mdx b/docs/docs/starter-projects/basic-prompting.mdx index 4e01f2472..594990eb6 100644 --- a/docs/docs/starter-projects/basic-prompting.mdx +++ b/docs/docs/starter-projects/basic-prompting.mdx @@ -18,13 +18,6 @@ This article demonstrates how to use Langflow's prompt tools to issue basic prom - [OpenAI API key created](https://platform.openai.com) - - Langflow is also available in HuggingFace Spaces. [Clone the space - using this - link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) - to create your own Langflow workspace in minutes. - - ## Create the basic prompting project 1. From the Langflow dashboard, click **New Project**. @@ -62,4 +55,4 @@ This should be interesting... The **Edit Prompt** window opens. 2. Change `Answer the user as if you were a pirate` to a different character, perhaps `Answer the user as if you were Harold Abelson.` 3. Run the basic prompting flow again. - The response will be markedly different. \ No newline at end of file + The response will be markedly different. diff --git a/docs/docs/starter-projects/blog-writer.mdx b/docs/docs/starter-projects/blog-writer.mdx index efaad8030..1c19c06b6 100644 --- a/docs/docs/starter-projects/blog-writer.mdx +++ b/docs/docs/starter-projects/blog-writer.mdx @@ -14,12 +14,13 @@ Build a blog writer with OpenAI that uses URLs for reference content. - [OpenAI API key created](https://platform.openai.com) - - Langflow is also available in HuggingFace Spaces. [Clone the space - using this - link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) - to create your own Langflow workspace in minutes. - +{/\* +Langflow is also available in HuggingFace Spaces. [Clone the space +using this +link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) +to create your own Langflow workspace in minutes. + + */} ## Create the Blog Writer project diff --git a/docs/docs/starter-projects/document-qa.mdx b/docs/docs/starter-projects/document-qa.mdx index 952285cdb..2e452522e 100644 --- a/docs/docs/starter-projects/document-qa.mdx +++ b/docs/docs/starter-projects/document-qa.mdx @@ -14,13 +14,6 @@ Build a question-and-answer chatbot with a document loaded from local memory. - [OpenAI API key created](https://platform.openai.com) - - Langflow is also available in HuggingFace Spaces. [Clone the space - using this - link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) - to create your own Langflow workspace in minutes. - - ## Create the Document QA project 1. From the Langflow dashboard, click **New Project**. diff --git a/docs/docs/starter-projects/memory-chatbot.mdx b/docs/docs/starter-projects/memory-chatbot.mdx index 8997170f8..bf5a428ca 100644 --- a/docs/docs/starter-projects/memory-chatbot.mdx +++ b/docs/docs/starter-projects/memory-chatbot.mdx @@ -14,13 +14,6 @@ This flow extends the [basic prompting flow](./basic-prompting) to include chat - [OpenAI API key created](https://platform.openai.com) - - Langflow is also available in HuggingFace Spaces. [Clone the space - using this - link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) - to create your own Langflow workspace in minutes. - - ## Create the memory chatbot project 1. From the Langflow dashboard, click **New Project**. @@ -81,4 +74,4 @@ To store **Session ID** as a Langflow variable, in the **Session ID** field, cli 1. In the **Variable Name** field, enter a name like `customer_chat_emea`. 2. In the **Value** field, enter a value like `1B5EBD79-6E9C-4533-B2C8-7E4FF29E983B`. 3. Click **Save Variable**. -4. Apply this variable to **Chat Input**. \ No newline at end of file +4. Apply this variable to **Chat Input**. diff --git a/docs/docs/starter-projects/vector-store-rag.mdx b/docs/docs/starter-projects/vector-store-rag.mdx index 120978439..4354295d8 100644 --- a/docs/docs/starter-projects/vector-store-rag.mdx +++ b/docs/docs/starter-projects/vector-store-rag.mdx @@ -16,13 +16,6 @@ We've chosen [Astra DB](https://astra.datastax.com/signup?utm_source=langflow-pr ## Prerequisites - - Langflow is also available in HuggingFace Spaces. [Clone the space - using this - link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) - to create your own Langflow workspace in minutes. - - - [Langflow installed and running](../getting-started/install-langflow) - [OpenAI API key](https://platform.openai.com) diff --git a/docs/docs/tutorials/rag-with-astradb.mdx b/docs/docs/tutorials/rag-with-astradb.mdx index 6cf5c172d..e3f4a3f1e 100644 --- a/docs/docs/tutorials/rag-with-astradb.mdx +++ b/docs/docs/tutorials/rag-with-astradb.mdx @@ -20,9 +20,8 @@ In this guide, we will use Astra DB as a vector store to store and retrieve the TLDR; - [Create a free Astra DB account](https://astra.datastax.com/signup?utm_source=langflow-pre-release&utm_medium=referral&utm_campaign=langflow-announcement&utm_content=create-a-free-astra-db-account) -- Duplicate our [Langflow 1.0 Space](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) - Create a new database, get a **Token** and the **API Endpoint** -- Click on the **New Project** button and look for Vector Store RAG. This will create a new project with the necessary components +- Start Langflow and click on the **New Project** button and look for Vector Store RAG. This will create a new project with the necessary components - Import the project into Langflow by dropping it on the Workspace or My Collection page - Update the **Token** and **API Endpoint** in the **Astra DB** components - Update the OpenAI API key in the **OpenAI** components From 285355c3bb6bea5052f9992dd5a811c5cb0a189d Mon Sep 17 00:00:00 2001 From: Carlos Date: Mon, 24 Jun 2024 01:04:05 -0300 Subject: [PATCH 035/229] - fix wrong comments - add comments in some catogories - change Custom Component title --- docs/docs/components/custom.mdx | 6 +-- docs/sidebars.js | 83 +++++++++++++++++---------------- 2 files changed, 45 insertions(+), 44 deletions(-) diff --git a/docs/docs/components/custom.mdx b/docs/docs/components/custom.mdx index 7ea32701f..f8af904b0 100644 --- a/docs/docs/components/custom.mdx +++ b/docs/docs/components/custom.mdx @@ -4,7 +4,7 @@ import ZoomableImage from "/src/theme/ZoomableImage.js"; import ReactPlayer from "react-player"; import Admonition from "@theme/Admonition"; -# Creating Custom Components in Langflow +# Custom Components Build custom components in Langflow for various data processing and transformation tasks. @@ -152,7 +152,7 @@ def process_data(self) -> Data: This example demonstrates a more complex component that routes data based on a condition. -Notice that this component has two outputs associated with the methods `true_response` and `false_response`. +Notice that this component has two outputs associated with the methods `true_response` and `false_response`. These methods trigger `self.stop` to block the transmission for the selected output, allowing for logic operations to be implemented visually. @@ -221,5 +221,3 @@ class ConditionalRouterComponent(Component): By following these steps and examples, you can create custom components in Langflow tailored to your specific needs. The modular structure of Custom Components allows for flexible and reusable components that can be easily integrated into your workflows. --- - - diff --git a/docs/sidebars.js b/docs/sidebars.js index 20f5dafb9..b9bd08828 100644 --- a/docs/sidebars.js +++ b/docs/sidebars.js @@ -50,7 +50,7 @@ module.exports = { }, { type: "category", - label: "Core Components", + label: "Components", collapsed: false, items: [ "components/inputs-and-outputs", @@ -63,45 +63,48 @@ module.exports = { "components/custom", ], }, - { - type: "category", - label: "Extended Components", - collapsed: true, - items: [ - "components/agents", - "components/chains", - "components/experimental", - "components/utilities", - "components/model_specs", - "components/retrievers", - "components/text-splitters", - "components/toolkits", - "components/tools", - ], - }, - { - type: "category", - label: "Example Components", - collapsed: true, - items: [ - "examples/chat-memory", - "examples/combine-text", - "examples/create-record", - "examples/pass", - "examples/store-message", - "examples/sub-flow", - "examples/text-operator", - ], - }, - { - type: "category", - label: "Migration", - collapsed: false, - items: [ - "migration/migrating-to-one-point-zero", - "migration/compatibility", - ], - }, + // RSN - Check if we need this + // { + // type: "category", + // label: "Extended Components", + // collapsed: true, + // items: [ + // "components/agents", + // "components/chains", + // "components/experimental", + // "components/utilities", + // "components/model_specs", + // "components/retrievers", + // "components/text-splitters", + // "components/toolkits", + // "components/tools", + // ], + // }, + // RSN - Check if we need this + // { + // type: "category", + // label: "Example Components", + // collapsed: true, + // items: [ + // "examples/chat-memory", + // "examples/combine-text", + // "examples/create-record", + // "examples/pass", + // "examples/store-message", + // "examples/sub-flow", + // "examples/text-operator", + // ], + // }, + // RSN - Check if we need this + // { + // type: "category", + // label: "Migration", + // collapsed: false, + // items: [ + // "migration/migrating-to-one-point-zero", + // "migration/compatibility", + // ], + // }, { type: "category", label: "Tutorials", From b2224a31793252f1c13a40efc082ef330d3c0680 Mon Sep 17 00:00:00 2001 From: Rodrigo Date: Mon, 24 Jun 2024 01:18:21 -0300 Subject: [PATCH 036/229] remove wrong regex --- docs/docs/getting-started/workspace.mdx | 12 ++---------- docs/docs/index.mdx | 10 ---------- docs/docs/starter-projects/blog-writer.mdx | 8 -------- 3 files changed, 2 insertions(+), 28 deletions(-) diff --git a/docs/docs/getting-started/workspace.mdx b/docs/docs/getting-started/workspace.mdx index aefe38751..374faca74 100644 --- a/docs/docs/getting-started/workspace.mdx +++ b/docs/docs/getting-started/workspace.mdx @@ -108,17 +108,9 @@ Components are the building blocks of flows. They consist of inputs, outputs, an {/*
*/} -{/\* On the top right corner of the component, you'll find the component status icon (![Status icon](/logos/playbutton.svg)). -Build the flow by clicking the **![Playground icon](/logos/botmessage.svg)Playground** at the bottom right of the workspace. +On the top right corner of the component, you'll find the a play button to run a component. Once it runs, a status icon appears and you can hover over that to visualize success or error messages. -Once the validation is complete, the status of each validated component should turn green (![Status icon](/logos/greencheck.svg)). -To debug, hover over the component status to see the outputs. \*/} - -{/*
*/} - -{/\* ### Multiple outputs - -A component can have multiple outputs. For example, this one Chat Input component routes through three prompt chains, and returns three different responses to a single question in the Playground. \*/} +Start interacting with your AI by clicking the **![Playground icon](/logos/botmessage.svg)Playground** at the bottom right of the workspace. ### Output Preview diff --git a/docs/docs/index.mdx b/docs/docs/index.mdx index 7e85c97cd..64946d6ad 100644 --- a/docs/docs/index.mdx +++ b/docs/docs/index.mdx @@ -29,19 +29,9 @@ Its intuitive interface allows for easy manipulation of AI building blocks, enab - [Langflow Workspace](/getting-started/workspace) - Learn more about the Langflow Workspace. -{/* Mentions wrong link */} -{/\* -Langflow is also available in HuggingFace Spaces. [Clone the space using this -link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) -to run your own Langflow instance in minutes. - - */} - ## Learn more about Langflow 1.0 Learn more about the exciting changes in Langflow 1.0, and how to migrate your existing Langflow projects. -{/* rsn */} - - [A new chapter for Langflow](/whats-new/a-new-chapter-langflow) - [Migration guides](/migration/migrating-to-one-point-zero) diff --git a/docs/docs/starter-projects/blog-writer.mdx b/docs/docs/starter-projects/blog-writer.mdx index 1c19c06b6..75f725d94 100644 --- a/docs/docs/starter-projects/blog-writer.mdx +++ b/docs/docs/starter-projects/blog-writer.mdx @@ -14,14 +14,6 @@ Build a blog writer with OpenAI that uses URLs for reference content. - [OpenAI API key created](https://platform.openai.com) -{/\* -Langflow is also available in HuggingFace Spaces. [Clone the space -using this -link](https://huggingface.co/spaces/Langflow/Langflow-Preview?duplicate=true) -to create your own Langflow workspace in minutes. - - */} - ## Create the Blog Writer project 1. From the Langflow dashboard, click **New Project**. From 5457af1f006f85d283bd462aa248306d56eaafd2 Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Mon, 24 Jun 2024 08:30:58 -0300 Subject: [PATCH 037/229] Changed possible instalation issues' location --- .../possible-installation-issues.mdx | 6 ++++++ docs/sidebars.js | 2 +- 2 files changed, 7 insertions(+), 1 deletion(-) rename docs/docs/{migration => getting-started}/possible-installation-issues.mdx (91%) diff --git a/docs/docs/migration/possible-installation-issues.mdx b/docs/docs/getting-started/possible-installation-issues.mdx similarity index 91% rename from docs/docs/migration/possible-installation-issues.mdx rename to docs/docs/getting-started/possible-installation-issues.mdx index 15e7ea382..21e6a5d1a 100644 --- a/docs/docs/migration/possible-installation-issues.mdx +++ b/docs/docs/getting-started/possible-installation-issues.mdx @@ -1,5 +1,11 @@ +import Admonition from "@theme/Admonition"; + # ❗️ Common Installation Issues + +This page may contain outdated information. It will be updated as soon as possible. + + This is a list of possible issues that you may encounter when installing Langflow and how to solve them. ## _`No module named 'langflow.__main__'`_ diff --git a/docs/sidebars.js b/docs/sidebars.js index b9bd08828..40f07baa0 100644 --- a/docs/sidebars.js +++ b/docs/sidebars.js @@ -15,7 +15,7 @@ module.exports = { "getting-started/install-langflow", "getting-started/quickstart", "getting-started/workspace", - "migration/possible-installation-issues", + "getting-started/possible-installation-issues", "getting-started/new-to-llms", ], }, From 21fd151fdc839152f0266d0e01d6182a6de395c1 Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Mon, 24 Jun 2024 08:31:06 -0300 Subject: [PATCH 038/229] Removed top bar --- docs/docusaurus.config.js | 7 ------- 1 file changed, 7 deletions(-) diff --git a/docs/docusaurus.config.js b/docs/docusaurus.config.js index 9580d7835..e42512b91 100644 --- a/docs/docusaurus.config.js +++ b/docs/docusaurus.config.js @@ -122,13 +122,6 @@ module.exports = { /* Respect user preferences, such as low light mode in the evening */ respectPrefersColorScheme: true, }, - announcementBar: { - content: - '⭐️ If you like ⛓️Langflow, star it on GitHub! ⭐️', - backgroundColor: "#E8EBF1", //Mustard Yellow #D19900 #D4B20B - Salmon #E9967A - textColor: "#1C1E21", - isCloseable: false, - }, zoom: { selector: ".markdown :not(a) > img:not(.no-zoom)", background: { From 9b88eab828c9fc03d08cccd3ce180a301a17a3f6 Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Mon, 24 Jun 2024 08:31:18 -0300 Subject: [PATCH 039/229] Added warning of outdated information to all components --- docs/docs/administration/api.mdx | 4 ++++ docs/docs/administration/chat-widget.mdx | 4 ++++ docs/docs/administration/cli.mdx | 6 ++++++ docs/docs/administration/collections-projects.mdx | 4 ++++ docs/docs/administration/global-env.mdx | 4 ++++ docs/docs/administration/login.mdx | 4 ++++ docs/docs/administration/logs.mdx | 4 ++++ docs/docs/administration/memories.mdx | 4 ++++ docs/docs/administration/playground.mdx | 4 ++++ docs/docs/administration/prompt-customization.mdx | 4 ++++ docs/docs/administration/settings.mdx | 6 ++++++ docs/docs/components/agents.mdx | 4 ++++ docs/docs/components/chains.mdx | 4 ++++ docs/docs/components/custom.mdx | 4 ++++ docs/docs/components/data.mdx | 4 ++++ docs/docs/components/embeddings.mdx | 6 ++++++ docs/docs/components/experimental.mdx | 4 ++++ docs/docs/components/helpers.mdx | 4 ++++ docs/docs/components/inputs-and-outputs.mdx | 4 ++++ docs/docs/components/loaders.mdx | 4 ++++ docs/docs/components/memories.mdx | 4 ++++ docs/docs/components/model_specs.mdx | 4 ++++ docs/docs/components/models.mdx | 4 ++++ docs/docs/components/retrievers.mdx | 4 ++++ docs/docs/components/text-and-record.mdx | 6 ++++++ docs/docs/components/text-splitters.mdx | 4 ++++ docs/docs/components/toolkits.mdx | 4 ++++ docs/docs/components/tools.mdx | 4 ++++ docs/docs/components/utilities.mdx | 4 ++++ docs/docs/components/vector-stores.mdx | 4 ++++ docs/docs/contributing/{community.md => community.mdx} | 6 ++++++ .../{contribute-component.md => contribute-component.mdx} | 5 +++++ .../contributing/{github-issues.md => github-issues.mdx} | 6 ++++++ .../contributing/{how-contribute.md => how-contribute.mdx} | 6 ++++++ docs/docs/deployment/{backend-only.md => backend-only.mdx} | 6 ++++++ docs/docs/deployment/{docker.md => docker.mdx} | 6 ++++++ .../deployment/{gcp-deployment.md => gcp-deployment.mdx} | 6 ++++++ docs/docs/examples/chat-memory.mdx | 4 ++++ docs/docs/examples/combine-text.mdx | 4 ++++ docs/docs/examples/create-record.mdx | 4 ++++ docs/docs/examples/pass.mdx | 4 ++++ docs/docs/examples/store-message.mdx | 4 ++++ docs/docs/examples/sub-flow.mdx | 4 ++++ docs/docs/examples/text-operator.mdx | 4 ++++ docs/docs/getting-started/install-langflow.mdx | 4 ++++ docs/docs/getting-started/quickstart.mdx | 4 ++++ docs/docs/getting-started/rag-with-astradb.mdx | 4 ++++ docs/docs/getting-started/workspace.mdx | 4 ++++ docs/docs/integrations/langsmith/intro.mdx | 4 ++++ docs/docs/integrations/notion/add-content-to-page.md | 4 ++++ docs/docs/integrations/notion/intro.md | 4 ++++ docs/docs/integrations/notion/list-database-properties.md | 4 ++++ docs/docs/integrations/notion/list-pages.md | 4 ++++ docs/docs/integrations/notion/list-users.md | 4 ++++ docs/docs/integrations/notion/page-content-viewer.md | 4 ++++ docs/docs/integrations/notion/page-create.md | 4 ++++ docs/docs/integrations/notion/page-update.md | 4 ++++ docs/docs/integrations/notion/search.md | 4 ++++ docs/docs/integrations/notion/setup.md | 4 ++++ docs/docs/migration/compatibility.mdx | 4 ++++ docs/docs/migration/migrating-to-one-point-zero.mdx | 4 ++++ docs/docs/starter-projects/basic-prompting.mdx | 4 ++++ docs/docs/starter-projects/blog-writer.mdx | 4 ++++ docs/docs/starter-projects/document-qa.mdx | 4 ++++ docs/docs/starter-projects/memory-chatbot.mdx | 4 ++++ docs/docs/starter-projects/vector-store-rag.mdx | 4 ++++ docs/docs/tutorials/chatprompttemplate_guide.mdx | 5 +++++ docs/docs/tutorials/custom_components.mdx | 4 ++++ docs/docs/tutorials/loading_document.mdx | 5 +++++ docs/docs/tutorials/rag-with-astradb.mdx | 4 ++++ 70 files changed, 303 insertions(+) rename docs/docs/contributing/{community.md => community.mdx} (85%) rename docs/docs/contributing/{contribute-component.md => contribute-component.mdx} (94%) rename docs/docs/contributing/{github-issues.md => github-issues.mdx} (88%) rename docs/docs/contributing/{how-contribute.md => how-contribute.mdx} (92%) rename docs/docs/deployment/{backend-only.md => backend-only.mdx} (96%) rename docs/docs/deployment/{docker.md => docker.mdx} (90%) rename docs/docs/deployment/{gcp-deployment.md => gcp-deployment.mdx} (93%) diff --git a/docs/docs/administration/api.mdx b/docs/docs/administration/api.mdx index db74fa506..737213cfd 100644 --- a/docs/docs/administration/api.mdx +++ b/docs/docs/administration/api.mdx @@ -4,6 +4,10 @@ import Admonition from "@theme/Admonition"; # API Keys + +This page may contain outdated information. It will be updated as soon as possible. + + Langflow provides an API key functionality that allows users to access their individual components and flows without traditional login authentication. The API key is a user-specific token that can be included in the request header or query parameter to authenticate API calls. This documentation outlines how to generate, use, and manage API keys in Langflow. diff --git a/docs/docs/administration/chat-widget.mdx b/docs/docs/administration/chat-widget.mdx index 0a6669cdd..e4d744a40 100644 --- a/docs/docs/administration/chat-widget.mdx +++ b/docs/docs/administration/chat-widget.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Chat Widget + +This page may contain outdated information. It will be updated as soon as possible. + +
The Langflow Chat Widget is a powerful web component that enables communication with a Langflow project. This widget allows for a chat interface diff --git a/docs/docs/administration/cli.mdx b/docs/docs/administration/cli.mdx index 4f11cc721..2a54c1fca 100644 --- a/docs/docs/administration/cli.mdx +++ b/docs/docs/administration/cli.mdx @@ -1,5 +1,11 @@ +import Admonition from "@theme/Admonition"; + # Command Line Interface (CLI) + +This page may contain outdated information. It will be updated as soon as possible. + + Langflow's Command Line Interface (CLI) is a powerful tool that allows you to interact with the Langflow server from the command line. The CLI provides a wide range of commands to help you shape Langflow to your needs. The available commands are below. Navigate to their individual sections of this page to see the parameters. diff --git a/docs/docs/administration/collections-projects.mdx b/docs/docs/administration/collections-projects.mdx index d289b5d71..f0ef70ee4 100644 --- a/docs/docs/administration/collections-projects.mdx +++ b/docs/docs/administration/collections-projects.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Collections and Projects + +This page may contain outdated information. It will be updated as soon as possible. + + My Collection is a space in Langflow where users can manage, organize, and access their flows and components. Flows and components are displayed as individual cards that provide relevant information. diff --git a/docs/docs/administration/global-env.mdx b/docs/docs/administration/global-env.mdx index 06ef488a8..fa8f7ff5d 100644 --- a/docs/docs/administration/global-env.mdx +++ b/docs/docs/administration/global-env.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Global Variables + +This page may contain outdated information. It will be updated as soon as possible. + + Global Variables are a useful feature of Langflow, allowing you to define reusable variables accessed from any Text field in your project. **TL;DR** diff --git a/docs/docs/administration/login.mdx b/docs/docs/administration/login.mdx index 9f3c12cf9..65ed2c178 100644 --- a/docs/docs/administration/login.mdx +++ b/docs/docs/administration/login.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Sign Up and Sign In + +This page may contain outdated information. It will be updated as soon as possible. + + The login functionality in Langflow serves to authenticate users and protect sensitive routes in the application. Starting from version 0.5, Langflow introduces an enhanced login mechanism that is governed by a few environment variables. This allows new secure features. ## Environment variables diff --git a/docs/docs/administration/logs.mdx b/docs/docs/administration/logs.mdx index 8f26d2f8a..85c1497be 100644 --- a/docs/docs/administration/logs.mdx +++ b/docs/docs/administration/logs.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Logs + +This page may contain outdated information. It will be updated as soon as possible. + + To view logs, go to **Project Options** > **Logs**. The **Logs** page provides a detailed record of all component executions within a workspace. diff --git a/docs/docs/administration/memories.mdx b/docs/docs/administration/memories.mdx index e0679afc7..5946590ec 100644 --- a/docs/docs/administration/memories.mdx +++ b/docs/docs/administration/memories.mdx @@ -5,6 +5,10 @@ import Admonition from "@theme/Admonition"; # Chat Memory + +This page may contain outdated information. It will be updated as soon as possible. + + Langflow allows every chat message to be stored, and a single flow can have multiple memory sessions. This enables you to create multiple “memories” for agents to store and recall specific information as needed. You can edit and remove previous messages to inspect and validate a model’s response behavior. Control, explore, and manage conversation histories to get your models acting just right. The **Chat Memory** component retrieves message histories by session ID. Users can change the session ID in the advanced settings, with the default session ID set to match the flow ID. These memories are accessible and manageable directly from the Playground; modifications to them directly affect the behavior of chatbot responses. Users can remove or edit previous messages to manipulate and explore model responses further. diff --git a/docs/docs/administration/playground.mdx b/docs/docs/administration/playground.mdx index dec2225c8..1ef59e08b 100644 --- a/docs/docs/administration/playground.mdx +++ b/docs/docs/administration/playground.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Playground + +This page may contain outdated information. It will be updated as soon as possible. + + From the **My Collection** page, click the Playground button in one of your flow cards. It will directly open up a window with that project's Playground, without even showing the flow (this also works for flows hosted on the Langflow Store!). diff --git a/docs/docs/administration/prompt-customization.mdx b/docs/docs/administration/prompt-customization.mdx index 2a1b1f210..661610611 100644 --- a/docs/docs/administration/prompt-customization.mdx +++ b/docs/docs/administration/prompt-customization.mdx @@ -5,6 +5,10 @@ import ReactPlayer from "react-player"; # Prompt Customization + +This page may contain outdated information. It will be updated as soon as possible. + + The prompt template allows users to create prompts and define variables that provide control over instructing the model. {" "} diff --git a/docs/docs/administration/settings.mdx b/docs/docs/administration/settings.mdx index 3599e967e..dba6da78b 100644 --- a/docs/docs/administration/settings.mdx +++ b/docs/docs/administration/settings.mdx @@ -1,5 +1,11 @@ +import Admonition from "@theme/Admonition"; + # Settings + +This page may contain outdated information. It will be updated as soon as possible. + + Change the **Project Settings** or **General Settings** for Langflow. ## Project Settings diff --git a/docs/docs/components/agents.mdx b/docs/docs/components/agents.mdx index 00d597804..4482c0637 100644 --- a/docs/docs/components/agents.mdx +++ b/docs/docs/components/agents.mdx @@ -2,6 +2,10 @@ import Admonition from "@theme/Admonition"; # Agents + +This page may contain outdated information. It will be updated as soon as possible. + + Agents are components that use reasoning to make decisions and take actions, designed to autonomously perform tasks or provide services with some degree of agency. LLM chains can only perform hardcoded sequences of actions, while agents use LLMs to reason through which actions to take, and in which order. --- diff --git a/docs/docs/components/chains.mdx b/docs/docs/components/chains.mdx index a57f442e3..3d4b60b6a 100644 --- a/docs/docs/components/chains.mdx +++ b/docs/docs/components/chains.mdx @@ -5,6 +5,10 @@ import Admonition from "@theme/Admonition"; # Chains + +This page may contain outdated information. It will be updated as soon as possible. + + Chains, in the context of language models, refer to a series of calls made to a language model. This approach allows for using the output of one call as the input for another. Different chain types facilitate varying complexity levels, making them useful for creating pipelines and executing specific scenarios. --- diff --git a/docs/docs/components/custom.mdx b/docs/docs/components/custom.mdx index f8af904b0..2d8ac9d87 100644 --- a/docs/docs/components/custom.mdx +++ b/docs/docs/components/custom.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Custom Components + +This page may contain outdated information. It will be updated as soon as possible. + + Build custom components in Langflow for various data processing and transformation tasks. This guide provides a comprehensive overview of how to create custom components using Langflow. diff --git a/docs/docs/components/data.mdx b/docs/docs/components/data.mdx index d7f525d7d..2c62b2664 100644 --- a/docs/docs/components/data.mdx +++ b/docs/docs/components/data.mdx @@ -2,6 +2,10 @@ import Admonition from "@theme/Admonition"; # Data + +This page may contain outdated information. It will be updated as soon as possible. + + ## API Request This component sends HTTP requests to the specified URLs. diff --git a/docs/docs/components/embeddings.mdx b/docs/docs/components/embeddings.mdx index 24743ec1c..9a224b048 100644 --- a/docs/docs/components/embeddings.mdx +++ b/docs/docs/components/embeddings.mdx @@ -1,5 +1,11 @@ +import Admonition from "@theme/Admonition"; + # Embeddings + +This page may contain outdated information. It will be updated as soon as possible. + + ## Amazon Bedrock Embeddings Used to load embedding models from [Amazon Bedrock](https://aws.amazon.com/bedrock/). diff --git a/docs/docs/components/experimental.mdx b/docs/docs/components/experimental.mdx index a6f35d024..5abee146d 100644 --- a/docs/docs/components/experimental.mdx +++ b/docs/docs/components/experimental.mdx @@ -2,6 +2,10 @@ import Admonition from "@theme/Admonition"; # Experimental + +This page may contain outdated information. It will be updated as soon as possible. + + Components in the experimental phase are currently in beta. They have been initially developed and tested but haven't yet achieved a stable or fully supported status. We encourage users to explore these components, provide feedback, and report any issues encountered. --- diff --git a/docs/docs/components/helpers.mdx b/docs/docs/components/helpers.mdx index 59fb63564..c30315a42 100644 --- a/docs/docs/components/helpers.mdx +++ b/docs/docs/components/helpers.mdx @@ -2,6 +2,10 @@ import Admonition from "@theme/Admonition"; # Helpers + +This page may contain outdated information. It will be updated as soon as possible. + + ### Chat memory This component retrieves stored chat messages based on a specific session ID. diff --git a/docs/docs/components/inputs-and-outputs.mdx b/docs/docs/components/inputs-and-outputs.mdx index f5592e7fd..8b78d8567 100644 --- a/docs/docs/components/inputs-and-outputs.mdx +++ b/docs/docs/components/inputs-and-outputs.mdx @@ -4,6 +4,10 @@ import useBaseUrl from "@docusaurus/useBaseUrl"; # Inputs and Outputs + +This page may contain outdated information. It will be updated as soon as possible. + + Inputs and Outputs are a category of components that are used to define where data comes in and out of your flow. They also dynamically change the Playground and can be renamed to facilitate building and maintaining your flows. diff --git a/docs/docs/components/loaders.mdx b/docs/docs/components/loaders.mdx index b7f2d11fb..66c0c3a31 100644 --- a/docs/docs/components/loaders.mdx +++ b/docs/docs/components/loaders.mdx @@ -2,6 +2,10 @@ import Admonition from '@theme/Admonition'; # Loaders + +This page may contain outdated information. It will be updated as soon as possible. + +

We appreciate your understanding as we polish our documentation – it may contain some rough edges. Share your feedback or report issues to help us improve! 🛠️📝 diff --git a/docs/docs/components/memories.mdx b/docs/docs/components/memories.mdx index a133c6a6a..3fdf61066 100644 --- a/docs/docs/components/memories.mdx +++ b/docs/docs/components/memories.mdx @@ -2,6 +2,10 @@ import Admonition from "@theme/Admonition"; # Memories + +This page may contain outdated information. It will be updated as soon as possible. + +

Thanks for your patience as we improve our documentation—it might have some diff --git a/docs/docs/components/model_specs.mdx b/docs/docs/components/model_specs.mdx index 21ee1849b..d5835e9d7 100644 --- a/docs/docs/components/model_specs.mdx +++ b/docs/docs/components/model_specs.mdx @@ -2,6 +2,10 @@ import Admonition from "@theme/Admonition"; # Large Language Models (LLMs) + +This page may contain outdated information. It will be updated as soon as possible. + + A Large Language Model (LLM) is a foundational component of Langflow. It provides a uniform interface for interacting with LLMs from various providers, including OpenAI, Cohere, and HuggingFace. Langflow extensively uses LLMs across its chains and agents, employing them to generate text based on specific prompts or inputs. --- diff --git a/docs/docs/components/models.mdx b/docs/docs/components/models.mdx index f02c1654b..4d739b59e 100644 --- a/docs/docs/components/models.mdx +++ b/docs/docs/components/models.mdx @@ -2,6 +2,10 @@ import Admonition from "@theme/Admonition"; # Models + +This page may contain outdated information. It will be updated as soon as possible. + + ## Amazon Bedrock This component facilitates the generation of text using the LLM (Large Language Model) model from Amazon Bedrock. diff --git a/docs/docs/components/retrievers.mdx b/docs/docs/components/retrievers.mdx index 792b9e20b..e13ed2d89 100644 --- a/docs/docs/components/retrievers.mdx +++ b/docs/docs/components/retrievers.mdx @@ -2,6 +2,10 @@ import Admonition from "@theme/Admonition"; # Retrievers + +This page may contain outdated information. It will be updated as soon as possible. + + A retriever is an interface that returns documents in response to an unstructured query. It's broader than a vector store because it doesn't need to store documents; it only needs to retrieve them. --- diff --git a/docs/docs/components/text-and-record.mdx b/docs/docs/components/text-and-record.mdx index e1ece5069..ab3f9302f 100644 --- a/docs/docs/components/text-and-record.mdx +++ b/docs/docs/components/text-and-record.mdx @@ -1,5 +1,11 @@ +import Admonition from "@theme/Admonition"; + # Text and Data + +This page may contain outdated information. It will be updated as soon as possible. + + There are two main input and output types: `Text` and `Data`. `Text` is a simple string input and output type, while `Data` is a structure very similar to a dictionary in Python. It is a key-value pair data structure. diff --git a/docs/docs/components/text-splitters.mdx b/docs/docs/components/text-splitters.mdx index 02e7a311b..b438d9c21 100644 --- a/docs/docs/components/text-splitters.mdx +++ b/docs/docs/components/text-splitters.mdx @@ -2,6 +2,10 @@ import Admonition from "@theme/Admonition"; # Text Splitters + +This page may contain outdated information. It will be updated as soon as possible. + + A text splitter is a tool that divides a document or text into smaller chunks or segments. This helps make large texts more manageable for analysis or processing. --- diff --git a/docs/docs/components/toolkits.mdx b/docs/docs/components/toolkits.mdx index 3ba7ed7c7..f4b2004ba 100644 --- a/docs/docs/components/toolkits.mdx +++ b/docs/docs/components/toolkits.mdx @@ -2,6 +2,10 @@ import Admonition from "@theme/Admonition"; # Toolkits + +This page may contain outdated information. It will be updated as soon as possible. + +

We appreciate your understanding as we polish our documentation - it may diff --git a/docs/docs/components/tools.mdx b/docs/docs/components/tools.mdx index 6460db860..a7daae919 100644 --- a/docs/docs/components/tools.mdx +++ b/docs/docs/components/tools.mdx @@ -2,6 +2,10 @@ import Admonition from "@theme/Admonition"; # Tools + +This page may contain outdated information. It will be updated as soon as possible. + + ## SearchApi SearchApi offers a real-time search engine results API that returns structured JSON data, including answer boxes, knowledge graphs, organic results, and more. diff --git a/docs/docs/components/utilities.mdx b/docs/docs/components/utilities.mdx index 44263f583..e0e95aa78 100644 --- a/docs/docs/components/utilities.mdx +++ b/docs/docs/components/utilities.mdx @@ -2,6 +2,10 @@ import Admonition from "@theme/Admonition"; # Utilities + +This page may contain outdated information. It will be updated as soon as possible. + + Utilities are a set of actions that can be used to perform common tasks in a flow. They are available in the **Utilities** section in the sidebar. --- diff --git a/docs/docs/components/vector-stores.mdx b/docs/docs/components/vector-stores.mdx index 56e4e094a..cf4dc1668 100644 --- a/docs/docs/components/vector-stores.mdx +++ b/docs/docs/components/vector-stores.mdx @@ -2,6 +2,10 @@ import Admonition from "@theme/Admonition"; # Vector Stores + +This page may contain outdated information. It will be updated as soon as possible. + + ### Astra DB The `Astra DB` initializes a vector store using Astra DB from Data. It creates Astra DB-based vector indexes to efficiently store and retrieve documents. diff --git a/docs/docs/contributing/community.md b/docs/docs/contributing/community.mdx similarity index 85% rename from docs/docs/contributing/community.md rename to docs/docs/contributing/community.mdx index 5c95718ec..964abf277 100644 --- a/docs/docs/contributing/community.md +++ b/docs/docs/contributing/community.mdx @@ -1,5 +1,11 @@ +import Admonition from "@theme/Admonition"; + # Community + +This page may contain outdated information. It will be updated as soon as possible. + + ## 🤖 Join **Langflow** Discord server Join us to ask questions and showcase your projects. diff --git a/docs/docs/contributing/contribute-component.md b/docs/docs/contributing/contribute-component.mdx similarity index 94% rename from docs/docs/contributing/contribute-component.md rename to docs/docs/contributing/contribute-component.mdx index 7f628623b..4ad8072f3 100644 --- a/docs/docs/contributing/contribute-component.md +++ b/docs/docs/contributing/contribute-component.mdx @@ -1,7 +1,12 @@ import ZoomableImage from "/src/theme/ZoomableImage.js"; +import Admonition from "@theme/Admonition"; # How to Contribute Components? + +This page may contain outdated information. It will be updated as soon as possible. + + New components are added as objects of the [CustomComponent](https://github.com/langflow-ai/langflow/blob/dev/src/backend/base/langflow/interface/custom/custom_component/custom_component.py) class and any dependencies are added to the [pyproject.toml](https://github.com/langflow-ai/langflow/blob/dev/pyproject.toml#L27) file. ## Add an example component diff --git a/docs/docs/contributing/github-issues.md b/docs/docs/contributing/github-issues.mdx similarity index 88% rename from docs/docs/contributing/github-issues.md rename to docs/docs/contributing/github-issues.mdx index 269c976cd..84d049849 100644 --- a/docs/docs/contributing/github-issues.md +++ b/docs/docs/contributing/github-issues.mdx @@ -1,5 +1,11 @@ +import Admonition from "@theme/Admonition"; + # GitHub Issues + +This page may contain outdated information. It will be updated as soon as possible. + + Our [issues](https://github.com/langflow-ai/langflow/issues) page is kept up to date with bugs, improvements, and feature requests. There is a taxonomy of labels to help with sorting and discovery of issues of interest. diff --git a/docs/docs/contributing/how-contribute.md b/docs/docs/contributing/how-contribute.mdx similarity index 92% rename from docs/docs/contributing/how-contribute.md rename to docs/docs/contributing/how-contribute.mdx index ff0df55a6..6776be0b1 100644 --- a/docs/docs/contributing/how-contribute.md +++ b/docs/docs/contributing/how-contribute.mdx @@ -1,5 +1,11 @@ +import Admonition from "@theme/Admonition"; + # How to Contribute? + +This page may contain outdated information. It will be updated as soon as possible. + + 👋 Hello there! We welcome contributions from developers of all levels to our open-source project on [GitHub](https://github.com/langflow-ai/langflow). If you'd like to contribute, please check our contributing guidelines and help make Langflow more accessible. As an open-source project in a rapidly developing field, we are extremely open diff --git a/docs/docs/deployment/backend-only.md b/docs/docs/deployment/backend-only.mdx similarity index 96% rename from docs/docs/deployment/backend-only.md rename to docs/docs/deployment/backend-only.mdx index 4122373f3..1fc16de2f 100644 --- a/docs/docs/deployment/backend-only.md +++ b/docs/docs/deployment/backend-only.mdx @@ -1,5 +1,11 @@ +import Admonition from "@theme/Admonition"; + # Backend-only + +This page may contain outdated information. It will be updated as soon as possible. + + You can run Langflow in `--backend-only` mode to expose your Langflow app as an API, without running the frontend UI. Start langflow in backend-only mode with `python3 -m langflow run --backend-only`. diff --git a/docs/docs/deployment/docker.md b/docs/docs/deployment/docker.mdx similarity index 90% rename from docs/docs/deployment/docker.md rename to docs/docs/deployment/docker.mdx index a8864db55..e734d6210 100644 --- a/docs/docs/deployment/docker.md +++ b/docs/docs/deployment/docker.mdx @@ -1,5 +1,11 @@ +import Admonition from "@theme/Admonition"; + # Docker + +This page may contain outdated information. It will be updated as soon as possible. + + This guide will help you get LangFlow up and running using Docker and Docker Compose. ## Prerequisites diff --git a/docs/docs/deployment/gcp-deployment.md b/docs/docs/deployment/gcp-deployment.mdx similarity index 93% rename from docs/docs/deployment/gcp-deployment.md rename to docs/docs/deployment/gcp-deployment.mdx index e126e785c..e2abace6b 100644 --- a/docs/docs/deployment/gcp-deployment.md +++ b/docs/docs/deployment/gcp-deployment.mdx @@ -1,5 +1,11 @@ +import Admonition from "@theme/Admonition"; + # Deploy on Google Cloud Platform + +This page may contain outdated information. It will be updated as soon as possible. + + ## Run Langflow from a New Google Cloud Project This guide will help you set up a Langflow development VM in a Google Cloud Platform project using Google Cloud Shell. diff --git a/docs/docs/examples/chat-memory.mdx b/docs/docs/examples/chat-memory.mdx index 174711ce8..4fa2775aa 100644 --- a/docs/docs/examples/chat-memory.mdx +++ b/docs/docs/examples/chat-memory.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Chat Memory + +This page may contain outdated information. It will be updated as soon as possible. + + The **Chat Memory** component restores previous messages given a Session ID, which can be any string. This component is available under the **Helpers** tab of the Langflow sidebar. diff --git a/docs/docs/examples/combine-text.mdx b/docs/docs/examples/combine-text.mdx index 6fb46555f..10c2e8900 100644 --- a/docs/docs/examples/combine-text.mdx +++ b/docs/docs/examples/combine-text.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Combine Text + +This page may contain outdated information. It will be updated as soon as possible. + + With LLM pipelines, combining text from different sources may be as important as splitting text. The **Combine Text** component concatenates two text inputs into a single chunk using a specified delimiter, such as whitespace or a newline. diff --git a/docs/docs/examples/create-record.mdx b/docs/docs/examples/create-record.mdx index 7858ca783..9e681699c 100644 --- a/docs/docs/examples/create-record.mdx +++ b/docs/docs/examples/create-record.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Create Data + +This page may contain outdated information. It will be updated as soon as possible. + + In Langflow, a `Data` has a structure very similar to a Python dictionary. It is a key-value pair data structure. The **Create Data** component allows you to dynamically create a `Data` from a specified number of inputs. You can add as many key-value pairs as you want (as long as it is less than 15 😅). Once you've chosen the number of `Data`, add keys and fill up values, or pass on values from other components to the component using the input handles. diff --git a/docs/docs/examples/pass.mdx b/docs/docs/examples/pass.mdx index ddfe35cca..5f75adac1 100644 --- a/docs/docs/examples/pass.mdx +++ b/docs/docs/examples/pass.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Pass + +This page may contain outdated information. It will be updated as soon as possible. + + Sometimes all you need to do is… nothing! The **Pass** component enables you to ignore one input and move forward with another one. This is super helpful to swap routes for A/B testing! diff --git a/docs/docs/examples/store-message.mdx b/docs/docs/examples/store-message.mdx index 75ff0bd46..df2cb3c39 100644 --- a/docs/docs/examples/store-message.mdx +++ b/docs/docs/examples/store-message.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Store Message + +This page may contain outdated information. It will be updated as soon as possible. + + The **Store Message** component allows you to save information under a specified Session ID and sender type. The **Message History** component can then be used to retrieve stored messages. diff --git a/docs/docs/examples/sub-flow.mdx b/docs/docs/examples/sub-flow.mdx index d2b9674ad..31cc7448e 100644 --- a/docs/docs/examples/sub-flow.mdx +++ b/docs/docs/examples/sub-flow.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Sub Flow + +This page may contain outdated information. It will be updated as soon as possible. + + The **Sub Flow** component enables a user to select a previously built flow and dynamically generate a component out of it.

+This page may contain outdated information. It will be updated as soon as possible. + + The **Text Operator** component simplifies logic. It evaluates the results from another component (for example, if the input text exactly equals `Tuna`) and runs another component based on the results. Basically, the text operator is an if/else component for your flow.
+This page may contain outdated information. It will be updated as soon as possible. + + Langflow **requires** Python version 3.10 or greater and [pip](https://pypi.org/project/pip/) or diff --git a/docs/docs/getting-started/quickstart.mdx b/docs/docs/getting-started/quickstart.mdx index 7d4f15573..e6151c1eb 100644 --- a/docs/docs/getting-started/quickstart.mdx +++ b/docs/docs/getting-started/quickstart.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # ⚡️ Quickstart + +This page may contain outdated information. It will be updated as soon as possible. + + This guide demonstrates how to build a basic flow and modify the prompt for different outcomes. ## Prerequisites diff --git a/docs/docs/getting-started/rag-with-astradb.mdx b/docs/docs/getting-started/rag-with-astradb.mdx index c719d8d94..015f50f3d 100644 --- a/docs/docs/getting-started/rag-with-astradb.mdx +++ b/docs/docs/getting-started/rag-with-astradb.mdx @@ -5,6 +5,10 @@ import Admonition from "@theme/Admonition"; # 🌟 RAG with Astra DB + +This page may contain outdated information. It will be updated as soon as possible. + + This guide will walk you through how to build a RAG (Retrieval Augmented Generation) application using **Astra DB** and **Langflow**. [Astra DB](https://www.datastax.com/products/datastax-astra?utm_source=langflow-pre-release&utm_medium=referral&utm_campaign=langflow-announcement&utm_content=astradb) is a cloud-native database built on Apache Cassandra that is optimized for the cloud. It is a fully managed database-as-a-service that simplifies operations and reduces costs. Astra DB is built on the same technology that powers the largest Cassandra deployments in the world. diff --git a/docs/docs/getting-started/workspace.mdx b/docs/docs/getting-started/workspace.mdx index 374faca74..e6951a5e1 100644 --- a/docs/docs/getting-started/workspace.mdx +++ b/docs/docs/getting-started/workspace.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # 🎨 Langflow Workspace + +This page may contain outdated information. It will be updated as soon as possible. + + ## The Langflow Workspace Interface The **Langflow Workspace** is where you assemble new flows and create AIs by connecting and running components. To get started, click on **New Project**. You can either build a flow from scratch (Blank Flow) or choose from pre-built starter examples. diff --git a/docs/docs/integrations/langsmith/intro.mdx b/docs/docs/integrations/langsmith/intro.mdx index 68f28a891..02f474e67 100644 --- a/docs/docs/integrations/langsmith/intro.mdx +++ b/docs/docs/integrations/langsmith/intro.mdx @@ -5,6 +5,10 @@ import ZoomableImage from "/src/theme/ZoomableImage.js"; # LangSmith + +This page may contain outdated information. It will be updated as soon as possible. + + LangSmith is a full-lifecycle DevOps service from LangChain that provides monitoring and observability. To integrate with Langflow, just add your LangChain API key as a Langflow environment variable and you are good to go! ## Step-by-step Configuration diff --git a/docs/docs/integrations/notion/add-content-to-page.md b/docs/docs/integrations/notion/add-content-to-page.md index ace43e103..197046922 100644 --- a/docs/docs/integrations/notion/add-content-to-page.md +++ b/docs/docs/integrations/notion/add-content-to-page.md @@ -5,6 +5,10 @@ import ZoomableImage from "/src/theme/ZoomableImage.js"; # Add Content To Page + +This page may contain outdated information. It will be updated as soon as possible. + + The `AddContentToPage` component converts markdown text to Notion blocks and appends them to a Notion page. [Notion Reference](https://developers.notion.com/reference/patch-block-children) diff --git a/docs/docs/integrations/notion/intro.md b/docs/docs/integrations/notion/intro.md index 293038d4f..77f09e5b6 100644 --- a/docs/docs/integrations/notion/intro.md +++ b/docs/docs/integrations/notion/intro.md @@ -5,6 +5,10 @@ import ZoomableImage from "/src/theme/ZoomableImage.js"; # Introduction to Notion in Langflow + +This page may contain outdated information. It will be updated as soon as possible. + + The Notion integration in Langflow enables seamless connectivity with Notion databases, pages, and users, facilitating automation and improving productivity. +This page may contain outdated information. It will be updated as soon as possible. + + The `NotionDatabaseProperties` component retrieves properties of a Notion database. It provides a convenient way to integrate Notion database information into your Langflow workflows. [Notion Reference](https://developers.notion.com/reference/post-database-query) diff --git a/docs/docs/integrations/notion/list-pages.md b/docs/docs/integrations/notion/list-pages.md index e1f6603b3..a232a594f 100644 --- a/docs/docs/integrations/notion/list-pages.md +++ b/docs/docs/integrations/notion/list-pages.md @@ -5,6 +5,10 @@ import ZoomableImage from "/src/theme/ZoomableImage.js"; # List Pages + +This page may contain outdated information. It will be updated as soon as possible. + + The `NotionListPages` component queries a Notion database with filtering and sorting. It provides a convenient way to integrate Notion database querying capabilities into your Langflow workflows. [Notion Reference](https://developers.notion.com/reference/post-database-query) diff --git a/docs/docs/integrations/notion/list-users.md b/docs/docs/integrations/notion/list-users.md index 17352c0c2..c3cd6696b 100644 --- a/docs/docs/integrations/notion/list-users.md +++ b/docs/docs/integrations/notion/list-users.md @@ -5,6 +5,10 @@ import ZoomableImage from "/src/theme/ZoomableImage.js"; # User List + +This page may contain outdated information. It will be updated as soon as possible. + + The `NotionUserList` component retrieves users from Notion. It provides a convenient way to integrate Notion user data into your Langflow workflows. [Notion Reference](https://developers.notion.com/reference/get-users) diff --git a/docs/docs/integrations/notion/page-content-viewer.md b/docs/docs/integrations/notion/page-content-viewer.md index 070d71800..df3ebdf60 100644 --- a/docs/docs/integrations/notion/page-content-viewer.md +++ b/docs/docs/integrations/notion/page-content-viewer.md @@ -5,6 +5,10 @@ import ZoomableImage from "/src/theme/ZoomableImage.js"; # Page Content + +This page may contain outdated information. It will be updated as soon as possible. + + The `NotionPageContent` component retrieves the content of a Notion page as plain text. It provides a convenient way to integrate Notion page content into your Langflow workflows. [Notion Reference](https://developers.notion.com/reference/get-page) diff --git a/docs/docs/integrations/notion/page-create.md b/docs/docs/integrations/notion/page-create.md index f942f257b..f2e7534d1 100644 --- a/docs/docs/integrations/notion/page-create.md +++ b/docs/docs/integrations/notion/page-create.md @@ -5,6 +5,10 @@ import ZoomableImage from "/src/theme/ZoomableImage.js"; # Page Create + +This page may contain outdated information. It will be updated as soon as possible. + + The `NotionPageCreator` component creates pages in a Notion database. It provides a convenient way to integrate Notion page creation into your Langflow workflows. [Notion Reference](https://developers.notion.com/reference/patch-block-children) diff --git a/docs/docs/integrations/notion/page-update.md b/docs/docs/integrations/notion/page-update.md index ca88f547d..3f9709f0a 100644 --- a/docs/docs/integrations/notion/page-update.md +++ b/docs/docs/integrations/notion/page-update.md @@ -5,6 +5,10 @@ import ZoomableImage from "/src/theme/ZoomableImage.js"; # Page Update + +This page may contain outdated information. It will be updated as soon as possible. + + The `NotionPageUpdate` component updates the properties of a Notion page. It provides a convenient way to integrate updating Notion page properties into your Langflow workflows. [Notion Reference](https://developers.notion.com/reference/patch-page) diff --git a/docs/docs/integrations/notion/search.md b/docs/docs/integrations/notion/search.md index 1e9b8c529..f7092fdb9 100644 --- a/docs/docs/integrations/notion/search.md +++ b/docs/docs/integrations/notion/search.md @@ -5,6 +5,10 @@ import ZoomableImage from "/src/theme/ZoomableImage.js"; # Notion Search + +This page may contain outdated information. It will be updated as soon as possible. + + The `NotionSearch` component is designed to search all pages and databases that have been shared with an integration in Notion. It provides a convenient way to integrate Notion search capabilities into your Langflow workflows. [Notion Reference](https://developers.notion.com/reference/search) diff --git a/docs/docs/integrations/notion/setup.md b/docs/docs/integrations/notion/setup.md index 72bb8f3b4..4ff81dd30 100644 --- a/docs/docs/integrations/notion/setup.md +++ b/docs/docs/integrations/notion/setup.md @@ -2,6 +2,10 @@ import Admonition from "@theme/Admonition"; # Setting up a Notion App + +This page may contain outdated information. It will be updated as soon as possible. + + To use Notion components in Langflow, you first need to create a Notion integration and configure it with the necessary capabilities. This guide will walk you through the process of setting up a Notion integration and granting it access to your Notion databases. ## Prerequisites diff --git a/docs/docs/migration/compatibility.mdx b/docs/docs/migration/compatibility.mdx index 0e18e4900..268214c4b 100644 --- a/docs/docs/migration/compatibility.mdx +++ b/docs/docs/migration/compatibility.mdx @@ -3,6 +3,10 @@ import ZoomableImage from "/src/theme/ZoomableImage.js"; # Compatibility with Previous Versions + +This page may contain outdated information. It will be updated as soon as possible. + + ## TLDR; - You'll need to add a few components to your flow to make it compatible with the new version of Langflow. diff --git a/docs/docs/migration/migrating-to-one-point-zero.mdx b/docs/docs/migration/migrating-to-one-point-zero.mdx index c6afa8ab2..78ae6b608 100644 --- a/docs/docs/migration/migrating-to-one-point-zero.mdx +++ b/docs/docs/migration/migrating-to-one-point-zero.mdx @@ -2,6 +2,10 @@ import Admonition from "@theme/Admonition"; # Migrating to Langflow 1.0: A Guide + +This page may contain outdated information. It will be updated as soon as possible. + + Langflow 1.0 is a significant update that brings many exciting changes and improvements to the platform. This guide will walk you through the key improvements and help you migrate your existing projects to the new version. diff --git a/docs/docs/starter-projects/basic-prompting.mdx b/docs/docs/starter-projects/basic-prompting.mdx index 594990eb6..dc5fc8c0f 100644 --- a/docs/docs/starter-projects/basic-prompting.mdx +++ b/docs/docs/starter-projects/basic-prompting.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Basic Prompting + +This page may contain outdated information. It will be updated as soon as possible. + + Prompts serve as the inputs to a large language model (LLM), acting as the interface between human instructions and computational tasks. By submitting natural language requests in a prompt to an LLM, you can obtain answers, generate text, and solve problems. diff --git a/docs/docs/starter-projects/blog-writer.mdx b/docs/docs/starter-projects/blog-writer.mdx index 75f725d94..1fb1a52d0 100644 --- a/docs/docs/starter-projects/blog-writer.mdx +++ b/docs/docs/starter-projects/blog-writer.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Blog Writer + +This page may contain outdated information. It will be updated as soon as possible. + + Build a blog writer with OpenAI that uses URLs for reference content. ## Prerequisites diff --git a/docs/docs/starter-projects/document-qa.mdx b/docs/docs/starter-projects/document-qa.mdx index 2e452522e..25f5d1234 100644 --- a/docs/docs/starter-projects/document-qa.mdx +++ b/docs/docs/starter-projects/document-qa.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Document QA + +This page may contain outdated information. It will be updated as soon as possible. + + Build a question-and-answer chatbot with a document loaded from local memory. ## Prerequisites diff --git a/docs/docs/starter-projects/memory-chatbot.mdx b/docs/docs/starter-projects/memory-chatbot.mdx index bf5a428ca..a620dd714 100644 --- a/docs/docs/starter-projects/memory-chatbot.mdx +++ b/docs/docs/starter-projects/memory-chatbot.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Memory Chatbot + +This page may contain outdated information. It will be updated as soon as possible. + + This flow extends the [basic prompting flow](./basic-prompting) to include chat memory for unique SessionIDs. ## Prerequisites diff --git a/docs/docs/starter-projects/vector-store-rag.mdx b/docs/docs/starter-projects/vector-store-rag.mdx index 4354295d8..6fb514d9a 100644 --- a/docs/docs/starter-projects/vector-store-rag.mdx +++ b/docs/docs/starter-projects/vector-store-rag.mdx @@ -6,6 +6,10 @@ import Admonition from "@theme/Admonition"; # Vector Store RAG + +This page may contain outdated information. It will be updated as soon as possible. + + Retrieval Augmented Generation, or RAG, is a pattern for training LLMs on your data and querying it. RAG is backed by a **vector store**, a vector database which stores embeddings of the ingested data. diff --git a/docs/docs/tutorials/chatprompttemplate_guide.mdx b/docs/docs/tutorials/chatprompttemplate_guide.mdx index e19f95f4a..9fd6ca1ea 100644 --- a/docs/docs/tutorials/chatprompttemplate_guide.mdx +++ b/docs/docs/tutorials/chatprompttemplate_guide.mdx @@ -2,9 +2,14 @@ import ThemedImage from "@theme/ThemedImage"; import useBaseUrl from "@docusaurus/useBaseUrl"; import ZoomableImage from "/src/theme/ZoomableImage.js"; import ReactPlayer from "react-player"; +import Admonition from "@theme/Admonition"; # Build Chatbots with the System Message Component + +This page may contain outdated information. It will be updated as soon as possible. + + ## Overview In this guide, we will modify the "Basic Chat with Prompt and History" example, integrating the ChatPromptTemplate with the SystemMessagePromptTemplate and HumanMessagePromptTemplate components. By following these steps, you'll be able to build a personalized chatbot that can interpret and respond based on user-defined System messages. diff --git a/docs/docs/tutorials/custom_components.mdx b/docs/docs/tutorials/custom_components.mdx index 127337937..6996bea72 100644 --- a/docs/docs/tutorials/custom_components.mdx +++ b/docs/docs/tutorials/custom_components.mdx @@ -8,6 +8,10 @@ import Admonition from "@theme/Admonition"; # Custom Components + +This page may contain outdated information. It will be updated as soon as possible. + + In Langflow, a Custom Component is a special component type that allows users to extend the platform's functionality by creating their own reusable and configurable components. A Custom Component is created from a user-defined Python script that uses the _`CustomComponent`_ class provided by the Langflow library. These components can be as simple as a basic function that takes and returns a string or as complex as a combination of multiple sub-components and API calls. diff --git a/docs/docs/tutorials/loading_document.mdx b/docs/docs/tutorials/loading_document.mdx index 3b1eca436..592332eee 100644 --- a/docs/docs/tutorials/loading_document.mdx +++ b/docs/docs/tutorials/loading_document.mdx @@ -2,9 +2,14 @@ import ThemedImage from "@theme/ThemedImage"; import useBaseUrl from "@docusaurus/useBaseUrl"; import ZoomableImage from "/src/theme/ZoomableImage.js"; import ReactPlayer from "react-player"; +import Admonition from "@theme/Admonition"; # Integrate Documents with Prompt Variables + +This page may contain outdated information. It will be updated as soon as possible. + + ## Overview This guide takes you through the process of augmenting the "Basic Chat with Prompt and History" example. You'll learn how to embed documents as context into the PromptTemplate component utilizing a WebBaseLoader. diff --git a/docs/docs/tutorials/rag-with-astradb.mdx b/docs/docs/tutorials/rag-with-astradb.mdx index e3f4a3f1e..0aa0dafe8 100644 --- a/docs/docs/tutorials/rag-with-astradb.mdx +++ b/docs/docs/tutorials/rag-with-astradb.mdx @@ -5,6 +5,10 @@ import Admonition from "@theme/Admonition"; # 🌟 RAG with Astra DB + +This page may contain outdated information. It will be updated as soon as possible. + + This guide will walk you through how to build a RAG (Retrieval Augmented Generation) application using **Astra DB** and **Langflow**. [Astra DB](https://www.datastax.com/products/datastax-astra?utm_source=langflow-pre-release&utm_medium=referral&utm_campaign=langflow-announcement&utm_content=astradb) is a cloud-native database built on Apache Cassandra that is optimized for the cloud. It is a fully managed database-as-a-service that simplifies operations and reduces costs. Astra DB is built on the same technology that powers the largest Cassandra deployments in the world. From 0ddb11664f8d4a6323153ecfd4845364c78cce96 Mon Sep 17 00:00:00 2001 From: Rodrigo Date: Sun, 23 Jun 2024 19:40:46 -0300 Subject: [PATCH 040/229] rearrange and remove components --- .../components/agents/ToolCallingAgent.py | 22 +++- .../AgentComponent.py | 0 .../CodeBlockExtractor.py | 0 .../DocumentsToData.py | 0 .../{experimental => deactivated}/Embed.py | 0 .../ExtractKeyFromData.py | 0 .../ListFlows.py | 0 .../MergeData.py | 0 .../{experimental => deactivated}/Message.py | 0 .../SelectivePassThrough.py | 0 .../{helpers => deactivated}/ShouldRunNext.py | 0 .../components/deactivated/SplitText.py | 69 +++++++++++ .../StoreMessage.py | 0 .../{experimental => deactivated}/SubFlow.py | 0 .../{experimental => deactivated}/__init__.py | 0 .../langflow/components/helpers/FilterData.py | 1 + .../components/helpers/IDGenerator.py | 2 - .../langflow/components/helpers/MergeData.py | 26 ++++ .../{experimental => helpers}/SplitText.py | 0 .../components/helpers/StoreMessage.py | 22 ++++ .../langflow/components/helpers/__init__.py | 27 ++-- .../ConditionalRouter.py | 0 .../{experimental => prototypes}/FlowTool.py | 1 + .../{experimental => prototypes}/Listen.py | 0 .../{experimental => prototypes}/Notify.py | 0 .../{experimental => prototypes}/Pass.py | 1 + .../PythonFunction.py | 1 + .../{experimental => prototypes}/RunFlow.py | 0 .../RunnableExecutor.py | 0 .../SQLExecutor.py | 0 .../langflow/components/prototypes/SubFlow.py | 115 ++++++++++++++++++ .../components/prototypes/__init__.py | 39 ++++++ 32 files changed, 310 insertions(+), 16 deletions(-) rename src/backend/base/langflow/components/{experimental => deactivated}/AgentComponent.py (100%) rename src/backend/base/langflow/components/{helpers => deactivated}/CodeBlockExtractor.py (100%) rename src/backend/base/langflow/components/{helpers => deactivated}/DocumentsToData.py (100%) rename src/backend/base/langflow/components/{experimental => deactivated}/Embed.py (100%) rename src/backend/base/langflow/components/{experimental => deactivated}/ExtractKeyFromData.py (100%) rename src/backend/base/langflow/components/{experimental => deactivated}/ListFlows.py (100%) rename src/backend/base/langflow/components/{experimental => deactivated}/MergeData.py (100%) rename src/backend/base/langflow/components/{experimental => deactivated}/Message.py (100%) rename src/backend/base/langflow/components/{experimental => deactivated}/SelectivePassThrough.py (100%) rename src/backend/base/langflow/components/{helpers => deactivated}/ShouldRunNext.py (100%) create mode 100644 src/backend/base/langflow/components/deactivated/SplitText.py rename src/backend/base/langflow/components/{experimental => deactivated}/StoreMessage.py (100%) rename src/backend/base/langflow/components/{experimental => deactivated}/SubFlow.py (100%) rename src/backend/base/langflow/components/{experimental => deactivated}/__init__.py (100%) create mode 100644 src/backend/base/langflow/components/helpers/MergeData.py rename src/backend/base/langflow/components/{experimental => helpers}/SplitText.py (100%) create mode 100644 src/backend/base/langflow/components/helpers/StoreMessage.py rename src/backend/base/langflow/components/{experimental => prototypes}/ConditionalRouter.py (100%) rename src/backend/base/langflow/components/{experimental => prototypes}/FlowTool.py (99%) rename src/backend/base/langflow/components/{experimental => prototypes}/Listen.py (100%) rename src/backend/base/langflow/components/{experimental => prototypes}/Notify.py (100%) rename src/backend/base/langflow/components/{experimental => prototypes}/Pass.py (98%) rename src/backend/base/langflow/components/{experimental => prototypes}/PythonFunction.py (97%) rename src/backend/base/langflow/components/{experimental => prototypes}/RunFlow.py (100%) rename src/backend/base/langflow/components/{experimental => prototypes}/RunnableExecutor.py (100%) rename src/backend/base/langflow/components/{experimental => prototypes}/SQLExecutor.py (100%) create mode 100644 src/backend/base/langflow/components/prototypes/SubFlow.py create mode 100644 src/backend/base/langflow/components/prototypes/__init__.py diff --git a/src/backend/base/langflow/components/agents/ToolCallingAgent.py b/src/backend/base/langflow/components/agents/ToolCallingAgent.py index 8c08d489b..a9403e861 100644 --- a/src/backend/base/langflow/components/agents/ToolCallingAgent.py +++ b/src/backend/base/langflow/components/agents/ToolCallingAgent.py @@ -1,19 +1,29 @@ -from typing import List, cast +from typing import List, Optional -from langchain.agents import AgentExecutor, BaseSingleActionAgent from langchain.agents.tool_calling_agent.base import create_tool_calling_agent from langchain_core.prompts import ChatPromptTemplate +<<<<<<< Updated upstream from langflow.custom import Component from langflow.io import BoolInput, HandleInput, MessageTextInput, Output from langflow.schema import Data +======= +from langchain.agents import AgentExecutor +from langchain_core.messages import BaseMessage +>>>>>>> Stashed changes from langflow.schema.message import Message +from langflow.custom import Component +from langflow.io import HandleInput, TextInput, BoolInput, Output +from langflow.schema import Data class ToolCallingAgentComponent(Component): display_name: str = "Tool Calling Agent" - description: str = "Agent that uses tools. Only models that are compatible with function calling are supported." + description: str = ( + "Agent that uses tools. Only models that are compatible with function calling are supported." + ) icon = "LangChain" + beta = True inputs = [ MessageTextInput( @@ -80,12 +90,12 @@ class ToolCallingAgentComponent(Component): agent = create_tool_calling_agent(self.llm, self.tools, prompt) runnable = AgentExecutor.from_agent_and_tools( - agent=cast(BaseSingleActionAgent, agent), + agent=agent, tools=self.tools, verbose=True, handle_parsing_errors=self.handle_parsing_errors, ) - input_dict: dict[str, str | list[dict[str, str]]] = {"input": self.input_value} + input_dict: dict[str, str | list[BaseMessage]] = {"input": self.input_value} if hasattr(self, "memory") and self.memory: input_dict["chat_history"] = self.convert_chat_history(self.memory) result = await runnable.ainvoke(input_dict) @@ -98,7 +108,7 @@ class ToolCallingAgentComponent(Component): return Message(text=result_string) - def convert_chat_history(self, chat_history: List[Data]) -> List[dict[str, str]]: + def convert_chat_history(self, chat_history: List[Data]) -> List[Dict[str, str]]: messages = [] for item in chat_history: role = "user" if item.sender == "User" else "assistant" diff --git a/src/backend/base/langflow/components/experimental/AgentComponent.py b/src/backend/base/langflow/components/deactivated/AgentComponent.py similarity index 100% rename from src/backend/base/langflow/components/experimental/AgentComponent.py rename to src/backend/base/langflow/components/deactivated/AgentComponent.py diff --git a/src/backend/base/langflow/components/helpers/CodeBlockExtractor.py b/src/backend/base/langflow/components/deactivated/CodeBlockExtractor.py similarity index 100% rename from src/backend/base/langflow/components/helpers/CodeBlockExtractor.py rename to src/backend/base/langflow/components/deactivated/CodeBlockExtractor.py diff --git a/src/backend/base/langflow/components/helpers/DocumentsToData.py b/src/backend/base/langflow/components/deactivated/DocumentsToData.py similarity index 100% rename from src/backend/base/langflow/components/helpers/DocumentsToData.py rename to src/backend/base/langflow/components/deactivated/DocumentsToData.py diff --git a/src/backend/base/langflow/components/experimental/Embed.py b/src/backend/base/langflow/components/deactivated/Embed.py similarity index 100% rename from src/backend/base/langflow/components/experimental/Embed.py rename to src/backend/base/langflow/components/deactivated/Embed.py diff --git a/src/backend/base/langflow/components/experimental/ExtractKeyFromData.py b/src/backend/base/langflow/components/deactivated/ExtractKeyFromData.py similarity index 100% rename from src/backend/base/langflow/components/experimental/ExtractKeyFromData.py rename to src/backend/base/langflow/components/deactivated/ExtractKeyFromData.py diff --git a/src/backend/base/langflow/components/experimental/ListFlows.py b/src/backend/base/langflow/components/deactivated/ListFlows.py similarity index 100% rename from src/backend/base/langflow/components/experimental/ListFlows.py rename to src/backend/base/langflow/components/deactivated/ListFlows.py diff --git a/src/backend/base/langflow/components/experimental/MergeData.py b/src/backend/base/langflow/components/deactivated/MergeData.py similarity index 100% rename from src/backend/base/langflow/components/experimental/MergeData.py rename to src/backend/base/langflow/components/deactivated/MergeData.py diff --git a/src/backend/base/langflow/components/experimental/Message.py b/src/backend/base/langflow/components/deactivated/Message.py similarity index 100% rename from src/backend/base/langflow/components/experimental/Message.py rename to src/backend/base/langflow/components/deactivated/Message.py diff --git a/src/backend/base/langflow/components/experimental/SelectivePassThrough.py b/src/backend/base/langflow/components/deactivated/SelectivePassThrough.py similarity index 100% rename from src/backend/base/langflow/components/experimental/SelectivePassThrough.py rename to src/backend/base/langflow/components/deactivated/SelectivePassThrough.py diff --git a/src/backend/base/langflow/components/helpers/ShouldRunNext.py b/src/backend/base/langflow/components/deactivated/ShouldRunNext.py similarity index 100% rename from src/backend/base/langflow/components/helpers/ShouldRunNext.py rename to src/backend/base/langflow/components/deactivated/ShouldRunNext.py diff --git a/src/backend/base/langflow/components/deactivated/SplitText.py b/src/backend/base/langflow/components/deactivated/SplitText.py new file mode 100644 index 000000000..73e87504c --- /dev/null +++ b/src/backend/base/langflow/components/deactivated/SplitText.py @@ -0,0 +1,69 @@ +from typing import List + +from langchain_text_splitters import CharacterTextSplitter +from langflow.custom import Component +from langflow.io import HandleInput, IntInput, Output, TextInput +from langflow.schema import Data +from langflow.utils.util import unescape_string + + +class SplitTextComponent(Component): + display_name: str = "Split Text" + description: str = "Split text into chunks based on specified criteria." + icon = "scissors-line-dashed" + + inputs = [ + HandleInput( + name="data_inputs", + display_name="Data Inputs", + info="The data to split.", + input_types=["Data"], + is_list=True, + ), + IntInput( + name="chunk_overlap", + display_name="Chunk Overlap", + info="Number of characters to overlap between chunks.", + value=200, + ), + IntInput( + name="chunk_size", + display_name="Chunk Size", + info="The maximum number of characters in each chunk.", + value=1000, + ), + TextInput( + name="separator", + display_name="Separator", + info="The character to split on. Defaults to newline.", + value="\n", + ), + ] + + outputs = [ + Output(display_name="Chunks", name="chunks", method="split_text"), + ] + + def _docs_to_data(self, docs): + data = [] + for doc in docs: + data.append(Data(text=doc.page_content, data=doc.metadata)) + return data + + def split_text(self) -> List[Data]: + separator = unescape_string(self.separator) + + documents = [] + for _input in self.data_inputs: + if isinstance(_input, Data): + documents.append(_input.to_lc_document()) + + splitter = CharacterTextSplitter( + chunk_overlap=self.chunk_overlap, + chunk_size=self.chunk_size, + separator=separator, + ) + docs = splitter.split_documents(documents) + data = self._docs_to_data(docs) + self.status = data + return data diff --git a/src/backend/base/langflow/components/experimental/StoreMessage.py b/src/backend/base/langflow/components/deactivated/StoreMessage.py similarity index 100% rename from src/backend/base/langflow/components/experimental/StoreMessage.py rename to src/backend/base/langflow/components/deactivated/StoreMessage.py diff --git a/src/backend/base/langflow/components/experimental/SubFlow.py b/src/backend/base/langflow/components/deactivated/SubFlow.py similarity index 100% rename from src/backend/base/langflow/components/experimental/SubFlow.py rename to src/backend/base/langflow/components/deactivated/SubFlow.py diff --git a/src/backend/base/langflow/components/experimental/__init__.py b/src/backend/base/langflow/components/deactivated/__init__.py similarity index 100% rename from src/backend/base/langflow/components/experimental/__init__.py rename to src/backend/base/langflow/components/deactivated/__init__.py diff --git a/src/backend/base/langflow/components/helpers/FilterData.py b/src/backend/base/langflow/components/helpers/FilterData.py index e589c2aa5..94551854d 100644 --- a/src/backend/base/langflow/components/helpers/FilterData.py +++ b/src/backend/base/langflow/components/helpers/FilterData.py @@ -9,6 +9,7 @@ class FilterDataComponent(Component): display_name = "Filter Data" description = "Filters a Data object based on a list of keys." icon = "filter" + beta = True inputs = [ DataInput( diff --git a/src/backend/base/langflow/components/helpers/IDGenerator.py b/src/backend/base/langflow/components/helpers/IDGenerator.py index 1e4e223b1..bf583229e 100644 --- a/src/backend/base/langflow/components/helpers/IDGenerator.py +++ b/src/backend/base/langflow/components/helpers/IDGenerator.py @@ -5,14 +5,12 @@ from langflow.custom import CustomComponent class UUIDGeneratorComponent(CustomComponent): - documentation: str = "http://docs.langflow.org/components/custom" display_name = "ID Generator" description = "Generates a unique ID." def update_build_config( self, build_config: dict, - field_value: Any, field_name: Optional[str] = None, ): if field_name == "unique_id": diff --git a/src/backend/base/langflow/components/helpers/MergeData.py b/src/backend/base/langflow/components/helpers/MergeData.py new file mode 100644 index 000000000..5d434d3cf --- /dev/null +++ b/src/backend/base/langflow/components/helpers/MergeData.py @@ -0,0 +1,26 @@ +from langflow.custom import CustomComponent +from langflow.schema import Data + + +class MergeDataComponent(CustomComponent): + display_name = "Merge Data" + description = "Combines multiple data sources into a single unified Data object." + beta: bool = True + + field_config = { + "data": {"display_name": "Data"}, + } + + def build(self, data: list[Data]) -> Data: + if not data: + return Data() + if len(data) == 1: + return data[0] + merged_data = Data() + for value in data: + if merged_data is None: + merged_data = value + else: + merged_data += value + self.status = merged_data + return merged_data diff --git a/src/backend/base/langflow/components/experimental/SplitText.py b/src/backend/base/langflow/components/helpers/SplitText.py similarity index 100% rename from src/backend/base/langflow/components/experimental/SplitText.py rename to src/backend/base/langflow/components/helpers/SplitText.py diff --git a/src/backend/base/langflow/components/helpers/StoreMessage.py b/src/backend/base/langflow/components/helpers/StoreMessage.py new file mode 100644 index 000000000..5d0abfbb9 --- /dev/null +++ b/src/backend/base/langflow/components/helpers/StoreMessage.py @@ -0,0 +1,22 @@ +from langflow.custom import CustomComponent +from langflow.memory import get_messages, store_message +from langflow.schema.message import Message + + +class StoreMessageComponent(CustomComponent): + display_name = "Store Message" + description = "Stores a chat message." + + def build_config(self): + return { + "message": {"display_name": "Message"}, + } + + def build( + self, + message: Message, + ) -> Message: + store_message(message, flow_id=self.graph.flow_id) + self.status = get_messages() + + return message diff --git a/src/backend/base/langflow/components/helpers/__init__.py b/src/backend/base/langflow/components/helpers/__init__.py index 1337aebd4..ab1f8d00a 100644 --- a/src/backend/base/langflow/components/helpers/__init__.py +++ b/src/backend/base/langflow/components/helpers/__init__.py @@ -1,15 +1,26 @@ +from .CombineText import CombineTextComponent from .CreateData import CreateDataComponent -from .CustomComponent import Component -from .ParseData import ParseDataComponent -from .DocumentsToData import DocumentsToDataComponent +from .CustomComponent import CustomComponent +from .FilterData import FilterDataComponent from .IDGenerator import UUIDGeneratorComponent +from .Memory import MemoryComponent +from .MergeData import MergeDataComponent +from .ParseData import ParseDataComponent +from .SplitText import SplitTextComponent +from .StoreMessage import StoreMessageComponent from .UpdateData import UpdateDataComponent + __all__ = [ - "Component", - "UpdateDataComponent", - "DocumentsToDataComponent", - "UUIDGeneratorComponent", - "ParseDataComponent", + "CombineTextComponent", "CreateDataComponent", + "CustomComponent", + "FilterDataComponent", + "UUIDGeneratorComponent", + "MemoryComponent", + "MergeDataComponent", + "ParseDataComponent", + "SplitTextComponent", + "StoreMessageComponent", + "UpdateDataComponent", ] diff --git a/src/backend/base/langflow/components/experimental/ConditionalRouter.py b/src/backend/base/langflow/components/prototypes/ConditionalRouter.py similarity index 100% rename from src/backend/base/langflow/components/experimental/ConditionalRouter.py rename to src/backend/base/langflow/components/prototypes/ConditionalRouter.py diff --git a/src/backend/base/langflow/components/experimental/FlowTool.py b/src/backend/base/langflow/components/prototypes/FlowTool.py similarity index 99% rename from src/backend/base/langflow/components/experimental/FlowTool.py rename to src/backend/base/langflow/components/prototypes/FlowTool.py index 103cd3c1f..a1c9bc4eb 100644 --- a/src/backend/base/langflow/components/experimental/FlowTool.py +++ b/src/backend/base/langflow/components/prototypes/FlowTool.py @@ -16,6 +16,7 @@ class FlowToolComponent(CustomComponent): description = "Construct a Tool from a function that runs the loaded Flow." field_order = ["flow_name", "name", "description", "return_direct"] trace_type = "tool" + beta = True def get_flow_names(self) -> List[str]: flow_datas = self.list_flows() diff --git a/src/backend/base/langflow/components/experimental/Listen.py b/src/backend/base/langflow/components/prototypes/Listen.py similarity index 100% rename from src/backend/base/langflow/components/experimental/Listen.py rename to src/backend/base/langflow/components/prototypes/Listen.py diff --git a/src/backend/base/langflow/components/experimental/Notify.py b/src/backend/base/langflow/components/prototypes/Notify.py similarity index 100% rename from src/backend/base/langflow/components/experimental/Notify.py rename to src/backend/base/langflow/components/prototypes/Notify.py diff --git a/src/backend/base/langflow/components/experimental/Pass.py b/src/backend/base/langflow/components/prototypes/Pass.py similarity index 98% rename from src/backend/base/langflow/components/experimental/Pass.py rename to src/backend/base/langflow/components/prototypes/Pass.py index d21fe0887..4e2f234c9 100644 --- a/src/backend/base/langflow/components/experimental/Pass.py +++ b/src/backend/base/langflow/components/prototypes/Pass.py @@ -9,6 +9,7 @@ class PassComponent(CustomComponent): display_name = "Pass" description = "A pass-through component that forwards the second input while ignoring the first, used for controlling workflow direction." field_order = ["ignored_input", "forwarded_input"] + beta = True def build_config(self) -> dict: return { diff --git a/src/backend/base/langflow/components/experimental/PythonFunction.py b/src/backend/base/langflow/components/prototypes/PythonFunction.py similarity index 97% rename from src/backend/base/langflow/components/experimental/PythonFunction.py rename to src/backend/base/langflow/components/prototypes/PythonFunction.py index d832e2f5c..f0f238636 100644 --- a/src/backend/base/langflow/components/experimental/PythonFunction.py +++ b/src/backend/base/langflow/components/prototypes/PythonFunction.py @@ -9,6 +9,7 @@ class PythonFunctionComponent(CustomComponent): display_name = "Python Function" description = "Define a Python function." icon = "Python" + beta = True def build_config(self): return { diff --git a/src/backend/base/langflow/components/experimental/RunFlow.py b/src/backend/base/langflow/components/prototypes/RunFlow.py similarity index 100% rename from src/backend/base/langflow/components/experimental/RunFlow.py rename to src/backend/base/langflow/components/prototypes/RunFlow.py diff --git a/src/backend/base/langflow/components/experimental/RunnableExecutor.py b/src/backend/base/langflow/components/prototypes/RunnableExecutor.py similarity index 100% rename from src/backend/base/langflow/components/experimental/RunnableExecutor.py rename to src/backend/base/langflow/components/prototypes/RunnableExecutor.py diff --git a/src/backend/base/langflow/components/experimental/SQLExecutor.py b/src/backend/base/langflow/components/prototypes/SQLExecutor.py similarity index 100% rename from src/backend/base/langflow/components/experimental/SQLExecutor.py rename to src/backend/base/langflow/components/prototypes/SQLExecutor.py diff --git a/src/backend/base/langflow/components/prototypes/SubFlow.py b/src/backend/base/langflow/components/prototypes/SubFlow.py new file mode 100644 index 000000000..b0631ee99 --- /dev/null +++ b/src/backend/base/langflow/components/prototypes/SubFlow.py @@ -0,0 +1,115 @@ +from typing import Any, List, Optional + +from langflow.base.flow_processing.utils import build_data_from_result_data +from langflow.custom import CustomComponent +from langflow.graph.graph.base import Graph +from langflow.graph.schema import RunOutputs +from langflow.graph.vertex.base import Vertex +from langflow.helpers.flow import get_flow_inputs +from langflow.schema import Data +from langflow.schema.dotdict import dotdict +from langflow.template.field.base import Input +from loguru import logger + + +class SubFlowComponent(CustomComponent): + display_name = "Sub Flow" + description = ( + "Dynamically Generates a Component from a Flow. The output is a list of data with keys 'result' and 'message'." + ) + beta: bool = True + field_order = ["flow_name"] + + def get_flow_names(self) -> List[str]: + flow_datas = self.list_flows() + return [flow_data.data["name"] for flow_data in flow_datas] + + def get_flow(self, flow_name: str) -> Optional[Data]: + flow_datas = self.list_flows() + for flow_data in flow_datas: + if flow_data.data["name"] == flow_name: + return flow_data + return None + + def update_build_config(self, build_config: dotdict, field_value: Any, field_name: str | None = None): + logger.debug(f"Updating build config with field value {field_value} and field name {field_name}") + if field_name == "flow_name": + build_config["flow_name"]["options"] = self.get_flow_names() + # Clean up the build config + for key in list(build_config.keys()): + if key not in self.field_order + ["code", "_type", "get_final_results_only"]: + del build_config[key] + if field_value is not None and field_name == "flow_name": + try: + flow_data = self.get_flow(field_value) + if not flow_data: + raise ValueError(f"Flow {field_value} not found.") + graph = Graph.from_payload(flow_data.data["data"]) + # Get all inputs from the graph + inputs = get_flow_inputs(graph) + # Add inputs to the build config + build_config = self.add_inputs_to_build_config(inputs, build_config) + except Exception as e: + logger.error(f"Error getting flow {field_value}: {str(e)}") + + return build_config + + def add_inputs_to_build_config(self, inputs: List[Vertex], build_config: dotdict): + new_fields: list[Input] = [] + for vertex in inputs: + field = Input( + display_name=vertex.display_name, + name=vertex.id, + info=vertex.description, + field_type="str", + value=None, + ) + new_fields.append(field) + logger.debug(new_fields) + for field in new_fields: + build_config[field.name] = field.to_dict() + return build_config + + def build_config(self): + return { + "input_value": { + "display_name": "Input Value", + "multiline": True, + }, + "flow_name": { + "display_name": "Flow Name", + "info": "The name of the flow to run.", + "options": [], + "real_time_refresh": True, + "refresh_button": True, + }, + "tweaks": { + "display_name": "Tweaks", + "info": "Tweaks to apply to the flow.", + }, + "get_final_results_only": { + "display_name": "Get Final Results Only", + "info": "If False, the output will contain all outputs from the flow.", + "advanced": True, + }, + } + + async def build(self, flow_name: str, get_final_results_only: bool = True, **kwargs) -> List[Data]: + tweaks = {key: {"input_value": value} for key, value in kwargs.items()} + run_outputs: List[Optional[RunOutputs]] = await self.run_flow( + tweaks=tweaks, + flow_name=flow_name, + ) + if not run_outputs: + return [] + run_output = run_outputs[0] + + data = [] + if run_output is not None: + for output in run_output.outputs: + if output: + data.extend(build_data_from_result_data(output, get_final_results_only)) + + self.status = data + logger.debug(data) + return data diff --git a/src/backend/base/langflow/components/prototypes/__init__.py b/src/backend/base/langflow/components/prototypes/__init__.py new file mode 100644 index 000000000..9b37551c0 --- /dev/null +++ b/src/backend/base/langflow/components/prototypes/__init__.py @@ -0,0 +1,39 @@ +# from .AgentComponent import AgentComponent +# from .ConditionalRouter import ConditionalRouterComponent +# from .ExtractKeyFromData import ExtractKeyFromDataComponent +# from .FlowTool import FlowToolComponent +# from .Listen import ListenComponent +# from .ListFlows import ListFlowsComponent +# from ..helpers.MergeData import MergeDataComponent +# from .Notify import NotifyComponent +# from .PythonFunction import PythonFunctionComponent +# from .RunFlow import RunFlowComponent +# from .RunnableExecutor import RunnableExecComponent +# from .SelectivePassThrough import SelectivePassThroughComponent +# from ..helpers.SplitText import SplitTextComponent +# from .SQLExecutor import SQLExecutorComponent +# from .SubFlow import SubFlowComponent + +from .ConditionalRouter import ConditionalRouterComponent +from .FlowTool import FlowToolComponent +from .Listen import ListenComponent +from .Notify import NotifyComponent +from .Pass import PassComponent +from .PythonFunction import PythonFunctionComponent +from .RunFlow import RunFlowComponent +from .RunnableExecutor import RunnableExecComponent +from .SQLExecutor import SQLExecutorComponent +from .SubFlow import SubFlowComponent + +__all__ = [ + "ConditionalRouterComponent", + "FlowToolComponent", + "ListenComponent", + "NotifyComponent", + "PassComponent", + "PythonFunctionComponent", + "RunFlowComponent", + "RunnableExecComponent", + "SQLExecutorComponent", + "SubFlowComponent", +] From 4876f183a1ca755546db052ebb2514624b0943fc Mon Sep 17 00:00:00 2001 From: Rodrigo Date: Sun, 23 Jun 2024 19:42:24 -0300 Subject: [PATCH 041/229] refactor: Remove unused import in IDGenerator.py --- src/backend/base/langflow/components/helpers/IDGenerator.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/backend/base/langflow/components/helpers/IDGenerator.py b/src/backend/base/langflow/components/helpers/IDGenerator.py index bf583229e..d55c4f71e 100644 --- a/src/backend/base/langflow/components/helpers/IDGenerator.py +++ b/src/backend/base/langflow/components/helpers/IDGenerator.py @@ -1,5 +1,5 @@ import uuid -from typing import Any, Optional +from typing import Optional from langflow.custom import CustomComponent From 6ceb19b9dd8c9e34b024a32d2f9ec8aea312e848 Mon Sep 17 00:00:00 2001 From: anovazzi1 Date: Sun, 23 Jun 2024 20:01:10 -0300 Subject: [PATCH 042/229] feat: Add beta label to Experimental parent disclosure title --- .../FlowPage/components/ParentDisclosureComponent/index.tsx | 3 ++- .../pages/FlowPage/components/extraSidebarComponent/index.tsx | 4 ++-- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/src/frontend/src/pages/FlowPage/components/ParentDisclosureComponent/index.tsx b/src/frontend/src/pages/FlowPage/components/ParentDisclosureComponent/index.tsx index c7293912b..5954e30b9 100644 --- a/src/frontend/src/pages/FlowPage/components/ParentDisclosureComponent/index.tsx +++ b/src/frontend/src/pages/FlowPage/components/ParentDisclosureComponent/index.tsx @@ -17,8 +17,9 @@ export default function ParentDisclosureComponent({ className="parent-disclosure-arrangement" data-testid={testId} > -
+
{title} + {title==="Experimental"&&
BETA
}
{buttons.map((btn, index) => ( diff --git a/src/frontend/src/pages/FlowPage/components/extraSidebarComponent/index.tsx b/src/frontend/src/pages/FlowPage/components/extraSidebarComponent/index.tsx index c51a5a282..35166b160 100644 --- a/src/frontend/src/pages/FlowPage/components/extraSidebarComponent/index.tsx +++ b/src/frontend/src/pages/FlowPage/components/extraSidebarComponent/index.tsx @@ -288,7 +288,7 @@ export default function ExtraSidebar(): JSX.Element {
- Basic Components + Components
{Object.keys(dataFilter) @@ -367,7 +367,7 @@ export default function ExtraSidebar(): JSX.Element { defaultOpen={search.length !== 0 || getFilterEdge.length !== 0} key={`${search.length !== 0}-${getFilterEdge.length !== 0}-Advanced`} button={{ - title: "Advanced", + title: "Experimental", Icon: nodeIconsLucide.unknown, }} testId="extended-disclosure" From 4bd09b925e2f2d9c43815c48ddec9d51ab052dfe Mon Sep 17 00:00:00 2001 From: anovazzi1 Date: Sun, 23 Jun 2024 23:02:34 +0000 Subject: [PATCH 043/229] Apply Prettier formatting --- .../components/ParentDisclosureComponent/index.tsx | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/src/frontend/src/pages/FlowPage/components/ParentDisclosureComponent/index.tsx b/src/frontend/src/pages/FlowPage/components/ParentDisclosureComponent/index.tsx index 5954e30b9..63fe656ca 100644 --- a/src/frontend/src/pages/FlowPage/components/ParentDisclosureComponent/index.tsx +++ b/src/frontend/src/pages/FlowPage/components/ParentDisclosureComponent/index.tsx @@ -17,9 +17,13 @@ export default function ParentDisclosureComponent({ className="parent-disclosure-arrangement" data-testid={testId} > -
+
{title} - {title==="Experimental"&&
BETA
} + {title === "Experimental" && ( +
+ BETA +
+ )}
{buttons.map((btn, index) => ( From e71a63432dbbce52883ae2433661beda35600371 Mon Sep 17 00:00:00 2001 From: anovazzi1 Date: Sun, 23 Jun 2024 20:45:18 -0300 Subject: [PATCH 044/229] added beta foreground soft color --- .../FlowPage/components/ParentDisclosureComponent/index.tsx | 2 +- src/frontend/src/style/index.css | 1 + src/frontend/tailwind.config.mjs | 1 + 3 files changed, 3 insertions(+), 1 deletion(-) diff --git a/src/frontend/src/pages/FlowPage/components/ParentDisclosureComponent/index.tsx b/src/frontend/src/pages/FlowPage/components/ParentDisclosureComponent/index.tsx index 63fe656ca..936269e45 100644 --- a/src/frontend/src/pages/FlowPage/components/ParentDisclosureComponent/index.tsx +++ b/src/frontend/src/pages/FlowPage/components/ParentDisclosureComponent/index.tsx @@ -20,7 +20,7 @@ export default function ParentDisclosureComponent({
{title} {title === "Experimental" && ( -
+
BETA
)} diff --git a/src/frontend/src/style/index.css b/src/frontend/src/style/index.css index 9a35b45aa..ba61e8fb8 100644 --- a/src/frontend/src/style/index.css +++ b/src/frontend/src/style/index.css @@ -46,6 +46,7 @@ --beta-background: rgb(219 234 254); --beta-foreground: rgb(37 99 235); + --beta-foreground-soft: rgb(37 99 235 / 80%); --chat-bot-icon: #afe6ef; --chat-user-icon: #aface9; diff --git a/src/frontend/tailwind.config.mjs b/src/frontend/tailwind.config.mjs index 4b1df3063..2fd7cb24a 100644 --- a/src/frontend/tailwind.config.mjs +++ b/src/frontend/tailwind.config.mjs @@ -98,6 +98,7 @@ const config = { "success-foreground": "var(--success-foreground)", "beta-background": "var(--beta-background)", "beta-foreground": "var(--beta-foreground)", + "beta-foreground-soft": "var(--beta-foreground-soft)", "chat-bot-icon": "var(--chat-bot-icon)", "chat-user-icon": "var(--chat-user-icon)", ice: "var(--ice)", From 55e4fe93c0997db04cdd6fe55ec511cac93d00f4 Mon Sep 17 00:00:00 2001 From: italojohnny Date: Sun, 23 Jun 2024 20:54:08 -0300 Subject: [PATCH 045/229] fix code --- .../components/agents/ToolCallingAgent.py | 16 +++------------- 1 file changed, 3 insertions(+), 13 deletions(-) diff --git a/src/backend/base/langflow/components/agents/ToolCallingAgent.py b/src/backend/base/langflow/components/agents/ToolCallingAgent.py index a9403e861..318c5c622 100644 --- a/src/backend/base/langflow/components/agents/ToolCallingAgent.py +++ b/src/backend/base/langflow/components/agents/ToolCallingAgent.py @@ -1,27 +1,17 @@ -from typing import List, Optional - +from typing import List, Dict from langchain.agents.tool_calling_agent.base import create_tool_calling_agent from langchain_core.prompts import ChatPromptTemplate -<<<<<<< Updated upstream - -from langflow.custom import Component -from langflow.io import BoolInput, HandleInput, MessageTextInput, Output -from langflow.schema import Data -======= from langchain.agents import AgentExecutor from langchain_core.messages import BaseMessage ->>>>>>> Stashed changes from langflow.schema.message import Message from langflow.custom import Component -from langflow.io import HandleInput, TextInput, BoolInput, Output +from langflow.io import HandleInput, BoolInput, Output, MessageTextInput from langflow.schema import Data class ToolCallingAgentComponent(Component): display_name: str = "Tool Calling Agent" - description: str = ( - "Agent that uses tools. Only models that are compatible with function calling are supported." - ) + description: str = "Agent that uses tools. Only models that are compatible with function calling are supported." icon = "LangChain" beta = True From 0f5b0c0ac3746ab12d675bb9439b30affb9516c6 Mon Sep 17 00:00:00 2001 From: italojohnny Date: Sun, 23 Jun 2024 23:49:56 -0300 Subject: [PATCH 046/229] disable component litellm --- .../components/{models => deactivated}/ChatLiteLLMModel.py | 0 src/backend/base/langflow/components/models/__init__.py | 2 -- 2 files changed, 2 deletions(-) rename src/backend/base/langflow/components/{models => deactivated}/ChatLiteLLMModel.py (100%) diff --git a/src/backend/base/langflow/components/models/ChatLiteLLMModel.py b/src/backend/base/langflow/components/deactivated/ChatLiteLLMModel.py similarity index 100% rename from src/backend/base/langflow/components/models/ChatLiteLLMModel.py rename to src/backend/base/langflow/components/deactivated/ChatLiteLLMModel.py diff --git a/src/backend/base/langflow/components/models/__init__.py b/src/backend/base/langflow/components/models/__init__.py index a348f230a..70e1ab10c 100644 --- a/src/backend/base/langflow/components/models/__init__.py +++ b/src/backend/base/langflow/components/models/__init__.py @@ -2,7 +2,6 @@ from .AmazonBedrockModel import AmazonBedrockComponent from .AnthropicModel import AnthropicModelComponent from .AzureOpenAIModel import AzureChatOpenAIComponent from .BaiduQianfanChatModel import QianfanChatEndpointComponent -from .ChatLiteLLMModel import ChatLiteLLMModelComponent from .CohereModel import CohereComponent from .GoogleGenerativeAIModel import GoogleGenerativeAIComponent from .HuggingFaceModel import HuggingFaceEndpointsComponent @@ -11,7 +10,6 @@ from .OpenAIModel import OpenAIModelComponent from .VertexAiModel import ChatVertexAIComponent __all__ = [ - "ChatLiteLLMModelComponent", "AmazonBedrockComponent", "AnthropicModelComponent", "AzureChatOpenAIComponent", From 9a76bcbac224792f52b25906f860ab5c04597172 Mon Sep 17 00:00:00 2001 From: italojohnny Date: Mon, 24 Jun 2024 00:57:31 -0300 Subject: [PATCH 047/229] move components from helpers to prototypes --- src/backend/base/langflow/components/helpers/__init__.py | 4 ---- .../langflow/components/{helpers => prototypes}/CreateData.py | 0 .../langflow/components/{helpers => prototypes}/UpdateData.py | 0 src/backend/base/langflow/components/prototypes/__init__.py | 4 ++++ 4 files changed, 4 insertions(+), 4 deletions(-) rename src/backend/base/langflow/components/{helpers => prototypes}/CreateData.py (100%) rename src/backend/base/langflow/components/{helpers => prototypes}/UpdateData.py (100%) diff --git a/src/backend/base/langflow/components/helpers/__init__.py b/src/backend/base/langflow/components/helpers/__init__.py index ab1f8d00a..1941e38b8 100644 --- a/src/backend/base/langflow/components/helpers/__init__.py +++ b/src/backend/base/langflow/components/helpers/__init__.py @@ -1,5 +1,4 @@ from .CombineText import CombineTextComponent -from .CreateData import CreateDataComponent from .CustomComponent import CustomComponent from .FilterData import FilterDataComponent from .IDGenerator import UUIDGeneratorComponent @@ -8,12 +7,10 @@ from .MergeData import MergeDataComponent from .ParseData import ParseDataComponent from .SplitText import SplitTextComponent from .StoreMessage import StoreMessageComponent -from .UpdateData import UpdateDataComponent __all__ = [ "CombineTextComponent", - "CreateDataComponent", "CustomComponent", "FilterDataComponent", "UUIDGeneratorComponent", @@ -22,5 +19,4 @@ __all__ = [ "ParseDataComponent", "SplitTextComponent", "StoreMessageComponent", - "UpdateDataComponent", ] diff --git a/src/backend/base/langflow/components/helpers/CreateData.py b/src/backend/base/langflow/components/prototypes/CreateData.py similarity index 100% rename from src/backend/base/langflow/components/helpers/CreateData.py rename to src/backend/base/langflow/components/prototypes/CreateData.py diff --git a/src/backend/base/langflow/components/helpers/UpdateData.py b/src/backend/base/langflow/components/prototypes/UpdateData.py similarity index 100% rename from src/backend/base/langflow/components/helpers/UpdateData.py rename to src/backend/base/langflow/components/prototypes/UpdateData.py diff --git a/src/backend/base/langflow/components/prototypes/__init__.py b/src/backend/base/langflow/components/prototypes/__init__.py index 9b37551c0..60498a530 100644 --- a/src/backend/base/langflow/components/prototypes/__init__.py +++ b/src/backend/base/langflow/components/prototypes/__init__.py @@ -24,6 +24,8 @@ from .RunFlow import RunFlowComponent from .RunnableExecutor import RunnableExecComponent from .SQLExecutor import SQLExecutorComponent from .SubFlow import SubFlowComponent +from .CreateData import CreateDataComponent +from .UpdateData import UpdateDataComponent __all__ = [ "ConditionalRouterComponent", @@ -36,4 +38,6 @@ __all__ = [ "RunnableExecComponent", "SQLExecutorComponent", "SubFlowComponent", + "CreateDataComponent", + "UpdateDataComponent", ] From 3f22a78c5ad91df0dc1a179c6066d56e71d8bb5d Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Mon, 24 Jun 2024 07:53:41 -0300 Subject: [PATCH 048/229] Fixed beta --- src/frontend/src/style/index.css | 1 + 1 file changed, 1 insertion(+) diff --git a/src/frontend/src/style/index.css b/src/frontend/src/style/index.css index ba61e8fb8..e362a0345 100644 --- a/src/frontend/src/style/index.css +++ b/src/frontend/src/style/index.css @@ -139,6 +139,7 @@ --beta-background: rgb(37 99 235); --beta-foreground: rgb(219 234 254); + --beta-foreground-soft: rgb(219 234 254); --chat-bot-icon: #235d70; --chat-user-icon: #4f3d6e; From 321ef411e5cfa083643d236f32ca1e7ffd24aa6b Mon Sep 17 00:00:00 2001 From: ogabrielluiz Date: Mon, 24 Jun 2024 11:14:14 +0000 Subject: [PATCH 049/229] Apply Prettier formatting --- src/frontend/package-lock.json | 1 - .../GenericNode/components/parameterComponent/index.tsx | 2 +- 2 files changed, 1 insertion(+), 2 deletions(-) diff --git a/src/frontend/package-lock.json b/src/frontend/package-lock.json index c73a25fee..d6b9d3b74 100644 --- a/src/frontend/package-lock.json +++ b/src/frontend/package-lock.json @@ -787,7 +787,6 @@ }, "node_modules/@clack/prompts/node_modules/is-unicode-supported": { "version": "1.3.0", - "extraneous": true, "inBundle": true, "license": "MIT", "engines": { diff --git a/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx b/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx index 9681ead39..afb15b8eb 100644 --- a/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx +++ b/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx @@ -650,7 +650,7 @@ export default function ParameterComponent({ value={ !data.node!.template[name]?.value || !Object.keys(data.node!.template[name]?.value || {}).length - ? [{"":""}] + ? [{ "": "" }] : convertObjToArray(data.node!.template[name]?.value, type!) } duplicateKey={errorDuplicateKey} From 70ffff186aa9dfe80473dc4fe98a2bfbee62d92b Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 08:32:53 -0300 Subject: [PATCH 050/229] refactor: Update ToolCallingAgent.py imports and type annotations --- .../langflow/components/agents/ToolCallingAgent.py | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/src/backend/base/langflow/components/agents/ToolCallingAgent.py b/src/backend/base/langflow/components/agents/ToolCallingAgent.py index 318c5c622..e2b643f1c 100644 --- a/src/backend/base/langflow/components/agents/ToolCallingAgent.py +++ b/src/backend/base/langflow/components/agents/ToolCallingAgent.py @@ -1,12 +1,14 @@ -from typing import List, Dict +from typing import Dict, List, cast + +from langchain.agents import AgentExecutor, BaseSingleActionAgent from langchain.agents.tool_calling_agent.base import create_tool_calling_agent -from langchain_core.prompts import ChatPromptTemplate -from langchain.agents import AgentExecutor from langchain_core.messages import BaseMessage -from langflow.schema.message import Message +from langchain_core.prompts import ChatPromptTemplate + from langflow.custom import Component -from langflow.io import HandleInput, BoolInput, Output, MessageTextInput +from langflow.io import BoolInput, HandleInput, MessageTextInput, Output from langflow.schema import Data +from langflow.schema.message import Message class ToolCallingAgentComponent(Component): @@ -80,7 +82,7 @@ class ToolCallingAgentComponent(Component): agent = create_tool_calling_agent(self.llm, self.tools, prompt) runnable = AgentExecutor.from_agent_and_tools( - agent=agent, + agent=cast(BaseSingleActionAgent, agent), tools=self.tools, verbose=True, handle_parsing_errors=self.handle_parsing_errors, From 783475e50dd902fd2409048e9ba26602110e4f93 Mon Sep 17 00:00:00 2001 From: Cezar Vasconcelos Date: Mon, 24 Jun 2024 00:57:36 +0000 Subject: [PATCH 051/229] refactor: Update VectaraVectorStoreComponent to handle embedding input and add documents to vector store --- .../components/vectorstores/Vectara.py | 89 ++++++++++++------- 1 file changed, 59 insertions(+), 30 deletions(-) diff --git a/src/backend/base/langflow/components/vectorstores/Vectara.py b/src/backend/base/langflow/components/vectorstores/Vectara.py index 674a35ff5..198baeb8d 100644 --- a/src/backend/base/langflow/components/vectorstores/Vectara.py +++ b/src/backend/base/langflow/components/vectorstores/Vectara.py @@ -1,30 +1,45 @@ -from typing import List +from typing import List, TYPE_CHECKING -from langchain_community.embeddings import FakeEmbeddings from langchain_community.vectorstores import Vectara +from loguru import logger from langflow.base.vectorstores.model import LCVectorStoreComponent from langflow.helpers.data import docs_to_data -from langflow.io import IntInput, StrInput, SecretStrInput, DataInput, MultilineInput +from langflow.io import HandleInput, IntInput, Output, SecretStrInput, StrInput, TextInput from langflow.schema import Data +if TYPE_CHECKING: + from langchain_community.vectorstores import Vectara class VectaraVectorStoreComponent(LCVectorStoreComponent): - display_name = "Vectara" - description = "Vectara Vector Store with search capabilities" - documentation = "https://python.langchain.com/v0.2/docs/integrations/vectorstores/vectara/" + """ + Vectara Vector Store with search capabilities + """ + + display_name: str = "Vectara" + description: str = "Vectara Vector Store with search capabilities" + documentation = "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/vectara" icon = "Vectara" inputs = [ StrInput(name="vectara_customer_id", display_name="Vectara Customer ID", required=True), StrInput(name="vectara_corpus_id", display_name="Vectara Corpus ID", required=True), SecretStrInput(name="vectara_api_key", display_name="Vectara API Key", required=True), - MultilineInput(name="search_query", display_name="Search Query"), - DataInput( + HandleInput( + name="embedding", + display_name="Embedding", + input_types=["Embeddings"], + ), + HandleInput( name="ingest_data", - display_name="Vector Store Inputs", + display_name="Ingest Data", + input_types=["Document", "Data"], is_list=True, ), + TextInput( + name="search_query", + display_name="Search Query", + ), IntInput( name="number_of_results", display_name="Number of Results", @@ -34,11 +49,33 @@ class VectaraVectorStoreComponent(LCVectorStoreComponent): ), ] - def build_vector_store(self) -> Vectara: - return self._build_vectara() + def build_vector_store(self) -> "Vectara": + """ + Builds the Vectara object. + """ + try: + from langchain_community.vectorstores import Vectara + except ImportError: + raise ImportError( + "Could not import Vectara. Please install it with `pip install langchain-community`." + ) - def _build_vectara(self) -> Vectara: - source = "Langflow" + vectara = Vectara( + vectara_customer_id=self.vectara_customer_id, + vectara_corpus_id=self.vectara_corpus_id, + vectara_api_key=self.vectara_api_key, + ) + + self._add_documents_to_vector_store(vectara) + return vectara + + def _add_documents_to_vector_store(self, vector_store: "Vectara") -> None: + """ + Adds documents to the Vector Store. + """ + if not self.ingest_data: + self.status = "No documents to add to Vectara" + return documents = [] for _input in self.ingest_data or []: @@ -48,24 +85,15 @@ class VectaraVectorStoreComponent(LCVectorStoreComponent): documents.append(_input) if documents: - return Vectara.from_documents( - documents=documents, - embedding=FakeEmbeddings(size=768), - vectara_customer_id=self.vectara_customer_id, - vectara_corpus_id=self.vectara_corpus_id, - vectara_api_key=self.vectara_api_key, - source=source, - ) - - return Vectara( - vectara_customer_id=self.vectara_customer_id, - vectara_corpus_id=self.vectara_corpus_id, - vectara_api_key=self.vectara_api_key, - source=source, - ) + logger.debug(f"Adding {len(documents)} documents to Vectara.") + vector_store.add_documents(documents) + self.status = f"Added {len(documents)} documents to Vectara" + else: + logger.debug("No documents to add to Vectara.") + self.status = "No valid documents to add to Vectara" def search_documents(self) -> List[Data]: - vector_store = self._build_vectara() + vector_store = self.build_vector_store() if self.search_query and isinstance(self.search_query, str) and self.search_query.strip(): docs = vector_store.similarity_search( @@ -74,7 +102,8 @@ class VectaraVectorStoreComponent(LCVectorStoreComponent): ) data = docs_to_data(docs) - self.status = data + self.status = f"Found {len(data)} results for the query: {self.search_query}" return data else: + self.status = "No search query provided" return [] From d11e7c6fc514b3c3e7e71be5f95b235b4b9055b6 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 08:42:51 -0300 Subject: [PATCH 052/229] fix: run ruff --- .../base/langflow/components/vectorstores/Vectara.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/src/backend/base/langflow/components/vectorstores/Vectara.py b/src/backend/base/langflow/components/vectorstores/Vectara.py index 198baeb8d..6bbf479bf 100644 --- a/src/backend/base/langflow/components/vectorstores/Vectara.py +++ b/src/backend/base/langflow/components/vectorstores/Vectara.py @@ -5,12 +5,13 @@ from loguru import logger from langflow.base.vectorstores.model import LCVectorStoreComponent from langflow.helpers.data import docs_to_data -from langflow.io import HandleInput, IntInput, Output, SecretStrInput, StrInput, TextInput +from langflow.io import HandleInput, IntInput, SecretStrInput, StrInput, TextInput from langflow.schema import Data if TYPE_CHECKING: from langchain_community.vectorstores import Vectara + class VectaraVectorStoreComponent(LCVectorStoreComponent): """ Vectara Vector Store with search capabilities @@ -56,9 +57,7 @@ class VectaraVectorStoreComponent(LCVectorStoreComponent): try: from langchain_community.vectorstores import Vectara except ImportError: - raise ImportError( - "Could not import Vectara. Please install it with `pip install langchain-community`." - ) + raise ImportError("Could not import Vectara. Please install it with `pip install langchain-community`.") vectara = Vectara( vectara_customer_id=self.vectara_customer_id, From 6ec39c81361d3c48471ad836f029bd2e2af7f28e Mon Sep 17 00:00:00 2001 From: italojohnny Date: Mon, 24 Jun 2024 08:33:11 -0300 Subject: [PATCH 053/229] fix erros reported by mypy --- .../langflow/components/deactivated/__init__.py | 16 ++++++++-------- .../langflow/components/helpers/IDGenerator.py | 8 +++++--- 2 files changed, 13 insertions(+), 11 deletions(-) diff --git a/src/backend/base/langflow/components/deactivated/__init__.py b/src/backend/base/langflow/components/deactivated/__init__.py index 28cf78d1b..123ff23b9 100644 --- a/src/backend/base/langflow/components/deactivated/__init__.py +++ b/src/backend/base/langflow/components/deactivated/__init__.py @@ -1,17 +1,17 @@ from .AgentComponent import AgentComponent -from .ConditionalRouter import ConditionalRouterComponent +from .ConditionalRouter import ConditionalRouterComponent # type: ignore from .ExtractKeyFromData import ExtractKeyFromDataComponent -from .FlowTool import FlowToolComponent -from .Listen import ListenComponent +from .FlowTool import FlowToolComponent # type: ignore +from .Listen import ListenComponent # type: ignore from .ListFlows import ListFlowsComponent from .MergeData import MergeDataComponent -from .Notify import NotifyComponent -from .PythonFunction import PythonFunctionComponent -from .RunFlow import RunFlowComponent +from .Notify import NotifyComponent # type: ignore +from .PythonFunction import PythonFunctionComponent # type: ignore +from .RunFlow import RunFlowComponent # type: ignore from .RunnableExecutor import RunnableExecComponent from .SelectivePassThrough import SelectivePassThroughComponent -from .SplitText import SplitTextComponent -from .SQLExecutor import SQLExecutorComponent +from .SplitText import SplitTextComponent # type: ignore +from .SQLExecutor import SQLExecutorComponent # type: ignore from .SubFlow import SubFlowComponent __all__ = [ diff --git a/src/backend/base/langflow/components/helpers/IDGenerator.py b/src/backend/base/langflow/components/helpers/IDGenerator.py index d55c4f71e..fa8805583 100644 --- a/src/backend/base/langflow/components/helpers/IDGenerator.py +++ b/src/backend/base/langflow/components/helpers/IDGenerator.py @@ -1,16 +1,18 @@ import uuid -from typing import Optional +from typing import Optional, Any, from langflow.custom import CustomComponent +from langflow.schema.dotdict import dotdict class UUIDGeneratorComponent(CustomComponent): display_name = "ID Generator" description = "Generates a unique ID." - def update_build_config( + def update_build_config( # type: ignore self, - build_config: dict, + build_config: dotdict, + field_value: Any, field_name: Optional[str] = None, ): if field_name == "unique_id": From c63bef8b780e2016111fb18cfb5fb4fe64c4b9d7 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 08:47:05 -0300 Subject: [PATCH 054/229] remove comment --- .../langflow/components/prototypes/__init__.py | 16 ---------------- 1 file changed, 16 deletions(-) diff --git a/src/backend/base/langflow/components/prototypes/__init__.py b/src/backend/base/langflow/components/prototypes/__init__.py index 60498a530..89c14f7e9 100644 --- a/src/backend/base/langflow/components/prototypes/__init__.py +++ b/src/backend/base/langflow/components/prototypes/__init__.py @@ -1,19 +1,3 @@ -# from .AgentComponent import AgentComponent -# from .ConditionalRouter import ConditionalRouterComponent -# from .ExtractKeyFromData import ExtractKeyFromDataComponent -# from .FlowTool import FlowToolComponent -# from .Listen import ListenComponent -# from .ListFlows import ListFlowsComponent -# from ..helpers.MergeData import MergeDataComponent -# from .Notify import NotifyComponent -# from .PythonFunction import PythonFunctionComponent -# from .RunFlow import RunFlowComponent -# from .RunnableExecutor import RunnableExecComponent -# from .SelectivePassThrough import SelectivePassThroughComponent -# from ..helpers.SplitText import SplitTextComponent -# from .SQLExecutor import SQLExecutorComponent -# from .SubFlow import SubFlowComponent - from .ConditionalRouter import ConditionalRouterComponent from .FlowTool import FlowToolComponent from .Listen import ListenComponent From d18ac624768f977495d1a441f21b6e1e3af533bd Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 08:52:52 -0300 Subject: [PATCH 055/229] chore: Update imports and remove unused components in deactivated and prototypes folders --- .../base/langflow/components/deactivated/__init__.py | 10 ---------- .../base/langflow/components/prototypes/__init__.py | 2 +- 2 files changed, 1 insertion(+), 11 deletions(-) diff --git a/src/backend/base/langflow/components/deactivated/__init__.py b/src/backend/base/langflow/components/deactivated/__init__.py index 123ff23b9..51ef2e465 100644 --- a/src/backend/base/langflow/components/deactivated/__init__.py +++ b/src/backend/base/langflow/components/deactivated/__init__.py @@ -1,17 +1,8 @@ from .AgentComponent import AgentComponent -from .ConditionalRouter import ConditionalRouterComponent # type: ignore from .ExtractKeyFromData import ExtractKeyFromDataComponent -from .FlowTool import FlowToolComponent # type: ignore -from .Listen import ListenComponent # type: ignore from .ListFlows import ListFlowsComponent from .MergeData import MergeDataComponent -from .Notify import NotifyComponent # type: ignore -from .PythonFunction import PythonFunctionComponent # type: ignore -from .RunFlow import RunFlowComponent # type: ignore -from .RunnableExecutor import RunnableExecComponent from .SelectivePassThrough import SelectivePassThroughComponent -from .SplitText import SplitTextComponent # type: ignore -from .SQLExecutor import SQLExecutorComponent # type: ignore from .SubFlow import SubFlowComponent __all__ = [ @@ -25,7 +16,6 @@ __all__ = [ "NotifyComponent", "PythonFunctionComponent", "RunFlowComponent", - "RunnableExecComponent", "SplitTextComponent", "SQLExecutorComponent", "SubFlowComponent", diff --git a/src/backend/base/langflow/components/prototypes/__init__.py b/src/backend/base/langflow/components/prototypes/__init__.py index 89c14f7e9..8624865a2 100644 --- a/src/backend/base/langflow/components/prototypes/__init__.py +++ b/src/backend/base/langflow/components/prototypes/__init__.py @@ -1,4 +1,4 @@ -from .ConditionalRouter import ConditionalRouterComponent +µfrom .ConditionalRouter import ConditionalRouterComponent from .FlowTool import FlowToolComponent from .Listen import ListenComponent from .Notify import NotifyComponent From 914e741e29b9a5a926b91b51249ad700799159a2 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 08:55:39 -0300 Subject: [PATCH 056/229] fix: imports from TextInput to MessageTextInput --- docs/docs/components/custom.mdx | 10 +- .../components/deactivated/SplitText.py | 5 +- .../VectorStore-RAG-Flows.json | 489 ++++++++++++++---- 3 files changed, 386 insertions(+), 118 deletions(-) diff --git a/docs/docs/components/custom.mdx b/docs/docs/components/custom.mdx index 2d8ac9d87..cbc5f13ff 100644 --- a/docs/docs/components/custom.mdx +++ b/docs/docs/components/custom.mdx @@ -38,7 +38,7 @@ class ExampleComponent(Component): icon = "icon-name" inputs = [ - TextInput( + MessageTextInput( name="input_text", display_name="Input Text", info="Text input for the component.", @@ -102,7 +102,7 @@ icon = "icon-name" ```python inputs = [ - TextInput( + MessageTextInput( name="input_text", display_name="Input Text", info="Text input for the component.", @@ -162,7 +162,7 @@ These methods trigger `self.stop` to block the transmission for the selected out ```python from langflow.custom import Component -from langflow.inputs import TextInput, DropdownInput, BoolInput +from langflow.inputs import MessageTextInput, DropdownInput, BoolInput from langflow.template import Output from langflow.field_typing import Text @@ -172,12 +172,12 @@ class ConditionalRouterComponent(Component): icon = "router" inputs = [ - TextInput( + MessageTextInput( name="input_value", display_name="Input Value", info="Value to be evaluated.", ), - TextInput( + MessageTextInput( name="comparison_value", display_name="Comparison Value", info="Value to compare against.", diff --git a/src/backend/base/langflow/components/deactivated/SplitText.py b/src/backend/base/langflow/components/deactivated/SplitText.py index 73e87504c..1f2aecc24 100644 --- a/src/backend/base/langflow/components/deactivated/SplitText.py +++ b/src/backend/base/langflow/components/deactivated/SplitText.py @@ -1,8 +1,9 @@ from typing import List from langchain_text_splitters import CharacterTextSplitter + from langflow.custom import Component -from langflow.io import HandleInput, IntInput, Output, TextInput +from langflow.io import HandleInput, IntInput, Output from langflow.schema import Data from langflow.utils.util import unescape_string @@ -32,7 +33,7 @@ class SplitTextComponent(Component): info="The maximum number of characters in each chunk.", value=1000, ), - TextInput( + MessageTextInput( name="separator", display_name="Separator", info="The character to split on. Defaults to newline.", diff --git a/src/backend/base/langflow/initial_setup/starter_projects/VectorStore-RAG-Flows.json b/src/backend/base/langflow/initial_setup/starter_projects/VectorStore-RAG-Flows.json index df5d8f072..23abdbd13 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/VectorStore-RAG-Flows.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/VectorStore-RAG-Flows.json @@ -8,12 +8,16 @@ "dataType": "Prompt", "id": "Prompt-VecUe", "name": "prompt", - "output_types": ["Message"] + "output_types": [ + "Message" + ] }, "targetHandle": { "fieldName": "input_value", "id": "OpenAIModel-PKrw7", - "inputTypes": ["Message"], + "inputTypes": [ + "Message" + ], "type": "str" } }, @@ -34,12 +38,17 @@ "dataType": "OpenAIModel", "id": "OpenAIModel-PKrw7", "name": "text_output", - "output_types": ["Message"] + "output_types": [ + "Message" + ] }, "targetHandle": { "fieldName": "input_value", "id": "ChatOutput-nUD9B", - "inputTypes": ["Message", "str"], + "inputTypes": [ + "Message", + "str" + ], "type": "str" } }, @@ -60,12 +69,17 @@ "dataType": "File", "id": "File-w2zxA", "name": "data", - "output_types": ["Data"] + "output_types": [ + "Data" + ] }, "targetHandle": { "fieldName": "data_input", "id": "RecursiveCharacterTextSplitter-CrApG", - "inputTypes": ["Document", "Data"], + "inputTypes": [ + "Document", + "Data" + ], "type": "other" } }, @@ -82,12 +96,16 @@ "dataType": "RecursiveCharacterTextSplitter", "id": "RecursiveCharacterTextSplitter-CrApG", "name": "data", - "output_types": ["Data"] + "output_types": [ + "Data" + ] }, "targetHandle": { "fieldName": "vector_store_inputs", "id": "AstraDB-rXo8b", - "inputTypes": ["Data"], + "inputTypes": [ + "Data" + ], "type": "other" } }, @@ -104,12 +122,17 @@ "dataType": "OpenAIEmbeddings", "id": "OpenAIEmbeddings-PCoh9", "name": "embeddings", - "output_types": ["Embeddings"] + "output_types": [ + "Embeddings" + ] }, "targetHandle": { "fieldName": "embedding", "id": "AstraDB-rXo8b", - "inputTypes": ["Embeddings", "dict"], + "inputTypes": [ + "Embeddings", + "dict" + ], "type": "other" } }, @@ -126,12 +149,17 @@ "dataType": "ChatInput", "id": "ChatInput-sn9b4", "name": "message", - "output_types": ["Message"] + "output_types": [ + "Message" + ] }, "targetHandle": { "fieldName": "search_input", "id": "AstraDB-61WgV", - "inputTypes": ["Message", "str"], + "inputTypes": [ + "Message", + "str" + ], "type": "str" } }, @@ -149,12 +177,17 @@ "dataType": "OpenAIEmbeddings", "id": "OpenAIEmbeddings-HsV7O", "name": "embeddings", - "output_types": ["Embeddings"] + "output_types": [ + "Embeddings" + ] }, "targetHandle": { "fieldName": "embedding", "id": "AstraDB-61WgV", - "inputTypes": ["Embeddings", "dict"], + "inputTypes": [ + "Embeddings", + "dict" + ], "type": "other" } }, @@ -172,12 +205,16 @@ "dataType": "AstraDB", "id": "AstraDB-61WgV", "name": "search_results", - "output_types": ["Data"] + "output_types": [ + "Data" + ] }, "targetHandle": { "fieldName": "data", "id": "ParseData-DXlFW", - "inputTypes": ["Data"], + "inputTypes": [ + "Data" + ], "type": "other" } }, @@ -195,12 +232,16 @@ "dataType": "ParseData", "id": "ParseData-DXlFW", "name": "text", - "output_types": ["Message"] + "output_types": [ + "Message" + ] }, "targetHandle": { "fieldName": "input_value", "id": "TextOutput-rT1Fj", - "inputTypes": ["Message"], + "inputTypes": [ + "Message" + ], "type": "str" } }, @@ -217,12 +258,17 @@ "dataType": "TextOutput", "id": "TextOutput-rT1Fj", "name": "text", - "output_types": ["Message"] + "output_types": [ + "Message" + ] }, "targetHandle": { "fieldName": "context", "id": "Prompt-VecUe", - "inputTypes": ["Message", "Text"], + "inputTypes": [ + "Message", + "Text" + ], "type": "str" } }, @@ -239,12 +285,17 @@ "dataType": "ChatInput", "id": "ChatInput-sn9b4", "name": "message", - "output_types": ["Message"] + "output_types": [ + "Message" + ] }, "targetHandle": { "fieldName": "question", "id": "Prompt-VecUe", - "inputTypes": ["Message", "Text"], + "inputTypes": [ + "Message", + "Text" + ], "type": "str" } }, @@ -260,7 +311,12 @@ "data": { "id": "ChatInput-sn9b4", "node": { - "base_classes": ["Text", "str", "object", "Record"], + "base_classes": [ + "Text", + "str", + "object", + "Record" + ], "beta": false, "custom_fields": { "input_value": null, @@ -284,7 +340,9 @@ "method": "message_response", "name": "message", "selected": "Message", - "types": ["Message"], + "types": [ + "Message" + ], "value": "__UNDEFINED__" } ], @@ -306,7 +364,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, Output, TextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n TextInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n TextInput(\n name=\"sender_name\",\n type=str,\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n TextInput(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, Output, MessageTextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n multiline=True,\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n type=str,\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\", type=str, display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" }, "input_value": { "advanced": false, @@ -315,7 +373,10 @@ "fileTypes": [], "file_path": "", "info": "Message to be passed as input.", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "multiline": true, @@ -335,12 +396,17 @@ "fileTypes": [], "file_path": "", "info": "Type of sender.", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": true, "load_from_db": false, "multiline": false, "name": "sender", - "options": ["Machine", "User"], + "options": [ + "Machine", + "User" + ], "password": false, "placeholder": "", "required": false, @@ -356,7 +422,10 @@ "fileTypes": [], "file_path": "", "info": "Name of the sender.", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "multiline": true, @@ -376,7 +445,10 @@ "fileTypes": [], "file_path": "", "info": "Session ID for the message.", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "multiline": true, @@ -415,7 +487,9 @@ "edited": false, "id": "TextOutput-rT1Fj", "node": { - "base_classes": ["Message"], + "base_classes": [ + "Message" + ], "beta": false, "conditional_paths": [], "custom_fields": {}, @@ -423,7 +497,9 @@ "display_name": "Extracted Chunks", "documentation": "", "edited": true, - "field_order": ["input_value"], + "field_order": [ + "input_value" + ], "frozen": false, "icon": "type", "output_types": [], @@ -435,7 +511,9 @@ "method": "text_response", "name": "text", "selected": "Message", - "types": ["Message"], + "types": [ + "Message" + ], "value": "__UNDEFINED__" } ], @@ -458,14 +536,16 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.text import TextComponent\nfrom langflow.io import Output\nfrom langflow.io import TextInput\nfrom langflow.schema.message import Message\n\n\nclass TextOutputComponent(TextComponent):\n display_name = \"Text Output\"\n description = \"Display a text output in the Playground.\"\n icon = \"type\"\n\n inputs = [\n TextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Text to be passed as output.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Message:\n message = Message(\n text=self.input_value,\n )\n self.status = self.input_value\n return message\n" + "value": "from langflow.base.io.text import TextComponent\nfrom langflow.io import Output\nfrom langflow.io import TextInput\nfrom langflow.schema.message import Message\n\n\nclass TextOutputComponent(TextComponent):\n display_name = \"Text Output\"\n description = \"Display a text output in the Playground.\"\n icon = \"type\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Text to be passed as output.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Message:\n message = Message(\n text=self.input_value,\n )\n self.status = self.input_value\n return message\n" }, "input_value": { "advanced": false, "display_name": "Text", "dynamic": false, "info": "Text to be passed as output.", - "input_types": ["Message"], + "input_types": [ + "Message" + ], "list": false, "load_from_db": false, "name": "input_value", @@ -499,7 +579,9 @@ "data": { "id": "OpenAIEmbeddings-HsV7O", "node": { - "base_classes": ["Embeddings"], + "base_classes": [ + "Embeddings" + ], "beta": false, "custom_fields": { "allowed_special": null, @@ -540,7 +622,9 @@ "method": "build_embeddings", "name": "embeddings", "selected": "Embeddings", - "types": ["Embeddings"], + "types": [ + "Embeddings" + ], "value": "__UNDEFINED__" } ], @@ -565,7 +649,10 @@ "display_name": "Client", "dynamic": false, "info": "", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "name": "client", @@ -592,7 +679,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_openai.embeddings.base import OpenAIEmbeddings\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import Embeddings\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, Output, SecretStrInput, TextInput\n\n\nclass OpenAIEmbeddingsComponent(LCModelComponent):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n icon = \"OpenAI\"\n inputs = [\n DictInput(\n name=\"default_headers\",\n display_name=\"Default Headers\",\n advanced=True,\n info=\"Default headers to use for the API request.\",\n ),\n DictInput(\n name=\"default_query\",\n display_name=\"Default Query\",\n advanced=True,\n info=\"Default query parameters to use for the API request.\",\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n TextInput(name=\"client\", display_name=\"Client\", advanced=True),\n TextInput(name=\"deployment\", display_name=\"Deployment\", advanced=True),\n IntInput(name=\"embedding_ctx_length\", display_name=\"Embedding Context Length\", advanced=True, value=1536),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", value=3, advanced=True),\n DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n advanced=False,\n options=[\n \"text-embedding-3-small\",\n \"text-embedding-3-large\",\n \"text-embedding-ada-002\",\n ],\n value=\"text-embedding-3-small\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n SecretStrInput(name=\"openai_api_base\", display_name=\"OpenAI API Base\", advanced=True),\n SecretStrInput(name=\"openai_api_key\", display_name=\"OpenAI API Key\"),\n SecretStrInput(name=\"openai_api_type\", display_name=\"OpenAI API Type\", advanced=True),\n TextInput(name=\"openai_api_version\", display_name=\"OpenAI API Version\", advanced=True),\n TextInput(\n name=\"openai_organization\",\n display_name=\"OpenAI Organization\",\n advanced=True,\n ),\n TextInput(name=\"openai_proxy\", display_name=\"OpenAI Proxy\", advanced=True),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n BoolInput(name=\"skip_empty\", display_name=\"Skip Empty\", advanced=True),\n TextInput(\n name=\"tiktoken_model_name\",\n display_name=\"TikToken Model Name\",\n advanced=True,\n ),\n BoolInput(\n name=\"tiktoken_enable\",\n display_name=\"TikToken Enable\",\n advanced=True,\n value=True,\n info=\"If False, you must have transformers installed.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Embeddings\", name=\"embeddings\", method=\"build_embeddings\"),\n ]\n\n def build_embeddings(self) -> Embeddings:\n return OpenAIEmbeddings(\n tiktoken_enabled=self.tiktoken_enable,\n default_headers=self.default_headers,\n default_query=self.default_query,\n allowed_special=\"all\",\n disallowed_special=\"all\",\n chunk_size=self.chunk_size,\n deployment=self.deployment,\n embedding_ctx_length=self.embedding_ctx_length,\n max_retries=self.max_retries,\n model=self.model,\n model_kwargs=self.model_kwargs,\n base_url=self.openai_api_base,\n api_key=self.openai_api_key,\n openai_api_type=self.openai_api_type,\n api_version=self.openai_api_version,\n organization=self.openai_organization,\n openai_proxy=self.openai_proxy,\n timeout=self.request_timeout or None,\n show_progress_bar=self.show_progress_bar,\n skip_empty=self.skip_empty,\n tiktoken_model_name=self.tiktoken_model_name,\n )\n" + "value": "from langchain_openai.embeddings.base import OpenAIEmbeddings\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import Embeddings\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, Output, SecretStrInput, MessageTextInput\n\n\nclass OpenAIEmbeddingsComponent(LCModelComponent):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n icon = \"OpenAI\"\n inputs = [\n DictInput(\n name=\"default_headers\",\n display_name=\"Default Headers\",\n advanced=True,\n info=\"Default headers to use for the API request.\",\n ),\n DictInput(\n name=\"default_query\",\n display_name=\"Default Query\",\n advanced=True,\n info=\"Default query parameters to use for the API request.\",\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n MessageTextInput(name=\"client\", display_name=\"Client\", advanced=True),\n MessageTextInput(name=\"deployment\", display_name=\"Deployment\", advanced=True),\n IntInput(name=\"embedding_ctx_length\", display_name=\"Embedding Context Length\", advanced=True, value=1536),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", value=3, advanced=True),\n DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n advanced=False,\n options=[\n \"text-embedding-3-small\",\n \"text-embedding-3-large\",\n \"text-embedding-ada-002\",\n ],\n value=\"text-embedding-3-small\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n SecretStrInput(name=\"openai_api_base\", display_name=\"OpenAI API Base\", advanced=True),\n SecretStrInput(name=\"openai_api_key\", display_name=\"OpenAI API Key\"),\n SecretStrInput(name=\"openai_api_type\", display_name=\"OpenAI API Type\", advanced=True),\n MessageTextInput(name=\"openai_api_version\", display_name=\"OpenAI API Version\", advanced=True),\n MessageTextInput(\n name=\"openai_organization\",\n display_name=\"OpenAI Organization\",\n advanced=True,\n ),\n MessageTextInput(name=\"openai_proxy\", display_name=\"OpenAI Proxy\", advanced=True),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n BoolInput(name=\"skip_empty\", display_name=\"Skip Empty\", advanced=True),\n MessageTextInput(\n name=\"tiktoken_model_name\",\n display_name=\"TikToken Model Name\",\n advanced=True,\n ),\n BoolInput(\n name=\"tiktoken_enable\",\n display_name=\"TikToken Enable\",\n advanced=True,\n value=True,\n info=\"If False, you must have transformers installed.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Embeddings\", name=\"embeddings\", method=\"build_embeddings\"),\n ]\n\n def build_embeddings(self) -> Embeddings:\n return OpenAIEmbeddings(\n tiktoken_enabled=self.tiktoken_enable,\n default_headers=self.default_headers,\n default_query=self.default_query,\n allowed_special=\"all\",\n disallowed_special=\"all\",\n chunk_size=self.chunk_size,\n deployment=self.deployment,\n embedding_ctx_length=self.embedding_ctx_length,\n max_retries=self.max_retries,\n model=self.model,\n model_kwargs=self.model_kwargs,\n base_url=self.openai_api_base,\n api_key=self.openai_api_key,\n openai_api_type=self.openai_api_type,\n api_version=self.openai_api_version,\n organization=self.openai_organization,\n openai_proxy=self.openai_proxy,\n timeout=self.request_timeout or None,\n show_progress_bar=self.show_progress_bar,\n skip_empty=self.skip_empty,\n tiktoken_model_name=self.tiktoken_model_name,\n )\n" }, "default_headers": { "advanced": true, @@ -627,7 +714,10 @@ "display_name": "Deployment", "dynamic": false, "info": "", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "name": "deployment", @@ -751,7 +841,10 @@ "display_name": "OpenAI API Version", "dynamic": false, "info": "", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "name": "openai_api_version", @@ -767,7 +860,10 @@ "display_name": "OpenAI Organization", "dynamic": false, "info": "", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "name": "openai_organization", @@ -783,7 +879,10 @@ "display_name": "OpenAI Proxy", "dynamic": false, "info": "", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "name": "openai_proxy", @@ -855,7 +954,10 @@ "display_name": "TikToken Model Name", "dynamic": false, "info": "", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "name": "tiktoken_model_name", @@ -889,7 +991,11 @@ "data": { "id": "OpenAIModel-PKrw7", "node": { - "base_classes": ["object", "Text", "str"], + "base_classes": [ + "object", + "Text", + "str" + ], "beta": false, "custom_fields": { "input_value": null, @@ -927,7 +1033,9 @@ "method": "text_response", "name": "text_output", "selected": "Message", - "types": ["Message"], + "types": [ + "Message" + ], "value": "__UNDEFINED__" }, { @@ -936,7 +1044,9 @@ "method": "build_model", "name": "model_output", "selected": "BaseLanguageModel", - "types": ["BaseLanguageModel"], + "types": [ + "BaseLanguageModel" + ], "value": "__UNDEFINED__" } ], @@ -967,7 +1077,9 @@ "fileTypes": [], "file_path": "", "info": "", - "input_types": ["Message"], + "input_types": [ + "Message" + ], "list": false, "load_from_db": false, "multiline": true, @@ -987,7 +1099,9 @@ "fileTypes": [], "file_path": "", "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": false, @@ -1007,7 +1121,9 @@ "fileTypes": [], "file_path": "", "info": "", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": false, @@ -1027,7 +1143,9 @@ "fileTypes": [], "file_path": "", "info": "", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": true, "load_from_db": false, "multiline": false, @@ -1054,7 +1172,9 @@ "fileTypes": [], "file_path": "", "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": true, @@ -1094,7 +1214,9 @@ "fileTypes": [], "file_path": "", "info": "Stream the response from the model. Streaming works only in Chat.", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": false, @@ -1114,7 +1236,9 @@ "fileTypes": [], "file_path": "", "info": "System message to pass to the model.", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": true, @@ -1134,7 +1258,9 @@ "fileTypes": [], "file_path": "", "info": "", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": false, @@ -1172,11 +1298,18 @@ "display_name": "Prompt", "id": "Prompt-VecUe", "node": { - "base_classes": ["object", "str", "Text"], + "base_classes": [ + "object", + "str", + "Text" + ], "beta": false, "conditional_paths": [], "custom_fields": { - "template": ["context", "question"] + "template": [ + "context", + "question" + ] }, "description": "Create a prompt template with dynamic variables.", "display_name": "Prompt", @@ -1198,7 +1331,9 @@ "method": "build_prompt", "name": "prompt", "selected": "Message", - "types": ["Message"], + "types": [ + "Message" + ], "value": "__UNDEFINED__" } ], @@ -1231,7 +1366,10 @@ "fileTypes": [], "file_path": "", "info": "", - "input_types": ["Message", "Text"], + "input_types": [ + "Message", + "Text" + ], "list": false, "load_from_db": false, "multiline": true, @@ -1252,7 +1390,10 @@ "fileTypes": [], "file_path": "", "info": "", - "input_types": ["Message", "Text"], + "input_types": [ + "Message", + "Text" + ], "list": false, "load_from_db": false, "multiline": true, @@ -1272,7 +1413,9 @@ "fileTypes": [], "file_path": "", "info": "", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": false, "load_from_db": false, "multiline": false, @@ -1308,7 +1451,12 @@ "data": { "id": "ChatOutput-nUD9B", "node": { - "base_classes": ["object", "Text", "Record", "str"], + "base_classes": [ + "object", + "Text", + "Record", + "str" + ], "beta": false, "custom_fields": { "input_value": null, @@ -1333,7 +1481,9 @@ "method": "message_response", "name": "message", "selected": "Message", - "types": ["Message"], + "types": [ + "Message" + ], "value": "__UNDEFINED__" } ], @@ -1355,7 +1505,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, Output, TextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n TextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n TextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n TextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n TextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, Output, MessageTextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" }, "input_value": { "advanced": false, @@ -1364,7 +1514,10 @@ "fileTypes": [], "file_path": "", "info": "Message to be passed as output.", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "multiline": true, @@ -1384,12 +1537,17 @@ "fileTypes": [], "file_path": "", "info": "Type of sender.", - "input_types": ["Text"], + "input_types": [ + "Text" + ], "list": true, "load_from_db": false, "multiline": false, "name": "sender", - "options": ["Machine", "User"], + "options": [ + "Machine", + "User" + ], "password": false, "placeholder": "", "required": false, @@ -1405,7 +1563,10 @@ "fileTypes": [], "file_path": "", "info": "Name of the sender.", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "multiline": true, @@ -1425,7 +1586,10 @@ "fileTypes": [], "file_path": "", "info": "Session ID for the message.", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "multiline": true, @@ -1461,7 +1625,9 @@ "data": { "id": "File-w2zxA", "node": { - "base_classes": ["Record"], + "base_classes": [ + "Record" + ], "beta": false, "custom_fields": { "path": null, @@ -1482,7 +1648,9 @@ "method": "load_file", "name": "data", "selected": "Data", - "types": ["Data"], + "types": [ + "Data" + ], "value": "__UNDEFINED__" } ], @@ -1578,7 +1746,9 @@ "data": { "id": "OpenAIEmbeddings-PCoh9", "node": { - "base_classes": ["Embeddings"], + "base_classes": [ + "Embeddings" + ], "beta": false, "custom_fields": { "allowed_special": null, @@ -1619,7 +1789,9 @@ "method": "build_embeddings", "name": "embeddings", "selected": "Embeddings", - "types": ["Embeddings"], + "types": [ + "Embeddings" + ], "value": "__UNDEFINED__" } ], @@ -1644,7 +1816,10 @@ "display_name": "Client", "dynamic": false, "info": "", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "name": "client", @@ -1671,7 +1846,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_openai.embeddings.base import OpenAIEmbeddings\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import Embeddings\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, Output, SecretStrInput, TextInput\n\n\nclass OpenAIEmbeddingsComponent(LCModelComponent):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n icon = \"OpenAI\"\n inputs = [\n DictInput(\n name=\"default_headers\",\n display_name=\"Default Headers\",\n advanced=True,\n info=\"Default headers to use for the API request.\",\n ),\n DictInput(\n name=\"default_query\",\n display_name=\"Default Query\",\n advanced=True,\n info=\"Default query parameters to use for the API request.\",\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n TextInput(name=\"client\", display_name=\"Client\", advanced=True),\n TextInput(name=\"deployment\", display_name=\"Deployment\", advanced=True),\n IntInput(name=\"embedding_ctx_length\", display_name=\"Embedding Context Length\", advanced=True, value=1536),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", value=3, advanced=True),\n DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n advanced=False,\n options=[\n \"text-embedding-3-small\",\n \"text-embedding-3-large\",\n \"text-embedding-ada-002\",\n ],\n value=\"text-embedding-3-small\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n SecretStrInput(name=\"openai_api_base\", display_name=\"OpenAI API Base\", advanced=True),\n SecretStrInput(name=\"openai_api_key\", display_name=\"OpenAI API Key\"),\n SecretStrInput(name=\"openai_api_type\", display_name=\"OpenAI API Type\", advanced=True),\n TextInput(name=\"openai_api_version\", display_name=\"OpenAI API Version\", advanced=True),\n TextInput(\n name=\"openai_organization\",\n display_name=\"OpenAI Organization\",\n advanced=True,\n ),\n TextInput(name=\"openai_proxy\", display_name=\"OpenAI Proxy\", advanced=True),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n BoolInput(name=\"skip_empty\", display_name=\"Skip Empty\", advanced=True),\n TextInput(\n name=\"tiktoken_model_name\",\n display_name=\"TikToken Model Name\",\n advanced=True,\n ),\n BoolInput(\n name=\"tiktoken_enable\",\n display_name=\"TikToken Enable\",\n advanced=True,\n value=True,\n info=\"If False, you must have transformers installed.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Embeddings\", name=\"embeddings\", method=\"build_embeddings\"),\n ]\n\n def build_embeddings(self) -> Embeddings:\n return OpenAIEmbeddings(\n tiktoken_enabled=self.tiktoken_enable,\n default_headers=self.default_headers,\n default_query=self.default_query,\n allowed_special=\"all\",\n disallowed_special=\"all\",\n chunk_size=self.chunk_size,\n deployment=self.deployment,\n embedding_ctx_length=self.embedding_ctx_length,\n max_retries=self.max_retries,\n model=self.model,\n model_kwargs=self.model_kwargs,\n base_url=self.openai_api_base,\n api_key=self.openai_api_key,\n openai_api_type=self.openai_api_type,\n api_version=self.openai_api_version,\n organization=self.openai_organization,\n openai_proxy=self.openai_proxy,\n timeout=self.request_timeout or None,\n show_progress_bar=self.show_progress_bar,\n skip_empty=self.skip_empty,\n tiktoken_model_name=self.tiktoken_model_name,\n )\n" + "value": "from langchain_openai.embeddings.base import OpenAIEmbeddings\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import Embeddings\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, Output, SecretStrInput, MessageTextInput\n\n\nclass OpenAIEmbeddingsComponent(LCModelComponent):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n icon = \"OpenAI\"\n inputs = [\n DictInput(\n name=\"default_headers\",\n display_name=\"Default Headers\",\n advanced=True,\n info=\"Default headers to use for the API request.\",\n ),\n DictInput(\n name=\"default_query\",\n display_name=\"Default Query\",\n advanced=True,\n info=\"Default query parameters to use for the API request.\",\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n MessageTextInput(name=\"client\", display_name=\"Client\", advanced=True),\n MessageTextInput(name=\"deployment\", display_name=\"Deployment\", advanced=True),\n IntInput(name=\"embedding_ctx_length\", display_name=\"Embedding Context Length\", advanced=True, value=1536),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", value=3, advanced=True),\n DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n advanced=False,\n options=[\n \"text-embedding-3-small\",\n \"text-embedding-3-large\",\n \"text-embedding-ada-002\",\n ],\n value=\"text-embedding-3-small\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n SecretStrInput(name=\"openai_api_base\", display_name=\"OpenAI API Base\", advanced=True),\n SecretStrInput(name=\"openai_api_key\", display_name=\"OpenAI API Key\"),\n SecretStrInput(name=\"openai_api_type\", display_name=\"OpenAI API Type\", advanced=True),\n MessageTextInput(name=\"openai_api_version\", display_name=\"OpenAI API Version\", advanced=True),\n MessageTextInput(\n name=\"openai_organization\",\n display_name=\"OpenAI Organization\",\n advanced=True,\n ),\n MessageTextInput(name=\"openai_proxy\", display_name=\"OpenAI Proxy\", advanced=True),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n BoolInput(name=\"skip_empty\", display_name=\"Skip Empty\", advanced=True),\n MessageTextInput(\n name=\"tiktoken_model_name\",\n display_name=\"TikToken Model Name\",\n advanced=True,\n ),\n BoolInput(\n name=\"tiktoken_enable\",\n display_name=\"TikToken Enable\",\n advanced=True,\n value=True,\n info=\"If False, you must have transformers installed.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Embeddings\", name=\"embeddings\", method=\"build_embeddings\"),\n ]\n\n def build_embeddings(self) -> Embeddings:\n return OpenAIEmbeddings(\n tiktoken_enabled=self.tiktoken_enable,\n default_headers=self.default_headers,\n default_query=self.default_query,\n allowed_special=\"all\",\n disallowed_special=\"all\",\n chunk_size=self.chunk_size,\n deployment=self.deployment,\n embedding_ctx_length=self.embedding_ctx_length,\n max_retries=self.max_retries,\n model=self.model,\n model_kwargs=self.model_kwargs,\n base_url=self.openai_api_base,\n api_key=self.openai_api_key,\n openai_api_type=self.openai_api_type,\n api_version=self.openai_api_version,\n organization=self.openai_organization,\n openai_proxy=self.openai_proxy,\n timeout=self.request_timeout or None,\n show_progress_bar=self.show_progress_bar,\n skip_empty=self.skip_empty,\n tiktoken_model_name=self.tiktoken_model_name,\n )\n" }, "default_headers": { "advanced": true, @@ -1706,7 +1881,10 @@ "display_name": "Deployment", "dynamic": false, "info": "", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "name": "deployment", @@ -1830,7 +2008,10 @@ "display_name": "OpenAI API Version", "dynamic": false, "info": "", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "name": "openai_api_version", @@ -1846,7 +2027,10 @@ "display_name": "OpenAI Organization", "dynamic": false, "info": "", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "name": "openai_organization", @@ -1862,7 +2046,10 @@ "display_name": "OpenAI Proxy", "dynamic": false, "info": "", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "name": "openai_proxy", @@ -1934,7 +2121,10 @@ "display_name": "TikToken Model Name", "dynamic": false, "info": "", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "name": "tiktoken_model_name", @@ -1970,7 +2160,9 @@ "display_name": "Recursive Character Text Splitter", "id": "RecursiveCharacterTextSplitter-CrApG", "node": { - "base_classes": ["Data"], + "base_classes": [ + "Data" + ], "beta": false, "conditional_paths": [], "custom_fields": {}, @@ -1985,7 +2177,9 @@ "separators" ], "frozen": false, - "output_types": ["Data"], + "output_types": [ + "Data" + ], "outputs": [ { "cache": true, @@ -1993,7 +2187,9 @@ "method": "build", "name": "data", "selected": "Data", - "types": ["Data"], + "types": [ + "Data" + ], "value": "__UNDEFINED__" } ], @@ -2044,14 +2240,17 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_text_splitters import RecursiveCharacterTextSplitter\n\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DataInput, IntInput, TextInput\nfrom langflow.schema import Data\nfrom langflow.template.field.base import Output\nfrom langflow.utils.util import build_loader_repr_from_data, unescape_string\n\n\nclass RecursiveCharacterTextSplitterComponent(Component):\n display_name: str = \"Recursive Character Text Splitter\"\n description: str = \"Split text into chunks of a specified length.\"\n documentation: str = \"https://docs.langflow.org/components/text-splitters#recursivecharactertextsplitter\"\n\n inputs = [\n IntInput(\n name=\"chunk_size\",\n display_name=\"Chunk Size\",\n info=\"The maximum length of each chunk.\",\n value=1000,\n ),\n IntInput(\n name=\"chunk_overlap\",\n display_name=\"Chunk Overlap\",\n info=\"The amount of overlap between chunks.\",\n value=200,\n ),\n DataInput(\n name=\"data_input\",\n display_name=\"Input\",\n info=\"The texts to split.\",\n input_types=[\"Document\", \"Data\"],\n ),\n TextInput(\n name=\"separators\",\n display_name=\"Separators\",\n info='The characters to split on.\\nIf left empty defaults to [\"\\\\n\\\\n\", \"\\\\n\", \" \", \"\"].',\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"build\"),\n ]\n\n def build(self) -> list[Data]:\n \"\"\"\n Split text into chunks of a specified length.\n\n Args:\n separators (list[str]): The characters to split on.\n chunk_size (int): The maximum length of each chunk.\n chunk_overlap (int): The amount of overlap between chunks.\n\n Returns:\n list[str]: The chunks of text.\n \"\"\"\n\n if self.separators == \"\":\n self.separators = None\n elif self.separators:\n # check if the separators list has escaped characters\n # if there are escaped characters, unescape them\n self.separators = [unescape_string(x) for x in self.separators]\n\n # Make sure chunk_size and chunk_overlap are ints\n if isinstance(self.chunk_size, str):\n self.chunk_size = int(self.chunk_size)\n if isinstance(self.chunk_overlap, str):\n self.chunk_overlap = int(self.chunk_overlap)\n splitter = RecursiveCharacterTextSplitter(\n separators=self.separators,\n chunk_size=self.chunk_size,\n chunk_overlap=self.chunk_overlap,\n )\n documents = []\n if not isinstance(self.data_input, list):\n self.data_input = [self.data_input]\n for _input in self.data_input:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n else:\n documents.append(_input)\n docs = splitter.split_documents(documents)\n data = self.to_data(docs)\n self.repr_value = build_loader_repr_from_data(data)\n return data\n" + "value": "from langchain_text_splitters import RecursiveCharacterTextSplitter\n\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DataInput, IntInput, MessageTextInput\nfrom langflow.schema import Data\nfrom langflow.template.field.base import Output\nfrom langflow.utils.util import build_loader_repr_from_data, unescape_string\n\n\nclass RecursiveCharacterTextSplitterComponent(Component):\n display_name: str = \"Recursive Character Text Splitter\"\n description: str = \"Split text into chunks of a specified length.\"\n documentation: str = \"https://docs.langflow.org/components/text-splitters#recursivecharactertextsplitter\"\n\n inputs = [\n IntInput(\n name=\"chunk_size\",\n display_name=\"Chunk Size\",\n info=\"The maximum length of each chunk.\",\n value=1000,\n ),\n IntInput(\n name=\"chunk_overlap\",\n display_name=\"Chunk Overlap\",\n info=\"The amount of overlap between chunks.\",\n value=200,\n ),\n DataInput(\n name=\"data_input\",\n display_name=\"Input\",\n info=\"The texts to split.\",\n input_types=[\"Document\", \"Data\"],\n ),\n MessageTextInput(\n name=\"separators\",\n display_name=\"Separators\",\n info='The characters to split on.\\nIf left empty defaults to [\"\\\\n\\\\n\", \"\\\\n\", \" \", \"\"].',\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"build\"),\n ]\n\n def build(self) -> list[Data]:\n \"\"\"\n Split text into chunks of a specified length.\n\n Args:\n separators (list[str]): The characters to split on.\n chunk_size (int): The maximum length of each chunk.\n chunk_overlap (int): The amount of overlap between chunks.\n\n Returns:\n list[str]: The chunks of text.\n \"\"\"\n\n if self.separators == \"\":\n self.separators = None\n elif self.separators:\n # check if the separators list has escaped characters\n # if there are escaped characters, unescape them\n self.separators = [unescape_string(x) for x in self.separators]\n\n # Make sure chunk_size and chunk_overlap are ints\n if isinstance(self.chunk_size, str):\n self.chunk_size = int(self.chunk_size)\n if isinstance(self.chunk_overlap, str):\n self.chunk_overlap = int(self.chunk_overlap)\n splitter = RecursiveCharacterTextSplitter(\n separators=self.separators,\n chunk_size=self.chunk_size,\n chunk_overlap=self.chunk_overlap,\n )\n documents = []\n if not isinstance(self.data_input, list):\n self.data_input = [self.data_input]\n for _input in self.data_input:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n else:\n documents.append(_input)\n docs = splitter.split_documents(documents)\n data = self.to_data(docs)\n self.repr_value = build_loader_repr_from_data(data)\n return data\n" }, "data_input": { "advanced": false, "display_name": "Input", "dynamic": false, "info": "The texts to split.", - "input_types": ["Document", "Data"], + "input_types": [ + "Document", + "Data" + ], "list": false, "name": "data_input", "placeholder": "", @@ -2066,7 +2265,10 @@ "display_name": "Separators", "dynamic": false, "info": "The characters to split on.\nIf left empty defaults to [\"\\n\\n\", \"\\n\", \" \", \"\"].", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": true, "load_from_db": false, "name": "separators", @@ -2075,7 +2277,9 @@ "show": true, "title_case": false, "type": "str", - "value": ["\\n"] + "value": [ + "\\n" + ] } } }, @@ -2102,7 +2306,9 @@ "display_name": "Astra DB Vector Store", "id": "AstraDB-rXo8b", "node": { - "base_classes": ["Data"], + "base_classes": [ + "Data" + ], "beta": false, "conditional_paths": [], "custom_fields": {}, @@ -2142,7 +2348,9 @@ "method": "build_base_retriever", "name": "base_retriever", "selected": "Data", - "types": ["Data"], + "types": [ + "Data" + ], "value": "__UNDEFINED__" }, { @@ -2151,7 +2359,9 @@ "method": "search_documents", "name": "search_results", "selected": "Data", - "types": ["Data"], + "types": [ + "Data" + ], "value": "__UNDEFINED__" } ], @@ -2297,7 +2507,10 @@ "display_name": "Embedding", "dynamic": false, "info": "", - "input_types": ["Embeddings", "dict"], + "input_types": [ + "Embeddings", + "dict" + ], "list": false, "name": "embedding", "placeholder": "", @@ -2343,7 +2556,11 @@ "dynamic": false, "info": "Optional distance metric for vector comparisons in the vector store.", "name": "metric", - "options": ["cosine", "dot_product", "euclidean"], + "options": [ + "cosine", + "dot_product", + "euclidean" + ], "placeholder": "", "required": false, "show": true, @@ -2399,7 +2616,10 @@ "display_name": "Search Input", "dynamic": false, "info": "", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "multiline": true, @@ -2417,7 +2637,10 @@ "dynamic": false, "info": "", "name": "search_type", - "options": ["Similarity", "MMR"], + "options": [ + "Similarity", + "MMR" + ], "placeholder": "", "required": false, "show": true, @@ -2431,7 +2654,11 @@ "dynamic": false, "info": "Configuration mode for setting up the vector store, with options like 'Sync', 'Async', or 'Off'.", "name": "setup_mode", - "options": ["Sync", "Async", "Off"], + "options": [ + "Sync", + "Async", + "Off" + ], "placeholder": "", "required": false, "show": true, @@ -2460,7 +2687,9 @@ "display_name": "Vector Store Inputs", "dynamic": false, "info": "", - "input_types": ["Data"], + "input_types": [ + "Data" + ], "list": true, "name": "vector_store_inputs", "placeholder": "", @@ -2495,7 +2724,9 @@ "display_name": "Astra DB Vector Store", "id": "AstraDB-61WgV", "node": { - "base_classes": ["Data"], + "base_classes": [ + "Data" + ], "beta": false, "conditional_paths": [], "custom_fields": {}, @@ -2535,7 +2766,9 @@ "method": "build_base_retriever", "name": "base_retriever", "selected": "Data", - "types": ["Data"], + "types": [ + "Data" + ], "value": "__UNDEFINED__" }, { @@ -2544,7 +2777,9 @@ "method": "search_documents", "name": "search_results", "selected": "Data", - "types": ["Data"], + "types": [ + "Data" + ], "value": "__UNDEFINED__" } ], @@ -2690,7 +2925,10 @@ "display_name": "Embedding", "dynamic": false, "info": "", - "input_types": ["Embeddings", "dict"], + "input_types": [ + "Embeddings", + "dict" + ], "list": false, "name": "embedding", "placeholder": "", @@ -2736,7 +2974,11 @@ "dynamic": false, "info": "Optional distance metric for vector comparisons in the vector store.", "name": "metric", - "options": ["cosine", "dot_product", "euclidean"], + "options": [ + "cosine", + "dot_product", + "euclidean" + ], "placeholder": "", "required": false, "show": true, @@ -2792,7 +3034,10 @@ "display_name": "Search Input", "dynamic": false, "info": "", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "multiline": true, @@ -2810,7 +3055,10 @@ "dynamic": false, "info": "", "name": "search_type", - "options": ["Similarity", "MMR"], + "options": [ + "Similarity", + "MMR" + ], "placeholder": "", "required": false, "show": true, @@ -2824,7 +3072,11 @@ "dynamic": false, "info": "Configuration mode for setting up the vector store, with options like 'Sync', 'Async', or 'Off'.", "name": "setup_mode", - "options": ["Sync", "Async", "Off"], + "options": [ + "Sync", + "Async", + "Off" + ], "placeholder": "", "required": false, "show": true, @@ -2853,7 +3105,9 @@ "display_name": "Vector Store Inputs", "dynamic": false, "info": "", - "input_types": ["Data"], + "input_types": [ + "Data" + ], "list": true, "name": "vector_store_inputs", "placeholder": "", @@ -2886,14 +3140,20 @@ "data": { "id": "ParseData-DXlFW", "node": { - "base_classes": ["Message"], + "base_classes": [ + "Message" + ], "beta": false, "conditional_paths": [], "custom_fields": {}, "description": "Convert Data into plain text following a specified template.", "display_name": "Parse Data", "documentation": "", - "field_order": ["data", "template", "sep"], + "field_order": [ + "data", + "template", + "sep" + ], "frozen": false, "icon": "braces", "output_types": [], @@ -2904,7 +3164,9 @@ "method": "parse_data", "name": "text", "selected": "Message", - "types": ["Message"], + "types": [ + "Message" + ], "value": "__UNDEFINED__" } ], @@ -2934,7 +3196,9 @@ "display_name": "Data", "dynamic": false, "info": "The data to convert to text.", - "input_types": ["Data"], + "input_types": [ + "Data" + ], "list": false, "name": "data", "placeholder": "", @@ -2964,7 +3228,10 @@ "display_name": "Template", "dynamic": false, "info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.", - "input_types": ["Message", "str"], + "input_types": [ + "Message", + "str" + ], "list": false, "load_from_db": false, "multiline": true, @@ -3008,4 +3275,4 @@ "is_component": false, "last_tested_version": "1.0.0a59", "name": "Vector Store RAG" -} +} \ No newline at end of file From 8c7063e0ec2abe10f11950bdd8aeca2e977f9d9a Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 08:58:38 -0300 Subject: [PATCH 057/229] refactor: Update VectaraVectorStoreComponent to handle embedding input and add documents to vector store --- .../base/langflow/components/vectorstores/Vectara.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/backend/base/langflow/components/vectorstores/Vectara.py b/src/backend/base/langflow/components/vectorstores/Vectara.py index 6bbf479bf..4945eb902 100644 --- a/src/backend/base/langflow/components/vectorstores/Vectara.py +++ b/src/backend/base/langflow/components/vectorstores/Vectara.py @@ -1,11 +1,11 @@ -from typing import List, TYPE_CHECKING +from typing import TYPE_CHECKING, List from langchain_community.vectorstores import Vectara from loguru import logger from langflow.base.vectorstores.model import LCVectorStoreComponent from langflow.helpers.data import docs_to_data -from langflow.io import HandleInput, IntInput, SecretStrInput, StrInput, TextInput +from langflow.io import HandleInput, IntInput, MessageTextInput, SecretStrInput, StrInput from langflow.schema import Data if TYPE_CHECKING: @@ -37,7 +37,7 @@ class VectaraVectorStoreComponent(LCVectorStoreComponent): input_types=["Document", "Data"], is_list=True, ), - TextInput( + MessageTextInput( name="search_query", display_name="Search Query", ), From 2530a25b71300bdf9cc8251347a43207a089bbbd Mon Sep 17 00:00:00 2001 From: italojohnny Date: Sun, 23 Jun 2024 21:50:06 -0300 Subject: [PATCH 058/229] set default temperature value --- .../base/langflow/components/embeddings/OllamaEmbeddings.py | 1 + 1 file changed, 1 insertion(+) diff --git a/src/backend/base/langflow/components/embeddings/OllamaEmbeddings.py b/src/backend/base/langflow/components/embeddings/OllamaEmbeddings.py index 430a8de29..5e115d3f8 100644 --- a/src/backend/base/langflow/components/embeddings/OllamaEmbeddings.py +++ b/src/backend/base/langflow/components/embeddings/OllamaEmbeddings.py @@ -25,6 +25,7 @@ class OllamaEmbeddingsComponent(LCModelComponent): FloatInput( name="temperature", display_name="Model Temperature", + value=1.0, advanced=True, ), ] From 5505d3fef63e371b59a424360f3a53730d3315d1 Mon Sep 17 00:00:00 2001 From: italojohnny Date: Mon, 24 Jun 2024 08:07:36 -0300 Subject: [PATCH 059/229] adjust model temperature value --- .../base/langflow/components/embeddings/OllamaEmbeddings.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/backend/base/langflow/components/embeddings/OllamaEmbeddings.py b/src/backend/base/langflow/components/embeddings/OllamaEmbeddings.py index 5e115d3f8..103ca3f1b 100644 --- a/src/backend/base/langflow/components/embeddings/OllamaEmbeddings.py +++ b/src/backend/base/langflow/components/embeddings/OllamaEmbeddings.py @@ -25,7 +25,7 @@ class OllamaEmbeddingsComponent(LCModelComponent): FloatInput( name="temperature", display_name="Model Temperature", - value=1.0, + value=0.1, advanced=True, ), ] From 0c75ba492da6d4bcfc3a47ad34500433c8bceed7 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 08:59:44 -0300 Subject: [PATCH 060/229] =?UTF-8?q?=E2=9C=A8=20(SplitText.py):=20Add=20Mes?= =?UTF-8?q?sageTextInput=20import=20to=20support=20handling=20message=20in?= =?UTF-8?q?put=20in=20langflow=20components.?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- src/backend/base/langflow/components/deactivated/SplitText.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/backend/base/langflow/components/deactivated/SplitText.py b/src/backend/base/langflow/components/deactivated/SplitText.py index 1f2aecc24..f3529baf3 100644 --- a/src/backend/base/langflow/components/deactivated/SplitText.py +++ b/src/backend/base/langflow/components/deactivated/SplitText.py @@ -3,7 +3,7 @@ from typing import List from langchain_text_splitters import CharacterTextSplitter from langflow.custom import Component -from langflow.io import HandleInput, IntInput, Output +from langflow.io import HandleInput, IntInput, MessageTextInput, Output from langflow.schema import Data from langflow.utils.util import unescape_string From 5c1ac1b273b496eca86debb4ad77ce0abfd02499 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 09:00:27 -0300 Subject: [PATCH 061/229] refactor: Update imports to use MessageTextInput instead of TextInput --- docs/docs/components/custom.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/components/custom.mdx b/docs/docs/components/custom.mdx index cbc5f13ff..10b45c9b7 100644 --- a/docs/docs/components/custom.mdx +++ b/docs/docs/components/custom.mdx @@ -27,7 +27,7 @@ A custom component in Python looks like this: ```python from langflow.custom import Component -from langflow.inputs import TextInput, IntInput, BoolInput, DropdownInput, HandleInput +from langflow.inputs import MessageTextInput, IntInput, BoolInput, DropdownInput, HandleInput from langflow.template import Output from langflow.schema import Data, Message from typing import List, Optional From 6f836c35b15acc57be0a09a0cc58054f13cb6d3a Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 09:03:58 -0300 Subject: [PATCH 062/229] style: run ruff --- .../components/embeddings/AstraVectorize.py | 20 +++++++++---------- .../components/helpers/IDGenerator.py | 7 ++----- .../components/prototypes/__init__.py | 2 +- .../components/vectorstores/AstraDB.py | 8 +++++--- 4 files changed, 18 insertions(+), 19 deletions(-) diff --git a/src/backend/base/langflow/components/embeddings/AstraVectorize.py b/src/backend/base/langflow/components/embeddings/AstraVectorize.py index f098828a1..8c9e6d974 100644 --- a/src/backend/base/langflow/components/embeddings/AstraVectorize.py +++ b/src/backend/base/langflow/components/embeddings/AstraVectorize.py @@ -1,6 +1,6 @@ from typing import Any from langflow.custom import Component -from langflow.inputs.inputs import DictInput, SecretStrInput, StrInput, MessageTextInput +from langflow.inputs.inputs import DictInput, SecretStrInput, MessageTextInput from langflow.template.field.base import Output @@ -14,30 +14,30 @@ class AstraVectorize(Component): MessageTextInput( name="provider", display_name="Provider name", - info='The embedding provider to use.', + info="The embedding provider to use.", ), MessageTextInput( name="model_name", display_name="Model name", - info='The embedding model to use.', + info="The embedding model to use.", ), DictInput( name="authentication", display_name="Authentication", - info='Authentication parameters. Use the Astra Portal to add the embedding provider integration to your Astra organization.', - is_list=True + info="Authentication parameters. Use the Astra Portal to add the embedding provider integration to your Astra organization.", + is_list=True, ), SecretStrInput( name="provider_api_key", display_name="Provider API Key", - info='An alternative to the Astra Authentication that let you use directly the API key of the provider.' + info="An alternative to the Astra Authentication that let you use directly the API key of the provider.", ), DictInput( name="model_parameters", display_name="Model parameters", - info='Additional model parameters.', + info="Additional model parameters.", advanced=True, - is_list=True + is_list=True, ), ] outputs = [ @@ -51,7 +51,7 @@ class AstraVectorize(Component): "provider": self.provider, "modelName": self.model_name, "authentication": self.authentication, - "parameters": self.model_parameters + "parameters": self.model_parameters, }, - "collection_embedding_api_key": self.provider_api_key + "collection_embedding_api_key": self.provider_api_key, } diff --git a/src/backend/base/langflow/components/helpers/IDGenerator.py b/src/backend/base/langflow/components/helpers/IDGenerator.py index fa8805583..72a944f71 100644 --- a/src/backend/base/langflow/components/helpers/IDGenerator.py +++ b/src/backend/base/langflow/components/helpers/IDGenerator.py @@ -1,5 +1,5 @@ import uuid -from typing import Optional, Any, +from typing import Any, Optional from langflow.custom import CustomComponent from langflow.schema.dotdict import dotdict @@ -10,10 +10,7 @@ class UUIDGeneratorComponent(CustomComponent): description = "Generates a unique ID." def update_build_config( # type: ignore - self, - build_config: dotdict, - field_value: Any, - field_name: Optional[str] = None, + self, build_config: dotdict, field_value: Any, field_name: Optional[str] = None ): if field_name == "unique_id": build_config[field_name]["value"] = str(uuid.uuid4()) diff --git a/src/backend/base/langflow/components/prototypes/__init__.py b/src/backend/base/langflow/components/prototypes/__init__.py index 8624865a2..89c14f7e9 100644 --- a/src/backend/base/langflow/components/prototypes/__init__.py +++ b/src/backend/base/langflow/components/prototypes/__init__.py @@ -1,4 +1,4 @@ -µfrom .ConditionalRouter import ConditionalRouterComponent +from .ConditionalRouter import ConditionalRouterComponent from .FlowTool import FlowToolComponent from .Listen import ListenComponent from .Notify import NotifyComponent diff --git a/src/backend/base/langflow/components/vectorstores/AstraDB.py b/src/backend/base/langflow/components/vectorstores/AstraDB.py index adcd546de..58e1d19ef 100644 --- a/src/backend/base/langflow/components/vectorstores/AstraDB.py +++ b/src/backend/base/langflow/components/vectorstores/AstraDB.py @@ -159,10 +159,12 @@ class AstraVectorStoreComponent(LCVectorStoreComponent): embedding_dict = {"embedding": self.embedding} else: from astrapy.info import CollectionVectorServiceOptions + dict_options = self.embedding.get("collection_vector_service_options", {}) - dict_options["authentication"] = {k: v for k, v in dict_options.get("authentication", {}).items() if k and v} - dict_options["parameters"] = {k: v for k, v in dict_options.get("parameters", {}).items() if - k and v} + dict_options["authentication"] = { + k: v for k, v in dict_options.get("authentication", {}).items() if k and v + } + dict_options["parameters"] = {k: v for k, v in dict_options.get("parameters", {}).items() if k and v} embedding_dict = { "collection_vector_service_options": CollectionVectorServiceOptions.from_dict(dict_options), "collection_embedding_api_key": self.embedding.get("collection_embedding_api_key"), From ef1e70d15101ca519475e0bc61649a37da215174 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 09:04:10 -0300 Subject: [PATCH 063/229] style: run prettier --- src/frontend/src/stores/flowStore.ts | 10 ++++------ 1 file changed, 4 insertions(+), 6 deletions(-) diff --git a/src/frontend/src/stores/flowStore.ts b/src/frontend/src/stores/flowStore.ts index 9167a6b05..df12c944c 100644 --- a/src/frontend/src/stores/flowStore.ts +++ b/src/frontend/src/stores/flowStore.ts @@ -243,12 +243,10 @@ const useFlowStore = create((set, get) => ({ } if (selection.nodes) { if (checkOldComponents({ nodes: selection.nodes ?? [] })) { - useAlertStore - .getState() - .setNoticeData({ - title: - "Components created before Langflow 1.0 may be unstable. Ensure components are up to date.", - }); + useAlertStore.getState().setNoticeData({ + title: + "Components created before Langflow 1.0 may be unstable. Ensure components are up to date.", + }); } } let minimumX = Infinity; From 47940c8aa5949eff975daa93cc890bfa448779fe Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 09:39:38 -0300 Subject: [PATCH 064/229] refactor: Update ToolCallingAgentComponent input_dict type to use Dict[str, str] for values --- src/backend/base/langflow/components/agents/ToolCallingAgent.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/backend/base/langflow/components/agents/ToolCallingAgent.py b/src/backend/base/langflow/components/agents/ToolCallingAgent.py index e2b643f1c..017003aaa 100644 --- a/src/backend/base/langflow/components/agents/ToolCallingAgent.py +++ b/src/backend/base/langflow/components/agents/ToolCallingAgent.py @@ -87,7 +87,7 @@ class ToolCallingAgentComponent(Component): verbose=True, handle_parsing_errors=self.handle_parsing_errors, ) - input_dict: dict[str, str | list[BaseMessage]] = {"input": self.input_value} + input_dict: dict[str, str | list[Dict[str, str]]] = {"input": self.input_value} if hasattr(self, "memory") and self.memory: input_dict["chat_history"] = self.convert_chat_history(self.memory) result = await runnable.ainvoke(input_dict) From 0268c7c0dd554311f96535d3dc83f8941155b060 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 09:41:56 -0300 Subject: [PATCH 065/229] refactor: remove unused tests --- tests/unit/test_helper_components.py | 42 ++++++++++++++-------------- 1 file changed, 21 insertions(+), 21 deletions(-) diff --git a/tests/unit/test_helper_components.py b/tests/unit/test_helper_components.py index 3baaf1be6..80c85b787 100644 --- a/tests/unit/test_helper_components.py +++ b/tests/unit/test_helper_components.py @@ -1,20 +1,20 @@ from langchain_core.documents import Document + from langflow.components import helpers from langflow.custom.utils import build_custom_component_template from langflow.schema import Data +# def test_update_data_component(): +# # Arrange +# update_data_component = helpers.UpdateDataComponent() -def test_update_data_component(): - # Arrange - update_data_component = helpers.UpdateDataComponent() - - # Act - new_data = {"new_key": "new_value"} - existing_data = Data(data={"existing_key": "existing_value"}) - result = update_data_component.build(existing_data, new_data) - assert result.data == {"existing_key": "existing_value", "new_key": "new_value"} - assert result.existing_key == "existing_value" - assert result.new_key == "new_value" +# # Act +# new_data = {"new_key": "new_value"} +# existing_data = Data(data={"existing_key": "existing_value"}) +# result = update_data_component.build(existing_data, new_data) +# assert result.data == {"existing_key": "existing_value", "new_key": "new_value"} +# assert result.existing_key == "existing_value" +# assert result.new_key == "new_value" def test_document_to_data_component(): @@ -67,15 +67,15 @@ def test_data_as_text_component(): assert result.text == "Data:{'key': 'value', 'bacon': 'eggs'} -- Bacon:eggs" -def test_text_to_data_component(): - # Arrange - text_to_data_component = helpers.CreateDataComponent() +# def test_text_to_data_component(): +# # Arrange +# text_to_data_component = helpers.CreateDataComponent() - # Act - # Replace with your actual test data - dict_with_text = {"field_1": {"key": "value"}} - result = text_to_data_component.build(number_of_fields=1, **dict_with_text) +# # Act +# # Replace with your actual test data +# dict_with_text = {"field_1": {"key": "value"}} +# result = text_to_data_component.build(number_of_fields=1, **dict_with_text) - # Assert - # Replace with your actual expected result - assert result == Data(data={"key": "value"}) +# # Assert +# # Replace with your actual expected result +# assert result == Data(data={"key": "value"}) From 7f94f5f5ddb48e92f9e56741a249d63aa32a3a53 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 09:29:42 -0300 Subject: [PATCH 066/229] Update project documentation URLs to use the new domain --- docs/static/data/AstraDB-RAG-Flows.json | 2 +- .../initial_setup/starter_projects/VectorStore-RAG-Flows.json | 2 +- src/frontend/src/components/headerComponent/index.tsx | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/static/data/AstraDB-RAG-Flows.json b/docs/static/data/AstraDB-RAG-Flows.json index 9a26ceb50..8865731d6 100644 --- a/docs/static/data/AstraDB-RAG-Flows.json +++ b/docs/static/data/AstraDB-RAG-Flows.json @@ -3238,7 +3238,7 @@ "zoom": 0.370642160653555 } }, - "description": "Visit https://pre-release.langflow.org/tutorials/rag-with-astradb for a detailed guide of this project.\nThis project give you both Ingestion and RAG in a single file. You'll need to visit https://astra.datastax.com/ to create an Astra DB instance, your Token and grab an API Endpoint.\nRunning this project requires you to add a file in the Files component, then define a Collection Name and click on the Play icon on the Astra DB component. \n\nAfter the ingestion ends you are ready to click on the Run button at the lower left corner and start asking questions about your data.", + "description": "Visit https://docs.langflow.org/tutorials/rag-with-astradb for a detailed guide of this project.\nThis project give you both Ingestion and RAG in a single file. You'll need to visit https://astra.datastax.com/ to create an Astra DB instance, your Token and grab an API Endpoint.\nRunning this project requires you to add a file in the Files component, then define a Collection Name and click on the Play icon on the Astra DB component. \n\nAfter the ingestion ends you are ready to click on the Run button at the lower left corner and start asking questions about your data.", "name": "Vector Store RAG", "last_tested_version": "1.0.0a61", "endpoint_name": null, diff --git a/src/backend/base/langflow/initial_setup/starter_projects/VectorStore-RAG-Flows.json b/src/backend/base/langflow/initial_setup/starter_projects/VectorStore-RAG-Flows.json index 23abdbd13..aa800d76f 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/VectorStore-RAG-Flows.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/VectorStore-RAG-Flows.json @@ -3269,7 +3269,7 @@ "zoom": 0.2936356220661912 } }, - "description": "Visit https://pre-release.langflow.org/tutorials/rag-with-astradb for a detailed guide of this project.\nThis project give you both Ingestion and RAG in a single file. You'll need to visit https://astra.datastax.com/ to create an Astra DB instance, your Token and grab an API Endpoint.\nRunning this project requires you to add a file in the Files component, then define a Collection Name and click on the Play icon on the Astra DB component. \n\nAfter the ingestion ends you are ready to click on the Run button at the lower left corner and start asking questions about your data.", + "description": "Visit https://docs.langflow.org/tutorials/rag-with-astradb for a detailed guide of this project.\nThis project give you both Ingestion and RAG in a single file. You'll need to visit https://astra.datastax.com/ to create an Astra DB instance, your Token and grab an API Endpoint.\nRunning this project requires you to add a file in the Files component, then define a Collection Name and click on the Play icon on the Astra DB component. \n\nAfter the ingestion ends you are ready to click on the Run button at the lower left corner and start asking questions about your data.", "endpoint_name": "None-2", "id": "0433f955-c8cc-4d24-a2bf-e8cd0d11f99c", "is_component": false, diff --git a/src/frontend/src/components/headerComponent/index.tsx b/src/frontend/src/components/headerComponent/index.tsx index ab186d1db..52818f940 100644 --- a/src/frontend/src/components/headerComponent/index.tsx +++ b/src/frontend/src/components/headerComponent/index.tsx @@ -263,7 +263,7 @@ export default function Header(): JSX.Element { - window.open("https://pre-release.langflow.org/", "_blank") + window.open("https://docs.langflow.org/", "_blank") } > From 5c09ff40d98b1535fd28a326c7a0f2a8284a3d6c Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 09:55:17 -0300 Subject: [PATCH 067/229] refactor: Update LangSmithTracer initialization error handling --- .../base/langflow/services/tracing/service.py | 24 +++++++++++-------- 1 file changed, 14 insertions(+), 10 deletions(-) diff --git a/src/backend/base/langflow/services/tracing/service.py b/src/backend/base/langflow/services/tracing/service.py index c23dba24b..95795c988 100644 --- a/src/backend/base/langflow/services/tracing/service.py +++ b/src/backend/base/langflow/services/tracing/service.py @@ -86,7 +86,7 @@ class TracingService(Service): await self.start() self._initialize_langsmith_tracer() except Exception as e: - logger.error(f"Error initializing tracers: {e}") + logger.debug(f"Error initializing tracers: {e}") def _initialize_langsmith_tracer(self): project_name = os.getenv("LANGCHAIN_PROJECT", "Langflow") @@ -188,15 +188,19 @@ class LangSmithTracer: self.trace_type = trace_type self.project_name = project_name self.trace_id = trace_id - self._run_tree = RunTree( - project_name=self.project_name, - name=self.trace_name, - run_type=self.trace_type, - id=self.trace_id, - ) - self._run_tree.add_event({"name": "Start", "time": datetime.now(timezone.utc).isoformat()}) - self._children: dict[str, RunTree] = {} - self._ready = self.setup_langsmith() + try: + self._run_tree = RunTree( + project_name=self.project_name, + name=self.trace_name, + run_type=self.trace_type, + id=self.trace_id, + ) + self._run_tree.add_event({"name": "Start", "time": datetime.now(timezone.utc).isoformat()}) + self._children: dict[str, RunTree] = {} + self._ready = self.setup_langsmith() + except Exception as e: + logger.debug(f"Error setting up LangSmith tracer: {e}") + self._ready = False @property def ready(self): From 1e12f05cb8f9f9623e517b4b568f3a28e385fd9f Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Fri, 29 Mar 2024 14:19:33 -0300 Subject: [PATCH 068/229] Fix unique constraints for id column (#1584) Fix unique constraints for id column (#1583) * Fix unique constraints for id column * Update version in pyproject.toml --- poetry.lock | 26 ++++++++++++++++++++++++++ 1 file changed, 26 insertions(+) diff --git a/poetry.lock b/poetry.lock index 3c816a29a..2aa4e6e54 100644 --- a/poetry.lock +++ b/poetry.lock @@ -3161,6 +3161,21 @@ files = [ grpcio = ">=1.62.2" protobuf = ">=4.21.6" +[[package]] +name = "grpcio-health-checking" +version = "1.62.1" +description = "Standard Health Checking Service for gRPC" +optional = false +python-versions = ">=3.6" +files = [ + {file = "grpcio-health-checking-1.62.1.tar.gz", hash = "sha256:9e56180a941b1d32a077d7491e0611d0483c396358afd5349bf00152612e4583"}, + {file = "grpcio_health_checking-1.62.1-py3-none-any.whl", hash = "sha256:9ce761c09fc383e7aa2f7e6c0b0b65d5a1157c1b98d1f5871f7c38aca47d49b9"}, +] + +[package.dependencies] +grpcio = ">=1.62.1" +protobuf = ">=4.21.6" + [[package]] name = "grpcio-status" version = "1.62.2" @@ -9811,6 +9826,17 @@ files = [ {file = "validators-0.28.3.tar.gz", hash = "sha256:c6c79840bcde9ba77b19f6218f7738188115e27830cbaff43264bc4ed24c429d"}, ] +[package.extras] +docs-offline = ["myst-parser (>=2.0.0)", "pypandoc-binary (>=1.11)", "sphinx (>=7.1.1)"] +docs-online = ["mkdocs (>=1.5.2)", "mkdocs-git-revision-date-localized-plugin (>=1.2.0)", "mkdocs-material (>=9.2.6)", "mkdocstrings[python] (>=0.22.0)", "pyaml (>=23.7.0)"] +hooks = ["pre-commit (>=3.3.3)"] +package = ["build (>=1.0.0)", "twine (>=4.0.2)"] +runner = ["tox (>=4.11.1)"] +sast = ["bandit[toml] (>=1.7.5)"] +testing = ["pytest (>=7.4.0)"] +tooling = ["black (>=23.7.0)", "pyright (>=1.1.325)", "ruff (>=0.0.287)"] +tooling-extras = ["pyaml (>=23.7.0)", "pypandoc-binary (>=1.11)", "pytest (>=7.4.0)"] + [[package]] name = "vine" version = "5.1.0" From abbc0097e7ba0ed3d022d1d25d83b38213de6bc6 Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Thu, 4 Apr 2024 00:51:31 +0200 Subject: [PATCH 069/229] Added GTAG for Google Analytics --- docs/package-lock.json | 339 ++++++++++++++++++++++++++++++++++++++++- docs/package.json | 2 +- 2 files changed, 339 insertions(+), 2 deletions(-) diff --git a/docs/package-lock.json b/docs/package-lock.json index 8709daa59..9de415c12 100644 --- a/docs/package-lock.json +++ b/docs/package-lock.json @@ -2571,6 +2571,343 @@ "react-dom": "^18.0.0" } }, + "node_modules/@docusaurus/plugin-google-gtag/node_modules/@docusaurus/core": { + "version": "3.2.0", + "resolved": "https://registry.npmjs.org/@docusaurus/core/-/core-3.2.0.tgz", + "integrity": "sha512-WTO6vW4404nhTmK9NL+95nd13I1JveFwZ8iOBYxb4xt+N2S3KzY+mm+1YtWw2vV37FbYfH+w+KrlrRaWuy5Hzw==", + "dependencies": { + "@babel/core": "^7.23.3", + "@babel/generator": "^7.23.3", + "@babel/plugin-syntax-dynamic-import": "^7.8.3", + "@babel/plugin-transform-runtime": "^7.22.9", + "@babel/preset-env": "^7.22.9", + "@babel/preset-react": "^7.22.5", + "@babel/preset-typescript": "^7.22.5", + 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17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Tue, 9 Apr 2024 11:08:26 -0300 Subject: [PATCH 070/229] Add logger import and fix error handling during upgrade in alembic scripts (#1650) * Add logger import in script.py.mako * Fix error handling during upgrade in alembic scripts * Bump version to 0.6.14 in pyproject.toml --- poetry.lock | 8 ++++---- .../versions/b2fa308044b5_add_unique_constraints.py | 5 +++-- 2 files changed, 7 insertions(+), 6 deletions(-) diff --git a/poetry.lock b/poetry.lock index 2aa4e6e54..6e755932e 100644 --- a/poetry.lock +++ b/poetry.lock @@ -3898,13 +3898,13 @@ files = [ [[package]] name = "joblib" -version = "1.3.2" +version = "1.4.0" description = "Lightweight pipelining with Python functions" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" files = [ - {file = "joblib-1.3.2-py3-none-any.whl", hash = "sha256:ef4331c65f239985f3f2220ecc87db222f08fd22097a3dd5698f693875f8cbb9"}, - {file = "joblib-1.3.2.tar.gz", hash = "sha256:92f865e621e17784e7955080b6d042489e3b8e294949cc44c6eac304f59772b1"}, + {file = "joblib-1.4.0-py3-none-any.whl", hash = "sha256:42942470d4062537be4d54c83511186da1fc14ba354961a2114da91efa9a4ed7"}, + {file = "joblib-1.4.0.tar.gz", hash = "sha256:1eb0dc091919cd384490de890cb5dfd538410a6d4b3b54eef09fb8c50b409b1c"}, ] [[package]] diff --git a/src/backend/base/langflow/alembic/versions/b2fa308044b5_add_unique_constraints.py b/src/backend/base/langflow/alembic/versions/b2fa308044b5_add_unique_constraints.py index ed5317bf5..11ba1a113 100644 --- a/src/backend/base/langflow/alembic/versions/b2fa308044b5_add_unique_constraints.py +++ b/src/backend/base/langflow/alembic/versions/b2fa308044b5_add_unique_constraints.py @@ -11,6 +11,7 @@ from typing import Sequence, Union import sqlalchemy as sa import sqlmodel from alembic import op +from loguru import logger # noqa from sqlalchemy.engine.reflection import Inspector # revision identifiers, used by Alembic. @@ -46,9 +47,9 @@ def upgrade() -> None: if "fk_flow_user_id_user" not in indices_names: batch_op.create_foreign_key("fk_flow_user_id_user", "user", ["user_id"], ["id"]) - except Exception: + except Exception as e: + logger.exception(f"Error during upgrade: {e}") pass - # ### end Alembic commands ### def downgrade() -> None: From 243a4e77f097b2c05e7c3171753dc460ffffdd42 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Tue, 9 Apr 2024 13:57:43 -0300 Subject: [PATCH 071/229] Update column types and bump version (#1653) * Add logger import in script.py.mako * Fix error handling during upgrade in alembic scripts * Bump version to 0.6.14 in pyproject.toml * Update column types in credential and api_key models * Bump version to 0.6.15 in pyproject.toml --- .../alembic/versions/2ac71eb9c3ae_adds_credential_table.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/backend/base/langflow/alembic/versions/2ac71eb9c3ae_adds_credential_table.py b/src/backend/base/langflow/alembic/versions/2ac71eb9c3ae_adds_credential_table.py index 2250a8b8c..617189071 100644 --- a/src/backend/base/langflow/alembic/versions/2ac71eb9c3ae_adds_credential_table.py +++ b/src/backend/base/langflow/alembic/versions/2ac71eb9c3ae_adds_credential_table.py @@ -34,7 +34,7 @@ def upgrade() -> None: sa.Column("provider", sqlmodel.sql.sqltypes.AutoString(), nullable=True), sa.Column("user_id", sqlmodel.sql.sqltypes.GUID(), nullable=False), sa.Column("id", sqlmodel.sql.sqltypes.GUID(), nullable=False), - sa.Column("created_at", sa.DateTime(), nullable=False), + sa.Column("created_at", sqlmodel.sql.sqltypes.DateTime(), nullable=False), sa.Column("updated_at", sa.DateTime(), nullable=True), sa.PrimaryKeyConstraint("id"), ) From c97d0d630f03e8516662d236ba2e3d935e658fa2 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 22 Apr 2024 19:58:15 -0300 Subject: [PATCH 072/229] Fix unique constraints for id column and update API key creation (#1764) * Update .gitignore to ignore additional files and directories * Add migration to fix column types * Bump version to 0.6.17 in pyproject.toml --- poetry.lock | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/poetry.lock b/poetry.lock index 6e755932e..72f9d46eb 100644 --- a/poetry.lock +++ b/poetry.lock @@ -3163,17 +3163,17 @@ protobuf = ">=4.21.6" [[package]] name = "grpcio-health-checking" -version = "1.62.1" +version = "1.62.2" description = "Standard Health Checking Service for gRPC" optional = false python-versions = ">=3.6" files = [ - {file = "grpcio-health-checking-1.62.1.tar.gz", hash = "sha256:9e56180a941b1d32a077d7491e0611d0483c396358afd5349bf00152612e4583"}, - {file = "grpcio_health_checking-1.62.1-py3-none-any.whl", hash = "sha256:9ce761c09fc383e7aa2f7e6c0b0b65d5a1157c1b98d1f5871f7c38aca47d49b9"}, + {file = "grpcio-health-checking-1.62.2.tar.gz", hash = "sha256:a44d1ea1e1510b5c62265dada04d86621bb1491d75de987713c9c0ea005c10a8"}, + {file = "grpcio_health_checking-1.62.2-py3-none-any.whl", hash = "sha256:f0d77e02457aa00e98ce12c741dca6df7e34dbcc3859681c4a473dc589288e56"}, ] [package.dependencies] -grpcio = ">=1.62.1" +grpcio = ">=1.62.2" protobuf = ">=4.21.6" [[package]] From 68e63001df91105d1fc8146b5f1011f391f48c19 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 29 Apr 2024 15:41:26 -0300 Subject: [PATCH 073/229] Fix bugs and make improvements (#1794) * add ? to prevent bug when template has no value * Refactor determine_component_name function in utils.py to use file name * Bump version to 0.6.18 in pyproject.toml --------- Co-authored-by: anovazzi1 --- poetry.lock | 11 ----------- 1 file changed, 11 deletions(-) diff --git a/poetry.lock b/poetry.lock index 72f9d46eb..9a4c60d43 100644 --- a/poetry.lock +++ b/poetry.lock @@ -9826,17 +9826,6 @@ files = [ {file = "validators-0.28.3.tar.gz", hash = "sha256:c6c79840bcde9ba77b19f6218f7738188115e27830cbaff43264bc4ed24c429d"}, ] -[package.extras] -docs-offline = ["myst-parser (>=2.0.0)", "pypandoc-binary (>=1.11)", "sphinx (>=7.1.1)"] -docs-online = ["mkdocs (>=1.5.2)", "mkdocs-git-revision-date-localized-plugin (>=1.2.0)", "mkdocs-material (>=9.2.6)", "mkdocstrings[python] (>=0.22.0)", "pyaml (>=23.7.0)"] -hooks = ["pre-commit (>=3.3.3)"] -package = ["build (>=1.0.0)", "twine (>=4.0.2)"] -runner = ["tox (>=4.11.1)"] -sast = ["bandit[toml] (>=1.7.5)"] -testing = ["pytest (>=7.4.0)"] -tooling = ["black (>=23.7.0)", "pyright (>=1.1.325)", "ruff (>=0.0.287)"] -tooling-extras = ["pyaml (>=23.7.0)", "pypandoc-binary (>=1.11)", "pytest (>=7.4.0)"] - [[package]] name = "vine" version = "5.1.0" From 57df2a07441b1981f78a1a89cd9cb81f3c753fda Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Tue, 7 May 2024 18:29:42 -0300 Subject: [PATCH 074/229] Fixes Pinecone implementation (#1856) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * ⬆️ (pyproject.toml): upgrade langchain-pinecone dependency to version 0.1.0 * 📝 (Pinecone.py): Update Pinecone component to use new DistanceStrategy enum for distance calculation and improve configuration options for Pinecone vector store creation. * ⬆️ (pyproject.toml): upgrade package version from 0.6.18 to 0.6.19 --- poetry.lock | 22 +++++++++++++++++++--- 1 file changed, 19 insertions(+), 3 deletions(-) diff --git a/poetry.lock b/poetry.lock index 9a4c60d43..7407c1a3d 100644 --- a/poetry.lock +++ b/poetry.lock @@ -3898,13 +3898,13 @@ files = [ [[package]] name = "joblib" -version = "1.4.0" +version = "1.4.2" description = "Lightweight pipelining with Python functions" optional = false python-versions = ">=3.8" files = [ - {file = "joblib-1.4.0-py3-none-any.whl", hash = "sha256:42942470d4062537be4d54c83511186da1fc14ba354961a2114da91efa9a4ed7"}, - {file = "joblib-1.4.0.tar.gz", hash = "sha256:1eb0dc091919cd384490de890cb5dfd538410a6d4b3b54eef09fb8c50b409b1c"}, + {file = "joblib-1.4.2-py3-none-any.whl", hash = "sha256:06d478d5674cbc267e7496a410ee875abd68e4340feff4490bcb7afb88060ae6"}, + {file = "joblib-1.4.2.tar.gz", hash = "sha256:2382c5816b2636fbd20a09e0f4e9dad4736765fdfb7dca582943b9c1366b3f0e"}, ] [[package]] @@ -4412,6 +4412,22 @@ langchain-core = ">=0.1.52,<0.3" numpy = ">=1,<2" pinecone-client = ">=3.2.2,<4.0.0" +[[package]] +name = "langchain-pinecone" +version = "0.1.0" +description = "An integration package connecting Pinecone and LangChain" +optional = false +python-versions = "<3.13,>=3.8.1" +files = [ + {file = "langchain_pinecone-0.1.0-py3-none-any.whl", hash = "sha256:d957f27b1cceab425c3e8603c7a32533d4593ce8705242e78f6dc03aa71cf417"}, + {file = "langchain_pinecone-0.1.0.tar.gz", hash = "sha256:93f81e7c3926027cc6a87b001ee4d2e02a432a916709dbd395162b342bf84586"}, +] + +[package.dependencies] +langchain-core = ">=0.1.40,<0.2.0" +numpy = ">=1,<2" +pinecone-client = ">=3.2.2,<4.0.0" + [[package]] name = "langchain-text-splitters" version = "0.2.1" From d0e84c1dc81d484f4d0a8020c48161e76e0b6342 Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Mon, 24 Jun 2024 09:17:06 -0300 Subject: [PATCH 075/229] Fixed starter examples --- ...son => Basic Prompting (Hello World).json} | 534 ++-- .../starter_projects/Blog Writer.json | 1055 ++++++++ .../starter_projects/Document QA.json | 1205 +++++++++ .../Langflow Blog Writer.json | 1337 ---------- .../Langflow Document QA.json | 1026 -------- ... Conversation.json => Memory Chatbot.json} | 482 ++-- .../starter_projects/Vector Store RAG.json | 2281 +++++++++++++++++ 7 files changed, 5069 insertions(+), 2851 deletions(-) rename src/backend/base/langflow/initial_setup/starter_projects/{Basic Prompting (Hello, world!).json => Basic Prompting (Hello World).json} (72%) create mode 100644 src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json create mode 100644 src/backend/base/langflow/initial_setup/starter_projects/Document QA.json delete mode 100644 src/backend/base/langflow/initial_setup/starter_projects/Langflow Blog Writer.json delete mode 100644 src/backend/base/langflow/initial_setup/starter_projects/Langflow Document QA.json rename src/backend/base/langflow/initial_setup/starter_projects/{Langflow Memory Conversation.json => Memory Chatbot.json} (82%) create mode 100644 src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, world!).json b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello World).json similarity index 72% rename from src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, world!).json rename to src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello World).json index 5e1b80c3e..592fe50d8 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, world!).json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello World).json @@ -3,36 +3,10 @@ "edges": [ { "className": "", - "data": { - "sourceHandle": { - "dataType": "OpenAIModel", - "id": "OpenAIModel-dqnxm", - "name": "text_output", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "ChatOutput-3k2BV", - "inputTypes": [ - "Message", - "str" - ], - "type": "str" - } - }, - "id": "reactflow__edge-OpenAIModel-dqnxm{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-dqnxmœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-3k2BV{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-3k2BVœ,œinputTypesœ:[œMessageœ,œstrœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-dqnxm", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-dqnxmœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-3k2BV", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-3k2BVœ, œinputTypesœ: [œMessageœ, œstrœ], œtypeœ: œstrœ}" - }, - { "data": { "sourceHandle": { "dataType": "ChatInput", - "id": "ChatInput-j8yVK", + "id": "ChatInput-8QeBH", "name": "message", "output_types": [ "Message" @@ -40,7 +14,7 @@ }, "targetHandle": { "fieldName": "user_input", - "id": "Prompt-669fA", + "id": "Prompt-GAmYb", "inputTypes": [ "Message", "Text" @@ -48,17 +22,18 @@ "type": "str" } }, - "id": "reactflow__edge-ChatInput-j8yVK{œdataTypeœ:œChatInputœ,œidœ:œChatInput-j8yVKœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-669fA{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-669fAœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ChatInput-j8yVK", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-j8yVKœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-669fA", - "targetHandle": "{œfieldNameœ: œuser_inputœ, œidœ: œPrompt-669fAœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-ChatInput-8QeBH{œdataTypeœ:œChatInputœ,œidœ:œChatInput-8QeBHœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-GAmYb{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-GAmYbœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ChatInput-8QeBH", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-8QeBHœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-GAmYb", + "targetHandle": "{œfieldNameœ: œuser_inputœ, œidœ: œPrompt-GAmYbœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" }, { + "className": "", "data": { "sourceHandle": { "dataType": "Prompt", - "id": "Prompt-669fA", + "id": "Prompt-GAmYb", "name": "prompt", "output_types": [ "Message" @@ -66,54 +41,81 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "OpenAIModel-dqnxm", + "id": "OpenAIModel-aN26e", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-Prompt-669fA{œdataTypeœ:œPromptœ,œidœ:œPrompt-669fAœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-dqnxm{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-dqnxmœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-669fA", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-669fAœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-dqnxm", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-dqnxmœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-Prompt-GAmYb{œdataTypeœ:œPromptœ,œidœ:œPrompt-GAmYbœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-aN26e{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-aN26eœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-GAmYb", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-GAmYbœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-aN26e", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-aN26eœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIModel", + "id": "OpenAIModel-aN26e", + "name": "text_output", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "ChatOutput-wokdr", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-OpenAIModel-aN26e{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-aN26eœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-wokdr{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-wokdrœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-aN26e", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-aN26eœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-wokdr", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-wokdrœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" } ], "nodes": [ { "data": { - "id": "ChatOutput-3k2BV", + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "edited": false, + "id": "Prompt-GAmYb", "node": { "base_classes": [ - "Record", - "Text", - "str", - "object" + "Message" ], "beta": false, + "conditional_paths": [], "custom_fields": { - "input_value": null, - "record_template": null, - "return_record": null, - "sender": null, - "sender_name": null, - "session_id": null + "template": [ + "user_input" + ] }, - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", "documentation": "", - "field_formatters": {}, - "field_order": [], + "edited": true, + "field_order": [ + "template" + ], "frozen": false, - "icon": "ChatOutput", + "icon": "prompts", "output_types": [], "outputs": [ { "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", + "display_name": "Prompt Message", + "hidden": false, + "method": "build_prompt", + "name": "prompt", "selected": "Message", "types": [ "Message" @@ -121,6 +123,7 @@ "value": "__UNDEFINED__" } ], + "pinned": false, "template": { "_type": "Component", "code": { @@ -139,95 +142,39 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, Output, MessageTextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def post_code_processing(self, new_build_config: dict, current_build_config: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_build_config, current_build_config)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_build_config\n # and update the frontend_node with those values\n update_template_values(frontend_template=frontend_node, raw_template=current_build_config[\"template\"])\n return frontend_node\n" }, - "input_value": { + "template": { "advanced": false, - "display_name": "Text", + "display_name": "Template", "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Message to be passed as output.", - "input_types": [ - "Message", - "str" - ], + "info": "", "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", - "password": false, + "name": "template", "placeholder": "", "required": false, "show": true, "title_case": false, - "type": "str", - "value": "" + "trace_as_input": true, + "type": "prompt", + "value": "Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: " }, - "sender": { - "advanced": true, - "display_name": "Sender Type", + "user_input": { + "advanced": false, + "display_name": "user_input", "dynamic": false, + "field_type": "str", "fileTypes": [], "file_path": "", - "info": "Type of sender.", + "info": "", "input_types": [ + "Message", "Text" ], - "list": true, - "load_from_db": false, - "multiline": false, - "name": "sender", - "options": [ - "Machine", - "User" - ], - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "Machine" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Name of the sender.", - "input_types": [ - "Message", - "str" - ], "list": false, "load_from_db": false, "multiline": true, - "name": "sender_name", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "AI" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Session ID for the message.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "session_id", + "name": "user_input", "password": false, "placeholder": "", "required": false, @@ -238,18 +185,18 @@ } } }, - "type": "ChatOutput" + "type": "Prompt" }, "dragging": false, - "height": 309, - "id": "ChatOutput-3k2BV", + "height": 422, + "id": "Prompt-GAmYb", "position": { - "x": 1193.250417197867, - "y": 71.88476890163852 + "x": 43.70859256635981, + "y": 1115.5304359666682 }, "positionAbsolute": { - "x": 1193.250417197867, - "y": 71.88476890163852 + "x": 43.70859256635981, + "y": 1115.5304359666682 }, "selected": false, "type": "genericNode", @@ -257,27 +204,28 @@ }, { "data": { - "id": "ChatInput-j8yVK", + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "edited": false, + "id": "ChatInput-8QeBH", "node": { "base_classes": [ - "object", - "Record", - "str", - "Text" + "Message" ], "beta": false, - "custom_fields": { - "input_value": null, - "return_record": null, - "sender": null, - "sender_name": null, - "session_id": null - }, + "conditional_paths": [], + "custom_fields": {}, "description": "Get chat inputs from the Playground.", "display_name": "Chat Input", "documentation": "", - "field_formatters": {}, - "field_order": [], + "edited": true, + "field_order": [ + "input_value", + "sender", + "sender_name", + "session_id", + "files" + ], "frozen": false, "icon": "ChatInput", "output_types": [], @@ -295,6 +243,7 @@ "value": "__UNDEFINED__" } ], + "pinned": false, "template": { "_type": "Component", "code": { @@ -313,54 +262,85 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MultilineInput, Output, MessageTextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n MessageTextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MultilineInput, Output, TextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n TextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n TextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + }, + "files": { + "advanced": true, + "display_name": "Files", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx", + "jpg", + "jpeg", + "png", + "bmp", + "image" + ], + "file_path": "", + "info": "Files to be sent with the message.", + "list": true, + "name": "files", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "file", + "value": "" }, "input_value": { "advanced": false, "display_name": "Text", "dynamic": false, - "fileTypes": [], - "file_path": "", "info": "Message to be passed as input.", "input_types": [ - "Message", - "str" + "Message" ], "list": false, "load_from_db": false, "multiline": true, "name": "input_value", - "password": false, "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", - "value": "hello!" + "value": "" }, "sender": { "advanced": true, "display_name": "Sender Type", "dynamic": false, - "fileTypes": [], - "file_path": "", "info": "Type of sender.", - "input_types": [ - "Text" - ], - "list": true, - "load_from_db": false, - "multiline": false, "name": "sender", "options": [ "Machine", "User" ], - "password": false, "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_metadata": true, "type": "str", "value": "User" }, @@ -368,22 +348,19 @@ "advanced": true, "display_name": "Sender Name", "dynamic": false, - "fileTypes": [], - "file_path": "", "info": "Name of the sender.", "input_types": [ - "Message", - "str" + "Message" ], "list": false, "load_from_db": false, - "multiline": true, "name": "sender_name", - "password": false, "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", "value": "User" }, @@ -391,22 +368,19 @@ "advanced": true, "display_name": "Session ID", "dynamic": false, - "fileTypes": [], - "file_path": "", "info": "Session ID for the message.", "input_types": [ - "Message", - "str" + "Message" ], "list": false, "load_from_db": false, - "multiline": true, "name": "session_id", - "password": false, "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", "value": "" } @@ -415,15 +389,15 @@ "type": "ChatInput" }, "dragging": false, - "height": 309, - "id": "ChatInput-j8yVK", + "height": 308, + "id": "ChatInput-8QeBH", "position": { - "x": -495.2223093083827, - "y": -232.56998443685862 + "x": -521.3324537445985, + "y": 1089.7620993695407 }, "positionAbsolute": { - "x": -495.2223093083827, - "y": -232.56998443685862 + "x": -521.3324537445985, + "y": 1089.7620993695407 }, "selected": false, "type": "genericNode", @@ -434,7 +408,7 @@ "description": "Generates text using OpenAI LLMs.", "display_name": "OpenAI", "edited": false, - "id": "OpenAIModel-dqnxm", + "id": "OpenAIModel-aN26e", "node": { "base_classes": [ "LanguageModel", @@ -524,6 +498,8 @@ "required": false, "show": true, "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", "value": "" }, @@ -538,6 +514,7 @@ "required": false, "show": true, "title_case": false, + "trace_as_metadata": true, "type": "int", "value": "" }, @@ -552,6 +529,7 @@ "required": false, "show": true, "title_case": false, + "trace_as_input": true, "type": "dict", "value": {} }, @@ -572,6 +550,7 @@ "required": false, "show": true, "title_case": false, + "trace_as_metadata": true, "type": "str", "value": "gpt-4o" }, @@ -587,6 +566,7 @@ "required": false, "show": true, "title_case": false, + "trace_as_metadata": true, "type": "str", "value": "" }, @@ -617,6 +597,7 @@ "required": false, "show": true, "title_case": false, + "trace_as_input": true, "type": "dict", "value": {} }, @@ -631,6 +612,7 @@ "required": false, "show": true, "title_case": false, + "trace_as_metadata": true, "type": "int", "value": 1 }, @@ -645,6 +627,7 @@ "required": false, "show": true, "title_case": false, + "trace_as_metadata": true, "type": "bool", "value": false }, @@ -660,6 +643,7 @@ "required": false, "show": true, "title_case": false, + "trace_as_metadata": true, "type": "str", "value": "" }, @@ -674,6 +658,7 @@ "required": false, "show": true, "title_case": false, + "trace_as_metadata": true, "type": "float", "value": 0.1 } @@ -682,15 +667,15 @@ "type": "OpenAIModel" }, "dragging": false, - "height": 623, - "id": "OpenAIModel-dqnxm", + "height": 621, + "id": "OpenAIModel-aN26e", "position": { - "x": 576.388859357137, - "y": 131.1662189663108 + "x": 584.9288140250019, + "y": 1149.0790574268922 }, "positionAbsolute": { - "x": 576.388859357137, - "y": 131.1662189663108 + "x": 584.9288140250019, + "y": 1149.0790574268922 }, "selected": false, "type": "genericNode", @@ -698,43 +683,37 @@ }, { "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "id": "Prompt-669fA", + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "edited": false, + "id": "ChatOutput-wokdr", "node": { "base_classes": [ "Message" ], "beta": false, "conditional_paths": [], - "custom_fields": { - "template": [ - "user_input" - ] - }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", "documentation": "", - "edited": false, - "error": null, + "edited": true, "field_order": [ - "template" + "input_value", + "sender", + "sender_name", + "session_id", + "data_template" ], "frozen": false, - "full_path": null, - "icon": "prompts", - "is_composition": null, - "is_input": null, - "is_output": null, - "name": "", + "icon": "ChatOutput", "output_types": [], "outputs": [ { "cache": true, - "display_name": "Prompt Message", - "hidden": false, - "method": "build_prompt", - "name": "prompt", + "display_name": "Message", + "method": "message_response", + "name": "message", "selected": "Message", "types": [ "Message" @@ -761,77 +740,136 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def post_code_processing(self, new_build_config: dict, current_build_config: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_build_config, current_build_config)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_build_config\n # and update the frontend_node with those values\n update_template_values(frontend_template=frontend_node, raw_template=current_build_config[\"template\"])\n return frontend_node\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, Output, TextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n TextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n TextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n TextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n TextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" }, - "template": { - "advanced": false, - "display_name": "Template", + "data_template": { + "advanced": true, + "display_name": "Data Template", "dynamic": false, - "info": "", + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], "list": false, - "name": "template", + "load_from_db": false, + "name": "data_template", "placeholder": "", "required": false, "show": true, "title_case": false, "trace_as_input": true, - "type": "prompt", - "value": "Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: " + "trace_as_metadata": true, + "type": "str", + "value": "{text}" }, - "user_input": { + "input_value": { "advanced": false, - "display_name": "user_input", + "display_name": "Text", "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", + "info": "Message to be passed as output.", "input_types": [ - "Message", - "Text" + "Message" ], "list": false, "load_from_db": false, - "multiline": true, - "name": "user_input", - "password": false, + "name": "input_value", "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "advanced": true, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "Session ID for the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", "value": "" } } }, - "type": "Prompt" + "type": "ChatOutput" }, "dragging": false, - "height": 423, - "id": "Prompt-669fA", + "height": 308, + "id": "ChatOutput-wokdr", "position": { - "x": 33.573076589480024, - "y": -103.0780954474625 + "x": 1157.3374592784412, + "y": 1160.9424490383622 }, "positionAbsolute": { - "x": 33.573076589480024, - "y": -103.0780954474625 + "x": 1157.3374592784412, + "y": 1160.9424490383622 }, - "selected": true, + "selected": false, "type": "genericNode", "width": 384 } ], "viewport": { - "x": 397.70356097447427, - "y": 260.7996290400466, - "zoom": 0.664116646149498 + "x": 353.0590737990465, + "y": -407.76221076623995, + "zoom": 0.5467255436493648 } }, "description": "This flow will get you experimenting with the basics of the UI, the Chat and the Prompt component. \n\nTry changing the Template in it to see how the model behaves. \nYou can change it to this and a Text Input into the `type_of_person` variable : \"Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: \" ", "endpoint_name": null, - "id": "a501072c-37ed-44cf-84ee-b1844d4bc3de", + "id": "d646c486-746c-402f-a94a-a03eb2f7941c", "is_component": false, - "last_tested_version": "1.0.0a61", - "name": "Basic Prompting (Hello, World)" + "last_tested_version": "1.0.0rc1", + "name": "Basic Prompting (Hello World)" } \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json b/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json new file mode 100644 index 000000000..5aac92e21 --- /dev/null +++ b/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json @@ -0,0 +1,1055 @@ +{ + "data": { + "edges": [ + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "TextInput", + "id": "TextInput-3mewH", + "name": "text", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "instructions", + "id": "Prompt-wvJkv", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-TextInput-3mewH{œdataTypeœ:œTextInputœ,œidœ:œTextInput-3mewHœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-wvJkv{œfieldNameœ:œinstructionsœ,œidœ:œPrompt-wvJkvœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "TextInput-3mewH", + "sourceHandle": "{œdataTypeœ: œTextInputœ, œidœ: œTextInput-3mewHœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-wvJkv", + "targetHandle": "{œfieldNameœ: œinstructionsœ, œidœ: œPrompt-wvJkvœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "URL", + "id": "URL-SvoqQ", + "name": "data", + "output_types": [ + "Data" + ] + }, + "targetHandle": { + "fieldName": "data", + "id": "ParseData-9nIVB", + "inputTypes": [ + "Data" + ], + "type": "other" + } + }, + "id": "reactflow__edge-URL-SvoqQ{œdataTypeœ:œURLœ,œidœ:œURL-SvoqQœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-ParseData-9nIVB{œfieldNameœ:œdataœ,œidœ:œParseData-9nIVBœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", + "source": "URL-SvoqQ", + "sourceHandle": "{œdataTypeœ: œURLœ, œidœ: œURL-SvoqQœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", + "target": "ParseData-9nIVB", + "targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-9nIVBœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "ParseData", + "id": "ParseData-9nIVB", + "name": "text", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "references", + "id": "Prompt-wvJkv", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ParseData-9nIVB{œdataTypeœ:œParseDataœ,œidœ:œParseData-9nIVBœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-wvJkv{œfieldNameœ:œreferencesœ,œidœ:œPrompt-wvJkvœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ParseData-9nIVB", + "sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-9nIVBœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-wvJkv", + "targetHandle": "{œfieldNameœ: œreferencesœ, œidœ: œPrompt-wvJkvœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-wvJkv", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "OpenAIModel-2W259", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-wvJkv{œdataTypeœ:œPromptœ,œidœ:œPrompt-wvJkvœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-2W259{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-2W259œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-wvJkv", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-wvJkvœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-2W259", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-2W259œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIModel", + "id": "OpenAIModel-2W259", + "name": "text_output", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "ChatOutput-1cGBh", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-OpenAIModel-2W259{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-2W259œ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-1cGBh{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-1cGBhœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-2W259", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-2W259œ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-1cGBh", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-1cGBhœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + } + ], + "nodes": [ + { + "data": { + "description": "Get text inputs from the Playground.", + "display_name": "Instructions", + "edited": false, + "id": "TextInput-3mewH", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get text inputs from the Playground.", + "display_name": "Instructions", + "documentation": "", + "edited": true, + "field_order": [ + "input_value" + ], + "frozen": false, + "icon": "type", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "hidden": false, + "method": "text_response", + "name": "text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.text import TextComponent\nfrom langflow.io import Output, MessageTextInput\nfrom langflow.schema.message import Message\n\n\nclass TextInputComponent(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Playground.\"\n icon = \"type\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Text to be passed as input.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Message:\n message = Message(\n text=self.input_value,\n )\n return message\n" + }, + "input_value": { + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Text to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "Use the references above for style to write a new blog/tutorial about Langflow and AI. Suggest non-covered topics." + } + } + }, + "type": "TextInput" + }, + "dragging": false, + "height": 309, + "id": "TextInput-3mewH", + "position": { + "x": 735.806436564132, + "y": 346.40301122327935 + }, + "positionAbsolute": { + "x": 735.806436564132, + "y": 346.40301122327935 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "id": "ParseData-9nIVB", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Convert Data into plain text following a specified template.", + "display_name": "Parse Data", + "documentation": "", + "field_order": [ + "data", + "template", + "sep" + ], + "frozen": false, + "icon": "braces", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "hidden": false, + "method": "parse_data", + "name": "text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n display_name = \"Parse Data\"\n description = \"Convert Data into plain text following a specified template.\"\n icon = \"braces\"\n\n inputs = [\n DataInput(name=\"data\", display_name=\"Data\", info=\"The data to convert to text.\"),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.\",\n value=\"{text}\",\n ),\n StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n ]\n\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"parse_data\"),\n ]\n\n def parse_data(self) -> Message:\n data = self.data if isinstance(self.data, list) else [self.data]\n template = self.template\n\n result_string = data_to_text(template, data, sep=self.sep)\n self.status = result_string\n return Message(text=result_string)\n" + }, + "data": { + "advanced": false, + "display_name": "Data", + "dynamic": false, + "info": "The data to convert to text.", + "input_types": [ + "Data" + ], + "list": false, + "name": "data", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "other", + "value": "" + }, + "sep": { + "advanced": true, + "display_name": "Separator", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "sep", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "---" + }, + "template": { + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.", + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "{text}" + } + } + }, + "type": "ParseData" + }, + "dragging": false, + "height": 377, + "id": "ParseData-9nIVB", + "position": { + "x": 759.575501198118, + "y": 760.6953079067359 + }, + "positionAbsolute": { + "x": 759.575501198118, + "y": 760.6953079067359 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "edited": false, + "id": "OpenAIModel-2W259", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": true, + "field_order": [ + "input_value", + "max_tokens", + "model_kwargs", + "output_schema", + "model_name", + "openai_api_base", + "openai_api_key", + "temperature", + "stream", + "system_message", + "seed" + ], + "frozen": false, + "icon": "OpenAI", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "hidden": false, + "method": "text_response", + "name": "text_output", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n" + }, + "input_value": { + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "max_tokens": { + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "model_kwargs": { + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "model_name": { + "advanced": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "gpt-3.5-turbo" + }, + "openai_api_base": { + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_key": { + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [], + "load_from_db": false, + "name": "openai_api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "output_schema": { + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "seed": { + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 1 + }, + "stream": { + "advanced": false, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": true + }, + "system_message": { + "advanced": true, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "temperature": { + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "float", + "value": 0.1 + } + } + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 699, + "id": "OpenAIModel-2W259", + "position": { + "x": 1918.8991680862073, + "y": 459.92681406971394 + }, + "positionAbsolute": { + "x": 1918.8991680862073, + "y": 459.92681406971394 + }, + "selected": true, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "edited": false, + "id": "ChatOutput-1cGBh", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": true, + "field_order": [ + "input_value", + "sender", + "sender_name", + "session_id", + "data_template" + ], + "frozen": false, + "icon": "ChatOutput", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + }, + "data_template": { + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "advanced": true, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "Session ID for the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + } + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 309, + "id": "ChatOutput-1cGBh", + "position": { + "x": 2473.1294450647747, + "y": 668.8159913425238 + }, + "positionAbsolute": { + "x": 2473.1294450647747, + "y": 668.8159913425238 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-wvJkv", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "references", + "instructions" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "error": null, + "field_order": [ + "template" + ], + "frozen": false, + "full_path": null, + "icon": "prompts", + "is_composition": null, + "is_input": null, + "is_output": null, + "name": "", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "hidden": false, + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def post_code_processing(self, new_build_config: dict, current_build_config: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_build_config, current_build_config)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_build_config\n # and update the frontend_node with those values\n update_template_values(frontend_template=frontend_node, raw_template=current_build_config[\"template\"])\n return frontend_node\n" + }, + "instructions": { + "advanced": false, + "display_name": "instructions", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "instructions", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "references": { + "advanced": false, + "display_name": "references", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "references", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "template": { + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "prompt", + "value": "Reference 1:\n\n{references}\n\n---\n\n{instructions}\n\nBlog: \n\n" + } + } + }, + "type": "Prompt" + }, + "dragging": false, + "height": 517, + "id": "Prompt-wvJkv", + "position": { + "x": 1288.0925694176524, + "y": 519.4286147510747 + }, + "positionAbsolute": { + "x": 1288.0925694176524, + "y": 519.4286147510747 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "id": "URL-SvoqQ", + "node": { + "base_classes": [ + "Data" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Fetch content from one or more URLs.", + "display_name": "URL", + "documentation": "", + "edited": false, + "field_order": [ + "urls" + ], + "frozen": false, + "icon": "layout-template", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Data", + "hidden": false, + "method": "fetch_content", + "name": "data", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import re\n\nfrom langchain_community.document_loaders.web_base import WebBaseLoader\n\nfrom langflow.custom import Component\nfrom langflow.io import MessageTextInput, Output\nfrom langflow.schema import Data\n\n\nclass URLComponent(Component):\n display_name = \"URL\"\n description = \"Fetch content from one or more URLs.\"\n icon = \"layout-template\"\n\n inputs = [\n MessageTextInput(\n name=\"urls\",\n display_name=\"URLs\",\n info=\"Enter one or more URLs, separated by commas.\",\n is_list=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"fetch_content\"),\n ]\n\n def ensure_url(self, string: str) -> str:\n \"\"\"\n Ensures the given string is a URL by adding 'http://' if it doesn't start with 'http://' or 'https://'.\n Raises an error if the string is not a valid URL.\n\n Parameters:\n string (str): The string to be checked and possibly modified.\n\n Returns:\n str: The modified string that is ensured to be a URL.\n\n Raises:\n ValueError: If the string is not a valid URL.\n \"\"\"\n if not string.startswith((\"http://\", \"https://\")):\n string = \"http://\" + string\n\n # Basic URL validation regex\n url_regex = re.compile(\n r\"^(https?:\\/\\/)?\" # optional protocol\n r\"(www\\.)?\" # optional www\n r\"([a-zA-Z0-9.-]+)\" # domain\n r\"(\\.[a-zA-Z]{2,})?\" # top-level domain\n r\"(:\\d+)?\" # optional port\n r\"(\\/[^\\s]*)?$\", # optional path\n re.IGNORECASE,\n )\n\n if not url_regex.match(string):\n raise ValueError(f\"Invalid URL: {string}\")\n\n return string\n\n def fetch_content(self) -> list[Data]:\n urls = [self.ensure_url(url.strip()) for url in self.urls if url.strip()]\n loader = WebBaseLoader(web_paths=urls, encoding=\"utf-8\")\n docs = loader.load()\n data = [Data(text=doc.page_content, **doc.metadata) for doc in docs]\n self.status = data\n return data\n" + }, + "urls": { + "advanced": false, + "display_name": "URLs", + "dynamic": false, + "info": "Enter one or more URLs, separated by commas.", + "input_types": [ + "Message" + ], + "list": true, + "load_from_db": false, + "name": "urls", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": [ + "langflow.org", + "docs.langflow.org/" + ] + } + } + }, + "type": "URL" + }, + "height": 359, + "id": "URL-SvoqQ", + "position": { + "x": 247.90599789054627, + "y": 514.1589932671732 + }, + "selected": false, + "type": "genericNode", + "width": 384 + } + ], + "viewport": { + "x": -75.20072339134504, + "y": -30.25319522994951, + "zoom": 0.4742390893506119 + } + }, + "description": "This flow can be used to create a blog post following instructions from the user, using two other blogs as reference.", + "endpoint_name": null, + "id": "7d35f945-f4ad-4d83-bdd8-3a11ddf6fc44", + "is_component": false, + "last_tested_version": "1.0.0rc1", + "name": "Blog Writer" +} \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Document QA.json b/src/backend/base/langflow/initial_setup/starter_projects/Document QA.json new file mode 100644 index 000000000..b813d5f50 --- /dev/null +++ b/src/backend/base/langflow/initial_setup/starter_projects/Document QA.json @@ -0,0 +1,1205 @@ +{ + "data": { + "edges": [ + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "File", + "id": "File-mzZHT", + "name": "data", + "output_types": [ + "Data" + ] + }, + "targetHandle": { + "fieldName": "data", + "id": "ParseData-SAHub", + "inputTypes": [ + "Data" + ], + "type": "other" + } + }, + "id": "reactflow__edge-File-mzZHT{œdataTypeœ:œFileœ,œidœ:œFile-mzZHTœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-ParseData-SAHub{œfieldNameœ:œdataœ,œidœ:œParseData-SAHubœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", + "source": "File-mzZHT", + "sourceHandle": "{œdataTypeœ: œFileœ, œidœ: œFile-mzZHTœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", + "target": "ParseData-SAHub", + "targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-SAHubœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "ParseData", + "id": "ParseData-SAHub", + "name": "text", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "Document", + "id": "Prompt-XHWTr", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ParseData-SAHub{œdataTypeœ:œParseDataœ,œidœ:œParseData-SAHubœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-XHWTr{œfieldNameœ:œDocumentœ,œidœ:œPrompt-XHWTrœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ParseData-SAHub", + "sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-SAHubœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-XHWTr", + "targetHandle": "{œfieldNameœ: œDocumentœ, œidœ: œPrompt-XHWTrœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "ChatInput", + "id": "ChatInput-tDiAG", + "name": "message", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "Question", + "id": "Prompt-XHWTr", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ChatInput-tDiAG{œdataTypeœ:œChatInputœ,œidœ:œChatInput-tDiAGœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-XHWTr{œfieldNameœ:œQuestionœ,œidœ:œPrompt-XHWTrœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ChatInput-tDiAG", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-tDiAGœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-XHWTr", + "targetHandle": "{œfieldNameœ: œQuestionœ, œidœ: œPrompt-XHWTrœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-XHWTr", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "OpenAIModel-HJR46", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-XHWTr{œdataTypeœ:œPromptœ,œidœ:œPrompt-XHWTrœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-HJR46{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-HJR46œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-XHWTr", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-XHWTrœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-HJR46", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-HJR46œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIModel", + "id": "OpenAIModel-HJR46", + "name": "text_output", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "ChatOutput-ob8F7", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-OpenAIModel-HJR46{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-HJR46œ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-ob8F7{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-ob8F7œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-HJR46", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-HJR46œ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-ob8F7", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-ob8F7œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + } + ], + "nodes": [ + { + "data": { + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "edited": false, + "id": "ChatInput-tDiAG", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "documentation": "", + "edited": true, + "field_order": [ + "input_value", + "sender", + "sender_name", + "session_id", + "files" + ], + "frozen": false, + "icon": "ChatInput", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "hidden": false, + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + }, + "files": { + "advanced": true, + "display_name": "Files", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx", + "jpg", + "jpeg", + "png", + "bmp", + "image" + ], + "file_path": "", + "info": "Files to be sent with the message.", + "list": true, + "name": "files", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "file", + "value": "" + }, + "input_value": { + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "advanced": true, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "sender_name": { + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "session_id": { + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "Session ID for the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + } + }, + "type": "ChatInput" + }, + "dragging": false, + "height": 309, + "id": "ChatInput-tDiAG", + "position": { + "x": -201.55524461361745, + "y": 411.67283602771283 + }, + "positionAbsolute": { + "x": -201.55524461361745, + "y": 411.67283602771283 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "edited": false, + "id": "ChatOutput-ob8F7", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": true, + "field_order": [ + "input_value", + "sender", + "sender_name", + "session_id", + "data_template" + ], + "frozen": false, + "icon": "ChatOutput", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + }, + "data_template": { + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "advanced": true, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "Session ID for the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + } + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 308, + "id": "ChatOutput-ob8F7", + "position": { + "x": 1733.3012915204283, + "y": 168.76098809939327 + }, + "positionAbsolute": { + "x": 1733.3012915204283, + "y": 168.76098809939327 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "A generic file loader.", + "display_name": "File", + "id": "File-mzZHT", + "node": { + "base_classes": [ + "Data" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "A generic file loader.", + "display_name": "File", + "documentation": "", + "edited": false, + "field_order": [ + "path", + "silent_errors" + ], + "frozen": false, + "icon": "file-text", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Data", + "hidden": false, + "method": "load_file", + "name": "data", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from pathlib import Path\n\nfrom langflow.base.data.utils import TEXT_FILE_TYPES, parse_text_file_to_data\nfrom langflow.custom import Component\nfrom langflow.io import BoolInput, FileInput, Output\nfrom langflow.schema import Data\n\n\nclass FileComponent(Component):\n display_name = \"File\"\n description = \"A generic file loader.\"\n icon = \"file-text\"\n\n inputs = [\n FileInput(\n name=\"path\",\n display_name=\"Path\",\n file_types=TEXT_FILE_TYPES,\n info=f\"Supported file types: {', '.join(TEXT_FILE_TYPES)}\",\n ),\n BoolInput(\n name=\"silent_errors\",\n display_name=\"Silent Errors\",\n advanced=True,\n info=\"If true, errors will not raise an exception.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"load_file\"),\n ]\n\n def load_file(self) -> Data:\n if not self.path:\n raise ValueError(\"Please, upload a file to use this component.\")\n resolved_path = self.resolve_path(self.path)\n silent_errors = self.silent_errors\n\n extension = Path(resolved_path).suffix[1:].lower()\n\n if extension == \"doc\":\n raise ValueError(\"doc files are not supported. Please save as .docx\")\n if extension not in TEXT_FILE_TYPES:\n raise ValueError(f\"Unsupported file type: {extension}\")\n\n data = parse_text_file_to_data(resolved_path, silent_errors)\n self.status = data if data else \"No data\"\n return data or Data()\n" + }, + "path": { + "advanced": false, + "display_name": "Path", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx" + ], + "file_path": "860235bc-cb3e-4576-8a52-afd711f4f138/IMKL24_Speaker Invitation_Rodrigo.pdf", + "info": "Supported file types: txt, md, mdx, csv, json, yaml, yml, xml, html, htm, pdf, docx, py, sh, sql, js, ts, tsx", + "list": false, + "name": "path", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "file", + "value": "" + }, + "silent_errors": { + "advanced": true, + "display_name": "Silent Errors", + "dynamic": false, + "info": "If true, errors will not raise an exception.", + "list": false, + "name": "silent_errors", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + } + } + }, + "type": "File" + }, + "dragging": false, + "height": 301, + "id": "File-mzZHT", + "position": { + "x": -423.1448900251602, + "y": -230.83411538932458 + }, + "positionAbsolute": { + "x": -423.1448900251602, + "y": -230.83411538932458 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "edited": false, + "id": "OpenAIModel-HJR46", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": true, + "field_order": [ + "input_value", + "max_tokens", + "model_kwargs", + "output_schema", + "model_name", + "openai_api_base", + "openai_api_key", + "temperature", + "stream", + "system_message", + "seed" + ], + "frozen": false, + "icon": "OpenAI", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "hidden": false, + "method": "text_response", + "name": "text_output", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n" + }, + "input_value": { + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "max_tokens": { + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "model_kwargs": { + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "model_name": { + "advanced": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "gpt-3.5-turbo" + }, + "openai_api_base": { + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_key": { + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [], + "load_from_db": false, + "name": "openai_api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "output_schema": { + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "seed": { + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 1 + }, + "stream": { + "advanced": true, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "system_message": { + "advanced": true, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "temperature": { + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "float", + "value": 0.1 + } + } + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 622, + "id": "OpenAIModel-HJR46", + "position": { + "x": 1205.1434354219589, + "y": -39.953851445891985 + }, + "positionAbsolute": { + "x": 1205.1434354219589, + "y": -39.953851445891985 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-XHWTr", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "Document", + "Question" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "error": null, + "field_order": [ + "template" + ], + "frozen": false, + "full_path": null, + "icon": "prompts", + "is_composition": null, + "is_input": null, + "is_output": null, + "name": "", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "hidden": false, + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "Document": { + "advanced": false, + "display_name": "Document", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "Document", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "Question": { + "advanced": false, + "display_name": "Question", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "Question", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def post_code_processing(self, new_build_config: dict, current_build_config: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_build_config, current_build_config)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_build_config\n # and update the frontend_node with those values\n update_template_values(frontend_template=frontend_node, raw_template=current_build_config[\"template\"])\n return frontend_node\n" + }, + "template": { + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "prompt", + "value": "Answer user's questions based on the document below:\n\n---\n\n{Document}\n\n---\n\nQuestion:\n{Question}\n\nAnswer:\n" + } + } + }, + "type": "Prompt" + }, + "dragging": false, + "height": 517, + "id": "Prompt-XHWTr", + "position": { + "x": 641.7559080574213, + "y": 96.74239207995313 + }, + "positionAbsolute": { + "x": 641.7559080574213, + "y": 96.74239207995313 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "id": "ParseData-SAHub", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Convert Data into plain text following a specified template.", + "display_name": "Parse Data", + "documentation": "", + "edited": false, + "field_order": [ + "data", + "template", + "sep" + ], + "frozen": false, + "icon": "braces", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "hidden": false, + "method": "parse_data", + "name": "text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n display_name = \"Parse Data\"\n description = \"Convert Data into plain text following a specified template.\"\n icon = \"braces\"\n\n inputs = [\n DataInput(name=\"data\", display_name=\"Data\", info=\"The data to convert to text.\"),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.\",\n value=\"{text}\",\n ),\n StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n ]\n\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"parse_data\"),\n ]\n\n def parse_data(self) -> Message:\n data = self.data if isinstance(self.data, list) else [self.data]\n template = self.template\n\n result_string = data_to_text(template, data, sep=self.sep)\n self.status = result_string\n return Message(text=result_string)\n" + }, + "data": { + "advanced": false, + "display_name": "Data", + "dynamic": false, + "info": "The data to convert to text.", + "input_types": [ + "Data" + ], + "list": false, + "name": "data", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "sep": { + "advanced": true, + "display_name": "Separator", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "sep", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "\n" + }, + "template": { + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + } + } + }, + "type": "ParseData" + }, + "dragging": false, + "height": 385, + "id": "ParseData-SAHub", + "position": { + "x": 122.60847618765547, + "y": -109.41723790443038 + }, + "positionAbsolute": { + "x": 122.60847618765547, + "y": -109.41723790443038 + }, + "selected": false, + "type": "genericNode", + "width": 384 + } + ], + "viewport": { + "x": 269.0008349738299, + "y": 216.31613407272368, + "zoom": 0.45804409165968474 + } + }, + "description": "This flow integrates PDF reading with a language model to answer document-specific questions. Ideal for small-scale texts, it facilitates direct queries with immediate insights.", + "endpoint_name": null, + "id": "69331d5f-fd14-4ea4-be1f-fd3a8c370562", + "is_component": false, + "last_tested_version": "1.0.0rc1", + "name": "Document QA" +} \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Blog Writer.json b/src/backend/base/langflow/initial_setup/starter_projects/Langflow Blog Writer.json deleted file mode 100644 index e137b567a..000000000 --- a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Blog Writer.json +++ /dev/null @@ -1,1337 +0,0 @@ -{ - "data": { - "edges": [ - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "TextInput", - "id": "TextInput-DbgJ3", - "name": "text", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "instructions", - "id": "Prompt-jJ1i7", - "inputTypes": [ - "Message", - "Text" - ], - "type": "str" - } - }, - "id": "reactflow__edge-TextInput-DbgJ3{œdataTypeœ:œTextInputœ,œidœ:œTextInput-DbgJ3œ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-jJ1i7{œfieldNameœ:œinstructionsœ,œidœ:œPrompt-jJ1i7œ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "TextInput-DbgJ3", - "sourceHandle": "{œdataTypeœ: œTextInputœ, œidœ: œTextInput-DbgJ3œ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-jJ1i7", - "targetHandle": "{œfieldNameœ: œinstructionsœ, œidœ: œPrompt-jJ1i7œ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "URL", - "id": "URL-43SB8", - "name": "data", - "output_types": [ - "Data" - ] - }, - "targetHandle": { - "fieldName": "data", - "id": "ParseData-34pEF", - "inputTypes": [ - "Data" - ], - "type": "other" - } - }, - "id": "reactflow__edge-URL-43SB8{œdataTypeœ:œURLœ,œidœ:œURL-43SB8œ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-ParseData-34pEF{œfieldNameœ:œdataœ,œidœ:œParseData-34pEFœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", - "selected": false, - "source": "URL-43SB8", - "sourceHandle": "{œdataTypeœ: œURLœ, œidœ: œURL-43SB8œ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", - "target": "ParseData-34pEF", - "targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-34pEFœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "URL", - "id": "URL-eFIqb", - "name": "data", - "output_types": [ - "Data" - ] - }, - "targetHandle": { - "fieldName": "data", - "id": "ParseData-iAHWq", - "inputTypes": [ - "Data" - ], - "type": "other" - } - }, - "id": "reactflow__edge-URL-eFIqb{œdataTypeœ:œURLœ,œidœ:œURL-eFIqbœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-ParseData-iAHWq{œfieldNameœ:œdataœ,œidœ:œParseData-iAHWqœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", - "source": "URL-eFIqb", - "sourceHandle": "{œdataTypeœ: œURLœ, œidœ: œURL-eFIqbœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", - "target": "ParseData-iAHWq", - "targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-iAHWqœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "ParseData", - "id": "ParseData-34pEF", - "name": "text", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "reference_2", - "id": "Prompt-jJ1i7", - 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"source": "ParseData-iAHWq", - "sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-iAHWqœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-jJ1i7", - "targetHandle": "{œfieldNameœ: œreference_1œ, œidœ: œPrompt-jJ1i7œ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "OpenAIModel", - "id": "OpenAIModel-slJZS", - "name": "text_output", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "ChatOutput-LkJX7", - "inputTypes": [ - "Message", - "str" - ], - "type": "str" - } - }, - "id": "reactflow__edge-OpenAIModel-slJZS{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-slJZSœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-LkJX7{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-LkJX7œ,œinputTypesœ:[œMessageœ,œstrœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-slJZS", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-slJZSœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-LkJX7", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-LkJX7œ, œinputTypesœ: [œMessageœ, œstrœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "Prompt", - "id": "Prompt-jJ1i7", - "name": "prompt", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "OpenAIModel-slJZS", - "inputTypes": [ - "Message" - ], - "type": "str" - } - }, - "id": "reactflow__edge-Prompt-jJ1i7{œdataTypeœ:œPromptœ,œidœ:œPrompt-jJ1i7œ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-slJZS{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-slJZSœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-jJ1i7", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-jJ1i7œ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-slJZS", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-slJZSœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" - } - ], - "nodes": [ - { - "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "id": "Prompt-jJ1i7", - "node": { - "base_classes": [ - "object", - "str", - "Text" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": { - "template": [ - "reference_1", - "reference_2", - "instructions" - ] - }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "documentation": "", - "error": null, - "field_order": [], - "frozen": false, - "full_path": null, - "icon": "prompts", - "is_composition": null, - "is_input": null, - "is_output": null, - "name": "", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Prompt Message", - "method": "build_prompt", - "name": "prompt", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n" - }, - "instructions": { - "advanced": false, - "display_name": "instructions", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "instructions", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "reference_1": { - "advanced": false, - "display_name": "reference_1", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "reference_1", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "reference_2": { - "advanced": false, - "display_name": "reference_2", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "reference_2", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "template": { - "advanced": false, - "display_name": "Template", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "template", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "prompt", - "value": "Reference 1:\n\n{reference_1}\n\n---\n\nReference 2:\n\n{reference_2}\n\n---\n\n{instructions}\n\nBlog: \n\n\n" - } - } - }, - "type": "Prompt" - }, - "dragging": false, - "height": 619, - "id": "Prompt-jJ1i7", - "position": { - "x": 1378.0386633467044, - "y": 547.0254869963999 - }, - "positionAbsolute": { - "x": 1378.0386633467044, - "y": 547.0254869963999 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "URL-43SB8", - "node": { - "base_classes": [ - "Record" - ], - "beta": false, - "custom_fields": { - "urls": null - }, - "description": "Fetch content from one or more URLs.", - "display_name": "URL", - "documentation": "", - "field_formatters": {}, - "field_order": [], - "frozen": false, - "icon": "layout-template", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Data", - "method": "fetch_content", - "name": "data", - "selected": "Data", - "types": [ - "Data" - ], - "value": "__UNDEFINED__" - } - ], - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import re\n\nfrom langchain_community.document_loaders.web_base import WebBaseLoader\n\nfrom langflow.custom import Component\nfrom langflow.io import Output, MessageTextInput\nfrom langflow.schema import Data\n\n\nclass URLComponent(Component):\n display_name = \"URL\"\n description = \"Fetch content from one or more URLs.\"\n icon = \"layout-template\"\n\n inputs = [\n MessageTextInput(\n name=\"urls\",\n display_name=\"URLs\",\n info=\"Enter one or more URLs, separated by commas.\",\n is_list=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"fetch_content\"),\n ]\n\n def ensure_url(self, string: str) -> str:\n \"\"\"\n Ensures the given string is a URL by adding 'http://' if it doesn't start with 'http://' or 'https://'.\n Raises an error if the string is not a valid URL.\n\n Parameters:\n string (str): The string to be checked and possibly modified.\n\n Returns:\n str: The modified string that is ensured to be a URL.\n\n Raises:\n ValueError: If the string is not a valid URL.\n \"\"\"\n if not string.startswith((\"http://\", \"https://\")):\n string = \"http://\" + string\n\n # Basic URL validation regex\n url_regex = re.compile(\n r\"^(http://|https://)?\" # http:// or https://\n r\"(([a-zA-Z0-9\\.-]+)\" # domain\n r\"(\\.[a-zA-Z]{2,}))\" # top-level domain\n r\"(:[0-9]{1,5})?\" # optional port\n r\"(\\/.*)?$\" # optional path\n )\n\n if not re.match(url_regex, string):\n raise ValueError(f\"Invalid URL: {string}\")\n\n return string\n\n def fetch_content(self) -> list[Data]:\n urls = [self.ensure_url(url.strip()) for url in self.urls if url.strip()]\n loader = WebBaseLoader(web_paths=urls, encoding=\"utf-8\")\n docs = loader.load()\n data = [Data(text=doc.page_content, **doc.metadata) for doc in docs]\n self.status = data\n return data\n" - }, - "urls": { - "advanced": false, - "display_name": "URLs", - "dynamic": false, - "info": "Enter one or more URLs, separated by commas.", - "list": true, - "load_from_db": false, - "name": "urls", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": [ - "https://www.promptingguide.ai/introduction/basics" - ] - } - } - }, - "type": "URL" - }, - "dragging": false, - "height": 301, - "id": "URL-43SB8", - "position": { - "x": 129.9069887328102, - "y": 1026.1629590683015 - }, - "positionAbsolute": { - "x": 129.9069887328102, - "y": 1026.1629590683015 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "URL-eFIqb", - "node": { - "base_classes": [ - "Record" - ], - "beta": false, - "custom_fields": { - "urls": null - }, - "description": "Fetch content from one or more URLs.", - "display_name": "URL", - "documentation": "", - "field_formatters": {}, - "field_order": [], - "frozen": false, - "icon": "layout-template", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Data", - "method": "fetch_content", - "name": "data", - "selected": "Data", - "types": [ - "Data" - ], - "value": "__UNDEFINED__" - } - ], - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import re\n\nfrom langchain_community.document_loaders.web_base import WebBaseLoader\n\nfrom langflow.custom import Component\nfrom langflow.io import Output, MessageTextInput\nfrom langflow.schema import Data\n\n\nclass URLComponent(Component):\n display_name = \"URL\"\n description = \"Fetch content from one or more URLs.\"\n icon = \"layout-template\"\n\n inputs = [\n MessageTextInput(\n name=\"urls\",\n display_name=\"URLs\",\n info=\"Enter one or more URLs, separated by commas.\",\n is_list=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"fetch_content\"),\n ]\n\n def ensure_url(self, string: str) -> str:\n \"\"\"\n Ensures the given string is a URL by adding 'http://' if it doesn't start with 'http://' or 'https://'.\n Raises an error if the string is not a valid URL.\n\n Parameters:\n string (str): The string to be checked and possibly modified.\n\n Returns:\n str: The modified string that is ensured to be a URL.\n\n Raises:\n ValueError: If the string is not a valid URL.\n \"\"\"\n if not string.startswith((\"http://\", \"https://\")):\n string = \"http://\" + string\n\n # Basic URL validation regex\n url_regex = re.compile(\n r\"^(http://|https://)?\" # http:// or https://\n r\"(([a-zA-Z0-9\\.-]+)\" # domain\n r\"(\\.[a-zA-Z]{2,}))\" # top-level domain\n r\"(:[0-9]{1,5})?\" # optional port\n r\"(\\/.*)?$\" # optional path\n )\n\n if not re.match(url_regex, string):\n raise ValueError(f\"Invalid URL: {string}\")\n\n return string\n\n def fetch_content(self) -> list[Data]:\n urls = [self.ensure_url(url.strip()) for url in self.urls if url.strip()]\n loader = WebBaseLoader(web_paths=urls, encoding=\"utf-8\")\n docs = loader.load()\n data = [Data(text=doc.page_content, **doc.metadata) for doc in docs]\n self.status = data\n return data\n" - }, - "urls": { - "advanced": false, - "display_name": "URLs", - "dynamic": false, - "info": "Enter one or more URLs, separated by commas.", - "list": true, - "load_from_db": false, - "name": "urls", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": [ - "https://www.promptingguide.ai/techniques/prompt_chaining" - ] - } - } - }, - "type": "URL" - }, - "dragging": false, - "height": 301, - "id": "URL-eFIqb", - "position": { - "x": 109.01828882212544, - "y": 635.7038211214808 - }, - "positionAbsolute": { - "x": 109.01828882212544, - "y": 635.7038211214808 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Get text inputs from the Playground.", - "display_name": "Instructions", - "edited": false, - "id": "TextInput-DbgJ3", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Get text inputs from the Playground.", - "display_name": "Instructions", - "documentation": "", - "edited": true, - "field_order": [ - "input_value" - ], - "frozen": false, - "icon": "type", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.io.text import TextComponent\nfrom langflow.io import Output, MessageTextInput\nfrom langflow.schema.message import Message\n\n\nclass TextInputComponent(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Playground.\"\n icon = \"type\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Text to be passed as input.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Message:\n message = Message(\n text=self.input_value,\n )\n return message\n" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "info": "Text to be passed as input.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "Use the references above for style to write a new blog/tutorial about prompt engineering techniques. Suggest non-covered topics." - } - } - }, - "type": "TextInput" - }, - "dragging": false, - "height": 309, - "id": "TextInput-DbgJ3", - "position": { - "x": 668.3436449795839, - "y": 213.40493638517057 - }, - "positionAbsolute": { - "x": 668.3436449795839, - "y": 213.40493638517057 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "ParseData-34pEF", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Convert Data into plain text following a specified template.", - "display_name": "Parse Data", - "documentation": "", - "field_order": [ - "data", - "template", - "sep" - ], - "frozen": false, - "icon": "braces", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "parse_data", - "name": "text", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n display_name = \"Parse Data\"\n description = \"Convert Data into plain text following a specified template.\"\n icon = \"braces\"\n\n inputs = [\n DataInput(name=\"data\", display_name=\"Data\", info=\"The data to convert to text.\"),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.\",\n value=\"{text}\",\n ),\n StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n ]\n\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"parse_data\"),\n ]\n\n def parse_data(self) -> Message:\n data = self.data if isinstance(self.data, list) else [self.data]\n template = self.template\n\n result_string = data_to_text(template, data, sep=self.sep)\n self.status = result_string\n return Message(text=result_string)\n" - }, - "data": { - "advanced": false, - "display_name": "Data", - "dynamic": false, - "info": "The data to convert to text.", - "input_types": [ - "Data" - ], - "list": false, - "name": "data", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "other", - "value": "" - }, - "sep": { - "advanced": true, - "display_name": "Separator", - "dynamic": false, - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "sep", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "---" - }, - "template": { - "advanced": false, - "display_name": "Template", - "dynamic": false, - "info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.", - "multiline": true, - "name": "template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "{text}" - } - } - }, - "type": "ParseData" - }, - "dragging": false, - "height": 377, - "id": "ParseData-34pEF", - "position": { - "x": 697.109388389247, - "y": 993.1273555676513 - }, - "positionAbsolute": { - "x": 697.109388389247, - "y": 993.1273555676513 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "ParseData-iAHWq", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Convert Data into plain text following a specified template.", - "display_name": "Parse Data", - "documentation": "", - "field_order": [ - "data", - "template", - "sep" - ], - "frozen": false, - "icon": "braces", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "parse_data", - "name": "text", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n display_name = \"Parse Data\"\n description = \"Convert Data into plain text following a specified template.\"\n icon = \"braces\"\n\n inputs = [\n DataInput(name=\"data\", display_name=\"Data\", info=\"The data to convert to text.\"),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.\",\n value=\"{text}\",\n ),\n StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n ]\n\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"parse_data\"),\n ]\n\n def parse_data(self) -> Message:\n data = self.data if isinstance(self.data, list) else [self.data]\n template = self.template\n\n result_string = data_to_text(template, data, sep=self.sep)\n self.status = result_string\n return Message(text=result_string)\n" - }, - "data": { - "advanced": false, - "display_name": "Data", - "dynamic": false, - "info": "The data to convert to text.", - "input_types": [ - "Data" - ], - "list": false, - "name": "data", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "other", - "value": "" - }, - "sep": { - "advanced": true, - "display_name": "Separator", - "dynamic": false, - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "sep", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "---" - }, - "template": { - "advanced": false, - "display_name": "Template", - "dynamic": false, - "info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.", - "multiline": true, - "name": "template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "{text}" - } - } - }, - "type": "ParseData" - }, - "dragging": false, - "height": 377, - "id": "ParseData-iAHWq", - "position": { - "x": 674.3059180422167, - "y": 594.1081812719365 - }, - "positionAbsolute": { - "x": 674.3059180422167, - "y": 594.1081812719365 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "edited": false, - "id": "OpenAIModel-slJZS", - "node": { - "base_classes": [ - "LanguageModel", - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "documentation": "", - "edited": true, - "field_order": [ - "input_value", - "max_tokens", - "model_kwargs", - "output_schema", - "model_name", - "openai_api_base", - "openai_api_key", - "temperature", - "stream", - "system_message", - "seed" - ], - "frozen": false, - "icon": "OpenAI", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text_output", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "max_tokens": { - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "list": false, - "name": "max_tokens", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": "" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "dict", - "value": {} - }, - "model_name": { - "advanced": false, - "display_name": "Model Name", - "dynamic": false, - "info": "", - "name": "model_name", - "options": [ - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "gpt-3.5-turbo" - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "list": false, - "load_from_db": false, - "name": "openai_api_base", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_api_key": { - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [], - "load_from_db": true, - "name": "openai_api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "output_schema": { - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "dict", - "value": {} - }, - "seed": { - "advanced": true, - "display_name": "Seed", - "dynamic": false, - "info": "The seed controls the reproducibility of the job.", - "list": false, - "name": "seed", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": 1 - }, - "stream": { - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "list": false, - "name": "stream", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "bool", - "value": false - }, - "system_message": { - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "info": "System message to pass to the model.", - "list": false, - "load_from_db": false, - "name": "system_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "temperature": { - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "info": "", - "list": false, - "name": "temperature", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "float", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 623, - "id": "OpenAIModel-slJZS", - "position": { - "x": 1968.999112433115, - "y": 528.8142375467121 - }, - "positionAbsolute": { - "x": 1968.999112433115, - "y": 528.8142375467121 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "ChatOutput-LkJX7", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "documentation": "", - "field_order": [ - "input_value", - "sender", - "sender_name", - "session_id", - "data_template" - ], - "frozen": false, - "icon": "ChatOutput", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, Output, MessageTextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" - }, - "data_template": { - "advanced": true, - "display_name": "Data Template", - "dynamic": false, - "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "data_template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "{text}" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "info": "Message to be passed as output.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "info": "Type of sender.", - "name": "sender", - "options": [ - "Machine", - "User" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "Machine" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "info": "Name of the sender.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "sender_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "AI" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "info": "Session ID for the message.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "session_id", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - } - } - }, - "type": "ChatOutput" - }, - "dragging": false, - "height": 309, - "id": "ChatOutput-LkJX7", - "position": { - "x": 2668.5087497211402, - "y": 859.3268817022193 - }, - "positionAbsolute": { - "x": 2668.5087497211402, - "y": 859.3268817022193 - }, - "selected": false, - "type": "genericNode", - "width": 384 - } - ], - "viewport": { - "x": 40.848461446679266, - "y": 89.0650521913791, - "zoom": 0.3782109149354305 - } - }, - "description": "This flow can be used to create a blog post following instructions from the user, using two other blogs as reference.", - "endpoint_name": null, - "id": "abcd5472-71fb-431c-9a08-6fd7781ffaa4", - "is_component": false, - "last_tested_version": "1.0.0a61", - "name": "Blog Writer" -} \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Document QA.json b/src/backend/base/langflow/initial_setup/starter_projects/Langflow Document QA.json deleted file mode 100644 index 2a937cc4c..000000000 --- a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Document QA.json +++ /dev/null @@ -1,1026 +0,0 @@ -{ - "data": { - "edges": [ - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "File", - "id": "File-z24tW", - "name": "data", - "output_types": [ - "Data" - ] - }, - "targetHandle": { - "fieldName": "Document", - "id": "Prompt-ws12t", - "inputTypes": [ - "Document", - "Message", - "Data", - "Text" - ], - "type": "str" - } - }, - "id": "reactflow__edge-File-z24tW{œdataTypeœ:œFileœ,œidœ:œFile-z24tWœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-Prompt-ws12t{œfieldNameœ:œDocumentœ,œidœ:œPrompt-ws12tœ,œinputTypesœ:[œDocumentœ,œMessageœ,œDataœ,œTextœ],œtypeœ:œstrœ}", - "source": "File-z24tW", - "sourceHandle": "{œdataTypeœ: œFileœ, œidœ: œFile-z24tWœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", - "target": "Prompt-ws12t", - "targetHandle": "{œfieldNameœ: œDocumentœ, œidœ: œPrompt-ws12tœ, œinputTypesœ: [œDocumentœ, œMessageœ, œDataœ, œTextœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "ChatInput", - "id": "ChatInput-YMjNE", - "name": "message", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "Question", - "id": "Prompt-ws12t", - "inputTypes": [ - "Document", - "Message", - "Data", - "Text" - ], - "type": "str" - } - }, - "id": "reactflow__edge-ChatInput-YMjNE{œdataTypeœ:œChatInputœ,œidœ:œChatInput-YMjNEœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-ws12t{œfieldNameœ:œQuestionœ,œidœ:œPrompt-ws12tœ,œinputTypesœ:[œDocumentœ,œMessageœ,œDataœ,œTextœ],œtypeœ:œstrœ}", - "source": "ChatInput-YMjNE", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-YMjNEœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-ws12t", - "targetHandle": "{œfieldNameœ: œQuestionœ, œidœ: œPrompt-ws12tœ, œinputTypesœ: [œDocumentœ, œMessageœ, œDataœ, œTextœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "Prompt", - "id": "Prompt-ws12t", - "name": "prompt", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "OpenAIModel-AdQdh", - "inputTypes": [ - "Message" - ], - "type": "str" - } - }, - "id": "reactflow__edge-Prompt-ws12t{œdataTypeœ:œPromptœ,œidœ:œPrompt-ws12tœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-AdQdh{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-AdQdhœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-ws12t", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-ws12tœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-AdQdh", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-AdQdhœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "OpenAIModel", - "id": "OpenAIModel-AdQdh", - "name": "text_output", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "ChatOutput-bSlkp", - "inputTypes": [ - "Message", - "str" - ], - "type": "str" - } - }, - "id": "reactflow__edge-OpenAIModel-AdQdh{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-AdQdhœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-bSlkp{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-bSlkpœ,œinputTypesœ:[œMessageœ,œstrœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-AdQdh", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-AdQdhœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-bSlkp", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-bSlkpœ, œinputTypesœ: [œMessageœ, œstrœ], œtypeœ: œstrœ}" - } - ], - "nodes": [ - { - "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "id": "Prompt-ws12t", - "node": { - "base_classes": [ - "object", - "str", - "Text" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": { - "template": [ - "Document", - "Question" - ] - }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "documentation": "", - "error": null, - "field_order": [], - "frozen": false, - "full_path": null, - "icon": "prompts", - "is_composition": null, - "is_input": null, - "is_output": null, - "name": "", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Prompt Message", - "method": "build_prompt", - "name": "prompt", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "Document": { - "advanced": false, - "display_name": "Document", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Document", - "Message", - "Data", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "Document", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "Question": { - "advanced": false, - "display_name": "Question", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Document", - "Message", - "Data", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "Question", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n" - }, - "template": { - "advanced": false, - "display_name": "Template", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "template", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "prompt", - "value": "Answer user's questions based on the document below:\n\n---\n\n{Document}\n\n---\n\nQuestion:\n{Question}\n\nAnswer:\n" - } - } - }, - "type": "Prompt" - }, - "dragging": false, - "height": 525, - "id": "Prompt-ws12t", - "position": { - "x": 585.7906101139403, - "y": 117.52115876762832 - }, - "positionAbsolute": { - "x": 585.7906101139403, - "y": 117.52115876762832 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "ChatInput-YMjNE", - "node": { - "base_classes": [ - "str", - "Record", - "Text", - "object" - ], - "beta": false, - "custom_fields": { - "input_value": null, - "return_record": null, - "sender": null, - "sender_name": null, - "session_id": null - }, - "description": "Get chat inputs from the Playground.", - "display_name": "Chat Input", - "documentation": "", - "field_formatters": {}, - "field_order": [], - "frozen": false, - "icon": "ChatInput", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MultilineInput, Output, MessageTextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n MessageTextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Message to be passed as input.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "what is this?" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Type of sender.", - "input_types": [ - "Text" - ], - "list": true, - "load_from_db": false, - "multiline": false, - "name": "sender", - "options": [ - "Machine", - "User" - ], - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "User" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Name of the sender.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "sender_name", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "User" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Session ID for the message.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "session_id", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - } - } - }, - "type": "ChatInput" - }, - "dragging": false, - "height": 309, - "id": "ChatInput-YMjNE", - "position": { - "x": -38.501719080514135, - "y": 379.81180230285355 - }, - "positionAbsolute": { - "x": -38.501719080514135, - "y": 379.81180230285355 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "ChatOutput-bSlkp", - "node": { - "base_classes": [ - "str", - "Record", - "Text", - "object" - ], - "beta": false, - "custom_fields": { - "input_value": null, - "return_record": null, - "sender": null, - "sender_name": null, - "session_id": null - }, - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "documentation": "", - "field_formatters": {}, - "field_order": [], - "frozen": false, - "icon": "ChatOutput", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, Output, MessageTextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Message to be passed as output.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Type of sender.", - "input_types": [ - "Text" - ], - "list": true, - "load_from_db": false, - "multiline": false, - "name": "sender", - "options": [ - "Machine", - "User" - ], - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "Machine" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Name of the sender.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "sender_name", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "AI" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Session ID for the message.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "session_id", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - } - } - }, - "type": "ChatOutput" - }, - "dragging": false, - "height": 309, - "id": "ChatOutput-bSlkp", - "position": { - "x": 1733.3012915204283, - "y": 168.76098809939327 - }, - "positionAbsolute": { - "x": 1733.3012915204283, - "y": 168.76098809939327 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "A generic file loader.", - "display_name": "File", - "id": "File-z24tW", - "node": { - "base_classes": [ - "Data" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "A generic file loader.", - "display_name": "File", - "documentation": "", - "edited": false, - "field_order": [ - "path", - "silent_errors" - ], - "frozen": false, - "icon": "file-text", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Data", - "method": "load_file", - "name": "data", - "selected": "Data", - "types": [ - "Data" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from pathlib import Path\n\nfrom langflow.base.data.utils import TEXT_FILE_TYPES, parse_text_file_to_data\nfrom langflow.custom import Component\nfrom langflow.io import BoolInput, FileInput, Output\nfrom langflow.schema import Data\n\n\nclass FileComponent(Component):\n display_name = \"File\"\n description = \"A generic file loader.\"\n icon = \"file-text\"\n\n inputs = [\n FileInput(\n name=\"path\",\n display_name=\"Path\",\n file_types=TEXT_FILE_TYPES,\n info=f\"Supported file types: {', '.join(TEXT_FILE_TYPES)}\",\n ),\n BoolInput(\n name=\"silent_errors\",\n display_name=\"Silent Errors\",\n advanced=True,\n info=\"If true, errors will not raise an exception.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"load_file\"),\n ]\n\n def load_file(self) -> Data:\n if not self.path:\n raise ValueError(\"Please, upload a file to use this component.\")\n resolved_path = self.resolve_path(self.path)\n silent_errors = self.silent_errors\n\n extension = Path(resolved_path).suffix[1:].lower()\n\n if extension == \"doc\":\n raise ValueError(\"doc files are not supported. Please save as .docx\")\n if extension not in TEXT_FILE_TYPES:\n raise ValueError(f\"Unsupported file type: {extension}\")\n\n data = parse_text_file_to_data(resolved_path, silent_errors)\n self.status = data if data else \"No data\"\n return data or Data()\n" - }, - "path": { - "advanced": false, - "display_name": "Path", - "dynamic": false, - "fileTypes": [ - "txt", - "md", - "mdx", - "csv", - "json", - "yaml", - "yml", - "xml", - "html", - "htm", - "pdf", - "docx", - "py", - "sh", - "sql", - "js", - "ts", - "tsx" - ], - "file_path": "e56e0529-7225-4f6c-9144-5ad0806f5fed/Math Router.json", - "info": "Supported file types: txt, md, mdx, csv, json, yaml, yml, xml, html, htm, pdf, docx, py, sh, sql, js, ts, tsx", - "list": false, - "name": "path", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "file", - "value": "" - }, - "silent_errors": { - "advanced": true, - "display_name": "Silent Errors", - "dynamic": false, - "info": "If true, errors will not raise an exception.", - "list": false, - "name": "silent_errors", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "bool", - "value": false - } - } - }, - "type": "File" - }, - "dragging": false, - "height": 301, - "id": "File-z24tW", - "position": { - "x": -37.064128418041946, - "y": 39.0475820447775 - }, - "positionAbsolute": { - "x": -37.064128418041946, - "y": 39.0475820447775 - }, - "selected": true, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "edited": false, - "id": "OpenAIModel-AdQdh", - "node": { - "base_classes": [ - "LanguageModel", - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "documentation": "", - "edited": true, - "field_order": [ - "input_value", - "max_tokens", - "model_kwargs", - "output_schema", - "model_name", - "openai_api_base", - "openai_api_key", - "temperature", - "stream", - "system_message", - "seed" - ], - "frozen": false, - "icon": "OpenAI", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text_output", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "max_tokens": { - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "list": false, - "name": "max_tokens", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": "" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "dict", - "value": {} - }, - "model_name": { - "advanced": false, - "display_name": "Model Name", - "dynamic": false, - "info": "", - "name": "model_name", - "options": [ - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "gpt-3.5-turbo" - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "list": false, - "load_from_db": false, - "name": "openai_api_base", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_api_key": { - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [], - "load_from_db": true, - "name": "openai_api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "output_schema": { - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "dict", - "value": {} - }, - "seed": { - "advanced": true, - "display_name": "Seed", - "dynamic": false, - "info": "The seed controls the reproducibility of the job.", - "list": false, - "name": "seed", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": 1 - }, - "stream": { - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "list": false, - "name": "stream", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "bool", - "value": false - }, - "system_message": { - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "info": "System message to pass to the model.", - "list": false, - "load_from_db": false, - "name": "system_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "temperature": { - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "info": "", - "list": false, - "name": "temperature", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "float", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 623, - "id": "OpenAIModel-AdQdh", - "position": { - "x": 1141.7303854551026, - "y": -51.19892217231286 - }, - "positionAbsolute": { - "x": 1141.7303854551026, - "y": -51.19892217231286 - }, - "selected": false, - "type": "genericNode", - "width": 384 - } - ], - "viewport": { - "x": 91.58014849142035, - "y": 287.8736279905512, - "zoom": 0.5335671198494703 - } - }, - "description": "This flow integrates PDF reading with a language model to answer document-specific questions. Ideal for small-scale texts, it facilitates direct queries with immediate insights.", - "endpoint_name": null, - "id": "e56e0529-7225-4f6c-9144-5ad0806f5fed", - "is_component": false, - "last_tested_version": "1.0.0a61", - "name": "Document QA" -} \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Memory Conversation.json b/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json similarity index 82% rename from src/backend/base/langflow/initial_setup/starter_projects/Langflow Memory Conversation.json rename to src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json index 5dceb0c15..354f0810b 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Memory Conversation.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json @@ -6,7 +6,7 @@ "data": { "sourceHandle": { "dataType": "Memory", - "id": "Memory-rvcL5", + "id": "Memory-Bn93i", "name": "messages_text", "output_types": [ "Message" @@ -14,28 +14,26 @@ }, "targetHandle": { "fieldName": "context", - "id": "Prompt-VuDd0", + "id": "Prompt-4IgSW", "inputTypes": [ - "Document", "Message", - "Record", "Text" ], "type": "str" } }, - "id": "reactflow__edge-Memory-rvcL5{œdataTypeœ:œMemoryœ,œidœ:œMemory-rvcL5œ,œnameœ:œmessages_textœ,œoutput_typesœ:[œMessageœ]}-Prompt-VuDd0{œfieldNameœ:œcontextœ,œidœ:œPrompt-VuDd0œ,œinputTypesœ:[œDocumentœ,œMessageœ,œRecordœ,œTextœ],œtypeœ:œstrœ}", - "source": "Memory-rvcL5", - "sourceHandle": "{œdataTypeœ: œMemoryœ, œidœ: œMemory-rvcL5œ, œnameœ: œmessages_textœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-VuDd0", - "targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-VuDd0œ, œinputTypesœ: [œDocumentœ, œMessageœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-Memory-Bn93i{œdataTypeœ:œMemoryœ,œidœ:œMemory-Bn93iœ,œnameœ:œmessages_textœ,œoutput_typesœ:[œMessageœ]}-Prompt-4IgSW{œfieldNameœ:œcontextœ,œidœ:œPrompt-4IgSWœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "Memory-Bn93i", + "sourceHandle": "{œdataTypeœ: œMemoryœ, œidœ: œMemory-Bn93iœ, œnameœ: œmessages_textœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-4IgSW", + "targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-4IgSWœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "ChatInput", - "id": "ChatInput-9iFsd", + "id": "ChatInput-ZV9JL", "name": "message", "output_types": [ "Message" @@ -43,28 +41,26 @@ }, "targetHandle": { "fieldName": "user_message", - "id": "Prompt-VuDd0", + "id": "Prompt-4IgSW", "inputTypes": [ - "Document", "Message", - "Record", "Text" ], "type": "str" } }, - "id": "reactflow__edge-ChatInput-9iFsd{œdataTypeœ:œChatInputœ,œidœ:œChatInput-9iFsdœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-VuDd0{œfieldNameœ:œuser_messageœ,œidœ:œPrompt-VuDd0œ,œinputTypesœ:[œDocumentœ,œMessageœ,œRecordœ,œTextœ],œtypeœ:œstrœ}", - "source": "ChatInput-9iFsd", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-9iFsdœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-VuDd0", - "targetHandle": "{œfieldNameœ: œuser_messageœ, œidœ: œPrompt-VuDd0œ, œinputTypesœ: [œDocumentœ, œMessageœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-ChatInput-ZV9JL{œdataTypeœ:œChatInputœ,œidœ:œChatInput-ZV9JLœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-4IgSW{œfieldNameœ:œuser_messageœ,œidœ:œPrompt-4IgSWœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ChatInput-ZV9JL", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-ZV9JLœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-4IgSW", + "targetHandle": "{œfieldNameœ: œuser_messageœ, œidœ: œPrompt-4IgSWœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "Prompt", - "id": "Prompt-VuDd0", + "id": "Prompt-4IgSW", "name": "prompt", "output_types": [ "Message" @@ -72,25 +68,25 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "OpenAIModel-uVOc5", + "id": "OpenAIModel-iT10n", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-Prompt-VuDd0{œdataTypeœ:œPromptœ,œidœ:œPrompt-VuDd0œ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-uVOc5{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-uVOc5œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-VuDd0", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-VuDd0œ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-uVOc5", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-uVOc5œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-Prompt-4IgSW{œdataTypeœ:œPromptœ,œidœ:œPrompt-4IgSWœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-iT10n{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-iT10nœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-4IgSW", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-4IgSWœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-iT10n", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-iT10nœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "OpenAIModel", - "id": "OpenAIModel-uVOc5", + "id": "OpenAIModel-iT10n", "name": "text_output", "output_types": [ "Message" @@ -98,186 +94,27 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "ChatOutput-R7jsA", + "id": "ChatOutput-Xi4hp", "inputTypes": [ - "Message", - "str" + "Message" ], "type": "str" } }, - "id": "reactflow__edge-OpenAIModel-uVOc5{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-uVOc5œ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-R7jsA{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-R7jsAœ,œinputTypesœ:[œMessageœ,œstrœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-uVOc5", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-uVOc5œ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-R7jsA", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-R7jsAœ, œinputTypesœ: [œMessageœ, œstrœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-OpenAIModel-iT10n{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-iT10nœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-Xi4hp{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-Xi4hpœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-iT10n", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-iT10nœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-Xi4hp", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-Xi4hpœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" } ], "nodes": [ - { - "data": { - "description": "A component for creating prompt templates using dynamic variables.", - "display_name": "Prompt", - "id": "Prompt-VuDd0", - "node": { - "base_classes": [ - "Text", - "str", - "object" - ], - "beta": false, - "custom_fields": { - "template": [ - "context", - "user_message" - ] - }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "documentation": "", - "error": null, - "field_formatters": {}, - "field_order": [], - "frozen": false, - "full_path": null, - "icon": "prompts", - "is_composition": null, - "is_input": null, - "is_output": null, - "name": "", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Prompt Message", - "method": "build_prompt", - "name": "prompt", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n" - }, - "context": { - "advanced": false, - "display_name": "context", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Document", - "Message", - "Record", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "context", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "template": { - "advanced": false, - "display_name": "Template", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "template", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "prompt", - "value": "{context}\n\nUser: {user_message}\nAI: " - }, - "user_message": { - "advanced": false, - "display_name": "user_message", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Document", - "Message", - "Record", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "user_message", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - } - } - }, - "type": "Prompt" - }, - "dragging": false, - "height": 525, - "id": "Prompt-VuDd0", - "position": { - "x": 1900.7563740044732, - "y": 755.4337191022057 - }, - "positionAbsolute": { - "x": 1900.7563740044732, - "y": 755.4337191022057 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, { "data": { "description": "Retrieves stored chat messages.", "display_name": "Memory", "edited": false, - "id": "Memory-rvcL5", + "id": "Memory-Bn93i", "node": { "base_classes": [ "Data", @@ -316,6 +153,7 @@ { "cache": true, "display_name": "Messages (Text)", + "hidden": false, "method": "retrieve_messages_as_text", "name": "messages_text", "selected": "Message", @@ -456,7 +294,7 @@ }, "dragging": false, "height": 267, - "id": "Memory-rvcL5", + "id": "Memory-Bn93i", "position": { "x": 1258.8089948698466, "y": 547.1243849102437 @@ -471,7 +309,10 @@ }, { "data": { - "id": "ChatInput-9iFsd", + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "edited": false, + "id": "ChatInput-ZV9JL", "node": { "base_classes": [ "Message" @@ -482,6 +323,7 @@ "description": "Get chat inputs from the Playground.", "display_name": "Chat Input", "documentation": "", + "edited": true, "field_order": [ "input_value", "sender", @@ -496,6 +338,7 @@ { "cache": true, "display_name": "Message", + "hidden": false, "method": "message_response", "name": "message", "selected": "Message", @@ -524,7 +367,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MultilineInput, Output, MessageTextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n MessageTextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" }, "files": { "advanced": true, @@ -563,6 +406,7 @@ "required": false, "show": true, "title_case": false, + "trace_as_metadata": true, "type": "file", "value": "" }, @@ -572,8 +416,7 @@ "dynamic": false, "info": "Message to be passed as input.", "input_types": [ - "Message", - "str" + "Message" ], "list": false, "load_from_db": false, @@ -583,6 +426,8 @@ "required": false, "show": true, "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", "value": "" }, @@ -600,6 +445,7 @@ "required": false, "show": true, "title_case": false, + "trace_as_metadata": true, "type": "str", "value": "User" }, @@ -609,17 +455,17 @@ "dynamic": false, "info": "Name of the sender.", "input_types": [ - "Message", - "str" + "Message" ], "list": false, "load_from_db": false, - "multiline": true, "name": "sender_name", "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", "value": "User" }, @@ -629,17 +475,17 @@ "dynamic": false, "info": "Session ID for the message.", "input_types": [ - "Message", - "str" + "Message" ], "list": false, "load_from_db": false, - "multiline": true, "name": "session_id", "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", "value": "" } @@ -647,18 +493,18 @@ }, "type": "ChatInput" }, - "dragging": false, + "dragging": true, "height": 309, - "id": "ChatInput-9iFsd", + "id": "ChatInput-ZV9JL", "position": { - "x": 1246.4850995457527, + "x": 1261.3748612945249, "y": 912.733279525042 }, "positionAbsolute": { - "x": 1246.4850995457527, + "x": 1261.3748612945249, "y": 912.733279525042 }, - "selected": false, + "selected": true, "type": "genericNode", "width": 384 }, @@ -667,7 +513,7 @@ "description": "Generates text using OpenAI LLMs.", "display_name": "OpenAI", "edited": false, - "id": "OpenAIModel-uVOc5", + "id": "OpenAIModel-iT10n", "node": { "base_classes": [ "LanguageModel", @@ -700,6 +546,7 @@ { "cache": true, "display_name": "Text", + "hidden": false, "method": "text_response", "name": "text_output", "selected": "Message", @@ -828,7 +675,7 @@ "dynamic": false, "info": "The OpenAI API Key to use for the OpenAI model.", "input_types": [], - "load_from_db": true, + "load_from_db": false, "name": "openai_api_key", "password": true, "placeholder": "", @@ -914,15 +761,15 @@ "type": "OpenAIModel" }, "dragging": false, - "height": 623, - "id": "OpenAIModel-uVOc5", + "height": 622, + "id": "OpenAIModel-iT10n", "position": { "x": 2495.6628431453228, - "y": 668.0955451423632 + "y": 669.9567653609598 }, "positionAbsolute": { "x": 2495.6628431453228, - "y": 668.0955451423632 + "y": 669.9567653609598 }, "selected": false, "type": "genericNode", @@ -930,7 +777,10 @@ }, { "data": { - "id": "ChatOutput-R7jsA", + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "edited": false, + "id": "ChatOutput-Xi4hp", "node": { "base_classes": [ "Message" @@ -941,6 +791,7 @@ "description": "Display a chat message in the Playground.", "display_name": "Chat Output", "documentation": "", + "edited": true, "field_order": [ "input_value", "sender", @@ -983,7 +834,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, Output, MessageTextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" }, "data_template": { "advanced": true, @@ -991,17 +842,17 @@ "dynamic": false, "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", "input_types": [ - "Message", - "str" + "Message" ], "list": false, "load_from_db": false, - "multiline": true, "name": "data_template", "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", "value": "{text}" }, @@ -1011,17 +862,17 @@ "dynamic": false, "info": "Message to be passed as output.", "input_types": [ - "Message", - "str" + "Message" ], "list": false, "load_from_db": false, - "multiline": true, "name": "input_value", "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", "value": "" }, @@ -1039,6 +890,7 @@ "required": false, "show": true, "title_case": false, + "trace_as_metadata": true, "type": "str", "value": "Machine" }, @@ -1048,17 +900,17 @@ "dynamic": false, "info": "Name of the sender.", "input_types": [ - "Message", - "str" + "Message" ], "list": false, "load_from_db": false, - "multiline": true, "name": "sender_name", "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", "value": "AI" }, @@ -1067,14 +919,164 @@ "display_name": "Session ID", "dynamic": false, "info": "Session ID for the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + } + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 308, + "id": "ChatOutput-Xi4hp", + "position": { + "x": 3028.2686266398873, + "y": 888.0854888768531 + }, + "positionAbsolute": { + "x": 3028.2686266398873, + "y": 888.0854888768531 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-4IgSW", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "context", + "user_message" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "error": null, + "field_order": [ + "template" + ], + "frozen": false, + "full_path": null, + "icon": "prompts", + "is_composition": null, + "is_input": null, + "is_output": null, + "name": "", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "hidden": false, + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def post_code_processing(self, new_build_config: dict, current_build_config: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_build_config, current_build_config)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_build_config\n # and update the frontend_node with those values\n update_template_values(frontend_template=frontend_node, raw_template=current_build_config[\"template\"])\n return frontend_node\n" + }, + "context": { + "advanced": false, + "display_name": "context", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", "input_types": [ "Message", - "str" + "Text" ], "list": false, "load_from_db": false, "multiline": true, - "name": "session_id", + "name": "context", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "template": { + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "prompt", + "value": "{context}\n\nUser: {user_message}\nAI: " + }, + "user_message": { + "advanced": false, + "display_name": "user_message", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "user_message", + "password": false, "placeholder": "", "required": false, "show": true, @@ -1084,18 +1086,18 @@ } } }, - "type": "ChatOutput" + "type": "Prompt" }, "dragging": false, - "height": 309, - "id": "ChatOutput-R7jsA", + "height": 517, + "id": "Prompt-4IgSW", "position": { - "x": 3129.987101578166, - "y": 888.0854888768531 + "x": 1879.4280156201567, + "y": 674.3958274263156 }, "positionAbsolute": { - "x": 3129.987101578166, - "y": 888.0854888768531 + "x": 1879.4280156201567, + "y": 674.3958274263156 }, "selected": false, "type": "genericNode", @@ -1103,15 +1105,15 @@ } ], "viewport": { - "x": -527.2609043386433, - "y": 33.26280492099636, - "zoom": 0.48650433790103115 + "x": -592.532107710133, + "y": -149.32118023592653, + "zoom": 0.5372819347267049 } }, "description": "This project can be used as a starting point for building a Chat experience with user specific memory. You can set a different Session ID to start a new message history.", "endpoint_name": null, - "id": "4e88f957-1541-4760-8a03-6132d4b14090", + "id": "fce26e32-fb38-4a46-b2bf-0ae0f61a2c5d", "is_component": false, - "last_tested_version": "1.0.0a61", + "last_tested_version": "1.0.0rc1", "name": "Memory Chatbot" } \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json b/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json new file mode 100644 index 000000000..cb1335388 --- /dev/null +++ b/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json @@ -0,0 +1,2281 @@ +{ + "data": { + "edges": [ + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "ChatInput", + "id": "ChatInput-vRBSi", + "name": "message", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "search_input", + "id": "AstraDB-N856w", + "inputTypes": [ + "Message", + "str" + ], + 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"reactflow__edge-ParseData-Z6n4v{œdataTypeœ:œParseDataœ,œidœ:œParseData-Z6n4vœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-8YnFi{œfieldNameœ:œcontextœ,œidœ:œPrompt-8YnFiœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ParseData-Z6n4v", + "sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-Z6n4vœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-8YnFi", + "targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-8YnFiœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-8YnFi", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "OpenAIModel-bxsF9", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-8YnFi{œdataTypeœ:œPromptœ,œidœ:œPrompt-8YnFiœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-bxsF9{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-bxsF9œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-8YnFi", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-8YnFiœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-bxsF9", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-bxsF9œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIModel", + "id": "OpenAIModel-bxsF9", + "name": "text_output", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "ChatOutput-FNGr5", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-OpenAIModel-bxsF9{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-bxsF9œ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-FNGr5{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-FNGr5œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-bxsF9", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-bxsF9œ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-FNGr5", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-FNGr5œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + } + ], + "nodes": [ + { + "data": { + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "edited": false, + "id": "ChatInput-vRBSi", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "documentation": "", + "edited": true, + "field_order": [ + "input_value", + "sender", + "sender_name", + "session_id", + "files" + ], + "frozen": false, + "icon": "ChatInput", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + }, + "files": { + "advanced": true, + "display_name": "Files", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx", + "jpg", + "jpeg", + "png", + "bmp", + "image" + ], + "file_path": "", + "info": "Files to be sent with the message.", + "list": true, + "name": "files", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "file", + "value": "" + }, + "input_value": { + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "advanced": true, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "sender_name": { + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "session_id": { + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "Session ID for the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + } + }, + "type": "ChatInput" + }, + "dragging": false, + "height": 309, + "id": "ChatInput-vRBSi", + "position": { + "x": 682.002772470747, + "y": 253.67030039648512 + }, + "positionAbsolute": { + "x": 682.002772470747, + "y": 253.67030039648512 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "id": "OpenAIEmbeddings-ftAK3", + "node": { + "base_classes": [ + "Embeddings" + ], + "beta": false, + "custom_fields": { + "allowed_special": null, + "chunk_size": null, + "client": null, + "default_headers": null, + "default_query": null, + "deployment": null, + "disallowed_special": null, + "embedding_ctx_length": null, + "max_retries": null, + "model": null, + "model_kwargs": null, + "openai_api_base": null, + "openai_api_key": null, + "openai_api_type": null, + "openai_api_version": null, + "openai_organization": null, + "openai_proxy": null, + "request_timeout": null, + "show_progress_bar": null, + "skip_empty": null, + "tiktoken_enable": null, + "tiktoken_model_name": null + }, + "description": "Generate embeddings using OpenAI models.", + "display_name": "OpenAI Embeddings", + "documentation": "", + "field_formatters": {}, + "field_order": [], + "frozen": false, + "icon": "OpenAI", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Embeddings", + "hidden": false, + "method": "build_embeddings", + "name": "embeddings", + "selected": "Embeddings", + "types": [ + "Embeddings" + ], + "value": "__UNDEFINED__" + } + ], + "template": { + "_type": "Component", + "chunk_size": { + "advanced": true, + "display_name": "Chunk Size", + "dynamic": false, + "info": "", + "list": false, + "name": "chunk_size", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 1000 + }, + "client": { + "advanced": true, + "display_name": "Client", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "client", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain_openai.embeddings.base import OpenAIEmbeddings\n\nfrom langflow.base.embeddings.model import LCEmbeddingsModel\nfrom langflow.field_typing import Embeddings\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, MessageTextInput\n\n\nclass OpenAIEmbeddingsComponent(LCEmbeddingsModel):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n icon = \"OpenAI\"\n inputs = [\n DictInput(\n name=\"default_headers\",\n display_name=\"Default Headers\",\n advanced=True,\n info=\"Default headers to use for the API request.\",\n ),\n DictInput(\n name=\"default_query\",\n display_name=\"Default Query\",\n advanced=True,\n info=\"Default query parameters to use for the API request.\",\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n MessageTextInput(name=\"client\", display_name=\"Client\", advanced=True),\n MessageTextInput(name=\"deployment\", display_name=\"Deployment\", advanced=True),\n IntInput(name=\"embedding_ctx_length\", display_name=\"Embedding Context Length\", advanced=True, value=1536),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", value=3, advanced=True),\n DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n advanced=False,\n options=[\n \"text-embedding-3-small\",\n \"text-embedding-3-large\",\n \"text-embedding-ada-002\",\n ],\n value=\"text-embedding-3-small\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n SecretStrInput(name=\"openai_api_base\", display_name=\"OpenAI API Base\", advanced=True),\n SecretStrInput(name=\"openai_api_key\", display_name=\"OpenAI API Key\"),\n SecretStrInput(name=\"openai_api_type\", display_name=\"OpenAI API Type\", advanced=True),\n MessageTextInput(name=\"openai_api_version\", display_name=\"OpenAI API Version\", advanced=True),\n MessageTextInput(\n name=\"openai_organization\",\n display_name=\"OpenAI Organization\",\n advanced=True,\n ),\n MessageTextInput(name=\"openai_proxy\", display_name=\"OpenAI Proxy\", advanced=True),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n BoolInput(name=\"skip_empty\", display_name=\"Skip Empty\", advanced=True),\n MessageTextInput(\n name=\"tiktoken_model_name\",\n display_name=\"TikToken Model Name\",\n advanced=True,\n ),\n BoolInput(\n name=\"tiktoken_enable\",\n display_name=\"TikToken Enable\",\n advanced=True,\n value=True,\n info=\"If False, you must have transformers installed.\",\n ),\n ]\n\n def build_embeddings(self) -> Embeddings:\n return OpenAIEmbeddings(\n tiktoken_enabled=self.tiktoken_enable,\n default_headers=self.default_headers,\n default_query=self.default_query,\n allowed_special=\"all\",\n disallowed_special=\"all\",\n chunk_size=self.chunk_size,\n deployment=self.deployment,\n embedding_ctx_length=self.embedding_ctx_length,\n max_retries=self.max_retries,\n model=self.model,\n model_kwargs=self.model_kwargs,\n base_url=self.openai_api_base,\n api_key=self.openai_api_key,\n openai_api_type=self.openai_api_type,\n api_version=self.openai_api_version,\n organization=self.openai_organization,\n openai_proxy=self.openai_proxy,\n timeout=self.request_timeout or None,\n show_progress_bar=self.show_progress_bar,\n skip_empty=self.skip_empty,\n tiktoken_model_name=self.tiktoken_model_name,\n )\n" + }, + "default_headers": { + "advanced": true, + "display_name": "Default Headers", + "dynamic": false, + "info": "Default headers to use for the API request.", + "list": false, + "name": "default_headers", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "default_query": { + "advanced": true, + "display_name": "Default Query", + "dynamic": false, + "info": "Default query parameters to use for the API request.", + "list": false, + "name": "default_query", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "deployment": { + "advanced": true, + "display_name": "Deployment", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "deployment", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "embedding_ctx_length": { + "advanced": true, + "display_name": "Embedding Context Length", + "dynamic": false, + "info": "", + "list": false, + "name": "embedding_ctx_length", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 1536 + }, + "max_retries": { + "advanced": true, + "display_name": "Max Retries", + "dynamic": false, + "info": "", + "list": false, + "name": "max_retries", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 3 + }, + "model": { + "advanced": false, + "display_name": "Model", + "dynamic": false, + "info": "", + "name": "model", + "options": [ + "text-embedding-3-small", + "text-embedding-3-large", + "text-embedding-ada-002" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "text-embedding-3-small" + }, + "model_kwargs": { + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "openai_api_base": { + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "", + "input_types": [], + "load_from_db": true, + "name": "openai_api_base", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_key": { + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "", + "input_types": [], + "load_from_db": false, + "name": "openai_api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_type": { + "advanced": true, + "display_name": "OpenAI API Type", + "dynamic": false, + "info": "", + "input_types": [], + "load_from_db": true, + "name": "openai_api_type", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_version": { + "advanced": true, + "display_name": "OpenAI API Version", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "openai_api_version", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_organization": { + "advanced": true, + "display_name": "OpenAI Organization", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "openai_organization", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_proxy": { + "advanced": true, + "display_name": "OpenAI Proxy", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "openai_proxy", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "request_timeout": { + "advanced": true, + "display_name": "Request Timeout", + "dynamic": false, + "info": "", + "list": false, + "name": "request_timeout", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "float", + "value": "" + }, + "show_progress_bar": { + "advanced": true, + "display_name": "Show Progress Bar", + "dynamic": false, + "info": "", + "list": false, + "name": "show_progress_bar", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "skip_empty": { + "advanced": true, + "display_name": "Skip Empty", + "dynamic": false, + "info": "", + "list": false, + "name": "skip_empty", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "tiktoken_enable": { + "advanced": true, + "display_name": "TikToken Enable", + "dynamic": false, + "info": "If False, you must have transformers installed.", + "list": false, + "name": "tiktoken_enable", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": true + }, + "tiktoken_model_name": { + "advanced": true, + "display_name": "TikToken Model Name", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "tiktoken_model_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + } + } + }, + "type": "OpenAIEmbeddings" + }, + "dragging": false, + "height": 393, + "id": "OpenAIEmbeddings-ftAK3", + "position": { + "x": 672.1192980997866, + "y": 786.6985113716086 + }, + "positionAbsolute": { + "x": 672.1192980997866, + "y": 786.6985113716086 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "edited": false, + "id": "OpenAIModel-bxsF9", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": true, + "field_order": [ + "input_value", + "max_tokens", + "model_kwargs", + "output_schema", + "model_name", + "openai_api_base", + "openai_api_key", + "temperature", + "stream", + "system_message", + "seed" + ], + "frozen": false, + "icon": "OpenAI", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "hidden": false, + "method": "text_response", + "name": "text_output", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n" + }, + "input_value": { + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "max_tokens": { + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "model_kwargs": { + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "model_name": { + "advanced": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "gpt-3.5-turbo" + }, + "openai_api_base": { + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_key": { + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [], + "load_from_db": false, + "name": "openai_api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "output_schema": { + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "seed": { + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 1 + }, + "stream": { + "advanced": true, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "system_message": { + "advanced": true, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "temperature": { + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "float", + "value": 0.1 + } + } + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 623, + "id": "OpenAIModel-bxsF9", + "position": { + "x": 3243.967394111999, + "y": 392.861541437184 + }, + "positionAbsolute": { + "x": 3243.967394111999, + "y": 392.861541437184 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "edited": false, + "id": "ChatOutput-FNGr5", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": true, + "field_order": [ + "input_value", + "sender", + "sender_name", + "session_id", + "data_template" + ], + "frozen": false, + "icon": "ChatOutput", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + }, + "data_template": { + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "advanced": true, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "Session ID for the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + } + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 309, + "id": "ChatOutput-FNGr5", + "position": { + "x": 3788.786948642587, + "y": 608.4077159222614 + }, + "positionAbsolute": { + "x": 3788.786948642587, + "y": 608.4077159222614 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "id": "File-Ldmqs", + "node": { + "base_classes": [ + "Record" + ], + "beta": false, + "custom_fields": { + "path": null, + "silent_errors": null + }, + "description": "A generic file loader.", + "display_name": "File", + "documentation": "", + "field_formatters": {}, + "field_order": [], + "frozen": false, + "icon": "file-text", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Data", + "hidden": false, + "method": "load_file", + "name": "data", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + } + ], + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from pathlib import Path\n\nfrom langflow.base.data.utils import TEXT_FILE_TYPES, parse_text_file_to_data\nfrom langflow.custom import Component\nfrom langflow.io import BoolInput, FileInput, Output\nfrom langflow.schema import Data\n\n\nclass FileComponent(Component):\n display_name = \"File\"\n description = \"A generic file loader.\"\n icon = \"file-text\"\n\n inputs = [\n FileInput(\n name=\"path\",\n display_name=\"Path\",\n file_types=TEXT_FILE_TYPES,\n info=f\"Supported file types: {', '.join(TEXT_FILE_TYPES)}\",\n ),\n BoolInput(\n name=\"silent_errors\",\n display_name=\"Silent Errors\",\n advanced=True,\n info=\"If true, errors will not raise an exception.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"load_file\"),\n ]\n\n def load_file(self) -> Data:\n if not self.path:\n raise ValueError(\"Please, upload a file to use this component.\")\n resolved_path = self.resolve_path(self.path)\n silent_errors = self.silent_errors\n\n extension = Path(resolved_path).suffix[1:].lower()\n\n if extension == \"doc\":\n raise ValueError(\"doc files are not supported. Please save as .docx\")\n if extension not in TEXT_FILE_TYPES:\n raise ValueError(f\"Unsupported file type: {extension}\")\n\n data = parse_text_file_to_data(resolved_path, silent_errors)\n self.status = data if data else \"No data\"\n return data or Data()\n" + }, + "path": { + "advanced": false, + "display_name": "Path", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx" + ], + "file_path": "bba1609b-3af2-431d-a884-322cc253c69d/flatland.pdf", + "info": "Supported file types: txt, md, mdx, csv, json, yaml, yml, xml, html, htm, pdf, docx, py, sh, sql, js, ts, tsx", + "list": false, + "name": "path", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "file", + "value": "" + }, + "silent_errors": { + "advanced": true, + "display_name": "Silent Errors", + "dynamic": false, + "info": "If true, errors will not raise an exception.", + "list": false, + "name": "silent_errors", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + } + } + }, + "type": "File" + }, + "dragging": false, + "height": 301, + "id": "File-Ldmqs", + "position": { + "x": -583.277913381927, + "y": 433.34221812460396 + }, + "positionAbsolute": { + "x": -583.277913381927, + "y": 433.34221812460396 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Implementation of Vector Store using Astra DB with search capabilities", + "display_name": "Astra DB Vector Store", + "id": "AstraDB-N856w", + "node": { + "base_classes": [ + "Data" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Implementation of Vector Store using Astra DB with search capabilities", + "display_name": "Astra DB Vector Store", + "documentation": "https://python.langchain.com/docs/integrations/vectorstores/astradb", + "edited": false, + "field_order": [ + "collection_name", + "token", + "api_endpoint", + "vector_store_inputs", + "embedding", + "namespace", + "metric", + "batch_size", + "bulk_insert_batch_concurrency", + "bulk_insert_overwrite_concurrency", + "bulk_delete_concurrency", + "setup_mode", + "pre_delete_collection", + "metadata_indexing_include", + "metadata_indexing_exclude", + "collection_indexing_policy", + "add_to_vector_store", + "search_input", + "search_type", + "number_of_results" + ], + "frozen": false, + "icon": "AstraDB", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Retriever", + "method": "build_base_retriever", + "name": "base_retriever", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Search Results", + "hidden": false, + "method": "search_documents", + "name": "search_results", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "add_to_vector_store": { + "advanced": false, + "display_name": "Add to Vector Store", + "dynamic": false, + "info": "If true, the Vector Store Inputs will be added to the Vector Store.", + "list": false, + "name": "add_to_vector_store", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": true + }, + "api_endpoint": { + "advanced": false, + "display_name": "API Endpoint", + "dynamic": false, + "info": "API endpoint URL for the Astra DB service.", + "input_types": [], + "load_from_db": false, + "name": "api_endpoint", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "batch_size": { + "advanced": true, + "display_name": "Batch Size", + "dynamic": false, + "info": "Optional number of data to process in a single batch.", + "list": false, + "name": "batch_size", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "bulk_delete_concurrency": { + "advanced": true, + "display_name": "Bulk Delete Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk delete operations.", + "list": false, + "name": "bulk_delete_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "bulk_insert_batch_concurrency": { + "advanced": true, + "display_name": "Bulk Insert Batch Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk insert operations.", + "list": false, + "name": "bulk_insert_batch_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "bulk_insert_overwrite_concurrency": { + "advanced": true, + "display_name": "Bulk Insert Overwrite Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk insert operations that overwrite existing data.", + "list": false, + "name": "bulk_insert_overwrite_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from loguru import logger\n\nfrom langflow.base.vectorstores.model import LCVectorStoreComponent\nfrom langflow.io import BoolInput, DropdownInput, HandleInput, IntInput, MultilineInput, SecretStrInput, StrInput\nfrom langflow.schema import Data\n\n\nclass AstraVectorStoreComponent(LCVectorStoreComponent):\n display_name: str = \"Astra DB Vector Store\"\n description: str = \"Implementation of Vector Store using Astra DB with search capabilities\"\n documentation: str = \"https://python.langchain.com/docs/integrations/vectorstores/astradb\"\n icon: str = \"AstraDB\"\n\n inputs = [\n StrInput(\n name=\"collection_name\",\n display_name=\"Collection Name\",\n info=\"The name of the collection within Astra DB where the vectors will be stored.\",\n ),\n SecretStrInput(\n name=\"token\",\n display_name=\"Astra DB Application Token\",\n info=\"Authentication token for accessing Astra DB.\",\n value=\"ASTRA_DB_APPLICATION_TOKEN\",\n ),\n SecretStrInput(\n name=\"api_endpoint\",\n display_name=\"API Endpoint\",\n info=\"API endpoint URL for the Astra DB service.\",\n value=\"ASTRA_DB_API_ENDPOINT\",\n ),\n HandleInput(\n name=\"vector_store_inputs\",\n display_name=\"Vector Store Inputs\",\n input_types=[\"Document\", \"Data\"],\n is_list=True,\n ),\n HandleInput(\n name=\"embedding\",\n display_name=\"Embedding\",\n input_types=[\"Embeddings\"],\n ),\n StrInput(\n name=\"namespace\",\n display_name=\"Namespace\",\n info=\"Optional namespace within Astra DB to use for the collection.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"metric\",\n display_name=\"Metric\",\n info=\"Optional distance metric for vector comparisons in the vector store.\",\n options=[\"cosine\", \"dot_product\", \"euclidean\"],\n advanced=True,\n ),\n IntInput(\n name=\"batch_size\",\n display_name=\"Batch Size\",\n info=\"Optional number of data to process in a single batch.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_batch_concurrency\",\n display_name=\"Bulk Insert Batch Concurrency\",\n info=\"Optional concurrency level for bulk insert operations.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_overwrite_concurrency\",\n display_name=\"Bulk Insert Overwrite Concurrency\",\n info=\"Optional concurrency level for bulk insert operations that overwrite existing data.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_delete_concurrency\",\n display_name=\"Bulk Delete Concurrency\",\n info=\"Optional concurrency level for bulk delete operations.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"setup_mode\",\n display_name=\"Setup Mode\",\n info=\"Configuration mode for setting up the vector store, with options like 'Sync', 'Async', or 'Off'.\",\n options=[\"Sync\", \"Async\", \"Off\"],\n advanced=True,\n value=\"Sync\",\n ),\n BoolInput(\n name=\"pre_delete_collection\",\n display_name=\"Pre Delete Collection\",\n info=\"Boolean flag to determine whether to delete the collection before creating a new one.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_include\",\n display_name=\"Metadata Indexing Include\",\n info=\"Optional list of metadata fields to include in the indexing.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_exclude\",\n display_name=\"Metadata Indexing Exclude\",\n info=\"Optional list of metadata fields to exclude from the indexing.\",\n advanced=True,\n ),\n StrInput(\n name=\"collection_indexing_policy\",\n display_name=\"Collection Indexing Policy\",\n info=\"Optional dictionary defining the indexing policy for the collection.\",\n advanced=True,\n ),\n BoolInput(\n name=\"add_to_vector_store\",\n display_name=\"Add to Vector Store\",\n info=\"If true, the Vector Store Inputs will be added to the Vector Store.\",\n ),\n MultilineInput(\n name=\"search_input\",\n display_name=\"Search Input\",\n ),\n DropdownInput(\n name=\"search_type\",\n display_name=\"Search Type\",\n options=[\"Similarity\", \"MMR\"],\n value=\"Similarity\",\n ),\n IntInput(\n name=\"number_of_results\",\n display_name=\"Number of Results\",\n info=\"Number of results to return.\",\n advanced=True,\n value=4,\n ),\n ]\n\n def build_vector_store(self):\n try:\n from langchain_astradb import AstraDBVectorStore\n from langchain_astradb.utils.astradb import SetupMode\n except ImportError:\n raise ImportError(\n \"Could not import langchain Astra DB integration package. \"\n \"Please install it with `pip install langchain-astradb`.\"\n )\n\n try:\n if not self.setup_mode:\n self.setup_mode = self._inputs[\"setup_mode\"].options[0]\n\n setup_mode_value = SetupMode[self.setup_mode.upper()]\n except KeyError:\n raise ValueError(f\"Invalid setup mode: {self.setup_mode}\")\n\n vector_store_kwargs = {\n \"embedding\": self.embedding,\n \"collection_name\": self.collection_name,\n \"token\": self.token,\n \"api_endpoint\": self.api_endpoint,\n \"namespace\": self.namespace or None,\n \"metric\": self.metric or None,\n \"batch_size\": self.batch_size or None,\n \"bulk_insert_batch_concurrency\": self.bulk_insert_batch_concurrency or None,\n \"bulk_insert_overwrite_concurrency\": self.bulk_insert_overwrite_concurrency or None,\n \"bulk_delete_concurrency\": self.bulk_delete_concurrency or None,\n \"setup_mode\": setup_mode_value,\n \"pre_delete_collection\": self.pre_delete_collection or False,\n }\n\n if self.metadata_indexing_include:\n vector_store_kwargs[\"metadata_indexing_include\"] = self.metadata_indexing_include\n elif self.metadata_indexing_exclude:\n vector_store_kwargs[\"metadata_indexing_exclude\"] = self.metadata_indexing_exclude\n elif self.collection_indexing_policy:\n vector_store_kwargs[\"collection_indexing_policy\"] = self.collection_indexing_policy\n\n try:\n vector_store = AstraDBVectorStore(**vector_store_kwargs)\n except Exception as e:\n raise ValueError(f\"Error initializing AstraDBVectorStore: {str(e)}\") from e\n\n if self.add_to_vector_store:\n self._add_documents_to_vector_store(vector_store)\n\n return vector_store\n\n def build_base_retriever(self):\n vector_store = self.build_vector_store()\n self.status = self._astradb_collection_to_data(vector_store.collection)\n return vector_store\n\n def _add_documents_to_vector_store(self, vector_store):\n documents = []\n for _input in self.vector_store_inputs or []:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n else:\n raise ValueError(\"Vector Store Inputs must be Data objects.\")\n\n if documents and self.embedding is not None:\n logger.debug(f\"Adding {len(documents)} documents to the Vector Store.\")\n try:\n vector_store.add_documents(documents)\n except Exception as e:\n raise ValueError(f\"Error adding documents to AstraDBVectorStore: {str(e)}\") from e\n else:\n logger.debug(\"No documents to add to the Vector Store.\")\n\n def search_documents(self):\n vector_store = self.build_vector_store()\n\n logger.debug(f\"Search input: {self.search_input}\")\n logger.debug(f\"Search type: {self.search_type}\")\n logger.debug(f\"Number of results: {self.number_of_results}\")\n\n if self.search_input and isinstance(self.search_input, str) and self.search_input.strip():\n try:\n if self.search_type == \"Similarity\":\n docs = vector_store.similarity_search(\n query=self.search_input,\n k=self.number_of_results,\n )\n elif self.search_type == \"MMR\":\n docs = vector_store.max_marginal_relevance_search(\n query=self.search_input,\n k=self.number_of_results,\n )\n else:\n raise ValueError(f\"Invalid search type: {self.search_type}\")\n except Exception as e:\n raise ValueError(f\"Error performing search in AstraDBVectorStore: {str(e)}\") from e\n\n logger.debug(f\"Retrieved documents: {len(docs)}\")\n\n data = [Data.from_document(doc) for doc in docs]\n logger.debug(f\"Converted documents to data: {len(data)}\")\n self.status = data\n return data\n else:\n logger.debug(\"No search input provided. Skipping search.\")\n return []\n\n def _astradb_collection_to_data(self, collection):\n data = []\n data_dict = collection.find()\n if data_dict and \"data\" in data_dict:\n data_dict = data_dict[\"data\"].get(\"documents\", [])\n\n for item in data_dict:\n data.append(Data(content=item[\"content\"]))\n return data\n" + }, + "collection_indexing_policy": { + "advanced": true, + "display_name": "Collection Indexing Policy", + "dynamic": false, + "info": "Optional dictionary defining the indexing policy for the collection.", + "list": false, + "load_from_db": false, + "name": "collection_indexing_policy", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "collection_name": { + "advanced": false, + "display_name": "Collection Name", + "dynamic": false, + "info": "The name of the collection within Astra DB where the vectors will be stored.", + "list": false, + "load_from_db": false, + "name": "collection_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "langflow" + }, + "embedding": { + "advanced": false, + "display_name": "Embedding", + "dynamic": false, + "info": "", + "input_types": [ + "Embeddings" + ], + "list": false, + "name": "embedding", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "other", + "value": "" + }, + "metadata_indexing_exclude": { + "advanced": true, + "display_name": "Metadata Indexing Exclude", + "dynamic": false, + "info": "Optional list of metadata fields to exclude from the indexing.", + "list": false, + "load_from_db": false, + "name": "metadata_indexing_exclude", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "metadata_indexing_include": { + "advanced": true, + "display_name": "Metadata Indexing Include", + "dynamic": false, + "info": "Optional list of metadata fields to include in the indexing.", + "list": false, + "load_from_db": false, + "name": "metadata_indexing_include", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "metric": { + "advanced": true, + "display_name": "Metric", + "dynamic": false, + "info": "Optional distance metric for vector comparisons in the vector store.", + "name": "metric", + "options": [ + "cosine", + "dot_product", + "euclidean" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "namespace": { + "advanced": true, + "display_name": "Namespace", + "dynamic": false, + "info": "Optional namespace within Astra DB to use for the collection.", + "list": false, + "load_from_db": false, + "name": "namespace", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "number_of_results": { + "advanced": true, + "display_name": "Number of Results", + "dynamic": false, + "info": "Number of results to return.", + "list": false, + "name": "number_of_results", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 4 + }, + "pre_delete_collection": { + "advanced": true, + "display_name": "Pre Delete Collection", + "dynamic": false, + "info": "Boolean flag to determine whether to delete the collection before creating a new one.", + "list": false, + "name": "pre_delete_collection", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "search_input": { + "advanced": false, + "display_name": "Search Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "search_input", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "search_type": { + "advanced": false, + "display_name": "Search Type", + "dynamic": false, + "info": "", + "name": "search_type", + "options": [ + "Similarity", + "MMR" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "Similarity" + }, + "setup_mode": { + "advanced": true, + "display_name": "Setup Mode", + "dynamic": false, + "info": "Configuration mode for setting up the vector store, with options like 'Sync', 'Async', or 'Off'.", + "name": "setup_mode", + "options": [ + "Sync", + "Async", + "Off" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "Sync" + }, + "token": { + "advanced": false, + "display_name": "Astra DB Application Token", + "dynamic": false, + "info": "Authentication token for accessing Astra DB.", + "input_types": [], + "load_from_db": false, + "name": "token", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "vector_store_inputs": { + "advanced": false, + "display_name": "Vector Store Inputs", + "dynamic": false, + "info": "", + "input_types": [ + "Document", + "Data" + ], + "list": true, + "name": "vector_store_inputs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "other", + "value": "" + } + } + }, + "type": "AstraDB" + }, + "dragging": false, + "height": 917, + "id": "AstraDB-N856w", + "position": { + "x": 1298.4611042465333, + "y": 160.7181472642742 + }, + "positionAbsolute": { + "x": 1298.4611042465333, + "y": 160.7181472642742 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "id": "ParseData-Z6n4v", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Convert Data into plain text following a specified template.", + "display_name": "Parse Data", + "documentation": "", + "field_order": [ + "data", + "template", + "sep" + ], + "frozen": false, + "icon": "braces", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "hidden": false, + "method": "parse_data", + "name": "text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n display_name = \"Parse Data\"\n description = \"Convert Data into plain text following a specified template.\"\n icon = \"braces\"\n\n inputs = [\n DataInput(name=\"data\", display_name=\"Data\", info=\"The data to convert to text.\"),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.\",\n value=\"{text}\",\n ),\n StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n ]\n\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"parse_data\"),\n ]\n\n def parse_data(self) -> Message:\n data = self.data if isinstance(self.data, list) else [self.data]\n template = self.template\n\n result_string = data_to_text(template, data, sep=self.sep)\n self.status = result_string\n return Message(text=result_string)\n" + }, + "data": { + "advanced": false, + "display_name": "Data", + "dynamic": false, + "info": "The data to convert to text.", + "input_types": [ + "Data" + ], + "list": false, + "name": "data", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "other", + "value": "" + }, + "sep": { + "advanced": true, + "display_name": "Separator", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "sep", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "---" + }, + "template": { + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "{text}" + } + } + }, + "type": "ParseData" + }, + "dragging": false, + "height": 385, + "id": "ParseData-Z6n4v", + "position": { + "x": 1911.4866480237615, + "y": 566.903831987901 + }, + "positionAbsolute": { + "x": 1911.4866480237615, + "y": 566.903831987901 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-8YnFi", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "context", + "question" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "error": null, + "field_order": [ + "template" + ], + "frozen": false, + "full_path": null, + "icon": "prompts", + "is_composition": null, + "is_input": null, + "is_output": null, + "name": "", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "hidden": false, + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def post_code_processing(self, new_build_config: dict, current_build_config: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_build_config, current_build_config)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_build_config\n # and update the frontend_node with those values\n update_template_values(frontend_template=frontend_node, raw_template=current_build_config[\"template\"])\n return frontend_node\n" + }, + "context": { + "advanced": false, + "display_name": "context", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "context", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "question": { + "advanced": false, + "display_name": "question", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "question", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "template": { + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "prompt", + "value": "{context}\n\n---\n\nGiven the context above, answer the question as best as possible.\n\nQuestion: {question}\n\nAnswer: " + } + } + }, + "type": "Prompt" + }, + "dragging": false, + "height": 517, + "id": "Prompt-8YnFi", + "position": { + "x": 2537.8054430938064, + "y": 442.35183727527414 + }, + "positionAbsolute": { + "x": 2537.8054430938064, + "y": 442.35183727527414 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "id": "SplitText-bqtiX", + "node": { + "base_classes": [ + "Data" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Split text into chunks based on specified criteria.", + "display_name": "Split Text", + "documentation": "", + "edited": false, + "field_order": [ + "data_inputs", + "chunk_overlap", + "chunk_size", + "separator" + ], + "frozen": false, + "icon": "scissors-line-dashed", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Chunks", + "hidden": false, + "method": "split_text", + "name": "chunks", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "chunk_overlap": { + "advanced": false, + "display_name": "Chunk Overlap", + "dynamic": false, + "info": "Number of characters to overlap between chunks.", + "list": false, + "name": "chunk_overlap", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 200 + }, + "chunk_size": { + "advanced": false, + "display_name": "Chunk Size", + "dynamic": false, + "info": "The maximum number of characters in each chunk.", + "list": false, + "name": "chunk_size", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1000 + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from typing import List\n\nfrom langchain_text_splitters import CharacterTextSplitter\n\nfrom langflow.custom import Component\nfrom langflow.io import HandleInput, IntInput, MessageTextInput, Output\nfrom langflow.schema import Data\nfrom langflow.utils.util import unescape_string\n\n\nclass SplitTextComponent(Component):\n display_name: str = \"Split Text\"\n description: str = \"Split text into chunks based on specified criteria.\"\n icon = \"scissors-line-dashed\"\n\n inputs = [\n HandleInput(\n name=\"data_inputs\",\n display_name=\"Data Inputs\",\n info=\"The data to split.\",\n input_types=[\"Data\"],\n is_list=True,\n ),\n IntInput(\n name=\"chunk_overlap\",\n display_name=\"Chunk Overlap\",\n info=\"Number of characters to overlap between chunks.\",\n value=200,\n ),\n IntInput(\n name=\"chunk_size\",\n display_name=\"Chunk Size\",\n info=\"The maximum number of characters in each chunk.\",\n value=1000,\n ),\n MessageTextInput(\n name=\"separator\",\n display_name=\"Separator\",\n info=\"The character to split on. Defaults to newline.\",\n value=\"\\n\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Chunks\", name=\"chunks\", method=\"split_text\"),\n ]\n\n def _docs_to_data(self, docs):\n data = []\n for doc in docs:\n data.append(Data(text=doc.page_content, data=doc.metadata))\n return data\n\n def split_text(self) -> List[Data]:\n separator = unescape_string(self.separator)\n\n documents = []\n for _input in self.data_inputs:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n\n splitter = CharacterTextSplitter(\n chunk_overlap=self.chunk_overlap,\n chunk_size=self.chunk_size,\n separator=separator,\n )\n docs = splitter.split_documents(documents)\n data = self._docs_to_data(docs)\n self.status = data\n return data\n" + }, + "data_inputs": { + "advanced": false, + "display_name": "Data Inputs", + "dynamic": false, + "info": "The data to split.", + "input_types": [ + "Data" + ], + "list": true, + "name": "data_inputs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "separator": { + "advanced": false, + "display_name": "Separator", + "dynamic": false, + "info": "The character to split on. Defaults to newline.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "separator", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "\n" + } + } + }, + "type": "SplitText" + }, + "dragging": false, + "height": 557, + "id": "SplitText-bqtiX", + "position": { + "x": 21.318397393309283, + "y": 273.27771123167287 + }, + "positionAbsolute": { + "x": 21.318397393309283, + "y": 273.27771123167287 + }, + "selected": false, + "type": "genericNode", + "width": 384 + } + ], + "viewport": { + "x": 194.05113865007206, + "y": 162.32064169887877, + "zoom": 0.2522219260543123 + } + }, + "description": "Visit https://docs.langflow.org/tutorials/rag-with-astradb for a detailed guide of this project.\nThis project give you both Ingestion and RAG in a single file. You'll need to visit https://astra.datastax.com/ to create an Astra DB instance, your Token and grab an API Endpoint.\nRunning this project requires you to add a file in the Files component, then define a Collection Name and click on the Play icon on the Astra DB component. \n\nAfter the ingestion ends you are ready to click on the Run button at the lower left corner and start asking questions about your data.", + "endpoint_name": null, + "id": "0e6c631a-1975-417b-a3f7-c23f97dbf0c7", + "is_component": false, + "last_tested_version": "1.0.0rc1", + "name": "Vector Store RAG" +} \ No newline at end of file From 4cc7ae1f2a2e3883a5715aa174268abe6ac7887a Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Mon, 24 Jun 2024 09:20:49 -0300 Subject: [PATCH 076/229] Fixed starter examples --- .../Basic Prompting (Hello World).json | 875 ------------- .../Basic Prompting (Hello, World).json | 1 + .../starter_projects/Memory Chatbot.json | 1120 +---------------- 3 files changed, 2 insertions(+), 1994 deletions(-) delete mode 100644 src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello World).json create mode 100644 src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello World).json b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello World).json deleted file mode 100644 index 592fe50d8..000000000 --- a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello World).json +++ /dev/null @@ -1,875 +0,0 @@ -{ - "data": { - "edges": [ - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "ChatInput", - "id": "ChatInput-8QeBH", - "name": "message", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "user_input", - "id": "Prompt-GAmYb", - "inputTypes": [ - "Message", - "Text" - ], - "type": "str" - } - }, - "id": "reactflow__edge-ChatInput-8QeBH{œdataTypeœ:œChatInputœ,œidœ:œChatInput-8QeBHœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-GAmYb{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-GAmYbœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ChatInput-8QeBH", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-8QeBHœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-GAmYb", - "targetHandle": "{œfieldNameœ: œuser_inputœ, œidœ: œPrompt-GAmYbœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "Prompt", - "id": "Prompt-GAmYb", - "name": "prompt", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "OpenAIModel-aN26e", - "inputTypes": [ - "Message" - ], - "type": "str" - } - }, - "id": "reactflow__edge-Prompt-GAmYb{œdataTypeœ:œPromptœ,œidœ:œPrompt-GAmYbœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-aN26e{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-aN26eœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-GAmYb", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-GAmYbœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-aN26e", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-aN26eœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "OpenAIModel", - "id": "OpenAIModel-aN26e", - "name": "text_output", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "ChatOutput-wokdr", - "inputTypes": [ - "Message" - ], - "type": "str" - } - }, - "id": "reactflow__edge-OpenAIModel-aN26e{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-aN26eœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-wokdr{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-wokdrœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-aN26e", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-aN26eœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-wokdr", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-wokdrœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" - } - ], - "nodes": [ - { - "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "edited": false, - "id": "Prompt-GAmYb", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": { - "template": [ - "user_input" - ] - }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "documentation": "", - "edited": true, - "field_order": [ - "template" - ], - "frozen": false, - "icon": "prompts", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Prompt Message", - "hidden": false, - "method": "build_prompt", - "name": "prompt", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def post_code_processing(self, new_build_config: dict, current_build_config: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_build_config, current_build_config)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_build_config\n # and update the frontend_node with those values\n update_template_values(frontend_template=frontend_node, raw_template=current_build_config[\"template\"])\n return frontend_node\n" - }, - "template": { - "advanced": false, - "display_name": "Template", - "dynamic": false, - "info": "", - "list": false, - "name": "template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "prompt", - "value": "Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: " - }, - "user_input": { - "advanced": false, - "display_name": "user_input", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "user_input", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - } - } - }, - "type": "Prompt" - }, - "dragging": false, - "height": 422, - "id": "Prompt-GAmYb", - "position": { - "x": 43.70859256635981, - "y": 1115.5304359666682 - }, - "positionAbsolute": { - "x": 43.70859256635981, - "y": 1115.5304359666682 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Get chat inputs from the Playground.", - "display_name": "Chat Input", - "edited": false, - "id": "ChatInput-8QeBH", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Get chat inputs from the Playground.", - "display_name": "Chat Input", - "documentation": "", - "edited": true, - "field_order": [ - "input_value", - "sender", - "sender_name", - "session_id", - "files" - ], - "frozen": false, - "icon": "ChatInput", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "hidden": false, - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MultilineInput, Output, TextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n TextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n TextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" - }, - "files": { - "advanced": true, - "display_name": "Files", - "dynamic": false, - "fileTypes": [ - "txt", - "md", - "mdx", - "csv", - "json", - "yaml", - "yml", - "xml", - "html", - "htm", - "pdf", - "docx", - "py", - "sh", - "sql", - "js", - "ts", - "tsx", - "jpg", - "jpeg", - "png", - "bmp", - "image" - ], - "file_path": "", - "info": "Files to be sent with the message.", - "list": true, - "name": "files", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "file", - "value": "" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "info": "Message to be passed as input.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "info": "Type of sender.", - "name": "sender", - "options": [ - "Machine", - "User" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "User" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "info": "Name of the sender.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "sender_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "User" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "info": "Session ID for the message.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "session_id", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - } - } - }, - "type": "ChatInput" - }, - "dragging": false, - "height": 308, - "id": "ChatInput-8QeBH", - "position": { - "x": -521.3324537445985, - "y": 1089.7620993695407 - }, - "positionAbsolute": { - "x": -521.3324537445985, - "y": 1089.7620993695407 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "edited": false, - "id": "OpenAIModel-aN26e", - "node": { - "base_classes": [ - "LanguageModel", - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "documentation": "", - "edited": true, - "field_order": [ - "input_value", - "max_tokens", - "model_kwargs", - "output_schema", - "model_name", - "openai_api_base", - "openai_api_key", - "temperature", - "stream", - "system_message", - "seed" - ], - "frozen": false, - "icon": "OpenAI", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "hidden": false, - "method": "text_response", - "name": "text_output", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "max_tokens": { - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "list": false, - "name": "max_tokens", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": "" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "model_name": { - "advanced": false, - "display_name": "Model Name", - "dynamic": false, - "info": "", - "name": "model_name", - "options": [ - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "gpt-4o" - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "list": false, - "load_from_db": false, - "name": "openai_api_base", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "openai_api_key": { - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [], - "load_from_db": false, - "name": "openai_api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "output_schema": { - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "dict", - "value": {} - }, - "seed": { - "advanced": true, - "display_name": "Seed", - "dynamic": false, - "info": "The seed controls the reproducibility of the job.", - "list": false, - "name": "seed", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 1 - }, - "stream": { - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "list": false, - "name": "stream", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "bool", - "value": false - }, - "system_message": { - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "info": "System message to pass to the model.", - "list": false, - "load_from_db": false, - "name": "system_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "temperature": { - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "info": "", - "list": false, - "name": "temperature", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "float", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 621, - "id": "OpenAIModel-aN26e", - "position": { - "x": 584.9288140250019, - "y": 1149.0790574268922 - }, - "positionAbsolute": { - "x": 584.9288140250019, - "y": 1149.0790574268922 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "edited": false, - "id": "ChatOutput-wokdr", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "documentation": "", - "edited": true, - "field_order": [ - "input_value", - "sender", - "sender_name", - "session_id", - "data_template" - ], - "frozen": false, - "icon": "ChatOutput", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, Output, TextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n TextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n TextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n TextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n TextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" - }, - "data_template": { - "advanced": true, - "display_name": "Data Template", - "dynamic": false, - "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "data_template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "{text}" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "info": "Message to be passed as output.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "info": "Type of sender.", - "name": "sender", - "options": [ - "Machine", - "User" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "Machine" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "info": "Name of the sender.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "sender_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "AI" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "info": "Session ID for the message.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "session_id", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - } - } - }, - "type": "ChatOutput" - }, - "dragging": false, - "height": 308, - "id": "ChatOutput-wokdr", - "position": { - "x": 1157.3374592784412, - "y": 1160.9424490383622 - }, - "positionAbsolute": { - "x": 1157.3374592784412, - "y": 1160.9424490383622 - }, - "selected": false, - "type": "genericNode", - "width": 384 - } - ], - "viewport": { - "x": 353.0590737990465, - "y": -407.76221076623995, - "zoom": 0.5467255436493648 - } - }, - "description": "This flow will get you experimenting with the basics of the UI, the Chat and the Prompt component. \n\nTry changing the Template in it to see how the model behaves. \nYou can change it to this and a Text Input into the `type_of_person` variable : \"Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: \" ", - "endpoint_name": null, - "id": "d646c486-746c-402f-a94a-a03eb2f7941c", - "is_component": false, - "last_tested_version": "1.0.0rc1", - "name": "Basic Prompting (Hello World)" -} \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json new file mode 100644 index 000000000..0813fef0a --- /dev/null +++ b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json @@ -0,0 +1 @@ +{"id":"81759149-1e58-4190-b4a4-48a96cf49734","data":{"nodes":[{"data":{"description":"Create a prompt template with dynamic variables.","display_name":"Prompt","edited":false,"id":"Prompt-fpHnR","node":{"base_classes":["Message"],"beta":false,"conditional_paths":[],"custom_fields":{"template":["user_input"]},"description":"Create a prompt template with dynamic variables.","display_name":"Prompt","documentation":"","edited":true,"field_order":["template"],"frozen":false,"icon":"prompts","output_types":[],"outputs":[{"cache":true,"display_name":"Prompt Message","hidden":false,"method":"build_prompt","name":"prompt","selected":"Message","types":["Message"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def post_code_processing(self, new_build_config: dict, current_build_config: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_build_config, current_build_config)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_build_config\n # and update the frontend_node with those values\n update_template_values(frontend_template=frontend_node, raw_template=current_build_config[\"template\"])\n return frontend_node\n"},"template":{"advanced":false,"display_name":"Template","dynamic":false,"info":"","list":false,"name":"template","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"type":"prompt","value":"Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: "},"user_input":{"advanced":false,"display_name":"user_input","dynamic":false,"field_type":"str","fileTypes":[],"file_path":"","info":"","input_types":["Message","Text"],"list":false,"load_from_db":false,"multiline":true,"name":"user_input","password":false,"placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""}}},"type":"Prompt"},"dragging":false,"height":422,"id":"Prompt-fpHnR","position":{"x":43.70859256635981,"y":1115.5304359666682},"positionAbsolute":{"x":43.70859256635981,"y":1115.5304359666682},"selected":false,"type":"genericNode","width":384},{"data":{"description":"Get chat inputs from the Playground.","display_name":"Chat Input","edited":false,"id":"ChatInput-74jnA","node":{"base_classes":["Message"],"beta":false,"conditional_paths":[],"custom_fields":{},"description":"Get chat inputs from the Playground.","display_name":"Chat Input","documentation":"","edited":true,"field_order":["input_value","sender","sender_name","session_id","files"],"frozen":false,"icon":"ChatInput","output_types":[],"outputs":[{"cache":true,"display_name":"Message","hidden":false,"method":"message_response","name":"message","selected":"Message","types":["Message"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MultilineInput, Output, TextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n TextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n TextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n"},"files":{"advanced":true,"display_name":"Files","dynamic":false,"fileTypes":["txt","md","mdx","csv","json","yaml","yml","xml","html","htm","pdf","docx","py","sh","sql","js","ts","tsx","jpg","jpeg","png","bmp","image"],"file_path":"","info":"Files to be sent with the message.","list":true,"name":"files","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"file","value":""},"input_value":{"advanced":false,"display_name":"Text","dynamic":false,"info":"Message to be passed as input.","input_types":["Message"],"list":false,"load_from_db":false,"multiline":true,"name":"input_value","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":""},"sender":{"advanced":true,"display_name":"Sender Type","dynamic":false,"info":"Type of sender.","name":"sender","options":["Machine","User"],"placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"str","value":"User"},"sender_name":{"advanced":true,"display_name":"Sender Name","dynamic":false,"info":"Name of the sender.","input_types":["Message"],"list":false,"load_from_db":false,"name":"sender_name","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":"User"},"session_id":{"advanced":true,"display_name":"Session ID","dynamic":false,"info":"Session ID for the message.","input_types":["Message"],"list":false,"load_from_db":false,"name":"session_id","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":""}}},"type":"ChatInput"},"dragging":false,"height":308,"id":"ChatInput-74jnA","position":{"x":-521.3324537445985,"y":1089.7620993695407},"positionAbsolute":{"x":-521.3324537445985,"y":1089.7620993695407},"selected":false,"type":"genericNode","width":384},{"data":{"description":"Generates text using OpenAI LLMs.","display_name":"OpenAI","edited":false,"id":"OpenAIModel-ehSar","node":{"base_classes":["LanguageModel","Message"],"beta":false,"conditional_paths":[],"custom_fields":{},"description":"Generates text using OpenAI LLMs.","display_name":"OpenAI","documentation":"","edited":true,"field_order":["input_value","max_tokens","model_kwargs","output_schema","model_name","openai_api_base","openai_api_key","temperature","stream","system_message","seed"],"frozen":false,"icon":"OpenAI","output_types":[],"outputs":[{"cache":true,"display_name":"Text","hidden":false,"method":"text_response","name":"text_output","selected":"Message","types":["Message"],"value":"__UNDEFINED__"},{"cache":true,"display_name":"Language Model","method":"build_model","name":"model_output","selected":"LanguageModel","types":["LanguageModel"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n"},"input_value":{"advanced":false,"display_name":"Input","dynamic":false,"info":"","input_types":["Message"],"list":false,"load_from_db":false,"name":"input_value","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":""},"max_tokens":{"advanced":true,"display_name":"Max Tokens","dynamic":false,"info":"The maximum number of tokens to generate. Set to 0 for unlimited tokens.","list":false,"name":"max_tokens","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"int","value":""},"model_kwargs":{"advanced":true,"display_name":"Model Kwargs","dynamic":false,"info":"","list":false,"name":"model_kwargs","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"type":"dict","value":{}},"model_name":{"advanced":false,"display_name":"Model Name","dynamic":false,"info":"","name":"model_name","options":["gpt-4o","gpt-4-turbo","gpt-4-turbo-preview","gpt-3.5-turbo","gpt-3.5-turbo-0125"],"placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"str","value":"gpt-3.5-turbo"},"openai_api_base":{"advanced":true,"display_name":"OpenAI API Base","dynamic":false,"info":"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.","list":false,"load_from_db":false,"name":"openai_api_base","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"str","value":""},"openai_api_key":{"advanced":false,"display_name":"OpenAI API Key","dynamic":false,"info":"The OpenAI API Key to use for the OpenAI model.","input_types":[],"load_from_db":false,"name":"openai_api_key","password":true,"placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""},"output_schema":{"advanced":true,"display_name":"Schema","dynamic":false,"info":"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.","list":true,"name":"output_schema","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"type":"dict","value":{}},"seed":{"advanced":true,"display_name":"Seed","dynamic":false,"info":"The seed controls the reproducibility of the job.","list":false,"name":"seed","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"int","value":1},"stream":{"advanced":true,"display_name":"Stream","dynamic":false,"info":"Stream the response from the model. Streaming works only in Chat.","list":false,"name":"stream","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"bool","value":false},"system_message":{"advanced":true,"display_name":"System Message","dynamic":false,"info":"System message to pass to the model.","list":false,"load_from_db":false,"name":"system_message","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"str","value":""},"temperature":{"advanced":false,"display_name":"Temperature","dynamic":false,"info":"","list":false,"name":"temperature","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"float","value":0.1}}},"type":"OpenAIModel"},"dragging":false,"height":621,"id":"OpenAIModel-ehSar","position":{"x":584.9288140250019,"y":1149.0790574268922},"positionAbsolute":{"x":584.9288140250019,"y":1149.0790574268922},"selected":false,"type":"genericNode","width":384},{"data":{"description":"Display a chat message in the Playground.","display_name":"Chat Output","edited":false,"id":"ChatOutput-KLLro","node":{"base_classes":["Message"],"beta":false,"conditional_paths":[],"custom_fields":{},"description":"Display a chat message in the Playground.","display_name":"Chat Output","documentation":"","edited":true,"field_order":["input_value","sender","sender_name","session_id","data_template"],"frozen":false,"icon":"ChatOutput","output_types":[],"outputs":[{"cache":true,"display_name":"Message","method":"message_response","name":"message","selected":"Message","types":["Message"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, Output, TextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n TextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n TextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n TextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n TextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n"},"data_template":{"advanced":true,"display_name":"Data Template","dynamic":false,"info":"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.","input_types":["Message"],"list":false,"load_from_db":false,"name":"data_template","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":"{text}"},"input_value":{"advanced":false,"display_name":"Text","dynamic":false,"info":"Message to be passed as output.","input_types":["Message"],"list":false,"load_from_db":false,"name":"input_value","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":""},"sender":{"advanced":true,"display_name":"Sender Type","dynamic":false,"info":"Type of sender.","name":"sender","options":["Machine","User"],"placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"str","value":"Machine"},"sender_name":{"advanced":true,"display_name":"Sender Name","dynamic":false,"info":"Name of the sender.","input_types":["Message"],"list":false,"load_from_db":false,"name":"sender_name","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":"AI"},"session_id":{"advanced":true,"display_name":"Session ID","dynamic":false,"info":"Session ID for the message.","input_types":["Message"],"list":false,"load_from_db":false,"name":"session_id","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":""}}},"type":"ChatOutput"},"dragging":false,"height":308,"id":"ChatOutput-KLLro","position":{"x":1157.3374592784412,"y":1160.9424490383622},"positionAbsolute":{"x":1157.3374592784412,"y":1160.9424490383622},"selected":false,"type":"genericNode","width":384}],"edges":[{"className":"","data":{"sourceHandle":{"dataType":"ChatInput","id":"ChatInput-74jnA","name":"message","output_types":["Message"]},"targetHandle":{"fieldName":"user_input","id":"Prompt-fpHnR","inputTypes":["Message","Text"],"type":"str"}},"id":"reactflow__edge-ChatInput-74jnA{œdataTypeœ:œChatInputœ,œidœ:œChatInput-74jnAœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-fpHnR{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-fpHnRœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}","source":"ChatInput-74jnA","sourceHandle":"{œdataTypeœ:œChatInputœ,œidœ:œChatInput-74jnAœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}","target":"Prompt-fpHnR","targetHandle":"{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-fpHnRœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}"},{"className":"","data":{"sourceHandle":{"dataType":"Prompt","id":"Prompt-fpHnR","name":"prompt","output_types":["Message"]},"targetHandle":{"fieldName":"input_value","id":"OpenAIModel-ehSar","inputTypes":["Message"],"type":"str"}},"id":"reactflow__edge-Prompt-fpHnR{œdataTypeœ:œPromptœ,œidœ:œPrompt-fpHnRœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-ehSar{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-ehSarœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}","source":"Prompt-fpHnR","sourceHandle":"{œdataTypeœ:œPromptœ,œidœ:œPrompt-fpHnRœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}","target":"OpenAIModel-ehSar","targetHandle":"{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-ehSarœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}"},{"className":"","data":{"sourceHandle":{"dataType":"OpenAIModel","id":"OpenAIModel-ehSar","name":"text_output","output_types":["Message"]},"targetHandle":{"fieldName":"input_value","id":"ChatOutput-KLLro","inputTypes":["Message"],"type":"str"}},"id":"reactflow__edge-OpenAIModel-ehSar{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-ehSarœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-KLLro{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-KLLroœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}","source":"OpenAIModel-ehSar","sourceHandle":"{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-ehSarœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}","target":"ChatOutput-KLLro","targetHandle":"{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-KLLroœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}"}],"viewport":{"x":353.0590737990465,"y":-407.76221076623995,"zoom":0.5467255436493648}},"description":"This flow will get you experimenting with the basics of the UI, the Chat and the Prompt component. \n\nTry changing the Template in it to see how the model behaves. \nYou can change it to this and a Text Input into the `type_of_person` variable : \"Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: \" ","name":"Basic Prompting (Hello, World)","last_tested_version":"1.0.0rc1","endpoint_name":null,"is_component":false} \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json b/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json index 354f0810b..4d99b40c5 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json @@ -1,1119 +1 @@ -{ - "data": { - "edges": [ - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "Memory", - "id": "Memory-Bn93i", - "name": "messages_text", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "context", - "id": "Prompt-4IgSW", - "inputTypes": [ - "Message", - "Text" - ], - "type": "str" - } - }, - "id": "reactflow__edge-Memory-Bn93i{œdataTypeœ:œMemoryœ,œidœ:œMemory-Bn93iœ,œnameœ:œmessages_textœ,œoutput_typesœ:[œMessageœ]}-Prompt-4IgSW{œfieldNameœ:œcontextœ,œidœ:œPrompt-4IgSWœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "Memory-Bn93i", - "sourceHandle": "{œdataTypeœ: œMemoryœ, œidœ: œMemory-Bn93iœ, œnameœ: œmessages_textœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-4IgSW", - "targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-4IgSWœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "ChatInput", - "id": "ChatInput-ZV9JL", - "name": "message", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "user_message", - "id": "Prompt-4IgSW", - "inputTypes": [ - "Message", - "Text" - ], - "type": "str" - } - }, - "id": "reactflow__edge-ChatInput-ZV9JL{œdataTypeœ:œChatInputœ,œidœ:œChatInput-ZV9JLœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-4IgSW{œfieldNameœ:œuser_messageœ,œidœ:œPrompt-4IgSWœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ChatInput-ZV9JL", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-ZV9JLœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-4IgSW", - "targetHandle": "{œfieldNameœ: œuser_messageœ, œidœ: œPrompt-4IgSWœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "Prompt", - "id": "Prompt-4IgSW", - "name": "prompt", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "OpenAIModel-iT10n", - "inputTypes": [ - "Message" - ], - "type": "str" - } - }, - "id": "reactflow__edge-Prompt-4IgSW{œdataTypeœ:œPromptœ,œidœ:œPrompt-4IgSWœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-iT10n{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-iT10nœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-4IgSW", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-4IgSWœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-iT10n", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-iT10nœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "OpenAIModel", - "id": "OpenAIModel-iT10n", - "name": "text_output", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "ChatOutput-Xi4hp", - "inputTypes": [ - "Message" - ], - "type": "str" - } - }, - "id": "reactflow__edge-OpenAIModel-iT10n{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-iT10nœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-Xi4hp{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-Xi4hpœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-iT10n", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-iT10nœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-Xi4hp", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-Xi4hpœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" - } - ], - "nodes": [ - { - "data": { - "description": "Retrieves stored chat messages.", - "display_name": "Memory", - "edited": false, - "id": "Memory-Bn93i", - "node": { - "base_classes": [ - "Data", - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Retrieves stored chat messages.", - "display_name": "Memory", - "documentation": "", - "edited": true, - "field_order": [ - "sender", - "sender_name", - "n_messages", - "session_id", - "order", - "template" - ], - "frozen": false, - "icon": "message-square-more", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Chat History", - "method": "retrieve_messages", - "name": "messages", - "selected": "Data", - "types": [ - "Data" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Messages (Text)", - "hidden": false, - "method": "retrieve_messages_as_text", - "name": "messages_text", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import DropdownInput, IntInput, MultilineInput, Output, MessageTextInput\nfrom langflow.memory import get_messages\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass MemoryComponent(Component):\n display_name = \"Chat Memory\"\n description = \"Retrieves stored chat messages.\"\n icon = \"message-square-more\"\n\n inputs = [\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\", \"Machine and User\"],\n value=\"Machine and User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n advanced=True,\n ),\n IntInput(\n name=\"n_messages\",\n display_name=\"Number of Messages\",\n value=100,\n info=\"Number of messages to retrieve.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"Session ID of the chat history.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"order\",\n display_name=\"Order\",\n options=[\"Ascending\", \"Descending\"],\n value=\"Ascending\",\n info=\"Order of the messages.\",\n advanced=True,\n ),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.\",\n value=\"{sender_name}: {text}\",\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Chat History\", name=\"messages\", method=\"retrieve_messages\"),\n Output(display_name=\"Messages (Text)\", name=\"messages_text\", method=\"retrieve_messages_as_text\"),\n ]\n\n def retrieve_messages(self) -> Data:\n sender = self.sender\n sender_name = self.sender_name\n session_id = self.session_id\n n_messages = self.n_messages\n order = \"DESC\" if self.order == \"Descending\" else \"ASC\"\n\n if sender == \"Machine and User\":\n sender = None\n\n messages = get_messages(\n sender=sender,\n sender_name=sender_name,\n session_id=session_id,\n limit=n_messages,\n order=order,\n )\n self.status = messages\n return messages\n\n def retrieve_messages_as_text(self) -> Message:\n messages_text = data_to_text(self.template, self.retrieve_messages())\n self.status = messages_text\n return Message(text=messages_text)\n" - }, - "n_messages": { - "advanced": true, - "display_name": "Number of Messages", - "dynamic": false, - "info": "Number of messages to retrieve.", - "list": false, - "name": "n_messages", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": 100 - }, - "order": { - "advanced": true, - "display_name": "Order", - "dynamic": false, - "info": "Order of the messages.", - "name": "order", - "options": [ - "Ascending", - "Descending" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "Ascending" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "info": "Type of sender.", - "name": "sender", - "options": [ - "Machine", - "User", - "Machine and User" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "Machine and User" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "info": "Name of the sender.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "sender_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "info": "Session ID of the chat history.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "session_id", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "template": { - "advanced": true, - "display_name": "Template", - "dynamic": false, - "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "{sender_name}: {text}" - } - } - }, - "type": "Memory" - }, - "dragging": false, - "height": 267, - "id": "Memory-Bn93i", - "position": { - "x": 1258.8089948698466, - "y": 547.1243849102437 - }, - "positionAbsolute": { - "x": 1258.8089948698466, - "y": 547.1243849102437 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Get chat inputs from the Playground.", - "display_name": "Chat Input", - "edited": false, - "id": "ChatInput-ZV9JL", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Get chat inputs from the Playground.", - "display_name": "Chat Input", - "documentation": "", - "edited": true, - "field_order": [ - "input_value", - "sender", - "sender_name", - "session_id", - "files" - ], - "frozen": false, - "icon": "ChatInput", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "hidden": false, - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" - }, - "files": { - "advanced": true, - "display_name": "Files", - "dynamic": false, - "fileTypes": [ - "txt", - "md", - "mdx", - "csv", - "json", - "yaml", - "yml", - "xml", - "html", - "htm", - "pdf", - "docx", - "py", - "sh", - "sql", - "js", - "ts", - "tsx", - "jpg", - "jpeg", - "png", - "bmp", - "image" - ], - "file_path": "", - "info": "Files to be sent with the message.", - "list": true, - "name": "files", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "file", - "value": "" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "info": "Message to be passed as input.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "info": "Type of sender.", - "name": "sender", - "options": [ - "Machine", - "User" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "User" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "info": "Name of the sender.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "sender_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "User" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "info": "Session ID for the message.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "session_id", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - } - } - }, - "type": "ChatInput" - }, - "dragging": true, - "height": 309, - "id": "ChatInput-ZV9JL", - "position": { - "x": 1261.3748612945249, - "y": 912.733279525042 - }, - "positionAbsolute": { - "x": 1261.3748612945249, - "y": 912.733279525042 - }, - "selected": true, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "edited": false, - "id": "OpenAIModel-iT10n", - "node": { - "base_classes": [ - "LanguageModel", - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "documentation": "", - "edited": true, - "field_order": [ - "input_value", - "max_tokens", - "model_kwargs", - "output_schema", - "model_name", - "openai_api_base", - "openai_api_key", - "temperature", - "stream", - "system_message", - "seed" - ], - "frozen": false, - "icon": "OpenAI", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "hidden": false, - "method": "text_response", - "name": "text_output", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "max_tokens": { - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "list": false, - "name": "max_tokens", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": "" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "dict", - "value": {} - }, - "model_name": { - "advanced": false, - "display_name": "Model Name", - "dynamic": false, - "info": "", - "name": "model_name", - "options": [ - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "gpt-4-turbo" - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "list": false, - "load_from_db": false, - "name": "openai_api_base", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_api_key": { - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [], - "load_from_db": false, - "name": "openai_api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "output_schema": { - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "dict", - "value": {} - }, - "seed": { - "advanced": true, - "display_name": "Seed", - "dynamic": false, - "info": "The seed controls the reproducibility of the job.", - "list": false, - "name": "seed", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": 1 - }, - "stream": { - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "list": false, - "name": "stream", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "bool", - "value": false - }, - "system_message": { - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "info": "System message to pass to the model.", - "list": false, - "load_from_db": false, - "name": "system_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "temperature": { - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "info": "", - "list": false, - "name": "temperature", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "float", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 622, - "id": "OpenAIModel-iT10n", - "position": { - "x": 2495.6628431453228, - "y": 669.9567653609598 - }, - "positionAbsolute": { - "x": 2495.6628431453228, - "y": 669.9567653609598 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "edited": false, - "id": "ChatOutput-Xi4hp", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "documentation": "", - "edited": true, - "field_order": [ - "input_value", - "sender", - "sender_name", - "session_id", - "data_template" - ], - "frozen": false, - "icon": "ChatOutput", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" - }, - "data_template": { - "advanced": true, - "display_name": "Data Template", - "dynamic": false, - "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "data_template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "{text}" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "info": "Message to be passed as output.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "info": "Type of sender.", - "name": "sender", - "options": [ - "Machine", - "User" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "Machine" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "info": "Name of the sender.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "sender_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "AI" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "info": "Session ID for the message.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "session_id", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - } - } - }, - "type": "ChatOutput" - }, - "dragging": false, - "height": 308, - "id": "ChatOutput-Xi4hp", - "position": { - "x": 3028.2686266398873, - "y": 888.0854888768531 - }, - "positionAbsolute": { - "x": 3028.2686266398873, - "y": 888.0854888768531 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "id": "Prompt-4IgSW", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": { - "template": [ - "context", - "user_message" - ] - }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "documentation": "", - "edited": false, - "error": null, - "field_order": [ - "template" - ], - "frozen": false, - "full_path": null, - "icon": "prompts", - "is_composition": null, - "is_input": null, - "is_output": null, - "name": "", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Prompt Message", - "hidden": false, - "method": "build_prompt", - "name": "prompt", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def post_code_processing(self, new_build_config: dict, current_build_config: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_build_config, current_build_config)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_build_config\n # and update the frontend_node with those values\n update_template_values(frontend_template=frontend_node, raw_template=current_build_config[\"template\"])\n return frontend_node\n" - }, - "context": { - "advanced": false, - "display_name": "context", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "context", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "template": { - "advanced": false, - "display_name": "Template", - "dynamic": false, - "info": "", - "list": false, - "name": "template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "prompt", - "value": "{context}\n\nUser: {user_message}\nAI: " - }, - "user_message": { - "advanced": false, - "display_name": "user_message", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "user_message", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - } - } - }, - "type": "Prompt" - }, - "dragging": false, - "height": 517, - "id": "Prompt-4IgSW", - "position": { - "x": 1879.4280156201567, - "y": 674.3958274263156 - }, - "positionAbsolute": { - "x": 1879.4280156201567, - "y": 674.3958274263156 - }, - "selected": false, - "type": "genericNode", - "width": 384 - } - ], - "viewport": { - "x": -592.532107710133, - "y": -149.32118023592653, - "zoom": 0.5372819347267049 - } - }, - "description": "This project can be used as a starting point for building a Chat experience with user specific memory. You can set a different Session ID to start a new message history.", - "endpoint_name": null, - "id": "fce26e32-fb38-4a46-b2bf-0ae0f61a2c5d", - "is_component": false, - "last_tested_version": "1.0.0rc1", - "name": "Memory Chatbot" -} \ No newline at end of file +{"id":"b4832b74-d12c-4c00-94e9-4d873abf56eb","data":{"nodes":[{"data":{"description":"Retrieves stored chat messages.","display_name":"Memory","edited":false,"id":"Memory-Kt0An","node":{"base_classes":["Data","Message"],"beta":false,"conditional_paths":[],"custom_fields":{},"description":"Retrieves stored chat messages.","display_name":"Memory","documentation":"","edited":true,"field_order":["sender","sender_name","n_messages","session_id","order","template"],"frozen":false,"icon":"message-square-more","output_types":[],"outputs":[{"cache":true,"display_name":"Chat History","method":"retrieve_messages","name":"messages","selected":"Data","types":["Data"],"value":"__UNDEFINED__"},{"cache":true,"display_name":"Messages (Text)","hidden":false,"method":"retrieve_messages_as_text","name":"messages_text","selected":"Message","types":["Message"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import DropdownInput, IntInput, MultilineInput, Output, MessageTextInput\nfrom langflow.memory import get_messages\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass MemoryComponent(Component):\n display_name = \"Chat Memory\"\n description = \"Retrieves stored chat messages.\"\n icon = \"message-square-more\"\n\n inputs = [\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\", \"Machine and User\"],\n value=\"Machine and User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n advanced=True,\n ),\n IntInput(\n name=\"n_messages\",\n display_name=\"Number of Messages\",\n value=100,\n info=\"Number of messages to retrieve.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"Session ID of the chat history.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"order\",\n display_name=\"Order\",\n options=[\"Ascending\", \"Descending\"],\n value=\"Ascending\",\n info=\"Order of the messages.\",\n advanced=True,\n ),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.\",\n value=\"{sender_name}: {text}\",\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Chat History\", name=\"messages\", method=\"retrieve_messages\"),\n Output(display_name=\"Messages (Text)\", name=\"messages_text\", method=\"retrieve_messages_as_text\"),\n ]\n\n def retrieve_messages(self) -> Data:\n sender = self.sender\n sender_name = self.sender_name\n session_id = self.session_id\n n_messages = self.n_messages\n order = \"DESC\" if self.order == \"Descending\" else \"ASC\"\n\n if sender == \"Machine and User\":\n sender = None\n\n messages = get_messages(\n sender=sender,\n sender_name=sender_name,\n session_id=session_id,\n limit=n_messages,\n order=order,\n )\n self.status = messages\n return messages\n\n def retrieve_messages_as_text(self) -> Message:\n messages_text = data_to_text(self.template, self.retrieve_messages())\n self.status = messages_text\n return Message(text=messages_text)\n"},"n_messages":{"advanced":true,"display_name":"Number of Messages","dynamic":false,"info":"Number of messages to retrieve.","list":false,"name":"n_messages","placeholder":"","required":false,"show":true,"title_case":false,"type":"int","value":100},"order":{"advanced":true,"display_name":"Order","dynamic":false,"info":"Order of the messages.","name":"order","options":["Ascending","Descending"],"placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":"Ascending"},"sender":{"advanced":true,"display_name":"Sender Type","dynamic":false,"info":"Type of sender.","name":"sender","options":["Machine","User","Machine and User"],"placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":"Machine and User"},"sender_name":{"advanced":true,"display_name":"Sender Name","dynamic":false,"info":"Name of the sender.","input_types":["Message"],"list":false,"load_from_db":false,"name":"sender_name","placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""},"session_id":{"advanced":true,"display_name":"Session ID","dynamic":false,"info":"Session ID of the chat history.","input_types":["Message"],"list":false,"load_from_db":false,"name":"session_id","placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""},"template":{"advanced":true,"display_name":"Template","dynamic":false,"info":"The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.","input_types":["Message"],"list":false,"load_from_db":false,"multiline":true,"name":"template","placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":"{sender_name}: {text}"}}},"type":"Memory"},"dragging":false,"height":267,"id":"Memory-Kt0An","position":{"x":1258.8089948698466,"y":547.1243849102437},"positionAbsolute":{"x":1258.8089948698466,"y":547.1243849102437},"selected":false,"type":"genericNode","width":384},{"data":{"description":"Get chat inputs from the Playground.","display_name":"Chat Input","edited":false,"id":"ChatInput-krw2d","node":{"base_classes":["Message"],"beta":false,"conditional_paths":[],"custom_fields":{},"description":"Get chat inputs from the Playground.","display_name":"Chat Input","documentation":"","edited":true,"field_order":["input_value","sender","sender_name","session_id","files"],"frozen":false,"icon":"ChatInput","output_types":[],"outputs":[{"cache":true,"display_name":"Message","hidden":false,"method":"message_response","name":"message","selected":"Message","types":["Message"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n"},"files":{"advanced":true,"display_name":"Files","dynamic":false,"fileTypes":["txt","md","mdx","csv","json","yaml","yml","xml","html","htm","pdf","docx","py","sh","sql","js","ts","tsx","jpg","jpeg","png","bmp","image"],"file_path":"","info":"Files to be sent with the message.","list":true,"name":"files","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"file","value":""},"input_value":{"advanced":false,"display_name":"Text","dynamic":false,"info":"Message to be passed as input.","input_types":["Message"],"list":false,"load_from_db":false,"multiline":true,"name":"input_value","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":""},"sender":{"advanced":true,"display_name":"Sender Type","dynamic":false,"info":"Type of sender.","name":"sender","options":["Machine","User"],"placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"str","value":"User"},"sender_name":{"advanced":true,"display_name":"Sender Name","dynamic":false,"info":"Name of the sender.","input_types":["Message"],"list":false,"load_from_db":false,"name":"sender_name","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":"User"},"session_id":{"advanced":true,"display_name":"Session ID","dynamic":false,"info":"Session ID for the message.","input_types":["Message"],"list":false,"load_from_db":false,"name":"session_id","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":""}}},"type":"ChatInput"},"dragging":true,"height":309,"id":"ChatInput-krw2d","position":{"x":1261.3748612945249,"y":912.733279525042},"positionAbsolute":{"x":1261.3748612945249,"y":912.733279525042},"selected":true,"type":"genericNode","width":384},{"data":{"description":"Generates text using OpenAI LLMs.","display_name":"OpenAI","edited":false,"id":"OpenAIModel-GAzmc","node":{"base_classes":["LanguageModel","Message"],"beta":false,"conditional_paths":[],"custom_fields":{},"description":"Generates text using OpenAI LLMs.","display_name":"OpenAI","documentation":"","edited":true,"field_order":["input_value","max_tokens","model_kwargs","output_schema","model_name","openai_api_base","openai_api_key","temperature","stream","system_message","seed"],"frozen":false,"icon":"OpenAI","output_types":[],"outputs":[{"cache":true,"display_name":"Text","hidden":false,"method":"text_response","name":"text_output","selected":"Message","types":["Message"],"value":"__UNDEFINED__"},{"cache":true,"display_name":"Language Model","method":"build_model","name":"model_output","selected":"LanguageModel","types":["LanguageModel"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n"},"input_value":{"advanced":false,"display_name":"Input","dynamic":false,"info":"","input_types":["Message"],"list":false,"load_from_db":false,"name":"input_value","placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""},"max_tokens":{"advanced":true,"display_name":"Max Tokens","dynamic":false,"info":"The maximum number of tokens to generate. Set to 0 for unlimited tokens.","list":false,"name":"max_tokens","placeholder":"","required":false,"show":true,"title_case":false,"type":"int","value":""},"model_kwargs":{"advanced":true,"display_name":"Model Kwargs","dynamic":false,"info":"","list":false,"name":"model_kwargs","placeholder":"","required":false,"show":true,"title_case":false,"type":"dict","value":{}},"model_name":{"advanced":false,"display_name":"Model Name","dynamic":false,"info":"","name":"model_name","options":["gpt-4o","gpt-4-turbo","gpt-4-turbo-preview","gpt-3.5-turbo","gpt-3.5-turbo-0125"],"placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":"gpt-3.5-turbo"},"openai_api_base":{"advanced":true,"display_name":"OpenAI API Base","dynamic":false,"info":"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.","list":false,"load_from_db":false,"name":"openai_api_base","placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""},"openai_api_key":{"advanced":false,"display_name":"OpenAI API Key","dynamic":false,"info":"The OpenAI API Key to use for the OpenAI model.","input_types":[],"load_from_db":false,"name":"openai_api_key","password":true,"placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""},"output_schema":{"advanced":true,"display_name":"Schema","dynamic":false,"info":"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.","list":true,"name":"output_schema","placeholder":"","required":false,"show":true,"title_case":false,"type":"dict","value":{}},"seed":{"advanced":true,"display_name":"Seed","dynamic":false,"info":"The seed controls the reproducibility of the job.","list":false,"name":"seed","placeholder":"","required":false,"show":true,"title_case":false,"type":"int","value":1},"stream":{"advanced":true,"display_name":"Stream","dynamic":false,"info":"Stream the response from the model. Streaming works only in Chat.","list":false,"name":"stream","placeholder":"","required":false,"show":true,"title_case":false,"type":"bool","value":false},"system_message":{"advanced":true,"display_name":"System Message","dynamic":false,"info":"System message to pass to the model.","list":false,"load_from_db":false,"name":"system_message","placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""},"temperature":{"advanced":false,"display_name":"Temperature","dynamic":false,"info":"","list":false,"name":"temperature","placeholder":"","required":false,"show":true,"title_case":false,"type":"float","value":0.1}}},"type":"OpenAIModel"},"dragging":false,"height":622,"id":"OpenAIModel-GAzmc","position":{"x":2495.6628431453228,"y":669.9567653609598},"positionAbsolute":{"x":2495.6628431453228,"y":669.9567653609598},"selected":false,"type":"genericNode","width":384},{"data":{"description":"Display a chat message in the Playground.","display_name":"Chat Output","edited":false,"id":"ChatOutput-Q4j7S","node":{"base_classes":["Message"],"beta":false,"conditional_paths":[],"custom_fields":{},"description":"Display a chat message in the Playground.","display_name":"Chat Output","documentation":"","edited":true,"field_order":["input_value","sender","sender_name","session_id","data_template"],"frozen":false,"icon":"ChatOutput","output_types":[],"outputs":[{"cache":true,"display_name":"Message","method":"message_response","name":"message","selected":"Message","types":["Message"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n"},"data_template":{"advanced":true,"display_name":"Data Template","dynamic":false,"info":"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.","input_types":["Message"],"list":false,"load_from_db":false,"name":"data_template","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":"{text}"},"input_value":{"advanced":false,"display_name":"Text","dynamic":false,"info":"Message to be passed as output.","input_types":["Message"],"list":false,"load_from_db":false,"name":"input_value","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":""},"sender":{"advanced":true,"display_name":"Sender Type","dynamic":false,"info":"Type of sender.","name":"sender","options":["Machine","User"],"placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"str","value":"Machine"},"sender_name":{"advanced":true,"display_name":"Sender Name","dynamic":false,"info":"Name of the sender.","input_types":["Message"],"list":false,"load_from_db":false,"name":"sender_name","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":"AI"},"session_id":{"advanced":true,"display_name":"Session ID","dynamic":false,"info":"Session ID for the message.","input_types":["Message"],"list":false,"load_from_db":false,"name":"session_id","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":""}}},"type":"ChatOutput"},"dragging":false,"height":308,"id":"ChatOutput-Q4j7S","position":{"x":3028.2686266398873,"y":888.0854888768531},"positionAbsolute":{"x":3028.2686266398873,"y":888.0854888768531},"selected":false,"type":"genericNode","width":384},{"data":{"description":"Create a prompt template with dynamic variables.","display_name":"Prompt","id":"Prompt-kXGJN","node":{"base_classes":["Message"],"beta":false,"conditional_paths":[],"custom_fields":{"template":["context","user_message"]},"description":"Create a prompt template with dynamic variables.","display_name":"Prompt","documentation":"","edited":false,"error":null,"field_order":["template"],"frozen":false,"full_path":null,"icon":"prompts","is_composition":null,"is_input":null,"is_output":null,"name":"","output_types":[],"outputs":[{"cache":true,"display_name":"Prompt Message","hidden":false,"method":"build_prompt","name":"prompt","selected":"Message","types":["Message"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def post_code_processing(self, new_build_config: dict, current_build_config: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_build_config, current_build_config)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_build_config\n # and update the frontend_node with those values\n update_template_values(frontend_template=frontend_node, raw_template=current_build_config[\"template\"])\n return frontend_node\n"},"context":{"advanced":false,"display_name":"context","dynamic":false,"field_type":"str","fileTypes":[],"file_path":"","info":"","input_types":["Message","Text"],"list":false,"load_from_db":false,"multiline":true,"name":"context","password":false,"placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""},"template":{"advanced":false,"display_name":"Template","dynamic":false,"info":"","list":false,"name":"template","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"type":"prompt","value":"{context}\n\nUser: {user_message}\nAI: "},"user_message":{"advanced":false,"display_name":"user_message","dynamic":false,"field_type":"str","fileTypes":[],"file_path":"","info":"","input_types":["Message","Text"],"list":false,"load_from_db":false,"multiline":true,"name":"user_message","password":false,"placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""}}},"type":"Prompt"},"dragging":false,"height":517,"id":"Prompt-kXGJN","position":{"x":1879.4280156201567,"y":674.3958274263156},"positionAbsolute":{"x":1879.4280156201567,"y":674.3958274263156},"selected":false,"type":"genericNode","width":384}],"edges":[{"className":"","data":{"sourceHandle":{"dataType":"Memory","id":"Memory-Kt0An","name":"messages_text","output_types":["Message"]},"targetHandle":{"fieldName":"context","id":"Prompt-kXGJN","inputTypes":["Message","Text"],"type":"str"}},"id":"reactflow__edge-Memory-Kt0An{œdataTypeœ:œMemoryœ,œidœ:œMemory-Kt0Anœ,œnameœ:œmessages_textœ,œoutput_typesœ:[œMessageœ]}-Prompt-kXGJN{œfieldNameœ:œcontextœ,œidœ:œPrompt-kXGJNœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}","source":"Memory-Kt0An","sourceHandle":"{œdataTypeœ:œMemoryœ,œidœ:œMemory-Kt0Anœ,œnameœ:œmessages_textœ,œoutput_typesœ:[œMessageœ]}","target":"Prompt-kXGJN","targetHandle":"{œfieldNameœ:œcontextœ,œidœ:œPrompt-kXGJNœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}"},{"className":"","data":{"sourceHandle":{"dataType":"ChatInput","id":"ChatInput-krw2d","name":"message","output_types":["Message"]},"targetHandle":{"fieldName":"user_message","id":"Prompt-kXGJN","inputTypes":["Message","Text"],"type":"str"}},"id":"reactflow__edge-ChatInput-krw2d{œdataTypeœ:œChatInputœ,œidœ:œChatInput-krw2dœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-kXGJN{œfieldNameœ:œuser_messageœ,œidœ:œPrompt-kXGJNœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}","source":"ChatInput-krw2d","sourceHandle":"{œdataTypeœ:œChatInputœ,œidœ:œChatInput-krw2dœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}","target":"Prompt-kXGJN","targetHandle":"{œfieldNameœ:œuser_messageœ,œidœ:œPrompt-kXGJNœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}"},{"className":"","data":{"sourceHandle":{"dataType":"Prompt","id":"Prompt-kXGJN","name":"prompt","output_types":["Message"]},"targetHandle":{"fieldName":"input_value","id":"OpenAIModel-GAzmc","inputTypes":["Message"],"type":"str"}},"id":"reactflow__edge-Prompt-kXGJN{œdataTypeœ:œPromptœ,œidœ:œPrompt-kXGJNœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-GAzmc{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-GAzmcœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}","source":"Prompt-kXGJN","sourceHandle":"{œdataTypeœ:œPromptœ,œidœ:œPrompt-kXGJNœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}","target":"OpenAIModel-GAzmc","targetHandle":"{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-GAzmcœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}"},{"className":"","data":{"sourceHandle":{"dataType":"OpenAIModel","id":"OpenAIModel-GAzmc","name":"text_output","output_types":["Message"]},"targetHandle":{"fieldName":"input_value","id":"ChatOutput-Q4j7S","inputTypes":["Message"],"type":"str"}},"id":"reactflow__edge-OpenAIModel-GAzmc{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-GAzmcœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-Q4j7S{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-Q4j7Sœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}","source":"OpenAIModel-GAzmc","sourceHandle":"{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-GAzmcœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}","target":"ChatOutput-Q4j7S","targetHandle":"{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-Q4j7Sœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}"}],"viewport":{"x":-592.532107710133,"y":-149.32118023592653,"zoom":0.5372819347267049}},"description":"This project can be used as a starting point for building a Chat experience with user specific memory. You can set a different Session ID to start a new message history.","name":"Memory Chatbot","last_tested_version":"1.0.0rc1","endpoint_name":null,"is_component":false} \ No newline at end of file From 723d854db22c8b9a2ce5496076833b1cf7040970 Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Mon, 24 Jun 2024 09:21:29 -0300 Subject: [PATCH 077/229] Fixed starter examples --- .../Basic Prompting (Hello, World).json | 876 ++++++++++++- .../starter_projects/Memory Chatbot.json | 1120 ++++++++++++++++- 2 files changed, 1994 insertions(+), 2 deletions(-) diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json index 0813fef0a..217d486c2 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json @@ -1 +1,875 @@ -{"id":"81759149-1e58-4190-b4a4-48a96cf49734","data":{"nodes":[{"data":{"description":"Create a prompt template with dynamic variables.","display_name":"Prompt","edited":false,"id":"Prompt-fpHnR","node":{"base_classes":["Message"],"beta":false,"conditional_paths":[],"custom_fields":{"template":["user_input"]},"description":"Create a prompt template with dynamic variables.","display_name":"Prompt","documentation":"","edited":true,"field_order":["template"],"frozen":false,"icon":"prompts","output_types":[],"outputs":[{"cache":true,"display_name":"Prompt Message","hidden":false,"method":"build_prompt","name":"prompt","selected":"Message","types":["Message"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def post_code_processing(self, new_build_config: dict, current_build_config: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_build_config, current_build_config)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_build_config\n # and update the frontend_node with those values\n update_template_values(frontend_template=frontend_node, raw_template=current_build_config[\"template\"])\n return frontend_node\n"},"template":{"advanced":false,"display_name":"Template","dynamic":false,"info":"","list":false,"name":"template","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"type":"prompt","value":"Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: "},"user_input":{"advanced":false,"display_name":"user_input","dynamic":false,"field_type":"str","fileTypes":[],"file_path":"","info":"","input_types":["Message","Text"],"list":false,"load_from_db":false,"multiline":true,"name":"user_input","password":false,"placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""}}},"type":"Prompt"},"dragging":false,"height":422,"id":"Prompt-fpHnR","position":{"x":43.70859256635981,"y":1115.5304359666682},"positionAbsolute":{"x":43.70859256635981,"y":1115.5304359666682},"selected":false,"type":"genericNode","width":384},{"data":{"description":"Get chat inputs from the Playground.","display_name":"Chat Input","edited":false,"id":"ChatInput-74jnA","node":{"base_classes":["Message"],"beta":false,"conditional_paths":[],"custom_fields":{},"description":"Get chat inputs from the Playground.","display_name":"Chat Input","documentation":"","edited":true,"field_order":["input_value","sender","sender_name","session_id","files"],"frozen":false,"icon":"ChatInput","output_types":[],"outputs":[{"cache":true,"display_name":"Message","hidden":false,"method":"message_response","name":"message","selected":"Message","types":["Message"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MultilineInput, Output, TextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n TextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n TextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n"},"files":{"advanced":true,"display_name":"Files","dynamic":false,"fileTypes":["txt","md","mdx","csv","json","yaml","yml","xml","html","htm","pdf","docx","py","sh","sql","js","ts","tsx","jpg","jpeg","png","bmp","image"],"file_path":"","info":"Files to be sent with the message.","list":true,"name":"files","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"file","value":""},"input_value":{"advanced":false,"display_name":"Text","dynamic":false,"info":"Message to be passed as input.","input_types":["Message"],"list":false,"load_from_db":false,"multiline":true,"name":"input_value","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":""},"sender":{"advanced":true,"display_name":"Sender Type","dynamic":false,"info":"Type of sender.","name":"sender","options":["Machine","User"],"placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"str","value":"User"},"sender_name":{"advanced":true,"display_name":"Sender Name","dynamic":false,"info":"Name of the sender.","input_types":["Message"],"list":false,"load_from_db":false,"name":"sender_name","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":"User"},"session_id":{"advanced":true,"display_name":"Session ID","dynamic":false,"info":"Session ID for the message.","input_types":["Message"],"list":false,"load_from_db":false,"name":"session_id","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":""}}},"type":"ChatInput"},"dragging":false,"height":308,"id":"ChatInput-74jnA","position":{"x":-521.3324537445985,"y":1089.7620993695407},"positionAbsolute":{"x":-521.3324537445985,"y":1089.7620993695407},"selected":false,"type":"genericNode","width":384},{"data":{"description":"Generates text using OpenAI LLMs.","display_name":"OpenAI","edited":false,"id":"OpenAIModel-ehSar","node":{"base_classes":["LanguageModel","Message"],"beta":false,"conditional_paths":[],"custom_fields":{},"description":"Generates text using OpenAI LLMs.","display_name":"OpenAI","documentation":"","edited":true,"field_order":["input_value","max_tokens","model_kwargs","output_schema","model_name","openai_api_base","openai_api_key","temperature","stream","system_message","seed"],"frozen":false,"icon":"OpenAI","output_types":[],"outputs":[{"cache":true,"display_name":"Text","hidden":false,"method":"text_response","name":"text_output","selected":"Message","types":["Message"],"value":"__UNDEFINED__"},{"cache":true,"display_name":"Language Model","method":"build_model","name":"model_output","selected":"LanguageModel","types":["LanguageModel"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n"},"input_value":{"advanced":false,"display_name":"Input","dynamic":false,"info":"","input_types":["Message"],"list":false,"load_from_db":false,"name":"input_value","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":""},"max_tokens":{"advanced":true,"display_name":"Max Tokens","dynamic":false,"info":"The maximum number of tokens to generate. Set to 0 for unlimited tokens.","list":false,"name":"max_tokens","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"int","value":""},"model_kwargs":{"advanced":true,"display_name":"Model Kwargs","dynamic":false,"info":"","list":false,"name":"model_kwargs","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"type":"dict","value":{}},"model_name":{"advanced":false,"display_name":"Model Name","dynamic":false,"info":"","name":"model_name","options":["gpt-4o","gpt-4-turbo","gpt-4-turbo-preview","gpt-3.5-turbo","gpt-3.5-turbo-0125"],"placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"str","value":"gpt-3.5-turbo"},"openai_api_base":{"advanced":true,"display_name":"OpenAI API Base","dynamic":false,"info":"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.","list":false,"load_from_db":false,"name":"openai_api_base","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"str","value":""},"openai_api_key":{"advanced":false,"display_name":"OpenAI API Key","dynamic":false,"info":"The OpenAI API Key to use for the OpenAI model.","input_types":[],"load_from_db":false,"name":"openai_api_key","password":true,"placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""},"output_schema":{"advanced":true,"display_name":"Schema","dynamic":false,"info":"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.","list":true,"name":"output_schema","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"type":"dict","value":{}},"seed":{"advanced":true,"display_name":"Seed","dynamic":false,"info":"The seed controls the reproducibility of the job.","list":false,"name":"seed","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"int","value":1},"stream":{"advanced":true,"display_name":"Stream","dynamic":false,"info":"Stream the response from the model. Streaming works only in Chat.","list":false,"name":"stream","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"bool","value":false},"system_message":{"advanced":true,"display_name":"System Message","dynamic":false,"info":"System message to pass to the model.","list":false,"load_from_db":false,"name":"system_message","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"str","value":""},"temperature":{"advanced":false,"display_name":"Temperature","dynamic":false,"info":"","list":false,"name":"temperature","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"float","value":0.1}}},"type":"OpenAIModel"},"dragging":false,"height":621,"id":"OpenAIModel-ehSar","position":{"x":584.9288140250019,"y":1149.0790574268922},"positionAbsolute":{"x":584.9288140250019,"y":1149.0790574268922},"selected":false,"type":"genericNode","width":384},{"data":{"description":"Display a chat message in the Playground.","display_name":"Chat Output","edited":false,"id":"ChatOutput-KLLro","node":{"base_classes":["Message"],"beta":false,"conditional_paths":[],"custom_fields":{},"description":"Display a chat message in the Playground.","display_name":"Chat Output","documentation":"","edited":true,"field_order":["input_value","sender","sender_name","session_id","data_template"],"frozen":false,"icon":"ChatOutput","output_types":[],"outputs":[{"cache":true,"display_name":"Message","method":"message_response","name":"message","selected":"Message","types":["Message"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, Output, TextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n TextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n TextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n TextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n TextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n"},"data_template":{"advanced":true,"display_name":"Data Template","dynamic":false,"info":"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.","input_types":["Message"],"list":false,"load_from_db":false,"name":"data_template","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":"{text}"},"input_value":{"advanced":false,"display_name":"Text","dynamic":false,"info":"Message to be passed as output.","input_types":["Message"],"list":false,"load_from_db":false,"name":"input_value","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":""},"sender":{"advanced":true,"display_name":"Sender Type","dynamic":false,"info":"Type of sender.","name":"sender","options":["Machine","User"],"placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"str","value":"Machine"},"sender_name":{"advanced":true,"display_name":"Sender Name","dynamic":false,"info":"Name of the sender.","input_types":["Message"],"list":false,"load_from_db":false,"name":"sender_name","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":"AI"},"session_id":{"advanced":true,"display_name":"Session ID","dynamic":false,"info":"Session ID for the 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flow will get you experimenting with the basics of the UI, the Chat and the Prompt component. \n\nTry changing the Template in it to see how the model behaves. \nYou can change it to this and a Text Input into the `type_of_person` variable : \"Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: \" ","name":"Basic Prompting (Hello, World)","last_tested_version":"1.0.0rc1","endpoint_name":null,"is_component":false} \ No newline at end of file +{ + "data": { + "edges": [ + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "ChatInput", + "id": "ChatInput-74jnA", + "name": "message", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "user_input", + "id": "Prompt-fpHnR", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ChatInput-74jnA{œdataTypeœ:œChatInputœ,œidœ:œChatInput-74jnAœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-fpHnR{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-fpHnRœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ChatInput-74jnA", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-74jnAœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-fpHnR", + "targetHandle": "{œfieldNameœ: œuser_inputœ, œidœ: œPrompt-fpHnRœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-fpHnR", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "OpenAIModel-ehSar", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-fpHnR{œdataTypeœ:œPromptœ,œidœ:œPrompt-fpHnRœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-ehSar{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-ehSarœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-fpHnR", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-fpHnRœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-ehSar", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-ehSarœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIModel", + "id": "OpenAIModel-ehSar", + "name": "text_output", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "ChatOutput-KLLro", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-OpenAIModel-ehSar{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-ehSarœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-KLLro{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-KLLroœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-ehSar", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-ehSarœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-KLLro", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-KLLroœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + } + ], + "nodes": [ + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "edited": false, + "id": "Prompt-fpHnR", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "user_input" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": true, + "field_order": [ + "template" + ], + "frozen": false, + "icon": "prompts", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "hidden": false, + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def post_code_processing(self, new_build_config: dict, current_build_config: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_build_config, current_build_config)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_build_config\n # and update the frontend_node with those values\n update_template_values(frontend_template=frontend_node, raw_template=current_build_config[\"template\"])\n return frontend_node\n" + }, + "template": { + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "prompt", + "value": "Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: " + }, + "user_input": { + "advanced": false, + "display_name": "user_input", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "user_input", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + } + } + }, + "type": "Prompt" + }, + "dragging": false, + "height": 422, + "id": "Prompt-fpHnR", + "position": { + "x": 43.70859256635981, + "y": 1115.5304359666682 + }, + "positionAbsolute": { + "x": 43.70859256635981, + "y": 1115.5304359666682 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "edited": false, + "id": "ChatInput-74jnA", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "documentation": "", + "edited": true, + "field_order": [ + "input_value", + "sender", + "sender_name", + "session_id", + "files" + ], + "frozen": false, + "icon": "ChatInput", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "hidden": false, + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MultilineInput, Output, TextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n TextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n TextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + }, + "files": { + "advanced": true, + "display_name": "Files", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx", + "jpg", + "jpeg", + "png", + "bmp", + "image" + ], + "file_path": "", + "info": "Files to be sent with the message.", + "list": true, + "name": "files", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "file", + "value": "" + }, + "input_value": { + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "advanced": true, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "sender_name": { + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "session_id": { + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "Session ID for the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + } + }, + "type": "ChatInput" + }, + "dragging": false, + "height": 308, + "id": "ChatInput-74jnA", + "position": { + "x": -521.3324537445985, + "y": 1089.7620993695407 + }, + "positionAbsolute": { + "x": -521.3324537445985, + "y": 1089.7620993695407 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "edited": false, + "id": "OpenAIModel-ehSar", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": true, + "field_order": [ + "input_value", + "max_tokens", + "model_kwargs", + "output_schema", + "model_name", + "openai_api_base", + "openai_api_key", + "temperature", + "stream", + "system_message", + "seed" + ], + "frozen": false, + "icon": "OpenAI", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "hidden": false, + "method": "text_response", + "name": "text_output", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n" + }, + "input_value": { + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "max_tokens": { + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": "" + }, + "model_kwargs": { + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "model_name": { + "advanced": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "gpt-3.5-turbo" + }, + "openai_api_base": { + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "openai_api_key": { + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [], + "load_from_db": false, + "name": "openai_api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "output_schema": { + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "dict", + "value": {} + }, + "seed": { + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1 + }, + "stream": { + "advanced": true, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "bool", + "value": false + }, + "system_message": { + "advanced": true, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "temperature": { + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "float", + "value": 0.1 + } + } + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 621, + "id": "OpenAIModel-ehSar", + "position": { + "x": 584.9288140250019, + "y": 1149.0790574268922 + }, + "positionAbsolute": { + "x": 584.9288140250019, + "y": 1149.0790574268922 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "edited": false, + "id": "ChatOutput-KLLro", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": true, + "field_order": [ + "input_value", + "sender", + "sender_name", + "session_id", + "data_template" + ], + "frozen": false, + "icon": "ChatOutput", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, Output, TextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n TextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n TextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n TextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n TextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + }, + "data_template": { + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "advanced": true, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "Session ID for the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + } + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 308, + "id": "ChatOutput-KLLro", + "position": { + "x": 1157.3374592784412, + "y": 1160.9424490383622 + }, + "positionAbsolute": { + "x": 1157.3374592784412, + "y": 1160.9424490383622 + }, + "selected": false, + "type": "genericNode", + "width": 384 + } + ], + "viewport": { + "x": 353.0590737990465, + "y": -407.76221076623995, + "zoom": 0.5467255436493648 + } + }, + "description": "This flow will get you experimenting with the basics of the UI, the Chat and the Prompt component. \n\nTry changing the Template in it to see how the model behaves. \nYou can change it to this and a Text Input into the `type_of_person` variable : \"Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: \" ", + "endpoint_name": null, + "id": "81759149-1e58-4190-b4a4-48a96cf49734", + "is_component": false, + "last_tested_version": "1.0.0rc1", + "name": "Basic Prompting (Hello, World)" +} \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json b/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json index 4d99b40c5..755f6ae1e 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json @@ -1 +1,1119 @@ -{"id":"b4832b74-d12c-4c00-94e9-4d873abf56eb","data":{"nodes":[{"data":{"description":"Retrieves stored chat messages.","display_name":"Memory","edited":false,"id":"Memory-Kt0An","node":{"base_classes":["Data","Message"],"beta":false,"conditional_paths":[],"custom_fields":{},"description":"Retrieves stored chat messages.","display_name":"Memory","documentation":"","edited":true,"field_order":["sender","sender_name","n_messages","session_id","order","template"],"frozen":false,"icon":"message-square-more","output_types":[],"outputs":[{"cache":true,"display_name":"Chat History","method":"retrieve_messages","name":"messages","selected":"Data","types":["Data"],"value":"__UNDEFINED__"},{"cache":true,"display_name":"Messages (Text)","hidden":false,"method":"retrieve_messages_as_text","name":"messages_text","selected":"Message","types":["Message"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import DropdownInput, IntInput, MultilineInput, Output, MessageTextInput\nfrom langflow.memory import get_messages\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass MemoryComponent(Component):\n display_name = \"Chat Memory\"\n description = \"Retrieves stored chat messages.\"\n icon = \"message-square-more\"\n\n inputs = [\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\", \"Machine and User\"],\n value=\"Machine and User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n advanced=True,\n ),\n IntInput(\n name=\"n_messages\",\n display_name=\"Number of Messages\",\n value=100,\n info=\"Number of messages to retrieve.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"Session ID of the chat history.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"order\",\n display_name=\"Order\",\n options=[\"Ascending\", \"Descending\"],\n value=\"Ascending\",\n info=\"Order of the messages.\",\n advanced=True,\n ),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.\",\n value=\"{sender_name}: {text}\",\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Chat History\", name=\"messages\", method=\"retrieve_messages\"),\n Output(display_name=\"Messages (Text)\", name=\"messages_text\", method=\"retrieve_messages_as_text\"),\n ]\n\n def retrieve_messages(self) -> Data:\n sender = self.sender\n sender_name = self.sender_name\n session_id = self.session_id\n n_messages = self.n_messages\n order = \"DESC\" if self.order == \"Descending\" else \"ASC\"\n\n if sender == \"Machine and User\":\n sender = None\n\n messages = get_messages(\n sender=sender,\n sender_name=sender_name,\n session_id=session_id,\n limit=n_messages,\n order=order,\n )\n self.status = messages\n return messages\n\n def retrieve_messages_as_text(self) -> Message:\n messages_text = data_to_text(self.template, self.retrieve_messages())\n self.status = messages_text\n return Message(text=messages_text)\n"},"n_messages":{"advanced":true,"display_name":"Number of Messages","dynamic":false,"info":"Number of messages to retrieve.","list":false,"name":"n_messages","placeholder":"","required":false,"show":true,"title_case":false,"type":"int","value":100},"order":{"advanced":true,"display_name":"Order","dynamic":false,"info":"Order of the messages.","name":"order","options":["Ascending","Descending"],"placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":"Ascending"},"sender":{"advanced":true,"display_name":"Sender Type","dynamic":false,"info":"Type of sender.","name":"sender","options":["Machine","User","Machine and User"],"placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":"Machine and User"},"sender_name":{"advanced":true,"display_name":"Sender Name","dynamic":false,"info":"Name of the sender.","input_types":["Message"],"list":false,"load_from_db":false,"name":"sender_name","placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""},"session_id":{"advanced":true,"display_name":"Session ID","dynamic":false,"info":"Session ID of the chat history.","input_types":["Message"],"list":false,"load_from_db":false,"name":"session_id","placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""},"template":{"advanced":true,"display_name":"Template","dynamic":false,"info":"The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.","input_types":["Message"],"list":false,"load_from_db":false,"multiline":true,"name":"template","placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":"{sender_name}: {text}"}}},"type":"Memory"},"dragging":false,"height":267,"id":"Memory-Kt0An","position":{"x":1258.8089948698466,"y":547.1243849102437},"positionAbsolute":{"x":1258.8089948698466,"y":547.1243849102437},"selected":false,"type":"genericNode","width":384},{"data":{"description":"Get chat inputs from the Playground.","display_name":"Chat Input","edited":false,"id":"ChatInput-krw2d","node":{"base_classes":["Message"],"beta":false,"conditional_paths":[],"custom_fields":{},"description":"Get chat inputs from the Playground.","display_name":"Chat Input","documentation":"","edited":true,"field_order":["input_value","sender","sender_name","session_id","files"],"frozen":false,"icon":"ChatInput","output_types":[],"outputs":[{"cache":true,"display_name":"Message","hidden":false,"method":"message_response","name":"message","selected":"Message","types":["Message"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n"},"files":{"advanced":true,"display_name":"Files","dynamic":false,"fileTypes":["txt","md","mdx","csv","json","yaml","yml","xml","html","htm","pdf","docx","py","sh","sql","js","ts","tsx","jpg","jpeg","png","bmp","image"],"file_path":"","info":"Files to be sent with the message.","list":true,"name":"files","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"file","value":""},"input_value":{"advanced":false,"display_name":"Text","dynamic":false,"info":"Message to be passed as input.","input_types":["Message"],"list":false,"load_from_db":false,"multiline":true,"name":"input_value","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":""},"sender":{"advanced":true,"display_name":"Sender Type","dynamic":false,"info":"Type of sender.","name":"sender","options":["Machine","User"],"placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"str","value":"User"},"sender_name":{"advanced":true,"display_name":"Sender Name","dynamic":false,"info":"Name of the sender.","input_types":["Message"],"list":false,"load_from_db":false,"name":"sender_name","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":"User"},"session_id":{"advanced":true,"display_name":"Session ID","dynamic":false,"info":"Session ID for the message.","input_types":["Message"],"list":false,"load_from_db":false,"name":"session_id","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":""}}},"type":"ChatInput"},"dragging":true,"height":309,"id":"ChatInput-krw2d","position":{"x":1261.3748612945249,"y":912.733279525042},"positionAbsolute":{"x":1261.3748612945249,"y":912.733279525042},"selected":true,"type":"genericNode","width":384},{"data":{"description":"Generates text using OpenAI LLMs.","display_name":"OpenAI","edited":false,"id":"OpenAIModel-GAzmc","node":{"base_classes":["LanguageModel","Message"],"beta":false,"conditional_paths":[],"custom_fields":{},"description":"Generates text using OpenAI LLMs.","display_name":"OpenAI","documentation":"","edited":true,"field_order":["input_value","max_tokens","model_kwargs","output_schema","model_name","openai_api_base","openai_api_key","temperature","stream","system_message","seed"],"frozen":false,"icon":"OpenAI","output_types":[],"outputs":[{"cache":true,"display_name":"Text","hidden":false,"method":"text_response","name":"text_output","selected":"Message","types":["Message"],"value":"__UNDEFINED__"},{"cache":true,"display_name":"Language Model","method":"build_model","name":"model_output","selected":"LanguageModel","types":["LanguageModel"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n"},"input_value":{"advanced":false,"display_name":"Input","dynamic":false,"info":"","input_types":["Message"],"list":false,"load_from_db":false,"name":"input_value","placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""},"max_tokens":{"advanced":true,"display_name":"Max Tokens","dynamic":false,"info":"The maximum number of tokens to generate. Set to 0 for unlimited tokens.","list":false,"name":"max_tokens","placeholder":"","required":false,"show":true,"title_case":false,"type":"int","value":""},"model_kwargs":{"advanced":true,"display_name":"Model Kwargs","dynamic":false,"info":"","list":false,"name":"model_kwargs","placeholder":"","required":false,"show":true,"title_case":false,"type":"dict","value":{}},"model_name":{"advanced":false,"display_name":"Model Name","dynamic":false,"info":"","name":"model_name","options":["gpt-4o","gpt-4-turbo","gpt-4-turbo-preview","gpt-3.5-turbo","gpt-3.5-turbo-0125"],"placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":"gpt-3.5-turbo"},"openai_api_base":{"advanced":true,"display_name":"OpenAI API Base","dynamic":false,"info":"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.","list":false,"load_from_db":false,"name":"openai_api_base","placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""},"openai_api_key":{"advanced":false,"display_name":"OpenAI API Key","dynamic":false,"info":"The OpenAI API Key to use for the OpenAI model.","input_types":[],"load_from_db":false,"name":"openai_api_key","password":true,"placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""},"output_schema":{"advanced":true,"display_name":"Schema","dynamic":false,"info":"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.","list":true,"name":"output_schema","placeholder":"","required":false,"show":true,"title_case":false,"type":"dict","value":{}},"seed":{"advanced":true,"display_name":"Seed","dynamic":false,"info":"The seed controls the reproducibility of the job.","list":false,"name":"seed","placeholder":"","required":false,"show":true,"title_case":false,"type":"int","value":1},"stream":{"advanced":true,"display_name":"Stream","dynamic":false,"info":"Stream the response from the model. Streaming works only in Chat.","list":false,"name":"stream","placeholder":"","required":false,"show":true,"title_case":false,"type":"bool","value":false},"system_message":{"advanced":true,"display_name":"System Message","dynamic":false,"info":"System message to pass to the model.","list":false,"load_from_db":false,"name":"system_message","placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""},"temperature":{"advanced":false,"display_name":"Temperature","dynamic":false,"info":"","list":false,"name":"temperature","placeholder":"","required":false,"show":true,"title_case":false,"type":"float","value":0.1}}},"type":"OpenAIModel"},"dragging":false,"height":622,"id":"OpenAIModel-GAzmc","position":{"x":2495.6628431453228,"y":669.9567653609598},"positionAbsolute":{"x":2495.6628431453228,"y":669.9567653609598},"selected":false,"type":"genericNode","width":384},{"data":{"description":"Display a chat message in the Playground.","display_name":"Chat Output","edited":false,"id":"ChatOutput-Q4j7S","node":{"base_classes":["Message"],"beta":false,"conditional_paths":[],"custom_fields":{},"description":"Display a chat message in the Playground.","display_name":"Chat Output","documentation":"","edited":true,"field_order":["input_value","sender","sender_name","session_id","data_template"],"frozen":false,"icon":"ChatOutput","output_types":[],"outputs":[{"cache":true,"display_name":"Message","method":"message_response","name":"message","selected":"Message","types":["Message"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n"},"data_template":{"advanced":true,"display_name":"Data Template","dynamic":false,"info":"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.","input_types":["Message"],"list":false,"load_from_db":false,"name":"data_template","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":"{text}"},"input_value":{"advanced":false,"display_name":"Text","dynamic":false,"info":"Message to be passed as output.","input_types":["Message"],"list":false,"load_from_db":false,"name":"input_value","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":""},"sender":{"advanced":true,"display_name":"Sender Type","dynamic":false,"info":"Type of sender.","name":"sender","options":["Machine","User"],"placeholder":"","required":false,"show":true,"title_case":false,"trace_as_metadata":true,"type":"str","value":"Machine"},"sender_name":{"advanced":true,"display_name":"Sender Name","dynamic":false,"info":"Name of the sender.","input_types":["Message"],"list":false,"load_from_db":false,"name":"sender_name","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":"AI"},"session_id":{"advanced":true,"display_name":"Session ID","dynamic":false,"info":"Session ID for the message.","input_types":["Message"],"list":false,"load_from_db":false,"name":"session_id","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"trace_as_metadata":true,"type":"str","value":""}}},"type":"ChatOutput"},"dragging":false,"height":308,"id":"ChatOutput-Q4j7S","position":{"x":3028.2686266398873,"y":888.0854888768531},"positionAbsolute":{"x":3028.2686266398873,"y":888.0854888768531},"selected":false,"type":"genericNode","width":384},{"data":{"description":"Create a prompt template with dynamic variables.","display_name":"Prompt","id":"Prompt-kXGJN","node":{"base_classes":["Message"],"beta":false,"conditional_paths":[],"custom_fields":{"template":["context","user_message"]},"description":"Create a prompt template with dynamic variables.","display_name":"Prompt","documentation":"","edited":false,"error":null,"field_order":["template"],"frozen":false,"full_path":null,"icon":"prompts","is_composition":null,"is_input":null,"is_output":null,"name":"","output_types":[],"outputs":[{"cache":true,"display_name":"Prompt Message","hidden":false,"method":"build_prompt","name":"prompt","selected":"Message","types":["Message"],"value":"__UNDEFINED__"}],"pinned":false,"template":{"_type":"Component","code":{"advanced":true,"dynamic":true,"fileTypes":[],"file_path":"","info":"","list":false,"load_from_db":false,"multiline":true,"name":"code","password":false,"placeholder":"","required":true,"show":true,"title_case":false,"type":"code","value":"from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def post_code_processing(self, new_build_config: dict, current_build_config: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_build_config, current_build_config)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_build_config\n # and update the frontend_node with those values\n update_template_values(frontend_template=frontend_node, raw_template=current_build_config[\"template\"])\n return frontend_node\n"},"context":{"advanced":false,"display_name":"context","dynamic":false,"field_type":"str","fileTypes":[],"file_path":"","info":"","input_types":["Message","Text"],"list":false,"load_from_db":false,"multiline":true,"name":"context","password":false,"placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""},"template":{"advanced":false,"display_name":"Template","dynamic":false,"info":"","list":false,"name":"template","placeholder":"","required":false,"show":true,"title_case":false,"trace_as_input":true,"type":"prompt","value":"{context}\n\nUser: {user_message}\nAI: "},"user_message":{"advanced":false,"display_name":"user_message","dynamic":false,"field_type":"str","fileTypes":[],"file_path":"","info":"","input_types":["Message","Text"],"list":false,"load_from_db":false,"multiline":true,"name":"user_message","password":false,"placeholder":"","required":false,"show":true,"title_case":false,"type":"str","value":""}}},"type":"Prompt"},"dragging":false,"height":517,"id":"Prompt-kXGJN","position":{"x":1879.4280156201567,"y":674.3958274263156},"positionAbsolute":{"x":1879.4280156201567,"y":674.3958274263156},"selected":false,"type":"genericNode","width":384}],"edges":[{"className":"","data":{"sourceHandle":{"dataType":"Memory","id":"Memory-Kt0An","name":"messages_text","output_types":["Message"]},"targetHandle":{"fieldName":"context","id":"Prompt-kXGJN","inputTypes":["Message","Text"],"type":"str"}},"id":"reactflow__edge-Memory-Kt0An{œdataTypeœ:œMemoryœ,œidœ:œMemory-Kt0Anœ,œnameœ:œmessages_textœ,œoutput_typesœ:[œMessageœ]}-Prompt-kXGJN{œfieldNameœ:œcontextœ,œidœ:œPrompt-kXGJNœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}","source":"Memory-Kt0An","sourceHandle":"{œdataTypeœ:œMemoryœ,œidœ:œMemory-Kt0Anœ,œnameœ:œmessages_textœ,œoutput_typesœ:[œMessageœ]}","target":"Prompt-kXGJN","targetHandle":"{œfieldNameœ:œcontextœ,œidœ:œPrompt-kXGJNœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}"},{"className":"","data":{"sourceHandle":{"dataType":"ChatInput","id":"ChatInput-krw2d","name":"message","output_types":["Message"]},"targetHandle":{"fieldName":"user_message","id":"Prompt-kXGJN","inputTypes":["Message","Text"],"type":"str"}},"id":"reactflow__edge-ChatInput-krw2d{œdataTypeœ:œChatInputœ,œidœ:œChatInput-krw2dœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-kXGJN{œfieldNameœ:œuser_messageœ,œidœ:œPrompt-kXGJNœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}","source":"ChatInput-krw2d","sourceHandle":"{œdataTypeœ:œChatInputœ,œidœ:œChatInput-krw2dœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}","target":"Prompt-kXGJN","targetHandle":"{œfieldNameœ:œuser_messageœ,œidœ:œPrompt-kXGJNœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}"},{"className":"","data":{"sourceHandle":{"dataType":"Prompt","id":"Prompt-kXGJN","name":"prompt","output_types":["Message"]},"targetHandle":{"fieldName":"input_value","id":"OpenAIModel-GAzmc","inputTypes":["Message"],"type":"str"}},"id":"reactflow__edge-Prompt-kXGJN{œdataTypeœ:œPromptœ,œidœ:œPrompt-kXGJNœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-GAzmc{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-GAzmcœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}","source":"Prompt-kXGJN","sourceHandle":"{œdataTypeœ:œPromptœ,œidœ:œPrompt-kXGJNœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}","target":"OpenAIModel-GAzmc","targetHandle":"{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-GAzmcœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}"},{"className":"","data":{"sourceHandle":{"dataType":"OpenAIModel","id":"OpenAIModel-GAzmc","name":"text_output","output_types":["Message"]},"targetHandle":{"fieldName":"input_value","id":"ChatOutput-Q4j7S","inputTypes":["Message"],"type":"str"}},"id":"reactflow__edge-OpenAIModel-GAzmc{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-GAzmcœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-Q4j7S{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-Q4j7Sœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}","source":"OpenAIModel-GAzmc","sourceHandle":"{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-GAzmcœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}","target":"ChatOutput-Q4j7S","targetHandle":"{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-Q4j7Sœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}"}],"viewport":{"x":-592.532107710133,"y":-149.32118023592653,"zoom":0.5372819347267049}},"description":"This project can be used as a starting point for building a Chat experience with user specific memory. You can set a different Session ID to start a new message history.","name":"Memory Chatbot","last_tested_version":"1.0.0rc1","endpoint_name":null,"is_component":false} \ No newline at end of file +{ + "data": { + "edges": [ + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "Memory", + "id": "Memory-Kt0An", + "name": "messages_text", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "context", + "id": "Prompt-kXGJN", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Memory-Kt0An{œdataTypeœ:œMemoryœ,œidœ:œMemory-Kt0Anœ,œnameœ:œmessages_textœ,œoutput_typesœ:[œMessageœ]}-Prompt-kXGJN{œfieldNameœ:œcontextœ,œidœ:œPrompt-kXGJNœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "Memory-Kt0An", + "sourceHandle": "{œdataTypeœ: œMemoryœ, œidœ: œMemory-Kt0Anœ, œnameœ: œmessages_textœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-kXGJN", + "targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-kXGJNœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "ChatInput", + "id": "ChatInput-krw2d", + "name": "message", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "user_message", + "id": "Prompt-kXGJN", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ChatInput-krw2d{œdataTypeœ:œChatInputœ,œidœ:œChatInput-krw2dœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-kXGJN{œfieldNameœ:œuser_messageœ,œidœ:œPrompt-kXGJNœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ChatInput-krw2d", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-krw2dœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-kXGJN", + "targetHandle": "{œfieldNameœ: œuser_messageœ, œidœ: œPrompt-kXGJNœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-kXGJN", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "OpenAIModel-GAzmc", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-kXGJN{œdataTypeœ:œPromptœ,œidœ:œPrompt-kXGJNœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-GAzmc{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-GAzmcœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-kXGJN", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-kXGJNœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-GAzmc", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-GAzmcœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIModel", + "id": "OpenAIModel-GAzmc", + "name": "text_output", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "ChatOutput-Q4j7S", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-OpenAIModel-GAzmc{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-GAzmcœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-Q4j7S{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-Q4j7Sœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-GAzmc", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-GAzmcœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-Q4j7S", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-Q4j7Sœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + } + ], + "nodes": [ + { + "data": { + "description": "Retrieves stored chat messages.", + "display_name": "Memory", + "edited": false, + "id": "Memory-Kt0An", + "node": { + "base_classes": [ + "Data", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Retrieves stored chat messages.", + "display_name": "Memory", + "documentation": "", + "edited": true, + "field_order": [ + "sender", + "sender_name", + "n_messages", + "session_id", + "order", + "template" + ], + "frozen": false, + "icon": "message-square-more", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Chat History", + "method": "retrieve_messages", + "name": "messages", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Messages (Text)", + "hidden": false, + "method": "retrieve_messages_as_text", + "name": "messages_text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import DropdownInput, IntInput, MultilineInput, Output, MessageTextInput\nfrom langflow.memory import get_messages\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass MemoryComponent(Component):\n display_name = \"Chat Memory\"\n description = \"Retrieves stored chat messages.\"\n icon = \"message-square-more\"\n\n inputs = [\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\", \"Machine and User\"],\n value=\"Machine and User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n advanced=True,\n ),\n IntInput(\n name=\"n_messages\",\n display_name=\"Number of Messages\",\n value=100,\n info=\"Number of messages to retrieve.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\",\n display_name=\"Session ID\",\n info=\"Session ID of the chat history.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"order\",\n display_name=\"Order\",\n options=[\"Ascending\", \"Descending\"],\n value=\"Ascending\",\n info=\"Order of the messages.\",\n advanced=True,\n ),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.\",\n value=\"{sender_name}: {text}\",\n advanced=True,\n ),\n ]\n\n outputs = [\n Output(display_name=\"Chat History\", name=\"messages\", method=\"retrieve_messages\"),\n Output(display_name=\"Messages (Text)\", name=\"messages_text\", method=\"retrieve_messages_as_text\"),\n ]\n\n def retrieve_messages(self) -> Data:\n sender = self.sender\n sender_name = self.sender_name\n session_id = self.session_id\n n_messages = self.n_messages\n order = \"DESC\" if self.order == \"Descending\" else \"ASC\"\n\n if sender == \"Machine and User\":\n sender = None\n\n messages = get_messages(\n sender=sender,\n sender_name=sender_name,\n session_id=session_id,\n limit=n_messages,\n order=order,\n )\n self.status = messages\n return messages\n\n def retrieve_messages_as_text(self) -> Message:\n messages_text = data_to_text(self.template, self.retrieve_messages())\n self.status = messages_text\n return Message(text=messages_text)\n" + }, + "n_messages": { + "advanced": true, + "display_name": "Number of Messages", + "dynamic": false, + "info": "Number of messages to retrieve.", + "list": false, + "name": "n_messages", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 100 + }, + "order": { + "advanced": true, + "display_name": "Order", + "dynamic": false, + "info": "Order of the messages.", + "name": "order", + "options": [ + "Ascending", + "Descending" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "Ascending" + }, + "sender": { + "advanced": true, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User", + "Machine and User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "Machine and User" + }, + "sender_name": { + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "session_id": { + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "Session ID of the chat history.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "template": { + "advanced": true, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "{sender_name}: {text}" + } + } + }, + "type": "Memory" + }, + "dragging": false, + "height": 267, + "id": "Memory-Kt0An", + "position": { + "x": 1258.8089948698466, + "y": 547.1243849102437 + }, + "positionAbsolute": { + "x": 1258.8089948698466, + "y": 547.1243849102437 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "edited": false, + "id": "ChatInput-krw2d", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "documentation": "", + "edited": true, + "field_order": [ + "input_value", + "sender", + "sender_name", + "session_id", + "files" + ], + "frozen": false, + "icon": "ChatInput", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "hidden": false, + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + }, + "files": { + "advanced": true, + "display_name": "Files", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx", + "jpg", + "jpeg", + "png", + "bmp", + "image" + ], + "file_path": "", + "info": "Files to be sent with the message.", + "list": true, + "name": "files", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "file", + "value": "" + }, + "input_value": { + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "advanced": true, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "sender_name": { + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "session_id": { + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "Session ID for the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + } + }, + "type": "ChatInput" + }, + "dragging": true, + "height": 309, + "id": "ChatInput-krw2d", + "position": { + "x": 1261.3748612945249, + "y": 912.733279525042 + }, + "positionAbsolute": { + "x": 1261.3748612945249, + "y": 912.733279525042 + }, + "selected": true, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "edited": false, + "id": "OpenAIModel-GAzmc", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": true, + "field_order": [ + "input_value", + "max_tokens", + "model_kwargs", + "output_schema", + "model_name", + "openai_api_base", + "openai_api_key", + "temperature", + "stream", + "system_message", + "seed" + ], + "frozen": false, + "icon": "OpenAI", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "hidden": false, + "method": "text_response", + "name": "text_output", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n" + }, + "input_value": { + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "max_tokens": { + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "model_kwargs": { + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "model_name": { + "advanced": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "gpt-3.5-turbo" + }, + "openai_api_base": { + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_key": { + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [], + "load_from_db": false, + "name": "openai_api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "output_schema": { + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "seed": { + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 1 + }, + "stream": { + "advanced": true, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "system_message": { + "advanced": true, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "temperature": { + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "float", + "value": 0.1 + } + } + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 622, + "id": "OpenAIModel-GAzmc", + "position": { + "x": 2495.6628431453228, + "y": 669.9567653609598 + }, + "positionAbsolute": { + "x": 2495.6628431453228, + "y": 669.9567653609598 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "edited": false, + "id": "ChatOutput-Q4j7S", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": true, + "field_order": [ + "input_value", + "sender", + "sender_name", + "session_id", + "data_template" + ], + "frozen": false, + "icon": "ChatOutput", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + }, + "data_template": { + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "advanced": true, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "Session ID for the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + } + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 308, + "id": "ChatOutput-Q4j7S", + "position": { + "x": 3028.2686266398873, + "y": 888.0854888768531 + }, + "positionAbsolute": { + "x": 3028.2686266398873, + "y": 888.0854888768531 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-kXGJN", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "context", + "user_message" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "error": null, + "field_order": [ + "template" + ], + "frozen": false, + "full_path": null, + "icon": "prompts", + "is_composition": null, + "is_input": null, + "is_output": null, + "name": "", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "hidden": false, + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def post_code_processing(self, new_build_config: dict, current_build_config: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_build_config, current_build_config)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_build_config\n # and update the frontend_node with those values\n update_template_values(frontend_template=frontend_node, raw_template=current_build_config[\"template\"])\n return frontend_node\n" + }, + "context": { + "advanced": false, + "display_name": "context", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "context", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "template": { + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "prompt", + "value": "{context}\n\nUser: {user_message}\nAI: " + }, + "user_message": { + "advanced": false, + "display_name": "user_message", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "user_message", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + } + } + }, + "type": "Prompt" + }, + "dragging": false, + "height": 517, + "id": "Prompt-kXGJN", + "position": { + "x": 1879.4280156201567, + "y": 674.3958274263156 + }, + "positionAbsolute": { + "x": 1879.4280156201567, + "y": 674.3958274263156 + }, + "selected": false, + "type": "genericNode", + "width": 384 + } + ], + "viewport": { + "x": -592.532107710133, + "y": -149.32118023592653, + "zoom": 0.5372819347267049 + } + }, + "description": "This project can be used as a starting point for building a Chat experience with user specific memory. You can set a different Session ID to start a new message history.", + "endpoint_name": null, + "id": "b4832b74-d12c-4c00-94e9-4d873abf56eb", + "is_component": false, + "last_tested_version": "1.0.0rc1", + "name": "Memory Chatbot" +} \ No newline at end of file From 39320ae31e8dbbfce390888aa2403ecfbba2567c Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 09:21:50 -0300 Subject: [PATCH 078/229] refactor: Update nodeColors and nodeNames in styleUtils.ts for consistency --- src/frontend/src/utils/styleUtils.ts | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/frontend/src/utils/styleUtils.ts b/src/frontend/src/utils/styleUtils.ts index 1bc4818b5..30a22fd60 100644 --- a/src/frontend/src/utils/styleUtils.ts +++ b/src/frontend/src/utils/styleUtils.ts @@ -269,7 +269,7 @@ export const nodeColors: { [char: string]: string } = { toolkits: "#DB2C2C", wrappers: "#E6277A", helpers: "#31A3CC", - experimental: "#E6277A", + prototypes: "#E6277A", langchain_utilities: "#31A3CC", output_parsers: "#E6A627", // custom_components: "#ab11ab", @@ -310,7 +310,7 @@ export const nodeNames: { [char: string]: string } = { textsplitters: "Text Splitters", retrievers: "Retrievers", helpers: "Helpers", - experimental: "Experimental", + prototypes: "Prototypes", langchain_utilities: "Utilities", output_parsers: "Output Parsers", custom_components: "Custom", @@ -422,7 +422,7 @@ export const nodeIconsLucide: iconsType = { wrappers: Gift, helpers: Wand2, ScanEye, - experimental: FlaskConical, + prototypes: FlaskConical, langchain_utilities: PocketKnife, WolframAlphaAPIWrapper: SvgWolfram, output_parsers: Compass, From bb785c7be4cbd9c8e75210ecb4ea04a3b528f54b Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 09:25:12 -0300 Subject: [PATCH 079/229] fix: remove prompt chaining project --- .../Langflow Prompt Chaining.json | 1776 ----------------- 1 file changed, 1776 deletions(-) delete mode 100644 src/backend/base/langflow/initial_setup/starter_projects/Langflow Prompt Chaining.json diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Prompt Chaining.json b/src/backend/base/langflow/initial_setup/starter_projects/Langflow Prompt Chaining.json deleted file mode 100644 index b2ecbd035..000000000 --- a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Prompt Chaining.json +++ /dev/null @@ -1,1776 +0,0 @@ -{ - "data": { - "edges": [ - { - "className": "stroke-gray-900 stroke-connection", - "data": { - "sourceHandle": { - "dataType": "TextInput", - "id": "TextInput-sptaH", - "name": "text", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "document", - "id": "Prompt-amqBu", - "inputTypes": [ - "Document", - "Message", - "Record", - "Text" - ], - "type": "str" - } - }, - "id": "reactflow__edge-TextInput-sptaH{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œTextInputœ,œidœ:œTextInput-sptaHœ}-Prompt-amqBu{œfieldNameœ:œdocumentœ,œidœ:œPrompt-amqBuœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}", - "source": "TextInput-sptaH", - "sourceHandle": "{œdataTypeœ: œTextInputœ, œidœ: œTextInput-sptaHœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", - "style": { - "stroke": "#555" - }, - "target": "Prompt-amqBu", - "targetHandle": "{œfieldNameœ: œdocumentœ, œidœ: œPrompt-amqBuœ, œinputTypesœ: [œDocumentœ, œMessageœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" - }, - { - "className": "stroke-gray-900 stroke-connection", - "data": { - "sourceHandle": { - "dataType": "Prompt", - "id": "Prompt-amqBu", - "name": "text", - "output_types": [] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "TextOutput-2MS4a", - "inputTypes": [ - "Record", - "Text" - ], - "type": "str" - } - }, - "id": "reactflow__edge-Prompt-amqBu{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-amqBuœ}-TextOutput-2MS4a{œfieldNameœ:œinput_valueœ,œidœ:œTextOutput-2MS4aœ,œinputTypesœ:[œRecordœ,œTextœ],œtypeœ:œstrœ}", - "source": "Prompt-amqBu", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-amqBuœ, œnameœ: œtextœ, œoutput_typesœ: []}", - "style": { - "stroke": "#555" - }, - "target": "TextOutput-2MS4a", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œTextOutput-2MS4aœ, œinputTypesœ: [œRecordœ, œTextœ], œtypeœ: œstrœ}" - }, - { - "className": "stroke-gray-900 stroke-connection", - "data": { - "sourceHandle": { - "dataType": "Prompt", - "id": "Prompt-amqBu", - "name": "prompt", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "OpenAIModel-uYXZJ", - "inputTypes": [ - "Message" - ], - "type": "str" - } - }, - "id": "reactflow__edge-Prompt-amqBu{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-amqBuœ}-OpenAIModel-uYXZJ{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-uYXZJœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", - "source": "Prompt-amqBu", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-amqBuœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "style": { - "stroke": "#555" - }, - "target": "OpenAIModel-uYXZJ", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-uYXZJœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" - }, - { - "className": "stroke-gray-900 stroke-connection", - "data": { - "sourceHandle": { - "dataType": "OpenAIModel", - "id": "OpenAIModel-uYXZJ", - "name": "text_output", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "summary", - "id": "Prompt-gTNiz", - "inputTypes": [ - "Document", - "Message", - "Record", - "Text" - ], - "type": "str" - } - }, - "id": "reactflow__edge-OpenAIModel-uYXZJ{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-uYXZJœ}-Prompt-gTNiz{œfieldNameœ:œsummaryœ,œidœ:œPrompt-gTNizœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-uYXZJ", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-uYXZJœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "style": { - "stroke": "#555" - }, - "target": "Prompt-gTNiz", - "targetHandle": "{œfieldNameœ: œsummaryœ, œidœ: œPrompt-gTNizœ, œinputTypesœ: [œDocumentœ, œMessageœ, œRecordœ, œTextœ], œtypeœ: œstrœ}" - }, - { - "className": "stroke-gray-900 stroke-connection", - "data": { - "sourceHandle": { - "dataType": "OpenAIModel", - "id": "OpenAIModel-uYXZJ", - "name": "text_output", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "ChatOutput-EJkG3", - "inputTypes": [ - "Message", - "str" - ], - "type": "str" - } - }, - "id": "reactflow__edge-OpenAIModel-uYXZJ{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-uYXZJœ}-ChatOutput-EJkG3{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-EJkG3œ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-uYXZJ", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-uYXZJœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "style": { - "stroke": "#555" - }, - "target": "ChatOutput-EJkG3", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-EJkG3œ, œinputTypesœ: [œMessageœ, œstrœ], œtypeœ: œstrœ}" - }, - { - "className": "stroke-gray-900 stroke-connection", - "data": { - "sourceHandle": { - "dataType": "Prompt", - "id": "Prompt-gTNiz", - "name": "text", - "output_types": [] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "TextOutput-MUDOR", - "inputTypes": [ - "Record", - "Text" - ], - "type": "str" - } - }, - "id": "reactflow__edge-Prompt-gTNiz{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-gTNizœ}-TextOutput-MUDOR{œfieldNameœ:œinput_valueœ,œidœ:œTextOutput-MUDORœ,œinputTypesœ:[œRecordœ,œTextœ],œtypeœ:œstrœ}", - "source": "Prompt-gTNiz", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-gTNizœ, œnameœ: œtextœ, œoutput_typesœ: []}", - "style": { - "stroke": "#555" - }, - "target": "TextOutput-MUDOR", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œTextOutput-MUDORœ, œinputTypesœ: [œRecordœ, œTextœ], œtypeœ: œstrœ}" - }, - { - "className": "stroke-gray-900 stroke-connection", - "data": { - "sourceHandle": { - "dataType": "Prompt", - "id": "Prompt-gTNiz", - "name": "prompt", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "OpenAIModel-XawYB", - "inputTypes": [ - "Message" - ], - "type": "str" - } - }, - "id": "reactflow__edge-Prompt-gTNiz{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-gTNizœ}-OpenAIModel-XawYB{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-XawYBœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", - "source": "Prompt-gTNiz", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-gTNizœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "style": { - "stroke": "#555" - }, - "target": "OpenAIModel-XawYB", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-XawYBœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" - }, - { - "className": "stroke-gray-900 stroke-connection", - "data": { - "sourceHandle": { - "dataType": "OpenAIModel", - "id": "OpenAIModel-XawYB", - "name": "text_output", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "ChatOutput-DNmvg", - "inputTypes": [ - "Message", - "str" - ], - "type": "str" - } - }, - "id": "reactflow__edge-OpenAIModel-XawYB{œbaseClassesœ:[œstrœ,œTextœ,œobjectœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-XawYBœ}-ChatOutput-DNmvg{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-DNmvgœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-XawYB", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-XawYBœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "style": { - "stroke": "#555" - }, - "target": "ChatOutput-DNmvg", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-DNmvgœ, œinputTypesœ: [œMessageœ, œstrœ], œtypeœ: œstrœ}" - } - ], - "nodes": [ - { - "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "id": "Prompt-amqBu", - "node": { - "base_classes": [ - "object", - "str", - "Text" - ], - "beta": false, - "custom_fields": { - "template": [ - "document" - ] - }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "documentation": "", - "error": null, - "field_formatters": {}, - "field_order": [], - "frozen": false, - "full_path": null, - "icon": "prompts", - "is_composition": null, - "is_input": null, - "is_output": null, - "name": "", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Prompt Message", - "method": "build_prompt", - "name": "prompt", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n" - }, - "document": { - "advanced": false, - "display_name": "document", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Document", - "Message", - "Record", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "document", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "template": { - "advanced": false, - "display_name": "Template", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "template", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "prompt", - "value": "You are a helpful assistant. Given a long document, your task is to create a concise summary that captures the main points and key details. The summary should be clear, accurate, and succinct. Please provide the summary in the format below:\n####\n{document}\n####\n" - } - } - }, - "type": "Prompt" - }, - "dragging": false, - "height": 385, - "id": "Prompt-amqBu", - "position": { - "x": 2191.5837146441663, - "y": 1047.9307944451873 - }, - "positionAbsolute": { - "x": 2191.5837146441663, - "y": 1047.9307944451873 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "id": "Prompt-gTNiz", - "node": { - "base_classes": [ - "object", - "str", - "Text" - ], - "beta": false, - "custom_fields": { - "template": [ - "summary" - ] - }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "documentation": "", - "error": null, - "field_formatters": {}, - "field_order": [], - "frozen": false, - "full_path": null, - "icon": "prompts", - "is_composition": null, - "is_input": null, - "is_output": null, - "name": "", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Prompt Message", - "method": "build_prompt", - "name": "prompt", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n" - }, - "summary": { - "advanced": false, - "display_name": "summary", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Document", - "Message", - "Record", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "summary", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "template": { - "advanced": false, - "display_name": "Template", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "template", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "prompt", - "value": "Given a summary of an article, please create two multiple-choice questions that cover the key points and details mentioned. Ensure the questions are clear and provide three options (A, B, C), with one correct answer.\n####\n{summary}\n####" - } - } - }, - "type": "Prompt" - }, - "dragging": false, - "height": 385, - "id": "Prompt-gTNiz", - "position": { - "x": 3731.0813766902447, - "y": 799.631909121391 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "ChatOutput-EJkG3", - "node": { - "base_classes": [ - "object", - "Record", - "Text", - "str" - ], - "beta": false, - "custom_fields": { - "input_value": null, - "record_template": null, - "return_record": null, - "sender": null, - "sender_name": null, - "session_id": null - }, - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "documentation": "", - "field_formatters": {}, - "field_order": [], - "frozen": false, - "icon": "ChatOutput", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, Output, MessageTextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Message to be passed as output.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Type of sender.", - "input_types": [ - "Text" - ], - "list": true, - "load_from_db": false, - "multiline": false, - "name": "sender", - "options": [ - "Machine", - "User" - ], - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "Machine" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Name of the sender.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "sender_name", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "AI" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Session ID for the message.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "session_id", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - } - } - }, - "type": "ChatOutput" - }, - "dragging": false, - "height": 385, - "id": "ChatOutput-EJkG3", - "position": { - "x": 3722.1747844849388, - "y": 1283.413553222214 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "ChatOutput-DNmvg", - "node": { - "base_classes": [ - "object", - "Record", - "Text", - "str" - ], - "beta": false, - "custom_fields": { - "input_value": null, - "record_template": null, - "return_record": null, - "sender": null, - "sender_name": null, - "session_id": null - }, - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "documentation": "", - "field_formatters": {}, - "field_order": [], - "frozen": false, - "icon": "ChatOutput", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, Output, MessageTextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Message to be passed as output.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Type of sender.", - "input_types": [ - "Text" - ], - "list": true, - "load_from_db": false, - "multiline": false, - "name": "sender", - "options": [ - "Machine", - "User" - ], - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "Machine" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Name of the sender.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "sender_name", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "AI" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Session ID for the message.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "session_id", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - } - } - }, - "type": "ChatOutput" - }, - "height": 385, - "id": "ChatOutput-DNmvg", - "position": { - "x": 5077.71285886074, - "y": 1232.9152769735522 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "TextInput-sptaH", - "node": { - "base_classes": [ - "str", - "Text", - "object" - ], - "beta": false, - "custom_fields": { - "input_value": null, - "record_template": null - }, - "description": "Get text inputs from the Playground.", - "display_name": "Text Input", - "documentation": "", - "field_formatters": {}, - "field_order": [], - "frozen": false, - "icon": "type", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.io.text import TextComponent\nfrom langflow.io import Output, MessageTextInput\nfrom langflow.schema.message import Message\n\n\nclass TextInputComponent(TextComponent):\n display_name = \"Text Input\"\n description = \"Get text inputs from the Playground.\"\n icon = \"type\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Text to be passed as input.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Message:\n message = Message(\n text=self.input_value,\n )\n return message\n" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Text to be passed as input.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - } - } - }, - "type": "TextInput" - }, - "dragging": false, - "height": 290, - "id": "TextInput-sptaH", - "position": { - "x": 1700.5624822024752, - "y": 1039.603088937466 - }, - "positionAbsolute": { - "x": 1700.5624822024752, - "y": 1039.603088937466 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "TextOutput-2MS4a", - "node": { - "base_classes": [ - "str", - "Text", - "object" - ], - "beta": false, - "custom_fields": { - "input_value": null, - "record_template": null - }, - "description": "Display a text output in the Playground.", - "display_name": "First Prompt", - "documentation": "", - "field_formatters": {}, - "field_order": [], - "frozen": false, - "icon": "type", - "output_types": [ - "Text" - ], - "template": { - "_type": "CustomComponent", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from typing import Optional\n\nfrom langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\n\n\nclass TextOutput(TextComponent):\n display_name = \"Text Output\"\n description = \"Display a text output in the Playground.\"\n icon = \"type\"\n\n def build_config(self):\n return {\n \"input_value\": {\n \"display_name\": \"Value\",\n \"input_types\": [\"Record\", \"Text\"],\n \"info\": \"Text or Record to be passed as output.\",\n },\n \"record_template\": {\n \"display_name\": \"Record Template\",\n \"multiline\": True,\n \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n \"advanced\": True,\n },\n }\n\n def build(self, input_value: Optional[Text] = \"\", record_template: str = \"\") -> Text:\n return super().build(input_value=input_value, record_template=record_template)\n" - }, - "input_value": { - "advanced": false, - "display_name": "Value", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Text or Record to be passed as output.", - "input_types": [ - "Record", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "input_value", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "record_template": { - "advanced": true, - "display_name": "Record Template", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "record_template", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - } - } - }, - "type": "TextOutput" - }, - "dragging": false, - "height": 290, - "id": "TextOutput-2MS4a", - "position": { - "x": 2917.216113690115, - "y": 513.0058511435552 - }, - "positionAbsolute": { - "x": 2917.216113690115, - "y": 513.0058511435552 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "OpenAIModel-uYXZJ", - "node": { - "base_classes": [ - "str", - "Text", - "object" - ], - "beta": false, - "custom_fields": { - "input_value": null, - "max_tokens": null, - "model_kwargs": null, - "model_name": null, - "openai_api_base": null, - "openai_api_key": null, - "stream": null, - "system_message": null, - "temperature": null - }, - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "documentation": "", - "field_formatters": {}, - "field_order": [ - "max_tokens", - "model_kwargs", - "model_name", - "openai_api_base", - "openai_api_key", - "temperature", - "input_value", - "system_message", - "stream" - ], - "frozen": false, - "icon": "OpenAI", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text_output", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Message:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n\n return output\n" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "max_tokens": { - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "max_tokens", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "model_kwargs", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "model_name": { - "advanced": false, - "display_name": "Model Name", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Text" - ], - "list": true, - "load_from_db": false, - "multiline": false, - "name": "model_name", - "options": [ - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "gpt-3.5-turbo" - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "openai_api_base", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_api_key": { - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [], - "list": false, - "load_from_db": true, - "multiline": false, - "name": "openai_api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "OPENAI_API_KEY" - }, - "stream": { - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Stream the response from the model. Streaming works only in Chat.", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "stream", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": false - }, - "system_message": { - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "System message to pass to the model.", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "system_message", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "temperature": { - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "temperature", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 565, - "id": "OpenAIModel-uYXZJ", - "position": { - "x": 2925.784767523062, - "y": 933.6465680967775 - }, - "positionAbsolute": { - "x": 2925.784767523062, - "y": 933.6465680967775 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "TextOutput-MUDOR", - "node": { - "base_classes": [ - "str", - "Text", - "object" - ], - "beta": false, - "custom_fields": { - "input_value": null, - "record_template": null - }, - "description": "Display a text output in the Playground.", - "display_name": "Second Prompt", - "documentation": "", - "field_formatters": {}, - "field_order": [], - "frozen": false, - "icon": "type", - "output_types": [ - "Text" - ], - "template": { - "_type": "CustomComponent", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from typing import Optional\n\nfrom langflow.base.io.text import TextComponent\nfrom langflow.field_typing import Text\n\n\nclass TextOutput(TextComponent):\n display_name = \"Text Output\"\n description = \"Display a text output in the Playground.\"\n icon = \"type\"\n\n def build_config(self):\n return {\n \"input_value\": {\n \"display_name\": \"Value\",\n \"input_types\": [\"Record\", \"Text\"],\n \"info\": \"Text or Record to be passed as output.\",\n },\n \"record_template\": {\n \"display_name\": \"Record Template\",\n \"multiline\": True,\n \"info\": \"Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.\",\n \"advanced\": True,\n },\n }\n\n def build(self, input_value: Optional[Text] = \"\", record_template: str = \"\") -> Text:\n return super().build(input_value=input_value, record_template=record_template)\n" - }, - "input_value": { - "advanced": false, - "display_name": "Value", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Text or Record to be passed as output.", - "input_types": [ - "Record", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "input_value", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "record_template": { - "advanced": true, - "display_name": "Record Template", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "record_template", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - } - } - }, - "type": "TextOutput" - }, - "dragging": false, - "height": 290, - "id": "TextOutput-MUDOR", - "position": { - "x": 4446.064323520379, - "y": 633.833297518702 - }, - "positionAbsolute": { - "x": 4446.064323520379, - "y": 633.833297518702 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "OpenAIModel-XawYB", - "node": { - "base_classes": [ - "str", - "Text", - "object" - ], - "beta": false, - "custom_fields": { - "input_value": null, - "max_tokens": null, - "model_kwargs": null, - "model_name": null, - "openai_api_base": null, - "openai_api_key": null, - "stream": null, - "system_message": null, - "temperature": null - }, - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "documentation": "", - "field_formatters": {}, - "field_order": [ - "max_tokens", - "model_kwargs", - "model_name", - "openai_api_base", - "openai_api_key", - "temperature", - "input_value", - "system_message", - "stream" - ], - "frozen": false, - "icon": "OpenAI", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "method": "text_response", - "name": "text_output", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\nfrom langflow.schema.message import Message\nfrom langflow.template import Output\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text_output\", method=\"text_response\"),\n Output(display_name=\"Language Model\", name=\"model_output\", method=\"build_model\"),\n ]\n\n def text_response(self) -> Message:\n input_value = self.input_value\n stream = self.stream\n system_message = self.system_message\n output = self.build_model()\n result = self.get_chat_result(output, stream, input_value, system_message)\n self.status = result\n return result\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs or {},\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n seed=seed,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\")\n\n return output\n" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "max_tokens": { - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "max_tokens", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "model_kwargs", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "model_name": { - "advanced": false, - "display_name": "Model Name", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Text" - ], - "list": true, - "load_from_db": false, - "multiline": false, - "name": "model_name", - "options": [ - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "gpt-4o" - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "openai_api_base", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_api_key": { - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [], - "list": false, - "load_from_db": true, - "multiline": false, - "name": "openai_api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "OPENAI_API_KEY" - }, - "stream": { - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "Stream the response from the model. Streaming works only in Chat.", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "stream", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": false - }, - "system_message": { - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "System message to pass to the model.", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "system_message", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "temperature": { - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": false, - "name": "temperature", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 565, - "id": "OpenAIModel-XawYB", - "position": { - "x": 4500.152018344182, - "y": 1027.7382026227656 - }, - "positionAbsolute": { - "x": 4500.152018344182, - "y": 1027.7382026227656 - }, - "selected": false, - "type": "genericNode", - "width": 384 - } - ], - "viewport": { - "x": -383.7251879618552, - "y": 69.19813933800037, - "zoom": 0.3105753483695743 - } - }, - "description": "The Prompt Chaining flow chains prompts with LLMs, refining outputs through iterative stages.", - "id": "85392e54-20f3-4ab5-a179-cb4bef16f639", - "is_component": false, - "last_tested_version": "1.0.0a0", - "name": "Prompt Chaining" -} \ No newline at end of file From c55bbfdc9b856903d07444815b6ff8a571a85ecf Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Mon, 24 Jun 2024 09:26:45 -0300 Subject: [PATCH 080/229] Fixed examples to use gpt 4 --- .../Basic Prompting (Hello, World).json | 62 +++---- .../starter_projects/Blog Writer.json | 98 +++++----- .../starter_projects/Document QA.json | 98 +++++----- .../starter_projects/Memory Chatbot.json | 82 ++++----- .../starter_projects/Vector Store RAG.json | 169 +++++++++--------- 5 files changed, 255 insertions(+), 254 deletions(-) diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json index 217d486c2..72eb03a43 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json @@ -6,7 +6,7 @@ "data": { "sourceHandle": { "dataType": "ChatInput", - "id": "ChatInput-74jnA", + "id": "ChatInput-kMZti", "name": "message", "output_types": [ "Message" @@ -14,7 +14,7 @@ }, "targetHandle": { "fieldName": "user_input", - "id": "Prompt-fpHnR", + "id": "Prompt-p1yTM", "inputTypes": [ "Message", "Text" @@ -22,18 +22,18 @@ "type": "str" } }, - "id": "reactflow__edge-ChatInput-74jnA{œdataTypeœ:œChatInputœ,œidœ:œChatInput-74jnAœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-fpHnR{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-fpHnRœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ChatInput-74jnA", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-74jnAœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-fpHnR", - "targetHandle": "{œfieldNameœ: œuser_inputœ, œidœ: œPrompt-fpHnRœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-ChatInput-kMZti{œdataTypeœ:œChatInputœ,œidœ:œChatInput-kMZtiœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-p1yTM{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-p1yTMœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ChatInput-kMZti", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-kMZtiœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-p1yTM", + "targetHandle": "{œfieldNameœ: œuser_inputœ, œidœ: œPrompt-p1yTMœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "Prompt", - "id": "Prompt-fpHnR", + "id": "Prompt-p1yTM", "name": "prompt", "output_types": [ "Message" @@ -41,25 +41,25 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "OpenAIModel-ehSar", + "id": "OpenAIModel-wC7mR", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-Prompt-fpHnR{œdataTypeœ:œPromptœ,œidœ:œPrompt-fpHnRœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-ehSar{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-ehSarœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-fpHnR", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-fpHnRœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-ehSar", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-ehSarœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-Prompt-p1yTM{œdataTypeœ:œPromptœ,œidœ:œPrompt-p1yTMœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-wC7mR{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-wC7mRœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-p1yTM", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-p1yTMœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-wC7mR", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-wC7mRœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "OpenAIModel", - "id": "OpenAIModel-ehSar", + "id": "OpenAIModel-wC7mR", "name": "text_output", "output_types": [ "Message" @@ -67,18 +67,18 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "ChatOutput-KLLro", + "id": "ChatOutput-xh9wX", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-OpenAIModel-ehSar{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-ehSarœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-KLLro{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-KLLroœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-ehSar", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-ehSarœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-KLLro", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-KLLroœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-OpenAIModel-wC7mR{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-wC7mRœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-xh9wX{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-xh9wXœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-wC7mR", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-wC7mRœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-xh9wX", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-xh9wXœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" } ], "nodes": [ @@ -87,7 +87,7 @@ "description": "Create a prompt template with dynamic variables.", "display_name": "Prompt", "edited": false, - "id": "Prompt-fpHnR", + "id": "Prompt-p1yTM", "node": { "base_classes": [ "Message" @@ -189,7 +189,7 @@ }, "dragging": false, "height": 422, - "id": "Prompt-fpHnR", + "id": "Prompt-p1yTM", "position": { "x": 43.70859256635981, "y": 1115.5304359666682 @@ -207,7 +207,7 @@ "description": "Get chat inputs from the Playground.", "display_name": "Chat Input", "edited": false, - "id": "ChatInput-74jnA", + "id": "ChatInput-kMZti", "node": { "base_classes": [ "Message" @@ -390,7 +390,7 @@ }, "dragging": false, "height": 308, - "id": "ChatInput-74jnA", + "id": "ChatInput-kMZti", "position": { "x": -521.3324537445985, "y": 1089.7620993695407 @@ -408,7 +408,7 @@ "description": "Generates text using OpenAI LLMs.", "display_name": "OpenAI", "edited": false, - "id": "OpenAIModel-ehSar", + "id": "OpenAIModel-wC7mR", "node": { "base_classes": [ "LanguageModel", @@ -552,7 +552,7 @@ "title_case": false, "trace_as_metadata": true, "type": "str", - "value": "gpt-3.5-turbo" + "value": "gpt-4-turbo" }, "openai_api_base": { "advanced": true, @@ -668,7 +668,7 @@ }, "dragging": false, "height": 621, - "id": "OpenAIModel-ehSar", + "id": "OpenAIModel-wC7mR", "position": { "x": 584.9288140250019, "y": 1149.0790574268922 @@ -686,7 +686,7 @@ "description": "Display a chat message in the Playground.", "display_name": "Chat Output", "edited": false, - "id": "ChatOutput-KLLro", + "id": "ChatOutput-xh9wX", "node": { "base_classes": [ "Message" @@ -846,7 +846,7 @@ }, "dragging": false, "height": 308, - "id": "ChatOutput-KLLro", + "id": "ChatOutput-xh9wX", "position": { "x": 1157.3374592784412, "y": 1160.9424490383622 @@ -868,7 +868,7 @@ }, "description": "This flow will get you experimenting with the basics of the UI, the Chat and the Prompt component. \n\nTry changing the Template in it to see how the model behaves. \nYou can change it to this and a Text Input into the `type_of_person` variable : \"Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: \" ", "endpoint_name": null, - "id": "81759149-1e58-4190-b4a4-48a96cf49734", + "id": "65f25afc-1467-4f26-9e8a-d24792e76628", "is_component": false, "last_tested_version": "1.0.0rc1", "name": "Basic Prompting (Hello, World)" diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json b/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json index 5aac92e21..9c9c107a0 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Blog Writer.json @@ -6,7 +6,7 @@ "data": { "sourceHandle": { "dataType": "TextInput", - "id": "TextInput-3mewH", + "id": "TextInput-TDpSd", "name": "text", "output_types": [ "Message" @@ -14,7 +14,7 @@ }, "targetHandle": { "fieldName": "instructions", - "id": "Prompt-wvJkv", + "id": "Prompt-kfWwQ", "inputTypes": [ "Message", "Text" @@ -22,18 +22,18 @@ "type": "str" } }, - "id": "reactflow__edge-TextInput-3mewH{œdataTypeœ:œTextInputœ,œidœ:œTextInput-3mewHœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-wvJkv{œfieldNameœ:œinstructionsœ,œidœ:œPrompt-wvJkvœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "TextInput-3mewH", - "sourceHandle": "{œdataTypeœ: œTextInputœ, œidœ: œTextInput-3mewHœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-wvJkv", - "targetHandle": "{œfieldNameœ: œinstructionsœ, œidœ: œPrompt-wvJkvœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-TextInput-TDpSd{œdataTypeœ:œTextInputœ,œidœ:œTextInput-TDpSdœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-kfWwQ{œfieldNameœ:œinstructionsœ,œidœ:œPrompt-kfWwQœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "TextInput-TDpSd", + "sourceHandle": "{œdataTypeœ: œTextInputœ, œidœ: œTextInput-TDpSdœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-kfWwQ", + "targetHandle": "{œfieldNameœ: œinstructionsœ, œidœ: œPrompt-kfWwQœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "URL", - "id": "URL-SvoqQ", + "id": "URL-hivMA", "name": "data", "output_types": [ "Data" @@ -41,25 +41,25 @@ }, "targetHandle": { "fieldName": "data", - "id": "ParseData-9nIVB", + "id": "ParseData-O4Tzh", "inputTypes": [ "Data" ], "type": "other" } }, - "id": "reactflow__edge-URL-SvoqQ{œdataTypeœ:œURLœ,œidœ:œURL-SvoqQœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-ParseData-9nIVB{œfieldNameœ:œdataœ,œidœ:œParseData-9nIVBœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", - "source": "URL-SvoqQ", - "sourceHandle": "{œdataTypeœ: œURLœ, œidœ: œURL-SvoqQœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", - "target": "ParseData-9nIVB", - "targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-9nIVBœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" + "id": "reactflow__edge-URL-hivMA{œdataTypeœ:œURLœ,œidœ:œURL-hivMAœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-ParseData-O4Tzh{œfieldNameœ:œdataœ,œidœ:œParseData-O4Tzhœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", + "source": "URL-hivMA", + "sourceHandle": "{œdataTypeœ: œURLœ, œidœ: œURL-hivMAœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", + "target": "ParseData-O4Tzh", + "targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-O4Tzhœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "ParseData", - "id": "ParseData-9nIVB", + "id": "ParseData-O4Tzh", "name": "text", "output_types": [ "Message" @@ -67,7 +67,7 @@ }, "targetHandle": { "fieldName": "references", - "id": "Prompt-wvJkv", + "id": "Prompt-kfWwQ", "inputTypes": [ "Message", "Text" @@ -75,18 +75,18 @@ "type": "str" } }, - "id": "reactflow__edge-ParseData-9nIVB{œdataTypeœ:œParseDataœ,œidœ:œParseData-9nIVBœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-wvJkv{œfieldNameœ:œreferencesœ,œidœ:œPrompt-wvJkvœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ParseData-9nIVB", - "sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-9nIVBœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-wvJkv", - "targetHandle": "{œfieldNameœ: œreferencesœ, œidœ: œPrompt-wvJkvœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-ParseData-O4Tzh{œdataTypeœ:œParseDataœ,œidœ:œParseData-O4Tzhœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-kfWwQ{œfieldNameœ:œreferencesœ,œidœ:œPrompt-kfWwQœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ParseData-O4Tzh", + "sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-O4Tzhœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-kfWwQ", + "targetHandle": "{œfieldNameœ: œreferencesœ, œidœ: œPrompt-kfWwQœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "Prompt", - "id": "Prompt-wvJkv", + "id": "Prompt-kfWwQ", "name": "prompt", "output_types": [ "Message" @@ -94,25 +94,25 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "OpenAIModel-2W259", + "id": "OpenAIModel-hVXLt", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-Prompt-wvJkv{œdataTypeœ:œPromptœ,œidœ:œPrompt-wvJkvœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-2W259{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-2W259œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-wvJkv", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-wvJkvœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-2W259", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-2W259œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-Prompt-kfWwQ{œdataTypeœ:œPromptœ,œidœ:œPrompt-kfWwQœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-hVXLt{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-hVXLtœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-kfWwQ", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-kfWwQœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-hVXLt", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-hVXLtœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "OpenAIModel", - "id": "OpenAIModel-2W259", + "id": "OpenAIModel-hVXLt", "name": "text_output", "output_types": [ "Message" @@ -120,18 +120,18 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "ChatOutput-1cGBh", + "id": "ChatOutput-HrMHH", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-OpenAIModel-2W259{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-2W259œ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-1cGBh{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-1cGBhœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-2W259", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-2W259œ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-1cGBh", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-1cGBhœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-OpenAIModel-hVXLt{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-hVXLtœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-HrMHH{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-HrMHHœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-hVXLt", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-hVXLtœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-HrMHH", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-HrMHHœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" } ], "nodes": [ @@ -140,7 +140,7 @@ "description": "Get text inputs from the Playground.", "display_name": "Instructions", "edited": false, - "id": "TextInput-3mewH", + "id": "TextInput-TDpSd", "node": { "base_classes": [ "Message" @@ -217,7 +217,7 @@ }, "dragging": false, "height": 309, - "id": "TextInput-3mewH", + "id": "TextInput-TDpSd", "position": { "x": 735.806436564132, "y": 346.40301122327935 @@ -232,7 +232,7 @@ }, { "data": { - "id": "ParseData-9nIVB", + "id": "ParseData-O4Tzh", "node": { "base_classes": [ "Message" @@ -339,7 +339,7 @@ }, "dragging": false, "height": 377, - "id": "ParseData-9nIVB", + "id": "ParseData-O4Tzh", "position": { "x": 759.575501198118, "y": 760.6953079067359 @@ -357,7 +357,7 @@ "description": "Generates text using OpenAI LLMs.", "display_name": "OpenAI", "edited": false, - "id": "OpenAIModel-2W259", + "id": "OpenAIModel-hVXLt", "node": { "base_classes": [ "LanguageModel", @@ -496,7 +496,7 @@ "show": true, "title_case": false, "type": "str", - "value": "gpt-3.5-turbo" + "value": "gpt-4-turbo" }, "openai_api_base": { "advanced": true, @@ -606,7 +606,7 @@ }, "dragging": false, "height": 699, - "id": "OpenAIModel-2W259", + "id": "OpenAIModel-hVXLt", "position": { "x": 1918.8991680862073, "y": 459.92681406971394 @@ -624,7 +624,7 @@ "description": "Display a chat message in the Playground.", "display_name": "Chat Output", "edited": false, - "id": "ChatOutput-1cGBh", + "id": "ChatOutput-HrMHH", "node": { "base_classes": [ "Message" @@ -784,7 +784,7 @@ }, "dragging": false, "height": 309, - "id": "ChatOutput-1cGBh", + "id": "ChatOutput-HrMHH", "position": { "x": 2473.1294450647747, "y": 668.8159913425238 @@ -801,7 +801,7 @@ "data": { "description": "Create a prompt template with dynamic variables.", "display_name": "Prompt", - "id": "Prompt-wvJkv", + "id": "Prompt-kfWwQ", "node": { "base_classes": [ "Message" @@ -934,7 +934,7 @@ }, "dragging": false, "height": 517, - "id": "Prompt-wvJkv", + "id": "Prompt-kfWwQ", "position": { "x": 1288.0925694176524, "y": 519.4286147510747 @@ -949,7 +949,7 @@ }, { "data": { - "id": "URL-SvoqQ", + "id": "URL-hivMA", "node": { "base_classes": [ "Data" @@ -1030,7 +1030,7 @@ "type": "URL" }, "height": 359, - "id": "URL-SvoqQ", + "id": "URL-hivMA", "position": { "x": 247.90599789054627, "y": 514.1589932671732 @@ -1048,7 +1048,7 @@ }, "description": "This flow can be used to create a blog post following instructions from the user, using two other blogs as reference.", "endpoint_name": null, - "id": "7d35f945-f4ad-4d83-bdd8-3a11ddf6fc44", + "id": "26f5bcac-db01-4696-87dc-f7b38afc74ee", "is_component": false, "last_tested_version": "1.0.0rc1", "name": "Blog Writer" diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Document QA.json b/src/backend/base/langflow/initial_setup/starter_projects/Document QA.json index b813d5f50..cdfacf1c7 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Document QA.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Document QA.json @@ -6,7 +6,7 @@ "data": { "sourceHandle": { "dataType": "File", - "id": "File-mzZHT", + "id": "File-31fJd", "name": "data", "output_types": [ "Data" @@ -14,25 +14,25 @@ }, "targetHandle": { "fieldName": "data", - "id": "ParseData-SAHub", + "id": "ParseData-rLcoq", "inputTypes": [ "Data" ], "type": "other" } }, - "id": "reactflow__edge-File-mzZHT{œdataTypeœ:œFileœ,œidœ:œFile-mzZHTœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-ParseData-SAHub{œfieldNameœ:œdataœ,œidœ:œParseData-SAHubœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", - "source": "File-mzZHT", - "sourceHandle": "{œdataTypeœ: œFileœ, œidœ: œFile-mzZHTœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", - "target": "ParseData-SAHub", - "targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-SAHubœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" + "id": "reactflow__edge-File-31fJd{œdataTypeœ:œFileœ,œidœ:œFile-31fJdœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-ParseData-rLcoq{œfieldNameœ:œdataœ,œidœ:œParseData-rLcoqœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", + "source": "File-31fJd", + "sourceHandle": "{œdataTypeœ: œFileœ, œidœ: œFile-31fJdœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", + "target": "ParseData-rLcoq", + "targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-rLcoqœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "ParseData", - "id": "ParseData-SAHub", + "id": "ParseData-rLcoq", "name": "text", "output_types": [ "Message" @@ -40,7 +40,7 @@ }, "targetHandle": { "fieldName": "Document", - "id": "Prompt-XHWTr", + "id": "Prompt-L1GxH", "inputTypes": [ "Message", "Text" @@ -48,18 +48,18 @@ "type": "str" } }, - "id": "reactflow__edge-ParseData-SAHub{œdataTypeœ:œParseDataœ,œidœ:œParseData-SAHubœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-XHWTr{œfieldNameœ:œDocumentœ,œidœ:œPrompt-XHWTrœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ParseData-SAHub", - "sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-SAHubœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-XHWTr", - "targetHandle": "{œfieldNameœ: œDocumentœ, œidœ: œPrompt-XHWTrœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-ParseData-rLcoq{œdataTypeœ:œParseDataœ,œidœ:œParseData-rLcoqœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-L1GxH{œfieldNameœ:œDocumentœ,œidœ:œPrompt-L1GxHœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ParseData-rLcoq", + "sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-rLcoqœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-L1GxH", + "targetHandle": "{œfieldNameœ: œDocumentœ, œidœ: œPrompt-L1GxHœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "ChatInput", - "id": "ChatInput-tDiAG", + "id": "ChatInput-RuLDX", "name": "message", "output_types": [ "Message" @@ -67,7 +67,7 @@ }, "targetHandle": { "fieldName": "Question", - "id": "Prompt-XHWTr", + "id": "Prompt-L1GxH", "inputTypes": [ "Message", "Text" @@ -75,18 +75,18 @@ "type": "str" } }, - "id": "reactflow__edge-ChatInput-tDiAG{œdataTypeœ:œChatInputœ,œidœ:œChatInput-tDiAGœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-XHWTr{œfieldNameœ:œQuestionœ,œidœ:œPrompt-XHWTrœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ChatInput-tDiAG", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-tDiAGœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-XHWTr", - "targetHandle": "{œfieldNameœ: œQuestionœ, œidœ: œPrompt-XHWTrœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-ChatInput-RuLDX{œdataTypeœ:œChatInputœ,œidœ:œChatInput-RuLDXœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-L1GxH{œfieldNameœ:œQuestionœ,œidœ:œPrompt-L1GxHœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ChatInput-RuLDX", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-RuLDXœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-L1GxH", + "targetHandle": "{œfieldNameœ: œQuestionœ, œidœ: œPrompt-L1GxHœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "Prompt", - "id": "Prompt-XHWTr", + "id": "Prompt-L1GxH", "name": "prompt", "output_types": [ "Message" @@ -94,25 +94,25 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "OpenAIModel-HJR46", + "id": "OpenAIModel-4ptCk", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-Prompt-XHWTr{œdataTypeœ:œPromptœ,œidœ:œPrompt-XHWTrœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-HJR46{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-HJR46œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-XHWTr", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-XHWTrœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-HJR46", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-HJR46œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-Prompt-L1GxH{œdataTypeœ:œPromptœ,œidœ:œPrompt-L1GxHœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-4ptCk{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-4ptCkœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-L1GxH", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-L1GxHœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-4ptCk", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-4ptCkœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "OpenAIModel", - "id": "OpenAIModel-HJR46", + "id": "OpenAIModel-4ptCk", "name": "text_output", "output_types": [ "Message" @@ -120,18 +120,18 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "ChatOutput-ob8F7", + "id": "ChatOutput-DYHPP", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-OpenAIModel-HJR46{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-HJR46œ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-ob8F7{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-ob8F7œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-HJR46", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-HJR46œ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-ob8F7", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-ob8F7œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-OpenAIModel-4ptCk{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-4ptCkœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-DYHPP{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-DYHPPœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-4ptCk", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-4ptCkœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-DYHPP", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-DYHPPœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" } ], "nodes": [ @@ -140,7 +140,7 @@ "description": "Get chat inputs from the Playground.", "display_name": "Chat Input", "edited": false, - "id": "ChatInput-tDiAG", + "id": "ChatInput-RuLDX", "node": { "base_classes": [ "Message" @@ -323,7 +323,7 @@ }, "dragging": false, "height": 309, - "id": "ChatInput-tDiAG", + "id": "ChatInput-RuLDX", "position": { "x": -201.55524461361745, "y": 411.67283602771283 @@ -341,7 +341,7 @@ "description": "Display a chat message in the Playground.", "display_name": "Chat Output", "edited": false, - "id": "ChatOutput-ob8F7", + "id": "ChatOutput-DYHPP", "node": { "base_classes": [ "Message" @@ -501,7 +501,7 @@ }, "dragging": false, "height": 308, - "id": "ChatOutput-ob8F7", + "id": "ChatOutput-DYHPP", "position": { "x": 1733.3012915204283, "y": 168.76098809939327 @@ -518,7 +518,7 @@ "data": { "description": "A generic file loader.", "display_name": "File", - "id": "File-mzZHT", + "id": "File-31fJd", "node": { "base_classes": [ "Data" @@ -627,7 +627,7 @@ }, "dragging": false, "height": 301, - "id": "File-mzZHT", + "id": "File-31fJd", "position": { "x": -423.1448900251602, "y": -230.83411538932458 @@ -645,7 +645,7 @@ "description": "Generates text using OpenAI LLMs.", "display_name": "OpenAI", "edited": false, - "id": "OpenAIModel-HJR46", + "id": "OpenAIModel-4ptCk", "node": { "base_classes": [ "LanguageModel", @@ -784,7 +784,7 @@ "show": true, "title_case": false, "type": "str", - "value": "gpt-3.5-turbo" + "value": "gpt-4-turbo" }, "openai_api_base": { "advanced": true, @@ -894,7 +894,7 @@ }, "dragging": false, "height": 622, - "id": "OpenAIModel-HJR46", + "id": "OpenAIModel-4ptCk", "position": { "x": 1205.1434354219589, "y": -39.953851445891985 @@ -911,7 +911,7 @@ "data": { "description": "Create a prompt template with dynamic variables.", "display_name": "Prompt", - "id": "Prompt-XHWTr", + "id": "Prompt-L1GxH", "node": { "base_classes": [ "Message" @@ -1044,7 +1044,7 @@ }, "dragging": false, "height": 517, - "id": "Prompt-XHWTr", + "id": "Prompt-L1GxH", "position": { "x": 641.7559080574213, "y": 96.74239207995313 @@ -1059,7 +1059,7 @@ }, { "data": { - "id": "ParseData-SAHub", + "id": "ParseData-rLcoq", "node": { "base_classes": [ "Message" @@ -1176,7 +1176,7 @@ }, "dragging": false, "height": 385, - "id": "ParseData-SAHub", + "id": "ParseData-rLcoq", "position": { "x": 122.60847618765547, "y": -109.41723790443038 @@ -1198,7 +1198,7 @@ }, "description": "This flow integrates PDF reading with a language model to answer document-specific questions. Ideal for small-scale texts, it facilitates direct queries with immediate insights.", "endpoint_name": null, - "id": "69331d5f-fd14-4ea4-be1f-fd3a8c370562", + "id": "ebaa8c25-5d89-4f31-a945-3804be72ac58", "is_component": false, "last_tested_version": "1.0.0rc1", "name": "Document QA" diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json b/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json index 755f6ae1e..0ab839eee 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Memory Chatbot.json @@ -6,7 +6,7 @@ "data": { "sourceHandle": { "dataType": "Memory", - "id": "Memory-Kt0An", + "id": "Memory-A4OPp", "name": "messages_text", "output_types": [ "Message" @@ -14,7 +14,7 @@ }, "targetHandle": { "fieldName": "context", - "id": "Prompt-kXGJN", + "id": "Prompt-xhlQ7", "inputTypes": [ "Message", "Text" @@ -22,18 +22,18 @@ "type": "str" } }, - "id": "reactflow__edge-Memory-Kt0An{œdataTypeœ:œMemoryœ,œidœ:œMemory-Kt0Anœ,œnameœ:œmessages_textœ,œoutput_typesœ:[œMessageœ]}-Prompt-kXGJN{œfieldNameœ:œcontextœ,œidœ:œPrompt-kXGJNœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "Memory-Kt0An", - "sourceHandle": "{œdataTypeœ: œMemoryœ, œidœ: œMemory-Kt0Anœ, œnameœ: œmessages_textœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-kXGJN", - "targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-kXGJNœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-Memory-A4OPp{œdataTypeœ:œMemoryœ,œidœ:œMemory-A4OPpœ,œnameœ:œmessages_textœ,œoutput_typesœ:[œMessageœ]}-Prompt-xhlQ7{œfieldNameœ:œcontextœ,œidœ:œPrompt-xhlQ7œ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "Memory-A4OPp", + "sourceHandle": "{œdataTypeœ: œMemoryœ, œidœ: œMemory-A4OPpœ, œnameœ: œmessages_textœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-xhlQ7", + "targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-xhlQ7œ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "ChatInput", - "id": "ChatInput-krw2d", + "id": "ChatInput-ENTF8", "name": "message", "output_types": [ "Message" @@ -41,7 +41,7 @@ }, "targetHandle": { "fieldName": "user_message", - "id": "Prompt-kXGJN", + "id": "Prompt-xhlQ7", "inputTypes": [ "Message", "Text" @@ -49,18 +49,18 @@ "type": "str" } }, - "id": "reactflow__edge-ChatInput-krw2d{œdataTypeœ:œChatInputœ,œidœ:œChatInput-krw2dœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-kXGJN{œfieldNameœ:œuser_messageœ,œidœ:œPrompt-kXGJNœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ChatInput-krw2d", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-krw2dœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-kXGJN", - "targetHandle": "{œfieldNameœ: œuser_messageœ, œidœ: œPrompt-kXGJNœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-ChatInput-ENTF8{œdataTypeœ:œChatInputœ,œidœ:œChatInput-ENTF8œ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-xhlQ7{œfieldNameœ:œuser_messageœ,œidœ:œPrompt-xhlQ7œ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ChatInput-ENTF8", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-ENTF8œ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-xhlQ7", + "targetHandle": "{œfieldNameœ: œuser_messageœ, œidœ: œPrompt-xhlQ7œ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "Prompt", - "id": "Prompt-kXGJN", + "id": "Prompt-xhlQ7", "name": "prompt", "output_types": [ "Message" @@ -68,25 +68,25 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "OpenAIModel-GAzmc", + "id": "OpenAIModel-ZBIVC", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-Prompt-kXGJN{œdataTypeœ:œPromptœ,œidœ:œPrompt-kXGJNœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-GAzmc{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-GAzmcœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-kXGJN", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-kXGJNœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-GAzmc", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-GAzmcœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-Prompt-xhlQ7{œdataTypeœ:œPromptœ,œidœ:œPrompt-xhlQ7œ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-ZBIVC{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-ZBIVCœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-xhlQ7", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-xhlQ7œ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-ZBIVC", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-ZBIVCœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "OpenAIModel", - "id": "OpenAIModel-GAzmc", + "id": "OpenAIModel-ZBIVC", "name": "text_output", "output_types": [ "Message" @@ -94,18 +94,18 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "ChatOutput-Q4j7S", + "id": "ChatOutput-e8ruq", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-OpenAIModel-GAzmc{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-GAzmcœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-Q4j7S{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-Q4j7Sœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-GAzmc", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-GAzmcœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-Q4j7S", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-Q4j7Sœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-OpenAIModel-ZBIVC{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-ZBIVCœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-e8ruq{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-e8ruqœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-ZBIVC", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-ZBIVCœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-e8ruq", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-e8ruqœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" } ], "nodes": [ @@ -114,7 +114,7 @@ "description": "Retrieves stored chat messages.", "display_name": "Memory", "edited": false, - "id": "Memory-Kt0An", + "id": "Memory-A4OPp", "node": { "base_classes": [ "Data", @@ -294,7 +294,7 @@ }, "dragging": false, "height": 267, - "id": "Memory-Kt0An", + "id": "Memory-A4OPp", "position": { "x": 1258.8089948698466, "y": 547.1243849102437 @@ -312,7 +312,7 @@ "description": "Get chat inputs from the Playground.", "display_name": "Chat Input", "edited": false, - "id": "ChatInput-krw2d", + "id": "ChatInput-ENTF8", "node": { "base_classes": [ "Message" @@ -495,7 +495,7 @@ }, "dragging": true, "height": 309, - "id": "ChatInput-krw2d", + "id": "ChatInput-ENTF8", "position": { "x": 1261.3748612945249, "y": 912.733279525042 @@ -504,7 +504,7 @@ "x": 1261.3748612945249, "y": 912.733279525042 }, - "selected": true, + "selected": false, "type": "genericNode", "width": 384 }, @@ -513,7 +513,7 @@ "description": "Generates text using OpenAI LLMs.", "display_name": "OpenAI", "edited": false, - "id": "OpenAIModel-GAzmc", + "id": "OpenAIModel-ZBIVC", "node": { "base_classes": [ "LanguageModel", @@ -652,7 +652,7 @@ "show": true, "title_case": false, "type": "str", - "value": "gpt-3.5-turbo" + "value": "gpt-4-turbo" }, "openai_api_base": { "advanced": true, @@ -762,7 +762,7 @@ }, "dragging": false, "height": 622, - "id": "OpenAIModel-GAzmc", + "id": "OpenAIModel-ZBIVC", "position": { "x": 2495.6628431453228, "y": 669.9567653609598 @@ -780,7 +780,7 @@ "description": "Display a chat message in the Playground.", "display_name": "Chat Output", "edited": false, - "id": "ChatOutput-Q4j7S", + "id": "ChatOutput-e8ruq", "node": { "base_classes": [ "Message" @@ -940,7 +940,7 @@ }, "dragging": false, "height": 308, - "id": "ChatOutput-Q4j7S", + "id": "ChatOutput-e8ruq", "position": { "x": 3028.2686266398873, "y": 888.0854888768531 @@ -957,7 +957,7 @@ "data": { "description": "Create a prompt template with dynamic variables.", "display_name": "Prompt", - "id": "Prompt-kXGJN", + "id": "Prompt-xhlQ7", "node": { "base_classes": [ "Message" @@ -1090,7 +1090,7 @@ }, "dragging": false, "height": 517, - "id": "Prompt-kXGJN", + "id": "Prompt-xhlQ7", "position": { "x": 1879.4280156201567, "y": 674.3958274263156 @@ -1112,7 +1112,7 @@ }, "description": "This project can be used as a starting point for building a Chat experience with user specific memory. You can set a different Session ID to start a new message history.", "endpoint_name": null, - "id": "b4832b74-d12c-4c00-94e9-4d873abf56eb", + "id": "909c382d-d215-4d50-91b3-dcb6f3ffd93c", "is_component": false, "last_tested_version": "1.0.0rc1", "name": "Memory Chatbot" diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json b/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json index cb1335388..fd4aa39ae 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json @@ -6,7 +6,7 @@ "data": { "sourceHandle": { "dataType": "ChatInput", - "id": "ChatInput-vRBSi", + "id": "ChatInput-nER2k", "name": "message", "output_types": [ "Message" @@ -14,7 +14,7 @@ }, "targetHandle": { "fieldName": "search_input", - "id": "AstraDB-N856w", + "id": "AstraDB-QLZSs", "inputTypes": [ "Message", "str" @@ -22,19 +22,19 @@ "type": "str" } }, - "id": "reactflow__edge-ChatInput-vRBSi{œdataTypeœ:œChatInputœ,œidœ:œChatInput-vRBSiœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-AstraDB-N856w{œfieldNameœ:œsearch_inputœ,œidœ:œAstraDB-N856wœ,œinputTypesœ:[œMessageœ,œstrœ],œtypeœ:œstrœ}", + "id": "reactflow__edge-ChatInput-nER2k{œdataTypeœ:œChatInputœ,œidœ:œChatInput-nER2kœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-AstraDB-QLZSs{œfieldNameœ:œsearch_inputœ,œidœ:œAstraDB-QLZSsœ,œinputTypesœ:[œMessageœ,œstrœ],œtypeœ:œstrœ}", "selected": false, - "source": "ChatInput-vRBSi", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-vRBSiœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "AstraDB-N856w", - "targetHandle": "{œfieldNameœ: œsearch_inputœ, œidœ: œAstraDB-N856wœ, œinputTypesœ: [œMessageœ, œstrœ], œtypeœ: œstrœ}" + "source": "ChatInput-nER2k", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-nER2kœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "AstraDB-QLZSs", + "targetHandle": "{œfieldNameœ: œsearch_inputœ, œidœ: œAstraDB-QLZSsœ, œinputTypesœ: [œMessageœ, œstrœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "OpenAIEmbeddings", - "id": "OpenAIEmbeddings-ftAK3", + "id": "OpenAIEmbeddings-ylry8", "name": "embeddings", "output_types": [ "Embeddings" @@ -42,26 +42,26 @@ }, "targetHandle": { "fieldName": "embedding", - "id": "AstraDB-N856w", + "id": "AstraDB-QLZSs", "inputTypes": [ "Embeddings" ], "type": "other" } }, - "id": "reactflow__edge-OpenAIEmbeddings-ftAK3{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-ftAK3œ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}-AstraDB-N856w{œfieldNameœ:œembeddingœ,œidœ:œAstraDB-N856wœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}", + "id": "reactflow__edge-OpenAIEmbeddings-ylry8{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-ylry8œ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}-AstraDB-QLZSs{œfieldNameœ:œembeddingœ,œidœ:œAstraDB-QLZSsœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}", "selected": false, - "source": "OpenAIEmbeddings-ftAK3", - "sourceHandle": "{œdataTypeœ: œOpenAIEmbeddingsœ, œidœ: œOpenAIEmbeddings-ftAK3œ, œnameœ: œembeddingsœ, œoutput_typesœ: [œEmbeddingsœ]}", - "target": "AstraDB-N856w", - "targetHandle": "{œfieldNameœ: œembeddingœ, œidœ: œAstraDB-N856wœ, œinputTypesœ: [œEmbeddingsœ], œtypeœ: œotherœ}" + "source": "OpenAIEmbeddings-ylry8", + "sourceHandle": "{œdataTypeœ: œOpenAIEmbeddingsœ, œidœ: œOpenAIEmbeddings-ylry8œ, œnameœ: œembeddingsœ, œoutput_typesœ: [œEmbeddingsœ]}", + "target": "AstraDB-QLZSs", + "targetHandle": "{œfieldNameœ: œembeddingœ, œidœ: œAstraDB-QLZSsœ, œinputTypesœ: [œEmbeddingsœ], œtypeœ: œotherœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "AstraDB", - "id": "AstraDB-N856w", + "id": "AstraDB-QLZSs", "name": "search_results", "output_types": [ "Data" @@ -69,26 +69,26 @@ }, "targetHandle": { "fieldName": "data", - "id": "ParseData-Z6n4v", + "id": "ParseData-yHac6", "inputTypes": [ "Data" ], "type": "other" } }, - "id": "reactflow__edge-AstraDB-N856w{œdataTypeœ:œAstraDBœ,œidœ:œAstraDB-N856wœ,œnameœ:œsearch_resultsœ,œoutput_typesœ:[œDataœ]}-ParseData-Z6n4v{œfieldNameœ:œdataœ,œidœ:œParseData-Z6n4vœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", + "id": "reactflow__edge-AstraDB-QLZSs{œdataTypeœ:œAstraDBœ,œidœ:œAstraDB-QLZSsœ,œnameœ:œsearch_resultsœ,œoutput_typesœ:[œDataœ]}-ParseData-yHac6{œfieldNameœ:œdataœ,œidœ:œParseData-yHac6œ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", "selected": false, - "source": "AstraDB-N856w", - "sourceHandle": "{œdataTypeœ: œAstraDBœ, œidœ: œAstraDB-N856wœ, œnameœ: œsearch_resultsœ, œoutput_typesœ: [œDataœ]}", - "target": "ParseData-Z6n4v", - "targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-Z6n4vœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" + "source": "AstraDB-QLZSs", + "sourceHandle": "{œdataTypeœ: œAstraDBœ, œidœ: œAstraDB-QLZSsœ, œnameœ: œsearch_resultsœ, œoutput_typesœ: [œDataœ]}", + "target": "ParseData-yHac6", + "targetHandle": "{œfieldNameœ: œdataœ, œidœ: œParseData-yHac6œ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "ChatInput", - "id": "ChatInput-vRBSi", + "id": "ChatInput-nER2k", "name": "message", "output_types": [ "Message" @@ -96,7 +96,7 @@ }, "targetHandle": { "fieldName": "question", - "id": "Prompt-8YnFi", + "id": "Prompt-V2VHT", "inputTypes": [ "Message", "Text" @@ -104,18 +104,18 @@ "type": "str" } }, - "id": "reactflow__edge-ChatInput-vRBSi{œdataTypeœ:œChatInputœ,œidœ:œChatInput-vRBSiœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-8YnFi{œfieldNameœ:œquestionœ,œidœ:œPrompt-8YnFiœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ChatInput-vRBSi", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-vRBSiœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-8YnFi", - "targetHandle": "{œfieldNameœ: œquestionœ, œidœ: œPrompt-8YnFiœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-ChatInput-nER2k{œdataTypeœ:œChatInputœ,œidœ:œChatInput-nER2kœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-V2VHT{œfieldNameœ:œquestionœ,œidœ:œPrompt-V2VHTœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ChatInput-nER2k", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-nER2kœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-V2VHT", + "targetHandle": "{œfieldNameœ: œquestionœ, œidœ: œPrompt-V2VHTœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "File", - "id": "File-Ldmqs", + "id": "File-OGHlE", "name": "data", "output_types": [ "Data" @@ -123,25 +123,25 @@ }, "targetHandle": { "fieldName": "data_inputs", - "id": "SplitText-bqtiX", + "id": "SplitText-ARuL2", "inputTypes": [ "Data" ], "type": "other" } }, - "id": "reactflow__edge-File-Ldmqs{œdataTypeœ:œFileœ,œidœ:œFile-Ldmqsœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-SplitText-bqtiX{œfieldNameœ:œdata_inputsœ,œidœ:œSplitText-bqtiXœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", - "source": "File-Ldmqs", - "sourceHandle": "{œdataTypeœ: œFileœ, œidœ: œFile-Ldmqsœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", - "target": "SplitText-bqtiX", - "targetHandle": "{œfieldNameœ: œdata_inputsœ, œidœ: œSplitText-bqtiXœ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" + "id": "reactflow__edge-File-OGHlE{œdataTypeœ:œFileœ,œidœ:œFile-OGHlEœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-SplitText-ARuL2{œfieldNameœ:œdata_inputsœ,œidœ:œSplitText-ARuL2œ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", + "source": "File-OGHlE", + "sourceHandle": "{œdataTypeœ: œFileœ, œidœ: œFile-OGHlEœ, œnameœ: œdataœ, œoutput_typesœ: [œDataœ]}", + "target": "SplitText-ARuL2", + "targetHandle": "{œfieldNameœ: œdata_inputsœ, œidœ: œSplitText-ARuL2œ, œinputTypesœ: [œDataœ], œtypeœ: œotherœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "SplitText", - "id": "SplitText-bqtiX", + "id": "SplitText-ARuL2", "name": "chunks", "output_types": [ "Data" @@ -149,7 +149,7 @@ }, "targetHandle": { "fieldName": "vector_store_inputs", - "id": "AstraDB-N856w", + "id": "AstraDB-QLZSs", "inputTypes": [ "Document", "Data" @@ -157,18 +157,18 @@ "type": "other" } }, - "id": "reactflow__edge-SplitText-bqtiX{œdataTypeœ:œSplitTextœ,œidœ:œSplitText-bqtiXœ,œnameœ:œchunksœ,œoutput_typesœ:[œDataœ]}-AstraDB-N856w{œfieldNameœ:œvector_store_inputsœ,œidœ:œAstraDB-N856wœ,œinputTypesœ:[œDocumentœ,œDataœ],œtypeœ:œotherœ}", - "source": "SplitText-bqtiX", - "sourceHandle": "{œdataTypeœ: œSplitTextœ, œidœ: œSplitText-bqtiXœ, œnameœ: œchunksœ, œoutput_typesœ: [œDataœ]}", - "target": "AstraDB-N856w", - "targetHandle": "{œfieldNameœ: œvector_store_inputsœ, œidœ: œAstraDB-N856wœ, œinputTypesœ: [œDocumentœ, œDataœ], œtypeœ: œotherœ}" + "id": "reactflow__edge-SplitText-ARuL2{œdataTypeœ:œSplitTextœ,œidœ:œSplitText-ARuL2œ,œnameœ:œchunksœ,œoutput_typesœ:[œDataœ]}-AstraDB-QLZSs{œfieldNameœ:œvector_store_inputsœ,œidœ:œAstraDB-QLZSsœ,œinputTypesœ:[œDocumentœ,œDataœ],œtypeœ:œotherœ}", + "source": "SplitText-ARuL2", + "sourceHandle": "{œdataTypeœ: œSplitTextœ, œidœ: œSplitText-ARuL2œ, œnameœ: œchunksœ, œoutput_typesœ: [œDataœ]}", + "target": "AstraDB-QLZSs", + "targetHandle": "{œfieldNameœ: œvector_store_inputsœ, œidœ: œAstraDB-QLZSsœ, œinputTypesœ: [œDocumentœ, œDataœ], œtypeœ: œotherœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "ParseData", - "id": "ParseData-Z6n4v", + "id": "ParseData-yHac6", "name": "text", "output_types": [ "Message" @@ -176,7 +176,7 @@ }, "targetHandle": { "fieldName": "context", - "id": "Prompt-8YnFi", + "id": "Prompt-V2VHT", "inputTypes": [ "Message", "Text" @@ -184,18 +184,18 @@ "type": "str" } }, - "id": "reactflow__edge-ParseData-Z6n4v{œdataTypeœ:œParseDataœ,œidœ:œParseData-Z6n4vœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-8YnFi{œfieldNameœ:œcontextœ,œidœ:œPrompt-8YnFiœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ParseData-Z6n4v", - "sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-Z6n4vœ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-8YnFi", - "targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-8YnFiœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-ParseData-yHac6{œdataTypeœ:œParseDataœ,œidœ:œParseData-yHac6œ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-V2VHT{œfieldNameœ:œcontextœ,œidœ:œPrompt-V2VHTœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ParseData-yHac6", + "sourceHandle": "{œdataTypeœ: œParseDataœ, œidœ: œParseData-yHac6œ, œnameœ: œtextœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-V2VHT", + "targetHandle": "{œfieldNameœ: œcontextœ, œidœ: œPrompt-V2VHTœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "Prompt", - "id": "Prompt-8YnFi", + "id": "Prompt-V2VHT", "name": "prompt", "output_types": [ "Message" @@ -203,25 +203,25 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "OpenAIModel-bxsF9", + "id": "OpenAIModel-Tm5Ht", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-Prompt-8YnFi{œdataTypeœ:œPromptœ,œidœ:œPrompt-8YnFiœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-bxsF9{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-bxsF9œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-8YnFi", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-8YnFiœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-bxsF9", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-bxsF9œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-Prompt-V2VHT{œdataTypeœ:œPromptœ,œidœ:œPrompt-V2VHTœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-Tm5Ht{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-Tm5Htœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-V2VHT", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-V2VHTœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-Tm5Ht", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-Tm5Htœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "OpenAIModel", - "id": "OpenAIModel-bxsF9", + "id": "OpenAIModel-Tm5Ht", "name": "text_output", "output_types": [ "Message" @@ -229,18 +229,18 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "ChatOutput-FNGr5", + "id": "ChatOutput-ywruU", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-OpenAIModel-bxsF9{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-bxsF9œ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-FNGr5{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-FNGr5œ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-bxsF9", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-bxsF9œ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-FNGr5", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-FNGr5œ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-OpenAIModel-Tm5Ht{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-Tm5Htœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-ywruU{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-ywruUœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-Tm5Ht", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-Tm5Htœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-ywruU", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-ywruUœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" } ], "nodes": [ @@ -249,7 +249,7 @@ "description": "Get chat inputs from the Playground.", "display_name": "Chat Input", "edited": false, - "id": "ChatInput-vRBSi", + "id": "ChatInput-nER2k", "node": { "base_classes": [ "Message" @@ -275,6 +275,7 @@ { "cache": true, "display_name": "Message", + "hidden": false, "method": "message_response", "name": "message", "selected": "Message", @@ -431,7 +432,7 @@ }, "dragging": false, "height": 309, - "id": "ChatInput-vRBSi", + "id": "ChatInput-nER2k", "position": { "x": 682.002772470747, "y": 253.67030039648512 @@ -446,7 +447,7 @@ }, { "data": { - "id": "OpenAIEmbeddings-ftAK3", + "id": "OpenAIEmbeddings-ylry8", "node": { "base_classes": [ "Embeddings" @@ -844,7 +845,7 @@ }, "dragging": false, "height": 393, - "id": "OpenAIEmbeddings-ftAK3", + "id": "OpenAIEmbeddings-ylry8", "position": { "x": 672.1192980997866, "y": 786.6985113716086 @@ -862,7 +863,7 @@ "description": "Generates text using OpenAI LLMs.", "display_name": "OpenAI", "edited": false, - "id": "OpenAIModel-bxsF9", + "id": "OpenAIModel-Tm5Ht", "node": { "base_classes": [ "LanguageModel", @@ -1001,7 +1002,7 @@ "show": true, "title_case": false, "type": "str", - "value": "gpt-3.5-turbo" + "value": "gpt-4-turbo" }, "openai_api_base": { "advanced": true, @@ -1111,7 +1112,7 @@ }, "dragging": false, "height": 623, - "id": "OpenAIModel-bxsF9", + "id": "OpenAIModel-Tm5Ht", "position": { "x": 3243.967394111999, "y": 392.861541437184 @@ -1129,7 +1130,7 @@ "description": "Display a chat message in the Playground.", "display_name": "Chat Output", "edited": false, - "id": "ChatOutput-FNGr5", + "id": "ChatOutput-ywruU", "node": { "base_classes": [ "Message" @@ -1289,7 +1290,7 @@ }, "dragging": false, "height": 309, - "id": "ChatOutput-FNGr5", + "id": "ChatOutput-ywruU", "position": { "x": 3788.786948642587, "y": 608.4077159222614 @@ -1298,13 +1299,13 @@ "x": 3788.786948642587, "y": 608.4077159222614 }, - "selected": false, + "selected": true, "type": "genericNode", "width": 384 }, { "data": { - "id": "File-Ldmqs", + "id": "File-OGHlE", "node": { "base_classes": [ "Record" @@ -1411,7 +1412,7 @@ }, "dragging": false, "height": 301, - "id": "File-Ldmqs", + "id": "File-OGHlE", "position": { "x": -583.277913381927, "y": 433.34221812460396 @@ -1428,7 +1429,7 @@ "data": { "description": "Implementation of Vector Store using Astra DB with search capabilities", "display_name": "Astra DB Vector Store", - "id": "AstraDB-N856w", + "id": "AstraDB-QLZSs", "node": { "base_classes": [ "Data" @@ -1830,7 +1831,7 @@ }, "dragging": false, "height": 917, - "id": "AstraDB-N856w", + "id": "AstraDB-QLZSs", "position": { "x": 1298.4611042465333, "y": 160.7181472642742 @@ -1845,7 +1846,7 @@ }, { "data": { - "id": "ParseData-Z6n4v", + "id": "ParseData-yHac6", "node": { "base_classes": [ "Message" @@ -1957,7 +1958,7 @@ }, "dragging": false, "height": 385, - "id": "ParseData-Z6n4v", + "id": "ParseData-yHac6", "position": { "x": 1911.4866480237615, "y": 566.903831987901 @@ -1974,7 +1975,7 @@ "data": { "description": "Create a prompt template with dynamic variables.", "display_name": "Prompt", - "id": "Prompt-8YnFi", + "id": "Prompt-V2VHT", "node": { "base_classes": [ "Message" @@ -2107,7 +2108,7 @@ }, "dragging": false, "height": 517, - "id": "Prompt-8YnFi", + "id": "Prompt-V2VHT", "position": { "x": 2537.8054430938064, "y": 442.35183727527414 @@ -2122,7 +2123,7 @@ }, { "data": { - "id": "SplitText-bqtiX", + "id": "SplitText-ARuL2", "node": { "base_classes": [ "Data" @@ -2252,7 +2253,7 @@ }, "dragging": false, "height": 557, - "id": "SplitText-bqtiX", + "id": "SplitText-ARuL2", "position": { "x": 21.318397393309283, "y": 273.27771123167287 @@ -2274,7 +2275,7 @@ }, "description": "Visit https://docs.langflow.org/tutorials/rag-with-astradb for a detailed guide of this project.\nThis project give you both Ingestion and RAG in a single file. You'll need to visit https://astra.datastax.com/ to create an Astra DB instance, your Token and grab an API Endpoint.\nRunning this project requires you to add a file in the Files component, then define a Collection Name and click on the Play icon on the Astra DB component. \n\nAfter the ingestion ends you are ready to click on the Run button at the lower left corner and start asking questions about your data.", "endpoint_name": null, - "id": "0e6c631a-1975-417b-a3f7-c23f97dbf0c7", + "id": "7f5d5057-2371-4796-a398-f0236b963d1f", "is_component": false, "last_tested_version": "1.0.0rc1", "name": "Vector Store RAG" From 4e26b46825169dba26683d9944699c2903793143 Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Mon, 24 Jun 2024 09:28:48 -0300 Subject: [PATCH 081/229] FIxed basic prompting --- .../Basic Prompting (Hello, World).json | 66 +++++++++---------- 1 file changed, 33 insertions(+), 33 deletions(-) diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json index 72eb03a43..283e12da9 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Basic Prompting (Hello, World).json @@ -6,7 +6,7 @@ "data": { "sourceHandle": { "dataType": "ChatInput", - "id": "ChatInput-kMZti", + "id": "ChatInput-cIXVH", "name": "message", "output_types": [ "Message" @@ -14,7 +14,7 @@ }, "targetHandle": { "fieldName": "user_input", - "id": "Prompt-p1yTM", + "id": "Prompt-Ejl8w", "inputTypes": [ "Message", "Text" @@ -22,18 +22,18 @@ "type": "str" } }, - "id": "reactflow__edge-ChatInput-kMZti{œdataTypeœ:œChatInputœ,œidœ:œChatInput-kMZtiœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-p1yTM{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-p1yTMœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ChatInput-kMZti", - "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-kMZtiœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", - "target": "Prompt-p1yTM", - "targetHandle": "{œfieldNameœ: œuser_inputœ, œidœ: œPrompt-p1yTMœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-ChatInput-cIXVH{œdataTypeœ:œChatInputœ,œidœ:œChatInput-cIXVHœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-Ejl8w{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-Ejl8wœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ChatInput-cIXVH", + "sourceHandle": "{œdataTypeœ: œChatInputœ, œidœ: œChatInput-cIXVHœ, œnameœ: œmessageœ, œoutput_typesœ: [œMessageœ]}", + "target": "Prompt-Ejl8w", + "targetHandle": "{œfieldNameœ: œuser_inputœ, œidœ: œPrompt-Ejl8wœ, œinputTypesœ: [œMessageœ, œTextœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "Prompt", - "id": "Prompt-p1yTM", + "id": "Prompt-Ejl8w", "name": "prompt", "output_types": [ "Message" @@ -41,25 +41,25 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "OpenAIModel-wC7mR", + "id": "OpenAIModel-FAF7r", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-Prompt-p1yTM{œdataTypeœ:œPromptœ,œidœ:œPrompt-p1yTMœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-wC7mR{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-wC7mRœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-p1yTM", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-p1yTMœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-wC7mR", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-wC7mRœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-Prompt-Ejl8w{œdataTypeœ:œPromptœ,œidœ:œPrompt-Ejl8wœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-FAF7r{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-FAF7rœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-Ejl8w", + "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-Ejl8wœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", + "target": "OpenAIModel-FAF7r", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-FAF7rœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "OpenAIModel", - "id": "OpenAIModel-wC7mR", + "id": "OpenAIModel-FAF7r", "name": "text_output", "output_types": [ "Message" @@ -67,18 +67,18 @@ }, "targetHandle": { "fieldName": "input_value", - "id": "ChatOutput-xh9wX", + "id": "ChatOutput-riTzX", "inputTypes": [ "Message" ], "type": "str" } }, - "id": "reactflow__edge-OpenAIModel-wC7mR{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-wC7mRœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-xh9wX{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-xh9wXœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-wC7mR", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-wC7mRœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-xh9wX", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-xh9wXœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" + "id": "reactflow__edge-OpenAIModel-FAF7r{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-FAF7rœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-riTzX{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-riTzXœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-FAF7r", + "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-FAF7rœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", + "target": "ChatOutput-riTzX", + "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-riTzXœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" } ], "nodes": [ @@ -87,7 +87,7 @@ "description": "Create a prompt template with dynamic variables.", "display_name": "Prompt", "edited": false, - "id": "Prompt-p1yTM", + "id": "Prompt-Ejl8w", "node": { "base_classes": [ "Message" @@ -189,7 +189,7 @@ }, "dragging": false, "height": 422, - "id": "Prompt-p1yTM", + "id": "Prompt-Ejl8w", "position": { "x": 43.70859256635981, "y": 1115.5304359666682 @@ -207,7 +207,7 @@ "description": "Get chat inputs from the Playground.", "display_name": "Chat Input", "edited": false, - "id": "ChatInput-kMZti", + "id": "ChatInput-cIXVH", "node": { "base_classes": [ "Message" @@ -390,7 +390,7 @@ }, "dragging": false, "height": 308, - "id": "ChatInput-kMZti", + "id": "ChatInput-cIXVH", "position": { "x": -521.3324537445985, "y": 1089.7620993695407 @@ -408,7 +408,7 @@ "description": "Generates text using OpenAI LLMs.", "display_name": "OpenAI", "edited": false, - "id": "OpenAIModel-wC7mR", + "id": "OpenAIModel-FAF7r", "node": { "base_classes": [ "LanguageModel", @@ -668,7 +668,7 @@ }, "dragging": false, "height": 621, - "id": "OpenAIModel-wC7mR", + "id": "OpenAIModel-FAF7r", "position": { "x": 584.9288140250019, "y": 1149.0790574268922 @@ -686,7 +686,7 @@ "description": "Display a chat message in the Playground.", "display_name": "Chat Output", "edited": false, - "id": "ChatOutput-xh9wX", + "id": "ChatOutput-riTzX", "node": { "base_classes": [ "Message" @@ -846,7 +846,7 @@ }, "dragging": false, "height": 308, - "id": "ChatOutput-xh9wX", + "id": "ChatOutput-riTzX", "position": { "x": 1157.3374592784412, "y": 1160.9424490383622 @@ -861,14 +861,14 @@ } ], "viewport": { - "x": 353.0590737990465, - "y": -407.76221076623995, - "zoom": 0.5467255436493648 + "x": 382.9033026612555, + "y": -365.74767124549675, + "zoom": 0.5000000338450783 } }, "description": "This flow will get you experimenting with the basics of the UI, the Chat and the Prompt component. \n\nTry changing the Template in it to see how the model behaves. \nYou can change it to this and a Text Input into the `type_of_person` variable : \"Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: \" ", "endpoint_name": null, - "id": "65f25afc-1467-4f26-9e8a-d24792e76628", + "id": "52f28cee-19d7-48c4-ac36-12a6cc32206b", "is_component": false, "last_tested_version": "1.0.0rc1", "name": "Basic Prompting (Hello, World)" From 184f2524cf2d98cd93bb725c05bbc66ec5822dd2 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 09:36:45 -0300 Subject: [PATCH 082/229] refactor: make rag example be two flows again --- docs/static/data/AstraDB-RAG-Flows.json | 3394 +++++------ .../starter_projects/Vector Store RAG.json | 5410 ++++++++++------- 2 files changed, 4780 insertions(+), 4024 deletions(-) diff --git a/docs/static/data/AstraDB-RAG-Flows.json b/docs/static/data/AstraDB-RAG-Flows.json index 8865731d6..88c4a22a0 100644 --- a/docs/static/data/AstraDB-RAG-Flows.json +++ b/docs/static/data/AstraDB-RAG-Flows.json @@ -1,30 +1,31 @@ { - "id": "c9e0cb46-c474-451a-8496-413f58481d92", + "id": "152a031a-a41a-4df1-a161-19800f686776", "data": { "nodes": [ { "data": { - "id": "ChatInput-IY8UK", + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "edited": false, + "id": "ChatInput-8ZRjI", "node": { "base_classes": [ - "Text", - "str", - "object", - "Record" + "Message" ], "beta": false, - "custom_fields": { - "input_value": null, - "return_record": null, - "sender": null, - "sender_name": null, - "session_id": null - }, + "conditional_paths": [], + "custom_fields": {}, "description": "Get chat inputs from the Playground.", "display_name": "Chat Input", "documentation": "", - "field_formatters": {}, - "field_order": [], + "edited": true, + "field_order": [ + "input_value", + "sender", + "sender_name", + "session_id", + "files" + ], "frozen": false, "icon": "ChatInput", "output_types": [], @@ -32,16 +33,17 @@ { "cache": true, "display_name": "Message", + "hidden": false, "method": "message_response", "name": "message", "selected": "Message", "types": [ "Message" ], - "value": "__UNDEFINED__", - "hidden": false + "value": "__UNDEFINED__" } ], + "pinned": false, "template": { "_type": "Component", "code": { @@ -60,28 +62,67 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MultilineInput, Output, MessageTextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n MessageTextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + }, + "files": { + "advanced": true, + "display_name": "Files", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx", + "jpg", + "jpeg", + "png", + "bmp", + "image" + ], + "file_path": "", + "info": "Files to be sent with the message.", + "list": true, + "name": "files", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "file", + "value": "" }, "input_value": { "advanced": false, "display_name": "Text", "dynamic": false, - "fileTypes": [], - "file_path": "", "info": "Message to be passed as input.", "input_types": [ - "Message", - "str" + "Message" ], "list": false, "load_from_db": false, "multiline": true, "name": "input_value", - "password": false, "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", "value": "" }, @@ -89,25 +130,17 @@ "advanced": true, "display_name": "Sender Type", "dynamic": false, - "fileTypes": [], - "file_path": "", "info": "Type of sender.", - "input_types": [ - "Text" - ], - "list": true, - "load_from_db": false, - "multiline": false, "name": "sender", "options": [ "Machine", "User" ], - "password": false, "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_metadata": true, "type": "str", "value": "User" }, @@ -115,22 +148,19 @@ "advanced": true, "display_name": "Sender Name", "dynamic": false, - "fileTypes": [], - "file_path": "", "info": "Name of the sender.", "input_types": [ - "Message", - "str" + "Message" ], "list": false, "load_from_db": false, - "multiline": true, "name": "sender_name", - "password": false, "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", "value": "User" }, @@ -138,22 +168,19 @@ "advanced": true, "display_name": "Session ID", "dynamic": false, - "fileTypes": [], - "file_path": "", "info": "Session ID for the message.", "input_types": [ - "Message", - "str" + "Message" ], "list": false, "load_from_db": false, - "multiline": true, "name": "session_id", - "password": false, "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", "value": "" } @@ -163,14 +190,14 @@ }, "dragging": false, "height": 309, - "id": "ChatInput-IY8UK", + "id": "ChatInput-8ZRjI", "position": { - "x": 702.4571951501161, - "y": 119.7726926425525 + "x": 682.002772470747, + "y": 253.67030039648512 }, "positionAbsolute": { - "x": 702.4571951501161, - "y": 119.7726926425525 + "x": 682.002772470747, + "y": 253.67030039648512 }, "selected": false, "type": "genericNode", @@ -178,101 +205,7 @@ }, { "data": { - "description": "Display a text output in the Playground.", - "display_name": "Extracted Chunks", - "edited": false, - "id": "TextOutput-IxTee", - "node": { - "template": { - "_type": "Component", - "code": { - "type": "code", - "required": true, - "placeholder": "", - "list": false, - "show": true, - "multiline": true, - "value": "from langflow.base.io.text import TextComponent\nfrom langflow.io import Output, MessageTextInput\nfrom langflow.schema.message import Message\n\n\nclass TextOutputComponent(TextComponent):\n display_name = \"Text Output\"\n description = \"Display a text output in the Playground.\"\n icon = \"type\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Text to be passed as output.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"text_response\"),\n ]\n\n def text_response(self) -> Message:\n message = Message(\n text=self.input_value,\n )\n self.status = self.input_value\n return message\n", - "fileTypes": [], - "file_path": "", - "password": false, - "name": "code", - "advanced": true, - "dynamic": true, - "info": "", - "load_from_db": false, - "title_case": false - }, - "input_value": { - "load_from_db": false, - "list": false, - "required": false, - "placeholder": "", - "show": true, - "value": "", - "name": "input_value", - "display_name": "Text", - "advanced": false, - "input_types": [ - "Message" - ], - "dynamic": false, - "info": "Text to be passed as output.", - "title_case": false, - "type": "str" - } - }, - "description": "Display a text output in the Playground.", - "icon": "type", - "base_classes": [ - "Message" - ], - "display_name": "Extracted Chunks", - "documentation": "", - "custom_fields": {}, - "output_types": [], - "pinned": false, - "conditional_paths": [], - "frozen": false, - "outputs": [ - { - "types": [ - "Message" - ], - "selected": "Message", - "name": "text", - "display_name": "Text", - "method": "text_response", - "value": "__UNDEFINED__", - "cache": true - } - ], - "field_order": [ - "input_value" - ], - "beta": false, - "edited": true - }, - "type": "TextOutput" - }, - "dragging": false, - "height": 309, - "id": "TextOutput-IxTee", - "position": { - "x": 2439.792450398153, - "y": 661.149562774499 - }, - "positionAbsolute": { - "x": 2439.792450398153, - "y": 661.149562774499 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "OpenAIEmbeddings-HoSp5", + "id": "OpenAIEmbeddings-hNOwh", "node": { "base_classes": [ "Embeddings" @@ -314,14 +247,14 @@ { "cache": true, "display_name": "Embeddings", + "hidden": false, "method": "build_embeddings", "name": "embeddings", "selected": "Embeddings", "types": [ "Embeddings" ], - "value": "__UNDEFINED__", - "hidden": false + "value": "__UNDEFINED__" } ], "template": { @@ -375,7 +308,7 @@ "show": true, "title_case": false, "type": "code", - "value": "from langchain_openai.embeddings.base import OpenAIEmbeddings\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import Embeddings\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, Output, SecretStrInput, MessageTextInput\n\n\nclass OpenAIEmbeddingsComponent(LCModelComponent):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n icon = \"OpenAI\"\n inputs = [\n DictInput(\n name=\"default_headers\",\n display_name=\"Default Headers\",\n advanced=True,\n info=\"Default headers to use for the API request.\",\n ),\n DictInput(\n name=\"default_query\",\n display_name=\"Default Query\",\n advanced=True,\n info=\"Default query parameters to use for the API request.\",\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n MessageTextInput(name=\"client\", display_name=\"Client\", advanced=True),\n MessageTextInput(name=\"deployment\", display_name=\"Deployment\", advanced=True),\n IntInput(name=\"embedding_ctx_length\", display_name=\"Embedding Context Length\", advanced=True, value=1536),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", value=3, advanced=True),\n DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n advanced=False,\n options=[\n \"text-embedding-3-small\",\n \"text-embedding-3-large\",\n \"text-embedding-ada-002\",\n ],\n value=\"text-embedding-3-small\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n SecretStrInput(name=\"openai_api_base\", display_name=\"OpenAI API Base\", advanced=True),\n SecretStrInput(name=\"openai_api_key\", display_name=\"OpenAI API Key\"),\n SecretStrInput(name=\"openai_api_type\", display_name=\"OpenAI API Type\", advanced=True),\n MessageTextInput(name=\"openai_api_version\", display_name=\"OpenAI API Version\", advanced=True),\n MessageTextInput(\n name=\"openai_organization\",\n display_name=\"OpenAI Organization\",\n advanced=True,\n ),\n MessageTextInput(name=\"openai_proxy\", display_name=\"OpenAI Proxy\", advanced=True),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n BoolInput(name=\"skip_empty\", display_name=\"Skip Empty\", advanced=True),\n MessageTextInput(\n name=\"tiktoken_model_name\",\n display_name=\"TikToken Model Name\",\n advanced=True,\n ),\n BoolInput(\n name=\"tiktoken_enable\",\n display_name=\"TikToken Enable\",\n advanced=True,\n value=True,\n info=\"If False, you must have transformers installed.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Embeddings\", name=\"embeddings\", method=\"build_embeddings\"),\n ]\n\n def build_embeddings(self) -> Embeddings:\n return OpenAIEmbeddings(\n tiktoken_enabled=self.tiktoken_enable,\n default_headers=self.default_headers,\n default_query=self.default_query,\n allowed_special=\"all\",\n disallowed_special=\"all\",\n chunk_size=self.chunk_size,\n deployment=self.deployment,\n embedding_ctx_length=self.embedding_ctx_length,\n max_retries=self.max_retries,\n model=self.model,\n model_kwargs=self.model_kwargs,\n base_url=self.openai_api_base,\n api_key=self.openai_api_key,\n openai_api_type=self.openai_api_type,\n api_version=self.openai_api_version,\n organization=self.openai_organization,\n openai_proxy=self.openai_proxy,\n timeout=self.request_timeout or None,\n show_progress_bar=self.show_progress_bar,\n skip_empty=self.skip_empty,\n tiktoken_model_name=self.tiktoken_model_name,\n )\n" + "value": "from langchain_openai.embeddings.base import OpenAIEmbeddings\n\nfrom langflow.base.embeddings.model import LCEmbeddingsModel\nfrom langflow.field_typing import Embeddings\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, MessageTextInput\n\n\nclass OpenAIEmbeddingsComponent(LCEmbeddingsModel):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n icon = \"OpenAI\"\n inputs = [\n DictInput(\n name=\"default_headers\",\n display_name=\"Default Headers\",\n advanced=True,\n info=\"Default headers to use for the API request.\",\n ),\n DictInput(\n name=\"default_query\",\n display_name=\"Default Query\",\n advanced=True,\n info=\"Default query parameters to use for the API request.\",\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n MessageTextInput(name=\"client\", display_name=\"Client\", advanced=True),\n MessageTextInput(name=\"deployment\", display_name=\"Deployment\", advanced=True),\n IntInput(name=\"embedding_ctx_length\", display_name=\"Embedding Context Length\", advanced=True, value=1536),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", value=3, advanced=True),\n DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n advanced=False,\n options=[\n \"text-embedding-3-small\",\n \"text-embedding-3-large\",\n \"text-embedding-ada-002\",\n ],\n value=\"text-embedding-3-small\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n SecretStrInput(name=\"openai_api_base\", display_name=\"OpenAI API Base\", advanced=True),\n SecretStrInput(name=\"openai_api_key\", display_name=\"OpenAI API Key\"),\n SecretStrInput(name=\"openai_api_type\", display_name=\"OpenAI API Type\", advanced=True),\n MessageTextInput(name=\"openai_api_version\", display_name=\"OpenAI API Version\", advanced=True),\n MessageTextInput(\n name=\"openai_organization\",\n display_name=\"OpenAI Organization\",\n advanced=True,\n ),\n MessageTextInput(name=\"openai_proxy\", display_name=\"OpenAI Proxy\", advanced=True),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n BoolInput(name=\"skip_empty\", display_name=\"Skip Empty\", advanced=True),\n MessageTextInput(\n name=\"tiktoken_model_name\",\n display_name=\"TikToken Model Name\",\n advanced=True,\n ),\n BoolInput(\n name=\"tiktoken_enable\",\n display_name=\"TikToken Enable\",\n advanced=True,\n value=True,\n info=\"If False, you must have transformers installed.\",\n ),\n ]\n\n def build_embeddings(self) -> Embeddings:\n return OpenAIEmbeddings(\n tiktoken_enabled=self.tiktoken_enable,\n default_headers=self.default_headers,\n default_query=self.default_query,\n allowed_special=\"all\",\n disallowed_special=\"all\",\n chunk_size=self.chunk_size,\n deployment=self.deployment,\n embedding_ctx_length=self.embedding_ctx_length,\n max_retries=self.max_retries,\n model=self.model,\n model_kwargs=self.model_kwargs,\n base_url=self.openai_api_base,\n api_key=self.openai_api_key,\n openai_api_type=self.openai_api_type,\n api_version=self.openai_api_version,\n organization=self.openai_organization,\n openai_proxy=self.openai_proxy,\n timeout=self.request_timeout or None,\n show_progress_bar=self.show_progress_bar,\n skip_empty=self.skip_empty,\n tiktoken_model_name=self.tiktoken_model_name,\n )\n" }, "default_headers": { "advanced": true, @@ -506,7 +439,7 @@ "dynamic": false, "info": "", "input_types": [], - "load_from_db": true, + "load_from_db": false, "name": "openai_api_key", "password": true, "placeholder": "", @@ -669,15 +602,15 @@ "type": "OpenAIEmbeddings" }, "dragging": false, - "height": 395, - "id": "OpenAIEmbeddings-HoSp5", + "height": 393, + "id": "OpenAIEmbeddings-hNOwh", "position": { - "x": 690.5967478991026, - "y": 597.6680004855787 + "x": 672.1192980997866, + "y": 786.6985113716086 }, "positionAbsolute": { - "x": 690.5967478991026, - "y": 597.6680004855787 + "x": 672.1192980997866, + "y": 786.6985113716086 }, "selected": false, "type": "genericNode", @@ -685,235 +618,22 @@ }, { "data": { - "id": "OpenAIModel-ickkA", + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "edited": false, + "id": "OpenAIModel-euVNy", "node": { - "template": { - "_type": "Component", - "code": { - "type": "code", - "required": true, - "placeholder": "", - "list": false, - "show": true, - "multiline": true, - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n", - "fileTypes": [], - "file_path": "", - "password": false, - "name": "code", - "advanced": true, - "dynamic": true, - "info": "", - "load_from_db": false, - "title_case": false - }, - "input_value": { - "load_from_db": false, - "list": false, - "required": false, - "placeholder": "", - "show": true, - "value": "", - "name": "input_value", - "display_name": "Input", - "advanced": false, - "input_types": [ - "Message" - ], - "dynamic": false, - "info": "", - "title_case": false, - "type": "str" - }, - "max_tokens": { - "list": false, - "required": false, - "placeholder": "", - "show": true, - "value": "", - "name": "max_tokens", - "display_name": "Max Tokens", - "advanced": true, - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "title_case": false, - "type": "int" - }, - "model_kwargs": { - "list": false, - "required": false, - "placeholder": "", - "show": true, - "value": {}, - "name": "model_kwargs", - "display_name": "Model Kwargs", - "advanced": true, - "dynamic": false, - "info": "", - "title_case": false, - "type": "dict" - }, - "model_name": { - "options": [ - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "required": false, - "placeholder": "", - "show": true, - "value": "gpt-3.5-turbo", - "name": "model_name", - "display_name": "Model Name", - "advanced": false, - "dynamic": false, - "info": "", - "title_case": false, - "type": "str" - }, - "openai_api_base": { - "load_from_db": false, - "list": false, - "required": false, - "placeholder": "", - "show": true, - "value": "", - "name": "openai_api_base", - "display_name": "OpenAI API Base", - "advanced": true, - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "title_case": false, - "type": "str" - }, - "openai_api_key": { - "load_from_db": true, - "required": false, - "placeholder": "", - "show": true, - "value": "", - "name": "openai_api_key", - "display_name": "OpenAI API Key", - "advanced": false, - "input_types": [], - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "title_case": false, - "password": true, - "type": "str" - }, - "output_schema": { - "list": true, - "required": false, - "placeholder": "", - "show": true, - "value": {}, - "name": "output_schema", - "display_name": "Schema", - "advanced": true, - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.", - "title_case": false, - "type": "dict" - }, - "seed": { - "list": false, - "required": false, - "placeholder": "", - "show": true, - "value": 1, - "name": "seed", - "display_name": "Seed", - "advanced": true, - "dynamic": false, - "info": "The seed controls the reproducibility of the job.", - "title_case": false, - "type": "int" - }, - "stream": { - "list": false, - "required": false, - "placeholder": "", - "show": true, - "value": false, - "name": "stream", - "display_name": "Stream", - "advanced": true, - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "title_case": false, - "type": "bool" - }, - "system_message": { - "load_from_db": false, - "list": false, - "required": false, - "placeholder": "", - "show": true, - "value": "", - "name": "system_message", - "display_name": "System Message", - "advanced": true, - "dynamic": false, - "info": "System message to pass to the model.", - "title_case": false, - "type": "str" - }, - "temperature": { - "list": false, - "required": false, - "placeholder": "", - "show": true, - "value": 0.1, - "name": "temperature", - "display_name": "Temperature", - "advanced": false, - "dynamic": false, - "info": "", - "title_case": false, - "type": "float" - } - }, - "description": "Generates text using OpenAI LLMs.", - "icon": "OpenAI", "base_classes": [ "LanguageModel", "Message" ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", "display_name": "OpenAI", "documentation": "", - "custom_fields": {}, - "output_types": [], - "pinned": false, - "conditional_paths": [], - "frozen": false, - "outputs": [ - { - "types": [ - "Message" - ], - "selected": "Message", - "name": "text_output", - "display_name": "Text", - "method": "text_response", - "value": "__UNDEFINED__", - "cache": true, - "hidden": false - }, - { - "types": [ - "LanguageModel" - ], - "selected": "LanguageModel", - "name": "model_output", - "display_name": "Language Model", - "method": "build_model", - "value": "__UNDEFINED__", - "cache": true - } - ], + "edited": true, "field_order": [ "input_value", "max_tokens", @@ -927,73 +647,32 @@ "system_message", "seed" ], - "beta": false, - "edited": true - }, - "type": "OpenAIModel", - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "edited": false - }, - "dragging": false, - "height": 623, - "id": "OpenAIModel-ickkA", - "position": { - "x": 3410.117202077183, - "y": 431.2038048137648 - }, - "positionAbsolute": { - "x": 3410.117202077183, - "y": 431.2038048137648 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "id": "Prompt-jzPqb", - "node": { - "base_classes": [ - "object", - "str", - "Text" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": { - "template": [ - "context", - "question" - ] - }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "documentation": "", - "error": null, - "field_order": [], "frozen": false, - "full_path": null, - "icon": "prompts", - "is_composition": null, - "is_input": null, - "is_output": null, - "name": "", + "icon": "OpenAI", "output_types": [], "outputs": [ { "cache": true, - "display_name": "Prompt Message", - "method": "build_prompt", - "name": "prompt", + "display_name": "Text", + "hidden": false, + "method": "text_response", + "name": "text_output", "selected": "Message", "types": [ "Message" ], - "value": "__UNDEFINED__", - "hidden": false + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" } ], "pinned": false, @@ -1015,25 +694,19 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n" + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n" }, - "context": { + "input_value": { "advanced": false, - "display_name": "context", + "display_name": "Input", "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", "info": "", "input_types": [ - "Message", - "Text" + "Message" ], "list": false, "load_from_db": false, - "multiline": true, - "name": "context", - "password": false, + "name": "input_value", "placeholder": "", "required": false, "show": true, @@ -1041,23 +714,62 @@ "type": "str", "value": "" }, - "question": { - "advanced": false, - "display_name": "question", + "max_tokens": { + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "model_kwargs": { + "advanced": true, + "display_name": "Model Kwargs", "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", "info": "", - "input_types": [ - "Message", - "Text" + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "model_name": { + "advanced": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "gpt-4-turbo" + }, + "openai_api_base": { + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", "list": false, "load_from_db": false, - "multiline": true, - "name": "question", - "password": false, + "name": "openai_api_base", "placeholder": "", "required": false, "show": true, @@ -1065,42 +777,107 @@ "type": "str", "value": "" }, - "template": { + "openai_api_key": { "advanced": false, - "display_name": "Template", + "display_name": "OpenAI API Key", "dynamic": false, - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Text" - ], - "list": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [], "load_from_db": false, - "multiline": false, - "name": "template", - "password": false, + "name": "openai_api_key", + "password": true, "placeholder": "", "required": false, "show": true, "title_case": false, - "type": "prompt", - "value": "{context}\n\n---\n\nGiven the context above, answer the question as best as possible.\n\nQuestion: {question}\n\nAnswer: " + "type": "str", + "value": "" + }, + "output_schema": { + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "seed": { + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 1 + }, + "stream": { + "advanced": true, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "system_message": { + "advanced": true, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "temperature": { + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "float", + "value": 0.1 } } }, - "type": "Prompt" + "type": "OpenAIModel" }, "dragging": false, - "height": 525, - "id": "Prompt-jzPqb", + "height": 623, + "id": "OpenAIModel-euVNy", "position": { - "x": 2941.2776396951576, - "y": 446.43037366459487 + "x": 3243.967394111999, + "y": 392.861541437184 }, "positionAbsolute": { - "x": 2941.2776396951576, - "y": 446.43037366459487 + "x": 3243.967394111999, + "y": 392.861541437184 }, "selected": false, "type": "genericNode", @@ -1108,28 +885,28 @@ }, { "data": { - "id": "ChatOutput-Zy354", + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "edited": false, + "id": "ChatOutput-1eddV", "node": { "base_classes": [ - "object", - "Text", - "Record", - "str" + "Message" ], "beta": false, - "custom_fields": { - "input_value": null, - "record_template": null, - "return_record": null, - "sender": null, - "sender_name": null, - "session_id": null - }, + "conditional_paths": [], + "custom_fields": {}, "description": "Display a chat message in the Playground.", "display_name": "Chat Output", "documentation": "", - "field_formatters": {}, - "field_order": [], + "edited": true, + "field_order": [ + "input_value", + "sender", + "sender_name", + "session_id", + "data_template" + ], "frozen": false, "icon": "ChatOutput", "output_types": [], @@ -1146,6 +923,7 @@ "value": "__UNDEFINED__" } ], + "pinned": false, "template": { "_type": "Component", "code": { @@ -1164,28 +942,45 @@ "show": true, "title_case": false, "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, Output, MessageTextInput\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + }, + "data_template": { + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" }, "input_value": { "advanced": false, "display_name": "Text", "dynamic": false, - "fileTypes": [], - "file_path": "", "info": "Message to be passed as output.", "input_types": [ - "Message", - "str" + "Message" ], "list": false, "load_from_db": false, - "multiline": true, "name": "input_value", - "password": false, "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", "value": "" }, @@ -1193,25 +988,17 @@ "advanced": true, "display_name": "Sender Type", "dynamic": false, - "fileTypes": [], - "file_path": "", "info": "Type of sender.", - "input_types": [ - "Text" - ], - "list": true, - "load_from_db": false, - "multiline": false, "name": "sender", "options": [ "Machine", "User" ], - "password": false, "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_metadata": true, "type": "str", "value": "Machine" }, @@ -1219,22 +1006,19 @@ "advanced": true, "display_name": "Sender Name", "dynamic": false, - "fileTypes": [], - "file_path": "", "info": "Name of the sender.", "input_types": [ - "Message", - "str" + "Message" ], "list": false, "load_from_db": false, - "multiline": true, "name": "sender_name", - "password": false, "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", "value": "AI" }, @@ -1242,22 +1026,19 @@ "advanced": true, "display_name": "Session ID", "dynamic": false, - "fileTypes": [], - "file_path": "", "info": "Session ID for the message.", "input_types": [ - "Message", - "str" + "Message" ], "list": false, "load_from_db": false, - "multiline": true, "name": "session_id", - "password": false, "placeholder": "", "required": false, "show": true, "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, "type": "str", "value": "" } @@ -1267,14 +1048,14 @@ }, "dragging": false, "height": 309, - "id": "ChatOutput-Zy354", + "id": "ChatOutput-1eddV", "position": { - "x": 3998.201592537035, - "y": 603.4216529723935 + "x": 3788.786948642587, + "y": 608.4077159222614 }, "positionAbsolute": { - "x": 3998.201592537035, - "y": 603.4216529723935 + "x": 3788.786948642587, + "y": 608.4077159222614 }, "selected": false, "type": "genericNode", @@ -1282,7 +1063,7 @@ }, { "data": { - "id": "File-28ckd", + "id": "File-p2YBf", "node": { "base_classes": [ "Record" @@ -1304,14 +1085,14 @@ { "cache": true, "display_name": "Data", + "hidden": false, "method": "load_file", "name": "data", "selected": "Data", "types": [ "Data" ], - "value": "__UNDEFINED__", - "hidden": false + "value": "__UNDEFINED__" } ], "template": { @@ -1358,7 +1139,7 @@ "ts", "tsx" ], - "file_path": "c9e0cb46-c474-451a-8496-413f58481d92/Context Once.json", + "file_path": "bba1609b-3af2-431d-a884-322cc253c69d/flatland.pdf", "info": "Supported file types: txt, md, mdx, csv, json, yaml, yml, xml, html, htm, pdf, docx, py, sh, sql, js, ts, tsx", "list": false, "name": "path", @@ -1389,574 +1170,14 @@ }, "dragging": false, "height": 301, - "id": "File-28ckd", + "id": "File-p2YBf", "position": { - "x": 2257.233450682836, - "y": 1747.5389618367233 + "x": 1435.8917804347734, + "y": 1603.546667861399 }, "positionAbsolute": { - "x": 2257.233450682836, - "y": 1747.5389618367233 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "OpenAIEmbeddings-YeYtt", - "node": { - "base_classes": [ - "Embeddings" - ], - "beta": false, - "custom_fields": { - "allowed_special": null, - "chunk_size": null, - "client": null, - "default_headers": null, - "default_query": null, - "deployment": null, - "disallowed_special": null, - "embedding_ctx_length": null, - "max_retries": null, - "model": null, - "model_kwargs": null, - "openai_api_base": null, - "openai_api_key": null, - "openai_api_type": null, - "openai_api_version": null, - "openai_organization": null, - "openai_proxy": null, - "request_timeout": null, - "show_progress_bar": null, - "skip_empty": null, - "tiktoken_enable": null, - "tiktoken_model_name": null - }, - "description": "Generate embeddings using OpenAI models.", - "display_name": "OpenAI Embeddings", - "documentation": "", - "field_formatters": {}, - "field_order": [], - "frozen": false, - "icon": "OpenAI", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Embeddings", - "method": "build_embeddings", - "name": "embeddings", - "selected": "Embeddings", - "types": [ - "Embeddings" - ], - "value": "__UNDEFINED__", - "hidden": false - } - ], - "template": { - "_type": "Component", - "chunk_size": { - "advanced": true, - "display_name": "Chunk Size", - "dynamic": false, - "info": "", - "list": false, - "name": "chunk_size", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": 1000 - }, - "client": { - "advanced": true, - "display_name": "Client", - "dynamic": false, - "info": "", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "name": "client", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langchain_openai.embeddings.base import OpenAIEmbeddings\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import Embeddings\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, Output, SecretStrInput, MessageTextInput\n\n\nclass OpenAIEmbeddingsComponent(LCModelComponent):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n icon = \"OpenAI\"\n inputs = [\n DictInput(\n name=\"default_headers\",\n display_name=\"Default Headers\",\n advanced=True,\n info=\"Default headers to use for the API request.\",\n ),\n DictInput(\n name=\"default_query\",\n display_name=\"Default Query\",\n advanced=True,\n info=\"Default query parameters to use for the API request.\",\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n MessageTextInput(name=\"client\", display_name=\"Client\", advanced=True),\n MessageTextInput(name=\"deployment\", display_name=\"Deployment\", advanced=True),\n IntInput(name=\"embedding_ctx_length\", display_name=\"Embedding Context Length\", advanced=True, value=1536),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", value=3, advanced=True),\n DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n advanced=False,\n options=[\n \"text-embedding-3-small\",\n \"text-embedding-3-large\",\n \"text-embedding-ada-002\",\n ],\n value=\"text-embedding-3-small\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n SecretStrInput(name=\"openai_api_base\", display_name=\"OpenAI API Base\", advanced=True),\n SecretStrInput(name=\"openai_api_key\", display_name=\"OpenAI API Key\"),\n SecretStrInput(name=\"openai_api_type\", display_name=\"OpenAI API Type\", advanced=True),\n MessageTextInput(name=\"openai_api_version\", display_name=\"OpenAI API Version\", advanced=True),\n MessageTextInput(\n name=\"openai_organization\",\n display_name=\"OpenAI Organization\",\n advanced=True,\n ),\n MessageTextInput(name=\"openai_proxy\", display_name=\"OpenAI Proxy\", advanced=True),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n BoolInput(name=\"skip_empty\", display_name=\"Skip Empty\", advanced=True),\n MessageTextInput(\n name=\"tiktoken_model_name\",\n display_name=\"TikToken Model Name\",\n advanced=True,\n ),\n BoolInput(\n name=\"tiktoken_enable\",\n display_name=\"TikToken Enable\",\n advanced=True,\n value=True,\n info=\"If False, you must have transformers installed.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Embeddings\", name=\"embeddings\", method=\"build_embeddings\"),\n ]\n\n def build_embeddings(self) -> Embeddings:\n return OpenAIEmbeddings(\n tiktoken_enabled=self.tiktoken_enable,\n default_headers=self.default_headers,\n default_query=self.default_query,\n allowed_special=\"all\",\n disallowed_special=\"all\",\n chunk_size=self.chunk_size,\n deployment=self.deployment,\n embedding_ctx_length=self.embedding_ctx_length,\n max_retries=self.max_retries,\n model=self.model,\n model_kwargs=self.model_kwargs,\n base_url=self.openai_api_base,\n api_key=self.openai_api_key,\n openai_api_type=self.openai_api_type,\n api_version=self.openai_api_version,\n organization=self.openai_organization,\n openai_proxy=self.openai_proxy,\n timeout=self.request_timeout or None,\n show_progress_bar=self.show_progress_bar,\n skip_empty=self.skip_empty,\n tiktoken_model_name=self.tiktoken_model_name,\n )\n" - }, - "default_headers": { - "advanced": true, - "display_name": "Default Headers", - "dynamic": false, - "info": "Default headers to use for the API request.", - "list": false, - "name": "default_headers", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "dict", - "value": {} - }, - "default_query": { - "advanced": true, - "display_name": "Default Query", - "dynamic": false, - "info": "Default query parameters to use for the API request.", - "list": false, - "name": "default_query", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "dict", - "value": {} - }, - "deployment": { - "advanced": true, - "display_name": "Deployment", - "dynamic": false, - "info": "", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "name": "deployment", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "embedding_ctx_length": { - "advanced": true, - "display_name": "Embedding Context Length", - "dynamic": false, - "info": "", - "list": false, - "name": "embedding_ctx_length", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": 1536 - }, - "max_retries": { - "advanced": true, - "display_name": "Max Retries", - "dynamic": false, - "info": "", - "list": false, - "name": "max_retries", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": 3 - }, - "model": { - "advanced": false, - "display_name": "Model", - "dynamic": false, - "info": "", - "name": "model", - "options": [ - "text-embedding-3-small", - "text-embedding-3-large", - "text-embedding-ada-002" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "text-embedding-3-small" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "dict", - "value": {} - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "", - "input_types": [], - "load_from_db": true, - "name": "openai_api_base", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_api_key": { - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "", - "input_types": [], - "load_from_db": true, - "name": "openai_api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_api_type": { - "advanced": true, - "display_name": "OpenAI API Type", - "dynamic": false, - "info": "", - "input_types": [], - "load_from_db": true, - "name": "openai_api_type", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_api_version": { - "advanced": true, - "display_name": "OpenAI API Version", - "dynamic": false, - "info": "", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "name": "openai_api_version", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_organization": { - "advanced": true, - "display_name": "OpenAI Organization", - "dynamic": false, - "info": "", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "name": "openai_organization", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_proxy": { - "advanced": true, - "display_name": "OpenAI Proxy", - "dynamic": false, - "info": "", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "name": "openai_proxy", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "request_timeout": { - "advanced": true, - "display_name": "Request Timeout", - "dynamic": false, - "info": "", - "list": false, - "name": "request_timeout", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "float", - "value": "" - }, - "show_progress_bar": { - "advanced": true, - "display_name": "Show Progress Bar", - "dynamic": false, - "info": "", - "list": false, - "name": "show_progress_bar", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "bool", - "value": false - }, - "skip_empty": { - "advanced": true, - "display_name": "Skip Empty", - "dynamic": false, - "info": "", - "list": false, - "name": "skip_empty", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "bool", - "value": false - }, - "tiktoken_enable": { - "advanced": true, - "display_name": "TikToken Enable", - "dynamic": false, - "info": "If False, you must have transformers installed.", - "list": false, - "name": "tiktoken_enable", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "bool", - "value": true - }, - "tiktoken_model_name": { - "advanced": true, - "display_name": "TikToken Model Name", - "dynamic": false, - "info": "", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "name": "tiktoken_model_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - } - } - }, - "type": "OpenAIEmbeddings" - }, - "dragging": false, - "height": 395, - "id": "OpenAIEmbeddings-YeYtt", - "position": { - "x": 2781.1922529351923, - "y": 2206.267872396239 - }, - "positionAbsolute": { - "x": 2781.1922529351923, - "y": 2206.267872396239 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Split text into chunks of a specified length.", - "display_name": "Recursive Character Text Splitter", - "id": "RecursiveCharacterTextSplitter-HVESL", - "node": { - "base_classes": [ - "Data" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Split text into chunks of a specified length.", - "display_name": "Recursive Character Text Splitter", - "documentation": "https://docs.langflow.org/components/text-splitters#recursivecharactertextsplitter", - "edited": false, - "field_order": [ - "chunk_size", - "chunk_overlap", - "data_input", - "separators" - ], - "frozen": false, - "output_types": [ - "Data" - ], - "outputs": [ - { - "cache": true, - "display_name": "Data", - "method": "build", - "name": "data", - "selected": "Data", - "types": [ - "Data" - ], - "value": "__UNDEFINED__", - "hidden": false - } - ], - "pinned": false, - "template": { - "_type": "Component", - "chunk_overlap": { - "advanced": false, - "display_name": "Chunk Overlap", - "dynamic": false, - "info": "The amount of overlap between chunks.", - "list": false, - "name": "chunk_overlap", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": 200 - }, - "chunk_size": { - "advanced": false, - "display_name": "Chunk Size", - "dynamic": false, - "info": "The maximum length of each chunk.", - "list": false, - "name": "chunk_size", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": 1000 - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langchain_text_splitters import RecursiveCharacterTextSplitter\n\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DataInput, IntInput, MessageTextInput\nfrom langflow.schema import Data\nfrom langflow.template.field.base import Output\nfrom langflow.utils.util import build_loader_repr_from_data, unescape_string\n\n\nclass RecursiveCharacterTextSplitterComponent(Component):\n display_name: str = \"Recursive Character Text Splitter\"\n description: str = \"Split text into chunks of a specified length.\"\n documentation: str = \"https://docs.langflow.org/components/text-splitters#recursivecharactertextsplitter\"\n\n inputs = [\n IntInput(\n name=\"chunk_size\",\n display_name=\"Chunk Size\",\n info=\"The maximum length of each chunk.\",\n value=1000,\n ),\n IntInput(\n name=\"chunk_overlap\",\n display_name=\"Chunk Overlap\",\n info=\"The amount of overlap between chunks.\",\n value=200,\n ),\n DataInput(\n name=\"data_input\",\n display_name=\"Input\",\n info=\"The texts to split.\",\n input_types=[\"Document\", \"Data\"],\n ),\n MessageTextInput(\n name=\"separators\",\n display_name=\"Separators\",\n info='The characters to split on.\\nIf left empty defaults to [\"\\\\n\\\\n\", \"\\\\n\", \" \", \"\"].',\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"split_data\"),\n ]\n\n def split_data(self) -> list[Data]:\n \"\"\"\n Split text into chunks of a specified length.\n\n Args:\n separators (list[str]): The characters to split on.\n chunk_size (int): The maximum length of each chunk.\n chunk_overlap (int): The amount of overlap between chunks.\n\n Returns:\n list[str]: The chunks of text.\n \"\"\"\n\n if self.separators == \"\":\n self.separators = None\n elif self.separators:\n # check if the separators list has escaped characters\n # if there are escaped characters, unescape them\n self.separators = [unescape_string(x) for x in self.separators]\n\n # Make sure chunk_size and chunk_overlap are ints\n if isinstance(self.chunk_size, str):\n self.chunk_size = int(self.chunk_size)\n if isinstance(self.chunk_overlap, str):\n self.chunk_overlap = int(self.chunk_overlap)\n splitter = RecursiveCharacterTextSplitter(\n separators=self.separators,\n chunk_size=self.chunk_size,\n chunk_overlap=self.chunk_overlap,\n )\n documents = []\n if not isinstance(self.data_input, list):\n self.data_input = [self.data_input]\n for _input in self.data_input:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n else:\n documents.append(_input)\n docs = splitter.split_documents(documents)\n data = self.to_data(docs)\n self.repr_value = build_loader_repr_from_data(data)\n return data\n" - }, - "data_input": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "The texts to split.", - "input_types": [ - "Document", - "Data" - ], - "list": false, - "name": "data_input", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "other", - "value": "" - }, - "separators": { - "advanced": false, - "display_name": "Separators", - "dynamic": false, - "info": "The characters to split on.\nIf left empty defaults to [\"\\n\\n\", \"\\n\", \" \", \"\"].", - "input_types": [ - "Message", - "str" - ], - "list": true, - "load_from_db": false, - "name": "separators", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": [ - "\\n" - ] - } - } - }, - "type": "RecursiveCharacterTextSplitter" - }, - "dragging": false, - "height": 529, - "id": "RecursiveCharacterTextSplitter-HVESL", - "position": { - "x": 2726.46405760335, - "y": 1530.1666819162674 - }, - "positionAbsolute": { - "x": 2726.46405760335, - "y": 1530.1666819162674 + "x": 1435.8917804347734, + "y": 1603.546667861399 }, "selected": false, "type": "genericNode", @@ -1966,7 +1187,7 @@ "data": { "description": "Implementation of Vector Store using Astra DB with search capabilities", "display_name": "Astra DB Vector Store", - "id": "AstraDB-irvai", + "id": "AstraDB-p6135", "node": { "base_classes": [ "Data" @@ -2018,6 +1239,7 @@ { "cache": true, "display_name": "Search Results", + "hidden": false, "method": "search_documents", "name": "search_results", "selected": "Data", @@ -2042,7 +1264,7 @@ "show": true, "title_case": false, "type": "bool", - "value": true + "value": false }, "api_endpoint": { "advanced": false, @@ -2050,7 +1272,7 @@ "dynamic": false, "info": "API endpoint URL for the Astra DB service.", "input_types": [], - "load_from_db": true, + "load_from_db": false, "name": "api_endpoint", "password": true, "placeholder": "", @@ -2333,7 +1555,7 @@ "dynamic": false, "info": "Authentication token for accessing Astra DB.", "input_types": [], - "load_from_db": true, + "load_from_db": false, "name": "token", "password": true, "placeholder": "", @@ -2367,426 +1589,7 @@ }, "dragging": false, "height": 917, - "id": "AstraDB-irvai", - "position": { - "x": 3329.7211874614477, - "y": 1559.774393811144 - }, - "positionAbsolute": { - "x": 3329.7211874614477, - "y": 1559.774393811144 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Implementation of Vector Store using Astra DB with search capabilities", - "display_name": "Astra DB Vector Store", - "id": "AstraDB-wANQu", - "node": { - "base_classes": [ - "Data" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Implementation of Vector Store using Astra DB with search capabilities", - "display_name": "Astra DB Vector Store", - "documentation": "https://python.langchain.com/docs/integrations/vectorstores/astradb", - "edited": false, - "field_order": [ - "collection_name", - "token", - "api_endpoint", - "vector_store_inputs", - "embedding", - "namespace", - "metric", - "batch_size", - "bulk_insert_batch_concurrency", - "bulk_insert_overwrite_concurrency", - "bulk_delete_concurrency", - "setup_mode", - "pre_delete_collection", - "metadata_indexing_include", - "metadata_indexing_exclude", - "collection_indexing_policy", - "add_to_vector_store", - "search_input", - "search_type", - "number_of_results" - ], - "frozen": false, - "icon": "AstraDB", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Retriever", - "method": "build_base_retriever", - "name": "base_retriever", - "selected": "Data", - "types": [ - "Data" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Search Results", - "method": "search_documents", - "name": "search_results", - "selected": "Data", - "types": [ - "Data" - ], - "value": "__UNDEFINED__", - "hidden": false - } - ], - "pinned": false, - "template": { - "_type": "Component", - "add_to_vector_store": { - "advanced": false, - "display_name": "Add to Vector Store", - "dynamic": false, - "info": "If true, the Vector Store Inputs will be added to the Vector Store.", - "list": false, - "name": "add_to_vector_store", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "bool", - "value": true - }, - "api_endpoint": { - "advanced": false, - "display_name": "API Endpoint", - "dynamic": false, - "info": "API endpoint URL for the Astra DB service.", - "input_types": [], - "load_from_db": true, - "name": "api_endpoint", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "batch_size": { - "advanced": true, - "display_name": "Batch Size", - "dynamic": false, - "info": "Optional number of data to process in a single batch.", - "list": false, - "name": "batch_size", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": "" - }, - "bulk_delete_concurrency": { - "advanced": true, - "display_name": "Bulk Delete Concurrency", - "dynamic": false, - "info": "Optional concurrency level for bulk delete operations.", - "list": false, - "name": "bulk_delete_concurrency", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": "" - }, - "bulk_insert_batch_concurrency": { - "advanced": true, - "display_name": "Bulk Insert Batch Concurrency", - "dynamic": false, - "info": "Optional concurrency level for bulk insert operations.", - "list": false, - "name": "bulk_insert_batch_concurrency", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": "" - }, - "bulk_insert_overwrite_concurrency": { - "advanced": true, - "display_name": "Bulk Insert Overwrite Concurrency", - "dynamic": false, - "info": "Optional concurrency level for bulk insert operations that overwrite existing data.", - "list": false, - "name": "bulk_insert_overwrite_concurrency", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from loguru import logger\n\nfrom langflow.base.vectorstores.model import LCVectorStoreComponent\nfrom langflow.io import BoolInput, DropdownInput, HandleInput, IntInput, MultilineInput, SecretStrInput, StrInput\nfrom langflow.schema import Data\n\n\nclass AstraVectorStoreComponent(LCVectorStoreComponent):\n display_name: str = \"Astra DB Vector Store\"\n description: str = \"Implementation of Vector Store using Astra DB with search capabilities\"\n documentation: str = \"https://python.langchain.com/docs/integrations/vectorstores/astradb\"\n icon: str = \"AstraDB\"\n\n inputs = [\n StrInput(\n name=\"collection_name\",\n display_name=\"Collection Name\",\n info=\"The name of the collection within Astra DB where the vectors will be stored.\",\n ),\n SecretStrInput(\n name=\"token\",\n display_name=\"Astra DB Application Token\",\n info=\"Authentication token for accessing Astra DB.\",\n value=\"ASTRA_DB_APPLICATION_TOKEN\",\n ),\n SecretStrInput(\n name=\"api_endpoint\",\n display_name=\"API Endpoint\",\n info=\"API endpoint URL for the Astra DB service.\",\n value=\"ASTRA_DB_API_ENDPOINT\",\n ),\n HandleInput(\n name=\"vector_store_inputs\",\n display_name=\"Vector Store Inputs\",\n input_types=[\"Document\", \"Data\"],\n is_list=True,\n ),\n HandleInput(\n name=\"embedding\",\n display_name=\"Embedding\",\n input_types=[\"Embeddings\"],\n ),\n StrInput(\n name=\"namespace\",\n display_name=\"Namespace\",\n info=\"Optional namespace within Astra DB to use for the collection.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"metric\",\n display_name=\"Metric\",\n info=\"Optional distance metric for vector comparisons in the vector store.\",\n options=[\"cosine\", \"dot_product\", \"euclidean\"],\n advanced=True,\n ),\n IntInput(\n name=\"batch_size\",\n display_name=\"Batch Size\",\n info=\"Optional number of data to process in a single batch.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_batch_concurrency\",\n display_name=\"Bulk Insert Batch Concurrency\",\n info=\"Optional concurrency level for bulk insert operations.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_overwrite_concurrency\",\n display_name=\"Bulk Insert Overwrite Concurrency\",\n info=\"Optional concurrency level for bulk insert operations that overwrite existing data.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_delete_concurrency\",\n display_name=\"Bulk Delete Concurrency\",\n info=\"Optional concurrency level for bulk delete operations.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"setup_mode\",\n display_name=\"Setup Mode\",\n info=\"Configuration mode for setting up the vector store, with options like 'Sync', 'Async', or 'Off'.\",\n options=[\"Sync\", \"Async\", \"Off\"],\n advanced=True,\n value=\"Sync\",\n ),\n BoolInput(\n name=\"pre_delete_collection\",\n display_name=\"Pre Delete Collection\",\n info=\"Boolean flag to determine whether to delete the collection before creating a new one.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_include\",\n display_name=\"Metadata Indexing Include\",\n info=\"Optional list of metadata fields to include in the indexing.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_exclude\",\n display_name=\"Metadata Indexing Exclude\",\n info=\"Optional list of metadata fields to exclude from the indexing.\",\n advanced=True,\n ),\n StrInput(\n name=\"collection_indexing_policy\",\n display_name=\"Collection Indexing Policy\",\n info=\"Optional dictionary defining the indexing policy for the collection.\",\n advanced=True,\n ),\n BoolInput(\n name=\"add_to_vector_store\",\n display_name=\"Add to Vector Store\",\n info=\"If true, the Vector Store Inputs will be added to the Vector Store.\",\n ),\n MultilineInput(\n name=\"search_input\",\n display_name=\"Search Input\",\n ),\n DropdownInput(\n name=\"search_type\",\n display_name=\"Search Type\",\n options=[\"Similarity\", \"MMR\"],\n value=\"Similarity\",\n ),\n IntInput(\n name=\"number_of_results\",\n display_name=\"Number of Results\",\n info=\"Number of results to return.\",\n advanced=True,\n value=4,\n ),\n ]\n\n def build_vector_store(self):\n try:\n from langchain_astradb import AstraDBVectorStore\n from langchain_astradb.utils.astradb import SetupMode\n except ImportError:\n raise ImportError(\n \"Could not import langchain Astra DB integration package. \"\n \"Please install it with `pip install langchain-astradb`.\"\n )\n\n try:\n if not self.setup_mode:\n self.setup_mode = self._inputs[\"setup_mode\"].options[0]\n\n setup_mode_value = SetupMode[self.setup_mode.upper()]\n except KeyError:\n raise ValueError(f\"Invalid setup mode: {self.setup_mode}\")\n\n vector_store_kwargs = {\n \"embedding\": self.embedding,\n \"collection_name\": self.collection_name,\n \"token\": self.token,\n \"api_endpoint\": self.api_endpoint,\n \"namespace\": self.namespace or None,\n \"metric\": self.metric or None,\n \"batch_size\": self.batch_size or None,\n \"bulk_insert_batch_concurrency\": self.bulk_insert_batch_concurrency or None,\n \"bulk_insert_overwrite_concurrency\": self.bulk_insert_overwrite_concurrency or None,\n \"bulk_delete_concurrency\": self.bulk_delete_concurrency or None,\n \"setup_mode\": setup_mode_value,\n \"pre_delete_collection\": self.pre_delete_collection or False,\n }\n\n if self.metadata_indexing_include:\n vector_store_kwargs[\"metadata_indexing_include\"] = self.metadata_indexing_include\n elif self.metadata_indexing_exclude:\n vector_store_kwargs[\"metadata_indexing_exclude\"] = self.metadata_indexing_exclude\n elif self.collection_indexing_policy:\n vector_store_kwargs[\"collection_indexing_policy\"] = self.collection_indexing_policy\n\n try:\n vector_store = AstraDBVectorStore(**vector_store_kwargs)\n except Exception as e:\n raise ValueError(f\"Error initializing AstraDBVectorStore: {str(e)}\") from e\n\n if self.add_to_vector_store:\n self._add_documents_to_vector_store(vector_store)\n\n return vector_store\n\n def build_base_retriever(self):\n vector_store = self.build_vector_store()\n self.status = self._astradb_collection_to_data(vector_store.collection)\n return vector_store\n\n def _add_documents_to_vector_store(self, vector_store):\n documents = []\n for _input in self.vector_store_inputs or []:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n else:\n raise ValueError(\"Vector Store Inputs must be Data objects.\")\n\n if documents and self.embedding is not None:\n logger.debug(f\"Adding {len(documents)} documents to the Vector Store.\")\n try:\n vector_store.add_documents(documents)\n except Exception as e:\n raise ValueError(f\"Error adding documents to AstraDBVectorStore: {str(e)}\") from e\n else:\n logger.debug(\"No documents to add to the Vector Store.\")\n\n def search_documents(self):\n vector_store = self.build_vector_store()\n\n logger.debug(f\"Search input: {self.search_input}\")\n logger.debug(f\"Search type: {self.search_type}\")\n logger.debug(f\"Number of results: {self.number_of_results}\")\n\n if self.search_input and isinstance(self.search_input, str) and self.search_input.strip():\n try:\n if self.search_type == \"Similarity\":\n docs = vector_store.similarity_search(\n query=self.search_input,\n k=self.number_of_results,\n )\n elif self.search_type == \"MMR\":\n docs = vector_store.max_marginal_relevance_search(\n query=self.search_input,\n k=self.number_of_results,\n )\n else:\n raise ValueError(f\"Invalid search type: {self.search_type}\")\n except Exception as e:\n raise ValueError(f\"Error performing search in AstraDBVectorStore: {str(e)}\") from e\n\n logger.debug(f\"Retrieved documents: {len(docs)}\")\n\n data = [Data.from_document(doc) for doc in docs]\n logger.debug(f\"Converted documents to data: {len(data)}\")\n self.status = data\n return data\n else:\n logger.debug(\"No search input provided. Skipping search.\")\n return []\n\n def _astradb_collection_to_data(self, collection):\n data = []\n data_dict = collection.find()\n if data_dict and \"data\" in data_dict:\n data_dict = data_dict[\"data\"].get(\"documents\", [])\n\n for item in data_dict:\n data.append(Data(content=item[\"content\"]))\n return data\n" - }, - "collection_indexing_policy": { - "advanced": true, - "display_name": "Collection Indexing Policy", - "dynamic": false, - "info": "Optional dictionary defining the indexing policy for the collection.", - "list": false, - "load_from_db": false, - "name": "collection_indexing_policy", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "collection_name": { - "advanced": false, - "display_name": "Collection Name", - "dynamic": false, - "info": "The name of the collection within Astra DB where the vectors will be stored.", - "list": false, - "load_from_db": false, - "name": "collection_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "langflow" - }, - "embedding": { - "advanced": false, - "display_name": "Embedding", - "dynamic": false, - "info": "", - "input_types": [ - "Embeddings" - ], - "list": false, - "name": "embedding", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "other", - "value": "" - }, - "metadata_indexing_exclude": { - "advanced": true, - "display_name": "Metadata Indexing Exclude", - "dynamic": false, - "info": "Optional list of metadata fields to exclude from the indexing.", - "list": false, - "load_from_db": false, - "name": "metadata_indexing_exclude", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "metadata_indexing_include": { - "advanced": true, - "display_name": "Metadata Indexing Include", - "dynamic": false, - "info": "Optional list of metadata fields to include in the indexing.", - "list": false, - "load_from_db": false, - "name": "metadata_indexing_include", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "metric": { - "advanced": true, - "display_name": "Metric", - "dynamic": false, - "info": "Optional distance metric for vector comparisons in the vector store.", - "name": "metric", - "options": [ - "cosine", - "dot_product", - "euclidean" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "namespace": { - "advanced": true, - "display_name": "Namespace", - "dynamic": false, - "info": "Optional namespace within Astra DB to use for the collection.", - "list": false, - "load_from_db": false, - "name": "namespace", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "number_of_results": { - "advanced": true, - "display_name": "Number of Results", - "dynamic": false, - "info": "Number of results to return.", - "list": false, - "name": "number_of_results", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": 4 - }, - "pre_delete_collection": { - "advanced": true, - "display_name": "Pre Delete Collection", - "dynamic": false, - "info": "Boolean flag to determine whether to delete the collection before creating a new one.", - "list": false, - "name": "pre_delete_collection", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "bool", - "value": false - }, - "search_input": { - "advanced": false, - "display_name": "Search Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "search_input", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "search_type": { - "advanced": false, - "display_name": "Search Type", - "dynamic": false, - "info": "", - "name": "search_type", - "options": [ - "Similarity", - "MMR" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "Similarity" - }, - "setup_mode": { - "advanced": true, - "display_name": "Setup Mode", - "dynamic": false, - "info": "Configuration mode for setting up the vector store, with options like 'Sync', 'Async', or 'Off'.", - "name": "setup_mode", - "options": [ - "Sync", - "Async", - "Off" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "Sync" - }, - "token": { - "advanced": false, - "display_name": "Astra DB Application Token", - "dynamic": false, - "info": "Authentication token for accessing Astra DB.", - "input_types": [], - "load_from_db": true, - "name": "token", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "vector_store_inputs": { - "advanced": false, - "display_name": "Vector Store Inputs", - "dynamic": false, - "info": "", - "input_types": [ - "Document", - "Data" - ], - "list": true, - "name": "vector_store_inputs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "other", - "value": "" - } - } - }, - "type": "AstraDB" - }, - "dragging": false, - "height": 917, - "id": "AstraDB-wANQu", + "id": "AstraDB-p6135", "position": { "x": 1298.4611042465333, "y": 160.7181472642742 @@ -2801,7 +1604,7 @@ }, { "data": { - "id": "ParseData-C9tUn", + "id": "ParseData-9DrmC", "node": { "base_classes": [ "Message" @@ -2824,14 +1627,14 @@ { "cache": true, "display_name": "Text", + "hidden": false, "method": "parse_data", "name": "text", "selected": "Message", "types": [ "Message" ], - "value": "__UNDEFINED__", - "hidden": false + "value": "__UNDEFINED__" } ], "pinned": false, @@ -2913,7 +1716,7 @@ }, "dragging": false, "height": 385, - "id": "ParseData-C9tUn", + "id": "ParseData-9DrmC", "position": { "x": 1911.4866480237615, "y": 566.903831987901 @@ -2925,156 +1728,1142 @@ "selected": false, "type": "genericNode", "width": 384 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-EEXgw", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "context", + "question" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "error": null, + "field_order": [ + "template" + ], + "frozen": false, + "full_path": null, + "icon": "prompts", + "is_composition": null, + "is_input": null, + "is_output": null, + "name": "", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "hidden": false, + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def post_code_processing(self, new_build_config: dict, current_build_config: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_build_config, current_build_config)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_build_config\n # and update the frontend_node with those values\n update_template_values(frontend_template=frontend_node, raw_template=current_build_config[\"template\"])\n return frontend_node\n" + }, + "context": { + "advanced": false, + "display_name": "context", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "context", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "question": { + "advanced": false, + "display_name": "question", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "question", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "template": { + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "prompt", + "value": "{context}\n\n---\n\nGiven the context above, answer the question as best as possible.\n\nQuestion: {question}\n\nAnswer: " + } + } + }, + "type": "Prompt" + }, + "dragging": false, + "height": 517, + "id": "Prompt-EEXgw", + "position": { + "x": 2537.8054430938064, + "y": 442.35183727527414 + }, + "positionAbsolute": { + "x": 2537.8054430938064, + "y": 442.35183727527414 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "id": "SplitText-qI0jS", + "node": { + "base_classes": [ + "Data" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Split text into chunks based on specified criteria.", + "display_name": "Split Text", + "documentation": "", + "edited": false, + "field_order": [ + "data_inputs", + "chunk_overlap", + "chunk_size", + "separator" + ], + "frozen": false, + "icon": "scissors-line-dashed", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Chunks", + "hidden": false, + "method": "split_text", + "name": "chunks", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "chunk_overlap": { + "advanced": false, + "display_name": "Chunk Overlap", + "dynamic": false, + "info": "Number of characters to overlap between chunks.", + "list": false, + "name": "chunk_overlap", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 200 + }, + "chunk_size": { + "advanced": false, + "display_name": "Chunk Size", + "dynamic": false, + "info": "The maximum number of characters in each chunk.", + "list": false, + "name": "chunk_size", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1000 + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from typing import List\n\nfrom langchain_text_splitters import CharacterTextSplitter\n\nfrom langflow.custom import Component\nfrom langflow.io import HandleInput, IntInput, MessageTextInput, Output\nfrom langflow.schema import Data\nfrom langflow.utils.util import unescape_string\n\n\nclass SplitTextComponent(Component):\n display_name: str = \"Split Text\"\n description: str = \"Split text into chunks based on specified criteria.\"\n icon = \"scissors-line-dashed\"\n\n inputs = [\n HandleInput(\n name=\"data_inputs\",\n display_name=\"Data Inputs\",\n info=\"The data to split.\",\n input_types=[\"Data\"],\n is_list=True,\n ),\n IntInput(\n name=\"chunk_overlap\",\n display_name=\"Chunk Overlap\",\n info=\"Number of characters to overlap between chunks.\",\n value=200,\n ),\n IntInput(\n name=\"chunk_size\",\n display_name=\"Chunk Size\",\n info=\"The maximum number of characters in each chunk.\",\n value=1000,\n ),\n MessageTextInput(\n name=\"separator\",\n display_name=\"Separator\",\n info=\"The character to split on. Defaults to newline.\",\n value=\"\\n\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Chunks\", name=\"chunks\", method=\"split_text\"),\n ]\n\n def _docs_to_data(self, docs):\n data = []\n for doc in docs:\n data.append(Data(text=doc.page_content, data=doc.metadata))\n return data\n\n def split_text(self) -> List[Data]:\n separator = unescape_string(self.separator)\n\n documents = []\n for _input in self.data_inputs:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n\n splitter = CharacterTextSplitter(\n chunk_overlap=self.chunk_overlap,\n chunk_size=self.chunk_size,\n separator=separator,\n )\n docs = splitter.split_documents(documents)\n data = self._docs_to_data(docs)\n self.status = data\n return data\n" + }, + "data_inputs": { + "advanced": false, + "display_name": "Data Inputs", + "dynamic": false, + "info": "The data to split.", + "input_types": [ + "Data" + ], + "list": true, + "name": "data_inputs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "separator": { + "advanced": false, + "display_name": "Separator", + "dynamic": false, + "info": "The character to split on. Defaults to newline.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "separator", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "\n" + } + } + }, + "type": "SplitText" + }, + "dragging": false, + "height": 557, + "id": "SplitText-qI0jS", + "position": { + "x": 1992.5159478772907, + "y": 1190.8288727494814 + }, + "positionAbsolute": { + "x": 1992.5159478772907, + "y": 1190.8288727494814 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "id": "AstraDB-AX2Xz", + "type": "genericNode", + "position": { + "x": 2773.0562333179937, + "y": 1160.0660495763536 + }, + "data": { + "description": "Implementation of Vector Store using Astra DB with search capabilities", + "display_name": "Astra DB Vector Store", + "id": "AstraDB-AX2Xz", + "node": { + "base_classes": [ + "Data" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Implementation of Vector Store using Astra DB with search capabilities", + "display_name": "Astra DB Vector Store", + "documentation": "https://python.langchain.com/docs/integrations/vectorstores/astradb", + "edited": false, + "field_order": [ + "collection_name", + "token", + "api_endpoint", + "vector_store_inputs", + "embedding", + "namespace", + "metric", + "batch_size", + "bulk_insert_batch_concurrency", + "bulk_insert_overwrite_concurrency", + "bulk_delete_concurrency", + "setup_mode", + "pre_delete_collection", + "metadata_indexing_include", + "metadata_indexing_exclude", + "collection_indexing_policy", + "add_to_vector_store", + "search_input", + "search_type", + "number_of_results" + ], + "frozen": false, + "icon": "AstraDB", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Retriever", + "method": "build_base_retriever", + "name": "base_retriever", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Search Results", + "hidden": false, + "method": "search_documents", + "name": "search_results", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "add_to_vector_store": { + "advanced": false, + "display_name": "Add to Vector Store", + "dynamic": false, + "info": "If true, the Vector Store Inputs will be added to the Vector Store.", + "list": false, + "name": "add_to_vector_store", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": true + }, + "api_endpoint": { + "advanced": false, + "display_name": "API Endpoint", + "dynamic": false, + "info": "API endpoint URL for the Astra DB service.", + "input_types": [], + "load_from_db": false, + "name": "api_endpoint", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "batch_size": { + "advanced": true, + "display_name": "Batch Size", + "dynamic": false, + "info": "Optional number of data to process in a single batch.", + "list": false, + "name": "batch_size", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "bulk_delete_concurrency": { + "advanced": true, + "display_name": "Bulk Delete Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk delete operations.", + "list": false, + "name": "bulk_delete_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "bulk_insert_batch_concurrency": { + "advanced": true, + "display_name": "Bulk Insert Batch Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk insert operations.", + "list": false, + "name": "bulk_insert_batch_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "bulk_insert_overwrite_concurrency": { + "advanced": true, + "display_name": "Bulk Insert Overwrite Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk insert operations that overwrite existing data.", + "list": false, + "name": "bulk_insert_overwrite_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from loguru import logger\n\nfrom langflow.base.vectorstores.model import LCVectorStoreComponent\nfrom langflow.io import BoolInput, DropdownInput, HandleInput, IntInput, MultilineInput, SecretStrInput, StrInput\nfrom langflow.schema import Data\n\n\nclass AstraVectorStoreComponent(LCVectorStoreComponent):\n display_name: str = \"Astra DB Vector Store\"\n description: str = \"Implementation of Vector Store using Astra DB with search capabilities\"\n documentation: str = \"https://python.langchain.com/docs/integrations/vectorstores/astradb\"\n icon: str = \"AstraDB\"\n\n inputs = [\n StrInput(\n name=\"collection_name\",\n display_name=\"Collection Name\",\n info=\"The name of the collection within Astra DB where the vectors will be stored.\",\n ),\n SecretStrInput(\n name=\"token\",\n display_name=\"Astra DB Application Token\",\n info=\"Authentication token for accessing Astra DB.\",\n value=\"ASTRA_DB_APPLICATION_TOKEN\",\n ),\n SecretStrInput(\n name=\"api_endpoint\",\n display_name=\"API Endpoint\",\n info=\"API endpoint URL for the Astra DB service.\",\n value=\"ASTRA_DB_API_ENDPOINT\",\n ),\n HandleInput(\n name=\"vector_store_inputs\",\n display_name=\"Vector Store Inputs\",\n input_types=[\"Document\", \"Data\"],\n is_list=True,\n ),\n HandleInput(\n name=\"embedding\",\n display_name=\"Embedding\",\n input_types=[\"Embeddings\"],\n ),\n StrInput(\n name=\"namespace\",\n display_name=\"Namespace\",\n info=\"Optional namespace within Astra DB to use for the collection.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"metric\",\n display_name=\"Metric\",\n info=\"Optional distance metric for vector comparisons in the vector store.\",\n options=[\"cosine\", \"dot_product\", \"euclidean\"],\n advanced=True,\n ),\n IntInput(\n name=\"batch_size\",\n display_name=\"Batch Size\",\n info=\"Optional number of data to process in a single batch.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_batch_concurrency\",\n display_name=\"Bulk Insert Batch Concurrency\",\n info=\"Optional concurrency level for bulk insert operations.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_overwrite_concurrency\",\n display_name=\"Bulk Insert Overwrite Concurrency\",\n info=\"Optional concurrency level for bulk insert operations that overwrite existing data.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_delete_concurrency\",\n display_name=\"Bulk Delete Concurrency\",\n info=\"Optional concurrency level for bulk delete operations.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"setup_mode\",\n display_name=\"Setup Mode\",\n info=\"Configuration mode for setting up the vector store, with options like 'Sync', 'Async', or 'Off'.\",\n options=[\"Sync\", \"Async\", \"Off\"],\n advanced=True,\n value=\"Sync\",\n ),\n BoolInput(\n name=\"pre_delete_collection\",\n display_name=\"Pre Delete Collection\",\n info=\"Boolean flag to determine whether to delete the collection before creating a new one.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_include\",\n display_name=\"Metadata Indexing Include\",\n info=\"Optional list of metadata fields to include in the indexing.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_exclude\",\n display_name=\"Metadata Indexing Exclude\",\n info=\"Optional list of metadata fields to exclude from the indexing.\",\n advanced=True,\n ),\n StrInput(\n name=\"collection_indexing_policy\",\n display_name=\"Collection Indexing Policy\",\n info=\"Optional dictionary defining the indexing policy for the collection.\",\n advanced=True,\n ),\n BoolInput(\n name=\"add_to_vector_store\",\n display_name=\"Add to Vector Store\",\n info=\"If true, the Vector Store Inputs will be added to the Vector Store.\",\n ),\n MultilineInput(\n name=\"search_input\",\n display_name=\"Search Input\",\n ),\n DropdownInput(\n name=\"search_type\",\n display_name=\"Search Type\",\n options=[\"Similarity\", \"MMR\"],\n value=\"Similarity\",\n ),\n IntInput(\n name=\"number_of_results\",\n display_name=\"Number of Results\",\n info=\"Number of results to return.\",\n advanced=True,\n value=4,\n ),\n ]\n\n def build_vector_store(self):\n try:\n from langchain_astradb import AstraDBVectorStore\n from langchain_astradb.utils.astradb import SetupMode\n except ImportError:\n raise ImportError(\n \"Could not import langchain Astra DB integration package. \"\n \"Please install it with `pip install langchain-astradb`.\"\n )\n\n try:\n if not self.setup_mode:\n self.setup_mode = self._inputs[\"setup_mode\"].options[0]\n\n setup_mode_value = SetupMode[self.setup_mode.upper()]\n except KeyError:\n raise ValueError(f\"Invalid setup mode: {self.setup_mode}\")\n\n vector_store_kwargs = {\n \"embedding\": self.embedding,\n \"collection_name\": self.collection_name,\n \"token\": self.token,\n \"api_endpoint\": self.api_endpoint,\n \"namespace\": self.namespace or None,\n \"metric\": self.metric or None,\n \"batch_size\": self.batch_size or None,\n \"bulk_insert_batch_concurrency\": self.bulk_insert_batch_concurrency or None,\n \"bulk_insert_overwrite_concurrency\": self.bulk_insert_overwrite_concurrency or None,\n \"bulk_delete_concurrency\": self.bulk_delete_concurrency or None,\n \"setup_mode\": setup_mode_value,\n \"pre_delete_collection\": self.pre_delete_collection or False,\n }\n\n if self.metadata_indexing_include:\n vector_store_kwargs[\"metadata_indexing_include\"] = self.metadata_indexing_include\n elif self.metadata_indexing_exclude:\n vector_store_kwargs[\"metadata_indexing_exclude\"] = self.metadata_indexing_exclude\n elif self.collection_indexing_policy:\n vector_store_kwargs[\"collection_indexing_policy\"] = self.collection_indexing_policy\n\n try:\n vector_store = AstraDBVectorStore(**vector_store_kwargs)\n except Exception as e:\n raise ValueError(f\"Error initializing AstraDBVectorStore: {str(e)}\") from e\n\n if self.add_to_vector_store:\n self._add_documents_to_vector_store(vector_store)\n\n return vector_store\n\n def build_base_retriever(self):\n vector_store = self.build_vector_store()\n self.status = self._astradb_collection_to_data(vector_store.collection)\n return vector_store\n\n def _add_documents_to_vector_store(self, vector_store):\n documents = []\n for _input in self.vector_store_inputs or []:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n else:\n raise ValueError(\"Vector Store Inputs must be Data objects.\")\n\n if documents and self.embedding is not None:\n logger.debug(f\"Adding {len(documents)} documents to the Vector Store.\")\n try:\n vector_store.add_documents(documents)\n except Exception as e:\n raise ValueError(f\"Error adding documents to AstraDBVectorStore: {str(e)}\") from e\n else:\n logger.debug(\"No documents to add to the Vector Store.\")\n\n def search_documents(self):\n vector_store = self.build_vector_store()\n\n logger.debug(f\"Search input: {self.search_input}\")\n logger.debug(f\"Search type: {self.search_type}\")\n logger.debug(f\"Number of results: {self.number_of_results}\")\n\n if self.search_input and isinstance(self.search_input, str) and self.search_input.strip():\n try:\n if self.search_type == \"Similarity\":\n docs = vector_store.similarity_search(\n query=self.search_input,\n k=self.number_of_results,\n )\n elif self.search_type == \"MMR\":\n docs = vector_store.max_marginal_relevance_search(\n query=self.search_input,\n k=self.number_of_results,\n )\n else:\n raise ValueError(f\"Invalid search type: {self.search_type}\")\n except Exception as e:\n raise ValueError(f\"Error performing search in AstraDBVectorStore: {str(e)}\") from e\n\n logger.debug(f\"Retrieved documents: {len(docs)}\")\n\n data = [Data.from_document(doc) for doc in docs]\n logger.debug(f\"Converted documents to data: {len(data)}\")\n self.status = data\n return data\n else:\n logger.debug(\"No search input provided. Skipping search.\")\n return []\n\n def _astradb_collection_to_data(self, collection):\n data = []\n data_dict = collection.find()\n if data_dict and \"data\" in data_dict:\n data_dict = data_dict[\"data\"].get(\"documents\", [])\n\n for item in data_dict:\n data.append(Data(content=item[\"content\"]))\n return data\n" + }, + "collection_indexing_policy": { + "advanced": true, + "display_name": "Collection Indexing Policy", + "dynamic": false, + "info": "Optional dictionary defining the indexing policy for the collection.", + "list": false, + "load_from_db": false, + "name": "collection_indexing_policy", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "collection_name": { + "advanced": false, + "display_name": "Collection Name", + "dynamic": false, + "info": "The name of the collection within Astra DB where the vectors will be stored.", + "list": false, + "load_from_db": false, + "name": "collection_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "langflow" + }, + "embedding": { + "advanced": false, + "display_name": "Embedding", + "dynamic": false, + "info": "", + "input_types": [ + "Embeddings" + ], + "list": false, + "name": "embedding", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "other", + "value": "" + }, + "metadata_indexing_exclude": { + "advanced": true, + "display_name": "Metadata Indexing Exclude", + "dynamic": false, + "info": "Optional list of metadata fields to exclude from the indexing.", + "list": false, + "load_from_db": false, + "name": "metadata_indexing_exclude", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "metadata_indexing_include": { + "advanced": true, + "display_name": "Metadata Indexing Include", + "dynamic": false, + "info": "Optional list of metadata fields to include in the indexing.", + "list": false, + "load_from_db": false, + "name": "metadata_indexing_include", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "metric": { + "advanced": true, + "display_name": "Metric", + "dynamic": false, + "info": "Optional distance metric for vector comparisons in the vector store.", + "name": "metric", + "options": [ + "cosine", + "dot_product", + "euclidean" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "namespace": { + "advanced": true, + "display_name": "Namespace", + "dynamic": false, + "info": "Optional namespace within Astra DB to use for the collection.", + "list": false, + "load_from_db": false, + "name": "namespace", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "number_of_results": { + "advanced": true, + "display_name": "Number of Results", + "dynamic": false, + "info": "Number of results to return.", + "list": false, + "name": "number_of_results", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 4 + }, + "pre_delete_collection": { + "advanced": true, + "display_name": "Pre Delete Collection", + "dynamic": false, + "info": "Boolean flag to determine whether to delete the collection before creating a new one.", + "list": false, + "name": "pre_delete_collection", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "search_input": { + "advanced": false, + "display_name": "Search Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "search_input", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "search_type": { + "advanced": false, + "display_name": "Search Type", + "dynamic": false, + "info": "", + "name": "search_type", + "options": [ + "Similarity", + "MMR" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "Similarity" + }, + "setup_mode": { + "advanced": true, + "display_name": "Setup Mode", + "dynamic": false, + "info": "Configuration mode for setting up the vector store, with options like 'Sync', 'Async', or 'Off'.", + "name": "setup_mode", + "options": [ + "Sync", + "Async", + "Off" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "Sync" + }, + "token": { + "advanced": false, + "display_name": "Astra DB Application Token", + "dynamic": false, + "info": "Authentication token for accessing Astra DB.", + "input_types": [], + "load_from_db": false, + "name": "token", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "vector_store_inputs": { + "advanced": false, + "display_name": "Vector Store Inputs", + "dynamic": false, + "info": "", + "input_types": [ + "Document", + "Data" + ], + "list": true, + "name": "vector_store_inputs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "other", + "value": "" + } + } + }, + "type": "AstraDB" + }, + "selected": false, + "width": 384, + "height": 917, + "positionAbsolute": { + "x": 2773.0562333179937, + "y": 1160.0660495763536 + }, + "dragging": false + }, + { + "id": "OpenAIEmbeddings-PQc6x", + "type": "genericNode", + "position": { + "x": 1992.590633037642, + "y": 1850.2707576021312 + }, + "data": { + "id": "OpenAIEmbeddings-PQc6x", + "node": { + "base_classes": [ + "Embeddings" + ], + "beta": false, + "custom_fields": { + "allowed_special": null, + "chunk_size": null, + "client": null, + "default_headers": null, + "default_query": null, + "deployment": null, + "disallowed_special": null, + "embedding_ctx_length": null, + "max_retries": null, + "model": null, + "model_kwargs": null, + "openai_api_base": null, + "openai_api_key": null, + "openai_api_type": null, + "openai_api_version": null, + "openai_organization": null, + "openai_proxy": null, + "request_timeout": null, + "show_progress_bar": null, + "skip_empty": null, + "tiktoken_enable": null, + "tiktoken_model_name": null + }, + "description": "Generate embeddings using OpenAI models.", + "display_name": "OpenAI Embeddings", + "documentation": "", + "field_formatters": {}, + "field_order": [], + "frozen": false, + "icon": "OpenAI", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Embeddings", + "hidden": false, + "method": "build_embeddings", + "name": "embeddings", + "selected": "Embeddings", + "types": [ + "Embeddings" + ], + "value": "__UNDEFINED__" + } + ], + "template": { + "_type": "Component", + "chunk_size": { + "advanced": true, + "display_name": "Chunk Size", + "dynamic": false, + "info": "", + "list": false, + "name": "chunk_size", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 1000 + }, + "client": { + "advanced": true, + "display_name": "Client", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "client", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain_openai.embeddings.base import OpenAIEmbeddings\n\nfrom langflow.base.embeddings.model import LCEmbeddingsModel\nfrom langflow.field_typing import Embeddings\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, MessageTextInput\n\n\nclass OpenAIEmbeddingsComponent(LCEmbeddingsModel):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n icon = \"OpenAI\"\n inputs = [\n DictInput(\n name=\"default_headers\",\n display_name=\"Default Headers\",\n advanced=True,\n info=\"Default headers to use for the API request.\",\n ),\n DictInput(\n name=\"default_query\",\n display_name=\"Default Query\",\n advanced=True,\n info=\"Default query parameters to use for the API request.\",\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n MessageTextInput(name=\"client\", display_name=\"Client\", advanced=True),\n MessageTextInput(name=\"deployment\", display_name=\"Deployment\", advanced=True),\n IntInput(name=\"embedding_ctx_length\", display_name=\"Embedding Context Length\", advanced=True, value=1536),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", value=3, advanced=True),\n DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n advanced=False,\n options=[\n \"text-embedding-3-small\",\n \"text-embedding-3-large\",\n \"text-embedding-ada-002\",\n ],\n value=\"text-embedding-3-small\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n SecretStrInput(name=\"openai_api_base\", display_name=\"OpenAI API Base\", advanced=True),\n SecretStrInput(name=\"openai_api_key\", display_name=\"OpenAI API Key\"),\n SecretStrInput(name=\"openai_api_type\", display_name=\"OpenAI API Type\", advanced=True),\n MessageTextInput(name=\"openai_api_version\", display_name=\"OpenAI API Version\", advanced=True),\n MessageTextInput(\n name=\"openai_organization\",\n display_name=\"OpenAI Organization\",\n advanced=True,\n ),\n MessageTextInput(name=\"openai_proxy\", display_name=\"OpenAI Proxy\", advanced=True),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n BoolInput(name=\"skip_empty\", display_name=\"Skip Empty\", advanced=True),\n MessageTextInput(\n name=\"tiktoken_model_name\",\n display_name=\"TikToken Model Name\",\n advanced=True,\n ),\n BoolInput(\n name=\"tiktoken_enable\",\n display_name=\"TikToken Enable\",\n advanced=True,\n value=True,\n info=\"If False, you must have transformers installed.\",\n ),\n ]\n\n def build_embeddings(self) -> Embeddings:\n return OpenAIEmbeddings(\n tiktoken_enabled=self.tiktoken_enable,\n default_headers=self.default_headers,\n default_query=self.default_query,\n allowed_special=\"all\",\n disallowed_special=\"all\",\n chunk_size=self.chunk_size,\n deployment=self.deployment,\n embedding_ctx_length=self.embedding_ctx_length,\n max_retries=self.max_retries,\n model=self.model,\n model_kwargs=self.model_kwargs,\n base_url=self.openai_api_base,\n api_key=self.openai_api_key,\n openai_api_type=self.openai_api_type,\n api_version=self.openai_api_version,\n organization=self.openai_organization,\n openai_proxy=self.openai_proxy,\n timeout=self.request_timeout or None,\n show_progress_bar=self.show_progress_bar,\n skip_empty=self.skip_empty,\n tiktoken_model_name=self.tiktoken_model_name,\n )\n" + }, + "default_headers": { + "advanced": true, + "display_name": "Default Headers", + "dynamic": false, + "info": "Default headers to use for the API request.", + "list": false, + "name": "default_headers", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "default_query": { + "advanced": true, + "display_name": "Default Query", + "dynamic": false, + "info": "Default query parameters to use for the API request.", + "list": false, + "name": "default_query", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "deployment": { + "advanced": true, + "display_name": "Deployment", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "deployment", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "embedding_ctx_length": { + "advanced": true, + "display_name": "Embedding Context Length", + "dynamic": false, + "info": "", + "list": false, + "name": "embedding_ctx_length", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 1536 + }, + "max_retries": { + "advanced": true, + "display_name": "Max Retries", + "dynamic": false, + "info": "", + "list": false, + "name": "max_retries", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 3 + }, + "model": { + "advanced": false, + "display_name": "Model", + "dynamic": false, + "info": "", + "name": "model", + "options": [ + "text-embedding-3-small", + "text-embedding-3-large", + "text-embedding-ada-002" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "text-embedding-3-small" + }, + "model_kwargs": { + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "openai_api_base": { + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "", + "input_types": [], + "load_from_db": true, + "name": "openai_api_base", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_key": { + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "", + "input_types": [], + "load_from_db": false, + "name": "openai_api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_type": { + "advanced": true, + "display_name": "OpenAI API Type", + "dynamic": false, + "info": "", + "input_types": [], + "load_from_db": true, + "name": "openai_api_type", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_version": { + "advanced": true, + "display_name": "OpenAI API Version", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "openai_api_version", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_organization": { + "advanced": true, + "display_name": "OpenAI Organization", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "openai_organization", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_proxy": { + "advanced": true, + "display_name": "OpenAI Proxy", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "openai_proxy", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "request_timeout": { + "advanced": true, + "display_name": "Request Timeout", + "dynamic": false, + "info": "", + "list": false, + "name": "request_timeout", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "float", + "value": "" + }, + "show_progress_bar": { + "advanced": true, + "display_name": "Show Progress Bar", + "dynamic": false, + "info": "", + "list": false, + "name": "show_progress_bar", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "skip_empty": { + "advanced": true, + "display_name": "Skip Empty", + "dynamic": false, + "info": "", + "list": false, + "name": "skip_empty", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "tiktoken_enable": { + "advanced": true, + "display_name": "TikToken Enable", + "dynamic": false, + "info": "If False, you must have transformers installed.", + "list": false, + "name": "tiktoken_enable", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": true + }, + "tiktoken_model_name": { + "advanced": true, + "display_name": "TikToken Model Name", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "tiktoken_model_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + } + } + }, + "type": "OpenAIEmbeddings" + }, + "selected": true, + "width": 384, + "height": 395, + "positionAbsolute": { + "x": 1992.590633037642, + "y": 1850.2707576021312 + }, + "dragging": true } ], "edges": [ - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "Prompt", - "id": "Prompt-jzPqb", - "name": "prompt", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "OpenAIModel-ickkA", - "inputTypes": [ - "Message" - ], - "type": "str" - } - }, - "id": "reactflow__edge-Prompt-jzPqb{œdataTypeœ:œPromptœ,œidœ:œPrompt-jzPqbœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-ickkA{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-ickkAœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "selected": false, - "source": "Prompt-jzPqb", - "sourceHandle": 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"{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-ickkAœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}", - "style": { - "stroke": "#555" - }, - "target": "ChatOutput-Zy354", - "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-Zy354œ,œinputTypesœ:[œMessageœ,œstrœ],œtypeœ:œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "File", - "id": "File-28ckd", - "name": "data", - "output_types": [ - "Data" - ] - }, - "targetHandle": { - "fieldName": "data_input", - "id": "RecursiveCharacterTextSplitter-HVESL", - "inputTypes": [ - "Document", - "Data" - ], - "type": "other" - } - }, - "id": "reactflow__edge-File-28ckd{œdataTypeœ:œFileœ,œidœ:œFile-28ckdœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-RecursiveCharacterTextSplitter-HVESL{œfieldNameœ:œdata_inputœ,œidœ:œRecursiveCharacterTextSplitter-HVESLœ,œinputTypesœ:[œDocumentœ,œDataœ],œtypeœ:œotherœ}", - "source": "File-28ckd", - "sourceHandle": "{œdataTypeœ:œFileœ,œidœ:œFile-28ckdœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}", - "target": "RecursiveCharacterTextSplitter-HVESL", - "targetHandle": "{œfieldNameœ:œdata_inputœ,œidœ:œRecursiveCharacterTextSplitter-HVESLœ,œinputTypesœ:[œDocumentœ,œDataœ],œtypeœ:œotherœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "RecursiveCharacterTextSplitter", - "id": "RecursiveCharacterTextSplitter-HVESL", - "name": "data", - "output_types": [ - "Data" - ] - }, - "targetHandle": { - "fieldName": "vector_store_inputs", - "id": "AstraDB-irvai", - "inputTypes": [ - "Document", - "Data" - ], - "type": "other" - } - }, - "id": "reactflow__edge-RecursiveCharacterTextSplitter-HVESL{œdataTypeœ:œRecursiveCharacterTextSplitterœ,œidœ:œRecursiveCharacterTextSplitter-HVESLœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-AstraDB-irvai{œfieldNameœ:œvector_store_inputsœ,œidœ:œAstraDB-irvaiœ,œinputTypesœ:[œDocumentœ,œDataœ],œtypeœ:œotherœ}", - "source": "RecursiveCharacterTextSplitter-HVESL", - "sourceHandle": "{œdataTypeœ:œRecursiveCharacterTextSplitterœ,œidœ:œRecursiveCharacterTextSplitter-HVESLœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}", - "target": "AstraDB-irvai", - "targetHandle": "{œfieldNameœ:œvector_store_inputsœ,œidœ:œAstraDB-irvaiœ,œinputTypesœ:[œDocumentœ,œDataœ],œtypeœ:œotherœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "OpenAIEmbeddings", - "id": "OpenAIEmbeddings-YeYtt", - "name": "embeddings", - "output_types": [ - "Embeddings" - ] - }, - "targetHandle": { - "fieldName": "embedding", - "id": "AstraDB-irvai", - "inputTypes": [ - "Embeddings" - ], - "type": "other" - } - }, - "id": "reactflow__edge-OpenAIEmbeddings-YeYtt{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-YeYttœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}-AstraDB-irvai{œfieldNameœ:œembeddingœ,œidœ:œAstraDB-irvaiœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}", - "source": "OpenAIEmbeddings-YeYtt", - "sourceHandle": "{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-YeYttœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}", - "target": "AstraDB-irvai", - "targetHandle": "{œfieldNameœ:œembeddingœ,œidœ:œAstraDB-irvaiœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}" - }, { "className": "", "data": { "sourceHandle": { "dataType": "ChatInput", - "id": "ChatInput-IY8UK", + "id": "ChatInput-8ZRjI", "name": "message", "output_types": [ "Message" @@ -3082,7 +2871,7 @@ }, "targetHandle": { "fieldName": "search_input", - "id": "AstraDB-wANQu", + "id": "AstraDB-p6135", "inputTypes": [ "Message", "str" @@ -3090,19 +2879,19 @@ "type": "str" } }, - "id": "reactflow__edge-ChatInput-IY8UK{œdataTypeœ:œChatInputœ,œidœ:œChatInput-IY8UKœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-AstraDB-wANQu{œfieldNameœ:œsearch_inputœ,œidœ:œAstraDB-wANQuœ,œinputTypesœ:[œMessageœ,œstrœ],œtypeœ:œstrœ}", + "id": "reactflow__edge-ChatInput-8ZRjI{œdataTypeœ:œChatInputœ,œidœ:œChatInput-8ZRjIœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-AstraDB-p6135{œfieldNameœ:œsearch_inputœ,œidœ:œAstraDB-p6135œ,œinputTypesœ:[œMessageœ,œstrœ],œtypeœ:œstrœ}", "selected": false, - "source": "ChatInput-IY8UK", - "sourceHandle": "{œdataTypeœ:œChatInputœ,œidœ:œChatInput-IY8UKœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}", - "target": "AstraDB-wANQu", - "targetHandle": "{œfieldNameœ:œsearch_inputœ,œidœ:œAstraDB-wANQuœ,œinputTypesœ:[œMessageœ,œstrœ],œtypeœ:œstrœ}" + "source": "ChatInput-8ZRjI", + "sourceHandle": "{œdataTypeœ:œChatInputœ,œidœ:œChatInput-8ZRjIœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}", + "target": "AstraDB-p6135", + "targetHandle": "{œfieldNameœ:œsearch_inputœ,œidœ:œAstraDB-p6135œ,œinputTypesœ:[œMessageœ,œstrœ],œtypeœ:œstrœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "OpenAIEmbeddings", - "id": "OpenAIEmbeddings-HoSp5", + "id": "OpenAIEmbeddings-hNOwh", "name": "embeddings", "output_types": [ "Embeddings" @@ -3110,26 +2899,26 @@ }, "targetHandle": { "fieldName": "embedding", - "id": "AstraDB-wANQu", + "id": "AstraDB-p6135", "inputTypes": [ "Embeddings" ], "type": "other" } }, - "id": "reactflow__edge-OpenAIEmbeddings-HoSp5{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-HoSp5œ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}-AstraDB-wANQu{œfieldNameœ:œembeddingœ,œidœ:œAstraDB-wANQuœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}", + "id": "reactflow__edge-OpenAIEmbeddings-hNOwh{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-hNOwhœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}-AstraDB-p6135{œfieldNameœ:œembeddingœ,œidœ:œAstraDB-p6135œ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}", "selected": false, - "source": "OpenAIEmbeddings-HoSp5", - "sourceHandle": "{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-HoSp5œ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}", - "target": "AstraDB-wANQu", - "targetHandle": "{œfieldNameœ:œembeddingœ,œidœ:œAstraDB-wANQuœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}" + "source": "OpenAIEmbeddings-hNOwh", + "sourceHandle": "{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-hNOwhœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}", + "target": "AstraDB-p6135", + "targetHandle": "{œfieldNameœ:œembeddingœ,œidœ:œAstraDB-p6135œ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}" }, { "className": "", "data": { "sourceHandle": { "dataType": "AstraDB", - "id": "AstraDB-wANQu", + "id": "AstraDB-p6135", "name": "search_results", "output_types": [ "Data" @@ -3137,79 +2926,26 @@ }, "targetHandle": { "fieldName": "data", - "id": "ParseData-C9tUn", + "id": "ParseData-9DrmC", "inputTypes": [ "Data" ], "type": "other" } }, - "id": "reactflow__edge-AstraDB-wANQu{œdataTypeœ:œAstraDBœ,œidœ:œAstraDB-wANQuœ,œnameœ:œsearch_resultsœ,œoutput_typesœ:[œDataœ]}-ParseData-C9tUn{œfieldNameœ:œdataœ,œidœ:œParseData-C9tUnœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", + "id": 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"fieldName": "question", - "id": "Prompt-jzPqb", + "id": "Prompt-EEXgw", "inputTypes": [ "Message", "Text" @@ -3225,22 +2961,182 @@ "type": "str" } }, - "id": "reactflow__edge-ChatInput-IY8UK{œdataTypeœ:œChatInputœ,œidœ:œChatInput-IY8UKœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-jzPqb{œfieldNameœ:œquestionœ,œidœ:œPrompt-jzPqbœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", - "source": "ChatInput-IY8UK", - "sourceHandle": "{œdataTypeœ:œChatInputœ,œidœ:œChatInput-IY8UKœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}", - "target": "Prompt-jzPqb", - "targetHandle": "{œfieldNameœ:œquestionœ,œidœ:œPrompt-jzPqbœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}" + "id": "reactflow__edge-ChatInput-8ZRjI{œdataTypeœ:œChatInputœ,œidœ:œChatInput-8ZRjIœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-EEXgw{œfieldNameœ:œquestionœ,œidœ:œPrompt-EEXgwœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ChatInput-8ZRjI", + "sourceHandle": "{œdataTypeœ:œChatInputœ,œidœ:œChatInput-8ZRjIœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}", + "target": "Prompt-EEXgw", + "targetHandle": "{œfieldNameœ:œquestionœ,œidœ:œPrompt-EEXgwœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "File", + "id": "File-p2YBf", + "name": "data", + "output_types": [ + "Data" + ] + }, + "targetHandle": { + "fieldName": "data_inputs", + "id": "SplitText-qI0jS", + "inputTypes": [ + "Data" + ], + "type": "other" + } + }, + "id": "reactflow__edge-File-p2YBf{œdataTypeœ:œFileœ,œidœ:œFile-p2YBfœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-SplitText-qI0jS{œfieldNameœ:œdata_inputsœ,œidœ:œSplitText-qI0jSœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", + "source": "File-p2YBf", + "sourceHandle": "{œdataTypeœ:œFileœ,œidœ:œFile-p2YBfœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}", + "target": "SplitText-qI0jS", + "targetHandle": 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"dataType": "Prompt", + "id": "Prompt-EEXgw", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "OpenAIModel-euVNy", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-EEXgw{œdataTypeœ:œPromptœ,œidœ:œPrompt-EEXgwœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-euVNy{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-euVNyœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-EEXgw", + "sourceHandle": "{œdataTypeœ:œPromptœ,œidœ:œPrompt-EEXgwœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}", + "target": "OpenAIModel-euVNy", + "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-euVNyœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIModel", + "id": "OpenAIModel-euVNy", + "name": "text_output", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "ChatOutput-1eddV", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-OpenAIModel-euVNy{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-euVNyœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-1eddV{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-1eddVœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-euVNy", + "sourceHandle": "{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-euVNyœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}", + "target": "ChatOutput-1eddV", + "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-1eddVœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "SplitText", + "id": "SplitText-qI0jS", + "name": "chunks", + "output_types": [ + "Data" + ] + }, + "targetHandle": { + "fieldName": "vector_store_inputs", + "id": "AstraDB-AX2Xz", + "inputTypes": [ + "Document", + "Data" + ], + "type": "other" + } + }, + "source": "SplitText-qI0jS", + "sourceHandle": "{œdataTypeœ:œSplitTextœ,œidœ:œSplitText-qI0jSœ,œnameœ:œchunksœ,œoutput_typesœ:[œDataœ]}", + "target": "AstraDB-AX2Xz", + "targetHandle": "{œfieldNameœ:œvector_store_inputsœ,œidœ:œAstraDB-AX2Xzœ,œinputTypesœ:[œDocumentœ,œDataœ],œtypeœ:œotherœ}", + "id": "reactflow__edge-SplitText-qI0jS{œdataTypeœ:œSplitTextœ,œidœ:œSplitText-qI0jSœ,œnameœ:œchunksœ,œoutput_typesœ:[œDataœ]}-AstraDB-AX2Xz{œfieldNameœ:œvector_store_inputsœ,œidœ:œAstraDB-AX2Xzœ,œinputTypesœ:[œDocumentœ,œDataœ],œtypeœ:œotherœ}", + "selected": false + }, + { + "source": "OpenAIEmbeddings-PQc6x", + "sourceHandle": "{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-PQc6xœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}", + "target": "AstraDB-AX2Xz", + "targetHandle": "{œfieldNameœ:œembeddingœ,œidœ:œAstraDB-AX2Xzœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}", + "data": { + "targetHandle": { + "fieldName": "embedding", + "id": "AstraDB-AX2Xz", + "inputTypes": [ + "Embeddings" + ], + "type": "other" + }, + "sourceHandle": { + "dataType": "OpenAIEmbeddings", + "id": "OpenAIEmbeddings-PQc6x", + "name": "embeddings", + "output_types": [ + "Embeddings" + ] + } + }, + "id": "reactflow__edge-OpenAIEmbeddings-PQc6x{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-PQc6xœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}-AstraDB-AX2Xz{œfieldNameœ:œembeddingœ,œidœ:œAstraDB-AX2Xzœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}", + "selected": false } ], "viewport": { - "x": -124.92057698887993, - "y": 126.80996053902413, - "zoom": 0.370642160653555 + "x": -173.2239134973895, + "y": 90.45548562382544, + "zoom": 0.32281188532359306 } }, "description": "Visit https://docs.langflow.org/tutorials/rag-with-astradb for a detailed guide of this project.\nThis project give you both Ingestion and RAG in a single file. You'll need to visit https://astra.datastax.com/ to create an Astra DB instance, your Token and grab an API Endpoint.\nRunning this project requires you to add a file in the Files component, then define a Collection Name and click on the Play icon on the Astra DB component. \n\nAfter the ingestion ends you are ready to click on the Run button at the lower left corner and start asking questions about your data.", "name": "Vector Store RAG", - "last_tested_version": "1.0.0a61", + "last_tested_version": "1.0.0rc1", "endpoint_name": null, "is_component": false } \ No newline at end of file diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json b/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json index fd4aa39ae..5f974dc1a 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Vector Store RAG.json @@ -1,2282 +1,3142 @@ { - 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"reactflow__edge-Prompt-V2VHT{œdataTypeœ:œPromptœ,œidœ:œPrompt-V2VHTœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-Tm5Ht{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-Tm5Htœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "Prompt-V2VHT", - "sourceHandle": "{œdataTypeœ: œPromptœ, œidœ: œPrompt-V2VHTœ, œnameœ: œpromptœ, œoutput_typesœ: [œMessageœ]}", - "target": "OpenAIModel-Tm5Ht", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œOpenAIModel-Tm5Htœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" - }, - { - "className": "", - "data": { - "sourceHandle": { - "dataType": "OpenAIModel", - "id": "OpenAIModel-Tm5Ht", - "name": "text_output", - "output_types": [ - "Message" - ] - }, - "targetHandle": { - "fieldName": "input_value", - "id": "ChatOutput-ywruU", - "inputTypes": [ - "Message" - ], - "type": "str" - } - }, - "id": "reactflow__edge-OpenAIModel-Tm5Ht{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-Tm5Htœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-ywruU{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-ywruUœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", - "source": "OpenAIModel-Tm5Ht", - "sourceHandle": "{œdataTypeœ: œOpenAIModelœ, œidœ: œOpenAIModel-Tm5Htœ, œnameœ: œtext_outputœ, œoutput_typesœ: [œMessageœ]}", - "target": "ChatOutput-ywruU", - "targetHandle": "{œfieldNameœ: œinput_valueœ, œidœ: œChatOutput-ywruUœ, œinputTypesœ: [œMessageœ], œtypeœ: œstrœ}" - } - ], - "nodes": [ - { - "data": { - "description": "Get chat inputs from the Playground.", - "display_name": "Chat Input", - "edited": false, - "id": "ChatInput-nER2k", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Get chat inputs from the Playground.", - "display_name": "Chat Input", - "documentation": "", - "edited": true, - "field_order": [ - "input_value", - "sender", - "sender_name", - "session_id", - "files" - ], - "frozen": false, - "icon": "ChatInput", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "hidden": false, - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" - }, - "files": { - "advanced": true, - "display_name": "Files", - "dynamic": false, - "fileTypes": [ - "txt", - "md", - "mdx", - "csv", - "json", - "yaml", - "yml", - "xml", - "html", - "htm", - "pdf", - "docx", - "py", - "sh", - "sql", - "js", - "ts", - "tsx", - "jpg", - "jpeg", - "png", - "bmp", - "image" - ], - "file_path": "", - "info": "Files to be sent with the message.", - "list": true, - "name": "files", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "file", - "value": "" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "info": "Message to be passed as input.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "info": "Type of sender.", - "name": "sender", - "options": [ - "Machine", - "User" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "User" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "info": "Name of the sender.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "sender_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "User" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "info": "Session ID for the message.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "session_id", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - } - } - }, - "type": "ChatInput" - }, - "dragging": false, - "height": 309, - "id": "ChatInput-nER2k", - "position": { - "x": 682.002772470747, - "y": 253.67030039648512 - }, - "positionAbsolute": { - "x": 682.002772470747, - "y": 253.67030039648512 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "OpenAIEmbeddings-ylry8", - "node": { - "base_classes": [ - "Embeddings" - ], - "beta": false, - "custom_fields": { - "allowed_special": null, - "chunk_size": null, - "client": null, - "default_headers": null, - "default_query": null, - "deployment": null, - "disallowed_special": null, - "embedding_ctx_length": null, - "max_retries": null, - "model": null, - "model_kwargs": null, - "openai_api_base": null, - "openai_api_key": null, - "openai_api_type": null, - "openai_api_version": null, - "openai_organization": null, - "openai_proxy": null, - "request_timeout": null, - "show_progress_bar": null, - "skip_empty": null, - "tiktoken_enable": null, - "tiktoken_model_name": null + "id": "152a031a-a41a-4df1-a161-19800f686776", + "data": { + "nodes": [ + { + "data": { + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "edited": false, + "id": "ChatInput-8ZRjI", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Get chat inputs from the Playground.", + "display_name": "Chat Input", + "documentation": "", + "edited": true, + "field_order": [ + "input_value", + "sender", + "sender_name", + "session_id", + "files" + ], + "frozen": false, + "icon": "ChatInput", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "hidden": false, + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, FileInput, MessageTextInput, MultilineInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Playground.\"\n icon = \"ChatInput\"\n\n inputs = [\n MultilineInput(\n name=\"input_value\",\n display_name=\"Text\",\n value=\"\",\n info=\"Message to be passed as input.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"User\",\n info=\"Type of sender.\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"sender_name\",\n display_name=\"Sender Name\",\n info=\"Name of the sender.\",\n value=\"User\",\n advanced=True,\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n FileInput(\n name=\"files\",\n display_name=\"Files\",\n file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n info=\"Files to be sent with the message.\",\n advanced=True,\n is_list=True,\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n files=self.files,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + }, + "files": { + "advanced": true, + "display_name": "Files", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx", + "jpg", + "jpeg", + "png", + "bmp", + "image" + ], + "file_path": "", + "info": "Files to be sent with the message.", + "list": true, + "name": "files", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "file", + "value": "" + }, + "input_value": { + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as input.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "advanced": true, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "sender_name": { + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "User" + }, + "session_id": { + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "Session ID for the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + } + }, + "type": "ChatInput" + }, + "dragging": false, + "height": 309, + "id": "ChatInput-8ZRjI", + "position": { + "x": 682.002772470747, + "y": 253.67030039648512 + }, + "positionAbsolute": { + "x": 682.002772470747, + "y": 253.67030039648512 + }, + "selected": false, + "type": "genericNode", + "width": 384 }, - "description": "Generate embeddings using OpenAI models.", - "display_name": "OpenAI Embeddings", - "documentation": "", - "field_formatters": {}, - "field_order": [], - "frozen": false, - "icon": "OpenAI", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Embeddings", - "hidden": false, - "method": "build_embeddings", - "name": "embeddings", - "selected": "Embeddings", - "types": [ - "Embeddings" - ], - "value": "__UNDEFINED__" - } - ], - "template": { - "_type": "Component", - "chunk_size": { - "advanced": true, - "display_name": "Chunk Size", - "dynamic": false, - "info": "", - "list": false, - "name": "chunk_size", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": 1000 - }, - "client": { - "advanced": true, - "display_name": "Client", - "dynamic": false, - "info": "", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "name": "client", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langchain_openai.embeddings.base import OpenAIEmbeddings\n\nfrom langflow.base.embeddings.model import LCEmbeddingsModel\nfrom langflow.field_typing import Embeddings\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, MessageTextInput\n\n\nclass OpenAIEmbeddingsComponent(LCEmbeddingsModel):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n icon = \"OpenAI\"\n inputs = [\n DictInput(\n name=\"default_headers\",\n display_name=\"Default Headers\",\n advanced=True,\n info=\"Default headers to use for the API request.\",\n ),\n DictInput(\n name=\"default_query\",\n display_name=\"Default Query\",\n advanced=True,\n info=\"Default query parameters to use for the API request.\",\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n MessageTextInput(name=\"client\", display_name=\"Client\", advanced=True),\n MessageTextInput(name=\"deployment\", display_name=\"Deployment\", advanced=True),\n IntInput(name=\"embedding_ctx_length\", display_name=\"Embedding Context Length\", advanced=True, value=1536),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", value=3, advanced=True),\n DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n advanced=False,\n options=[\n \"text-embedding-3-small\",\n \"text-embedding-3-large\",\n \"text-embedding-ada-002\",\n ],\n value=\"text-embedding-3-small\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n SecretStrInput(name=\"openai_api_base\", display_name=\"OpenAI API Base\", advanced=True),\n SecretStrInput(name=\"openai_api_key\", display_name=\"OpenAI API Key\"),\n SecretStrInput(name=\"openai_api_type\", display_name=\"OpenAI API Type\", advanced=True),\n MessageTextInput(name=\"openai_api_version\", display_name=\"OpenAI API Version\", advanced=True),\n MessageTextInput(\n name=\"openai_organization\",\n display_name=\"OpenAI Organization\",\n advanced=True,\n ),\n MessageTextInput(name=\"openai_proxy\", display_name=\"OpenAI Proxy\", advanced=True),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n BoolInput(name=\"skip_empty\", display_name=\"Skip Empty\", advanced=True),\n MessageTextInput(\n name=\"tiktoken_model_name\",\n display_name=\"TikToken Model Name\",\n advanced=True,\n ),\n BoolInput(\n name=\"tiktoken_enable\",\n display_name=\"TikToken Enable\",\n advanced=True,\n value=True,\n info=\"If False, you must have transformers installed.\",\n ),\n ]\n\n def build_embeddings(self) -> Embeddings:\n return OpenAIEmbeddings(\n tiktoken_enabled=self.tiktoken_enable,\n default_headers=self.default_headers,\n default_query=self.default_query,\n allowed_special=\"all\",\n disallowed_special=\"all\",\n chunk_size=self.chunk_size,\n deployment=self.deployment,\n embedding_ctx_length=self.embedding_ctx_length,\n max_retries=self.max_retries,\n model=self.model,\n model_kwargs=self.model_kwargs,\n base_url=self.openai_api_base,\n api_key=self.openai_api_key,\n openai_api_type=self.openai_api_type,\n api_version=self.openai_api_version,\n organization=self.openai_organization,\n openai_proxy=self.openai_proxy,\n timeout=self.request_timeout or None,\n show_progress_bar=self.show_progress_bar,\n skip_empty=self.skip_empty,\n tiktoken_model_name=self.tiktoken_model_name,\n )\n" - }, - "default_headers": { - "advanced": true, - "display_name": "Default Headers", - "dynamic": false, - "info": "Default headers to use for the API request.", - "list": false, - "name": "default_headers", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "dict", - "value": {} - }, - "default_query": { - "advanced": true, - "display_name": "Default Query", - "dynamic": false, - "info": "Default query parameters to use for the API request.", - "list": false, - "name": "default_query", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "dict", - "value": {} - }, - "deployment": { - "advanced": true, - "display_name": "Deployment", - "dynamic": false, - "info": "", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "name": "deployment", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "embedding_ctx_length": { - "advanced": true, - "display_name": "Embedding Context Length", - "dynamic": false, - "info": "", - "list": false, - "name": "embedding_ctx_length", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": 1536 - }, - "max_retries": { - "advanced": true, - "display_name": "Max Retries", - "dynamic": false, - "info": "", - "list": false, - "name": "max_retries", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": 3 - }, - "model": { - "advanced": false, - "display_name": "Model", - "dynamic": false, - "info": "", - "name": "model", - "options": [ - "text-embedding-3-small", - "text-embedding-3-large", - "text-embedding-ada-002" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "text-embedding-3-small" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "dict", - "value": {} - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "", - "input_types": [], - "load_from_db": true, - "name": "openai_api_base", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_api_key": { - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "", - "input_types": [], - "load_from_db": false, - "name": "openai_api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_api_type": { - "advanced": true, - "display_name": "OpenAI API Type", - "dynamic": false, - "info": "", - "input_types": [], - "load_from_db": true, - "name": "openai_api_type", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_api_version": { - "advanced": true, - "display_name": "OpenAI API Version", - "dynamic": false, - "info": "", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "name": "openai_api_version", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_organization": { - "advanced": true, - "display_name": "OpenAI Organization", - "dynamic": false, - "info": "", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "name": "openai_organization", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_proxy": { - "advanced": true, - "display_name": "OpenAI Proxy", - "dynamic": false, - "info": "", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "name": "openai_proxy", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "request_timeout": { - "advanced": true, - "display_name": "Request Timeout", - "dynamic": false, - "info": "", - "list": false, - "name": "request_timeout", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "float", - "value": "" - }, - "show_progress_bar": { - "advanced": true, - "display_name": "Show Progress Bar", - "dynamic": false, - "info": "", - "list": false, - "name": "show_progress_bar", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "bool", - "value": false - }, - "skip_empty": { - "advanced": true, - "display_name": "Skip Empty", - "dynamic": false, - "info": "", - "list": false, - "name": "skip_empty", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "bool", - "value": false - }, - "tiktoken_enable": { - "advanced": true, - "display_name": "TikToken Enable", - "dynamic": false, - "info": "If False, you must have transformers installed.", - "list": false, - "name": "tiktoken_enable", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "bool", - "value": true - }, - "tiktoken_model_name": { - "advanced": true, - "display_name": "TikToken Model Name", - "dynamic": false, - "info": "", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "name": "tiktoken_model_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - } - } - }, - "type": "OpenAIEmbeddings" - }, - "dragging": false, - "height": 393, - "id": "OpenAIEmbeddings-ylry8", - "position": { - "x": 672.1192980997866, - "y": 786.6985113716086 - }, - "positionAbsolute": { - "x": 672.1192980997866, - "y": 786.6985113716086 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "edited": false, - "id": "OpenAIModel-Tm5Ht", - "node": { - "base_classes": [ - "LanguageModel", - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Generates text using OpenAI LLMs.", - "display_name": "OpenAI", - "documentation": "", - "edited": true, - "field_order": [ - "input_value", - "max_tokens", - "model_kwargs", - "output_schema", - "model_name", - "openai_api_base", - "openai_api_key", - "temperature", - "stream", - "system_message", - "seed" - ], - "frozen": false, - "icon": "OpenAI", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "hidden": false, - "method": "text_response", - "name": "text_output", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Language Model", - "method": "build_model", - "name": "model_output", - "selected": "LanguageModel", - "types": [ - "LanguageModel" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n" - }, - "input_value": { - "advanced": false, - "display_name": "Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "max_tokens": { - "advanced": true, - "display_name": "Max Tokens", - "dynamic": false, - "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", - "list": false, - "name": "max_tokens", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": "" - }, - "model_kwargs": { - "advanced": true, - "display_name": "Model Kwargs", - "dynamic": false, - "info": "", - "list": false, - "name": "model_kwargs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "dict", - "value": {} - }, - "model_name": { - "advanced": false, - "display_name": "Model Name", - "dynamic": false, - "info": "", - "name": "model_name", - "options": [ - "gpt-4o", - "gpt-4-turbo", - "gpt-4-turbo-preview", - "gpt-3.5-turbo", - "gpt-3.5-turbo-0125" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "gpt-4-turbo" - }, - "openai_api_base": { - "advanced": true, - "display_name": "OpenAI API Base", - "dynamic": false, - "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", - "list": false, - "load_from_db": false, - "name": "openai_api_base", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "openai_api_key": { - "advanced": false, - "display_name": "OpenAI API Key", - "dynamic": false, - "info": "The OpenAI API Key to use for the OpenAI model.", - "input_types": [], - "load_from_db": false, - "name": "openai_api_key", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "output_schema": { - "advanced": true, - "display_name": "Schema", - "dynamic": false, - "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.", - "list": true, - "name": "output_schema", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "dict", - "value": {} - }, - "seed": { - "advanced": true, - "display_name": "Seed", - "dynamic": false, - "info": "The seed controls the reproducibility of the job.", - "list": false, - "name": "seed", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": 1 - }, - "stream": { - "advanced": true, - "display_name": "Stream", - "dynamic": false, - "info": "Stream the response from the model. Streaming works only in Chat.", - "list": false, - "name": "stream", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "bool", - "value": false - }, - "system_message": { - "advanced": true, - "display_name": "System Message", - "dynamic": false, - "info": "System message to pass to the model.", - "list": false, - "load_from_db": false, - "name": "system_message", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "temperature": { - "advanced": false, - "display_name": "Temperature", - "dynamic": false, - "info": "", - "list": false, - "name": "temperature", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "float", - "value": 0.1 - } - } - }, - "type": "OpenAIModel" - }, - "dragging": false, - "height": 623, - "id": "OpenAIModel-Tm5Ht", - "position": { - "x": 3243.967394111999, - "y": 392.861541437184 - }, - "positionAbsolute": { - "x": 3243.967394111999, - "y": 392.861541437184 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "edited": false, - "id": "ChatOutput-ywruU", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Display a chat message in the Playground.", - "display_name": "Chat Output", - "documentation": "", - "edited": true, - "field_order": [ - "input_value", - "sender", - "sender_name", - "session_id", - "data_template" - ], - "frozen": false, - "icon": "ChatOutput", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Message", - "method": "message_response", - "name": "message", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" - }, - "data_template": { - "advanced": true, - "display_name": "Data Template", - "dynamic": false, - "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "data_template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "{text}" - }, - "input_value": { - "advanced": false, - "display_name": "Text", - "dynamic": false, - "info": "Message to be passed as output.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "input_value", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - }, - "sender": { - "advanced": true, - "display_name": "Sender Type", - "dynamic": false, - "info": "Type of sender.", - "name": "sender", - "options": [ - "Machine", - "User" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "str", - "value": "Machine" - }, - "sender_name": { - "advanced": true, - "display_name": "Sender Name", - "dynamic": false, - "info": "Name of the sender.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "sender_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "AI" - }, - "session_id": { - "advanced": true, - "display_name": "Session ID", - "dynamic": false, - "info": "Session ID for the message.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "session_id", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "" - } - } - }, - "type": "ChatOutput" - }, - "dragging": false, - "height": 309, - "id": "ChatOutput-ywruU", - "position": { - "x": 3788.786948642587, - "y": 608.4077159222614 - }, - "positionAbsolute": { - "x": 3788.786948642587, - "y": 608.4077159222614 - }, - "selected": true, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "File-OGHlE", - "node": { - "base_classes": [ - "Record" - ], - "beta": false, - "custom_fields": { - "path": null, - "silent_errors": null + { + "data": { + "id": "OpenAIEmbeddings-hNOwh", + "node": { + "base_classes": [ + "Embeddings" + ], + "beta": false, + "custom_fields": { + "allowed_special": null, + "chunk_size": null, + "client": null, + "default_headers": null, + "default_query": null, + "deployment": null, + "disallowed_special": null, + "embedding_ctx_length": null, + "max_retries": null, + "model": null, + "model_kwargs": null, + "openai_api_base": null, + "openai_api_key": null, + "openai_api_type": null, + "openai_api_version": null, + "openai_organization": null, + "openai_proxy": null, + "request_timeout": null, + "show_progress_bar": null, + "skip_empty": null, + "tiktoken_enable": null, + "tiktoken_model_name": null + }, + "description": "Generate embeddings using OpenAI models.", + "display_name": "OpenAI Embeddings", + "documentation": "", + "field_formatters": {}, + "field_order": [], + "frozen": false, + "icon": "OpenAI", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Embeddings", + "hidden": false, + "method": "build_embeddings", + "name": "embeddings", + "selected": "Embeddings", + "types": [ + "Embeddings" + ], + "value": "__UNDEFINED__" + } + ], + "template": { + "_type": "Component", + "chunk_size": { + "advanced": true, + "display_name": "Chunk Size", + "dynamic": false, + "info": "", + "list": false, + "name": "chunk_size", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 1000 + }, + "client": { + "advanced": true, + "display_name": "Client", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "client", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain_openai.embeddings.base import OpenAIEmbeddings\n\nfrom langflow.base.embeddings.model import LCEmbeddingsModel\nfrom langflow.field_typing import Embeddings\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, MessageTextInput\n\n\nclass OpenAIEmbeddingsComponent(LCEmbeddingsModel):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n icon = \"OpenAI\"\n inputs = [\n DictInput(\n name=\"default_headers\",\n display_name=\"Default Headers\",\n advanced=True,\n info=\"Default headers to use for the API request.\",\n ),\n DictInput(\n name=\"default_query\",\n display_name=\"Default Query\",\n advanced=True,\n info=\"Default query parameters to use for the API request.\",\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n MessageTextInput(name=\"client\", display_name=\"Client\", advanced=True),\n MessageTextInput(name=\"deployment\", display_name=\"Deployment\", advanced=True),\n IntInput(name=\"embedding_ctx_length\", display_name=\"Embedding Context Length\", advanced=True, value=1536),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", value=3, advanced=True),\n DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n advanced=False,\n options=[\n \"text-embedding-3-small\",\n \"text-embedding-3-large\",\n \"text-embedding-ada-002\",\n ],\n value=\"text-embedding-3-small\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n SecretStrInput(name=\"openai_api_base\", display_name=\"OpenAI API Base\", advanced=True),\n SecretStrInput(name=\"openai_api_key\", display_name=\"OpenAI API Key\"),\n SecretStrInput(name=\"openai_api_type\", display_name=\"OpenAI API Type\", advanced=True),\n MessageTextInput(name=\"openai_api_version\", display_name=\"OpenAI API Version\", advanced=True),\n MessageTextInput(\n name=\"openai_organization\",\n display_name=\"OpenAI Organization\",\n advanced=True,\n ),\n MessageTextInput(name=\"openai_proxy\", display_name=\"OpenAI Proxy\", advanced=True),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n BoolInput(name=\"skip_empty\", display_name=\"Skip Empty\", advanced=True),\n MessageTextInput(\n name=\"tiktoken_model_name\",\n display_name=\"TikToken Model Name\",\n advanced=True,\n ),\n BoolInput(\n name=\"tiktoken_enable\",\n display_name=\"TikToken Enable\",\n advanced=True,\n value=True,\n info=\"If False, you must have transformers installed.\",\n ),\n ]\n\n def build_embeddings(self) -> Embeddings:\n return OpenAIEmbeddings(\n tiktoken_enabled=self.tiktoken_enable,\n default_headers=self.default_headers,\n default_query=self.default_query,\n allowed_special=\"all\",\n disallowed_special=\"all\",\n chunk_size=self.chunk_size,\n deployment=self.deployment,\n embedding_ctx_length=self.embedding_ctx_length,\n max_retries=self.max_retries,\n model=self.model,\n model_kwargs=self.model_kwargs,\n base_url=self.openai_api_base,\n api_key=self.openai_api_key,\n openai_api_type=self.openai_api_type,\n api_version=self.openai_api_version,\n organization=self.openai_organization,\n openai_proxy=self.openai_proxy,\n timeout=self.request_timeout or None,\n show_progress_bar=self.show_progress_bar,\n skip_empty=self.skip_empty,\n tiktoken_model_name=self.tiktoken_model_name,\n )\n" + }, + "default_headers": { + "advanced": true, + "display_name": "Default Headers", + "dynamic": false, + "info": "Default headers to use for the API request.", + "list": false, + "name": "default_headers", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "default_query": { + "advanced": true, + "display_name": "Default Query", + "dynamic": false, + "info": "Default query parameters to use for the API request.", + "list": false, + "name": "default_query", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "deployment": { + "advanced": true, + "display_name": "Deployment", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "deployment", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "embedding_ctx_length": { + "advanced": true, + "display_name": "Embedding Context Length", + "dynamic": false, + "info": "", + "list": false, + "name": "embedding_ctx_length", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 1536 + }, + "max_retries": { + "advanced": true, + "display_name": "Max Retries", + "dynamic": false, + "info": "", + "list": false, + "name": "max_retries", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 3 + }, + "model": { + "advanced": false, + "display_name": "Model", + "dynamic": false, + "info": "", + "name": "model", + "options": [ + "text-embedding-3-small", + "text-embedding-3-large", + "text-embedding-ada-002" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "text-embedding-3-small" + }, + "model_kwargs": { + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "openai_api_base": { + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "", + "input_types": [], + "load_from_db": true, + "name": "openai_api_base", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_key": { + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "", + "input_types": [], + "load_from_db": false, + "name": "openai_api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_type": { + "advanced": true, + "display_name": "OpenAI API Type", + "dynamic": false, + "info": "", + "input_types": [], + "load_from_db": true, + "name": "openai_api_type", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_version": { + "advanced": true, + "display_name": "OpenAI API Version", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "openai_api_version", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_organization": { + "advanced": true, + "display_name": "OpenAI Organization", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "openai_organization", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_proxy": { + "advanced": true, + "display_name": "OpenAI Proxy", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "openai_proxy", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "request_timeout": { + "advanced": true, + "display_name": "Request Timeout", + "dynamic": false, + "info": "", + "list": false, + "name": "request_timeout", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "float", + "value": "" + }, + "show_progress_bar": { + "advanced": true, + "display_name": "Show Progress Bar", + "dynamic": false, + "info": "", + "list": false, + "name": "show_progress_bar", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "skip_empty": { + "advanced": true, + "display_name": "Skip Empty", + "dynamic": false, + "info": "", + "list": false, + "name": "skip_empty", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "tiktoken_enable": { + "advanced": true, + "display_name": "TikToken Enable", + "dynamic": false, + "info": "If False, you must have transformers installed.", + "list": false, + "name": "tiktoken_enable", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": true + }, + "tiktoken_model_name": { + "advanced": true, + "display_name": "TikToken Model Name", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "tiktoken_model_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + } + } + }, + "type": "OpenAIEmbeddings" + }, + "dragging": false, + "height": 393, + "id": "OpenAIEmbeddings-hNOwh", + "position": { + "x": 672.1192980997866, + "y": 786.6985113716086 + }, + "positionAbsolute": { + "x": 672.1192980997866, + "y": 786.6985113716086 + }, + "selected": false, + "type": "genericNode", + "width": 384 }, - "description": "A generic file loader.", - "display_name": "File", - "documentation": "", - "field_formatters": {}, - "field_order": [], - "frozen": false, - "icon": "file-text", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Data", - "hidden": false, - "method": "load_file", - "name": "data", - "selected": "Data", - "types": [ - "Data" - ], - "value": "__UNDEFINED__" - } - ], - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from pathlib import Path\n\nfrom langflow.base.data.utils import TEXT_FILE_TYPES, parse_text_file_to_data\nfrom langflow.custom import Component\nfrom langflow.io import BoolInput, FileInput, Output\nfrom langflow.schema import Data\n\n\nclass FileComponent(Component):\n display_name = \"File\"\n description = \"A generic file loader.\"\n icon = \"file-text\"\n\n inputs = [\n FileInput(\n name=\"path\",\n display_name=\"Path\",\n file_types=TEXT_FILE_TYPES,\n info=f\"Supported file types: {', '.join(TEXT_FILE_TYPES)}\",\n ),\n BoolInput(\n name=\"silent_errors\",\n display_name=\"Silent Errors\",\n advanced=True,\n info=\"If true, errors will not raise an exception.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"load_file\"),\n ]\n\n def load_file(self) -> Data:\n if not self.path:\n raise ValueError(\"Please, upload a file to use this component.\")\n resolved_path = self.resolve_path(self.path)\n silent_errors = self.silent_errors\n\n extension = Path(resolved_path).suffix[1:].lower()\n\n if extension == \"doc\":\n raise ValueError(\"doc files are not supported. Please save as .docx\")\n if extension not in TEXT_FILE_TYPES:\n raise ValueError(f\"Unsupported file type: {extension}\")\n\n data = parse_text_file_to_data(resolved_path, silent_errors)\n self.status = data if data else \"No data\"\n return data or Data()\n" - }, - "path": { - "advanced": false, - "display_name": "Path", - "dynamic": false, - "fileTypes": [ - "txt", - "md", - "mdx", - "csv", - "json", - "yaml", - "yml", - "xml", - "html", - "htm", - "pdf", - "docx", - "py", - "sh", - "sql", - "js", - "ts", - "tsx" - ], - "file_path": "bba1609b-3af2-431d-a884-322cc253c69d/flatland.pdf", - "info": "Supported file types: txt, md, mdx, csv, json, yaml, yml, xml, html, htm, pdf, docx, py, sh, sql, js, ts, tsx", - "list": false, - "name": "path", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "file", - "value": "" - }, - "silent_errors": { - "advanced": true, - "display_name": "Silent Errors", - "dynamic": false, - "info": "If true, errors will not raise an exception.", - "list": false, - "name": "silent_errors", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "bool", - "value": false - } - } - }, - "type": "File" - }, - "dragging": false, - "height": 301, - "id": "File-OGHlE", - "position": { - "x": -583.277913381927, - "y": 433.34221812460396 - }, - "positionAbsolute": { - "x": -583.277913381927, - "y": 433.34221812460396 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Implementation of Vector Store using Astra DB with search capabilities", - "display_name": "Astra DB Vector Store", - "id": "AstraDB-QLZSs", - "node": { - "base_classes": [ - "Data" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Implementation of Vector Store using Astra DB with search capabilities", - "display_name": "Astra DB Vector Store", - "documentation": "https://python.langchain.com/docs/integrations/vectorstores/astradb", - "edited": false, - "field_order": [ - "collection_name", - "token", - "api_endpoint", - "vector_store_inputs", - "embedding", - "namespace", - "metric", - "batch_size", - "bulk_insert_batch_concurrency", - "bulk_insert_overwrite_concurrency", - "bulk_delete_concurrency", - "setup_mode", - "pre_delete_collection", - "metadata_indexing_include", - "metadata_indexing_exclude", - "collection_indexing_policy", - "add_to_vector_store", - "search_input", - "search_type", - "number_of_results" - ], - "frozen": false, - "icon": "AstraDB", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Retriever", - "method": "build_base_retriever", - "name": "base_retriever", - "selected": "Data", - "types": [ - "Data" - ], - "value": "__UNDEFINED__" - }, - { - "cache": true, - "display_name": "Search Results", - "hidden": false, - "method": "search_documents", - "name": "search_results", - "selected": "Data", - "types": [ - "Data" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "add_to_vector_store": { - "advanced": false, - "display_name": "Add to Vector Store", - "dynamic": false, - "info": "If true, the Vector Store Inputs will be added to the Vector Store.", - "list": false, - "name": "add_to_vector_store", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "bool", - "value": true - }, - "api_endpoint": { - "advanced": false, - "display_name": "API Endpoint", - "dynamic": false, - "info": "API endpoint URL for the Astra DB service.", - "input_types": [], - "load_from_db": false, - "name": "api_endpoint", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "batch_size": { - "advanced": true, - "display_name": "Batch Size", - "dynamic": false, - "info": "Optional number of data to process in a single batch.", - "list": false, - "name": "batch_size", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": "" - }, - "bulk_delete_concurrency": { - "advanced": true, - "display_name": "Bulk Delete Concurrency", - "dynamic": false, - "info": "Optional concurrency level for bulk delete operations.", - "list": false, - "name": "bulk_delete_concurrency", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": "" - }, - "bulk_insert_batch_concurrency": { - "advanced": true, - "display_name": "Bulk Insert Batch Concurrency", - "dynamic": false, - "info": "Optional concurrency level for bulk insert operations.", - "list": false, - "name": "bulk_insert_batch_concurrency", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": "" - }, - "bulk_insert_overwrite_concurrency": { - "advanced": true, - "display_name": "Bulk Insert Overwrite Concurrency", - "dynamic": false, - "info": "Optional concurrency level for bulk insert operations that overwrite existing data.", - "list": false, - "name": "bulk_insert_overwrite_concurrency", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": "" - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from loguru import logger\n\nfrom langflow.base.vectorstores.model import LCVectorStoreComponent\nfrom langflow.io import BoolInput, DropdownInput, HandleInput, IntInput, MultilineInput, SecretStrInput, StrInput\nfrom langflow.schema import Data\n\n\nclass AstraVectorStoreComponent(LCVectorStoreComponent):\n display_name: str = \"Astra DB Vector Store\"\n description: str = \"Implementation of Vector Store using Astra DB with search capabilities\"\n documentation: str = \"https://python.langchain.com/docs/integrations/vectorstores/astradb\"\n icon: str = \"AstraDB\"\n\n inputs = [\n StrInput(\n name=\"collection_name\",\n display_name=\"Collection Name\",\n info=\"The name of the collection within Astra DB where the vectors will be stored.\",\n ),\n SecretStrInput(\n name=\"token\",\n display_name=\"Astra DB Application Token\",\n info=\"Authentication token for accessing Astra DB.\",\n value=\"ASTRA_DB_APPLICATION_TOKEN\",\n ),\n SecretStrInput(\n name=\"api_endpoint\",\n display_name=\"API Endpoint\",\n info=\"API endpoint URL for the Astra DB service.\",\n value=\"ASTRA_DB_API_ENDPOINT\",\n ),\n HandleInput(\n name=\"vector_store_inputs\",\n display_name=\"Vector Store Inputs\",\n input_types=[\"Document\", \"Data\"],\n is_list=True,\n ),\n HandleInput(\n name=\"embedding\",\n display_name=\"Embedding\",\n input_types=[\"Embeddings\"],\n ),\n StrInput(\n name=\"namespace\",\n display_name=\"Namespace\",\n info=\"Optional namespace within Astra DB to use for the collection.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"metric\",\n display_name=\"Metric\",\n info=\"Optional distance metric for vector comparisons in the vector store.\",\n options=[\"cosine\", \"dot_product\", \"euclidean\"],\n advanced=True,\n ),\n IntInput(\n name=\"batch_size\",\n display_name=\"Batch Size\",\n info=\"Optional number of data to process in a single batch.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_batch_concurrency\",\n display_name=\"Bulk Insert Batch Concurrency\",\n info=\"Optional concurrency level for bulk insert operations.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_overwrite_concurrency\",\n display_name=\"Bulk Insert Overwrite Concurrency\",\n info=\"Optional concurrency level for bulk insert operations that overwrite existing data.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_delete_concurrency\",\n display_name=\"Bulk Delete Concurrency\",\n info=\"Optional concurrency level for bulk delete operations.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"setup_mode\",\n display_name=\"Setup Mode\",\n info=\"Configuration mode for setting up the vector store, with options like 'Sync', 'Async', or 'Off'.\",\n options=[\"Sync\", \"Async\", \"Off\"],\n advanced=True,\n value=\"Sync\",\n ),\n BoolInput(\n name=\"pre_delete_collection\",\n display_name=\"Pre Delete Collection\",\n info=\"Boolean flag to determine whether to delete the collection before creating a new one.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_include\",\n display_name=\"Metadata Indexing Include\",\n info=\"Optional list of metadata fields to include in the indexing.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_exclude\",\n display_name=\"Metadata Indexing Exclude\",\n info=\"Optional list of metadata fields to exclude from the indexing.\",\n advanced=True,\n ),\n StrInput(\n name=\"collection_indexing_policy\",\n display_name=\"Collection Indexing Policy\",\n info=\"Optional dictionary defining the indexing policy for the collection.\",\n advanced=True,\n ),\n BoolInput(\n name=\"add_to_vector_store\",\n display_name=\"Add to Vector Store\",\n info=\"If true, the Vector Store Inputs will be added to the Vector Store.\",\n ),\n MultilineInput(\n name=\"search_input\",\n display_name=\"Search Input\",\n ),\n DropdownInput(\n name=\"search_type\",\n display_name=\"Search Type\",\n options=[\"Similarity\", \"MMR\"],\n value=\"Similarity\",\n ),\n IntInput(\n name=\"number_of_results\",\n display_name=\"Number of Results\",\n info=\"Number of results to return.\",\n advanced=True,\n value=4,\n ),\n ]\n\n def build_vector_store(self):\n try:\n from langchain_astradb import AstraDBVectorStore\n from langchain_astradb.utils.astradb import SetupMode\n except ImportError:\n raise ImportError(\n \"Could not import langchain Astra DB integration package. \"\n \"Please install it with `pip install langchain-astradb`.\"\n )\n\n try:\n if not self.setup_mode:\n self.setup_mode = self._inputs[\"setup_mode\"].options[0]\n\n setup_mode_value = SetupMode[self.setup_mode.upper()]\n except KeyError:\n raise ValueError(f\"Invalid setup mode: {self.setup_mode}\")\n\n vector_store_kwargs = {\n \"embedding\": self.embedding,\n \"collection_name\": self.collection_name,\n \"token\": self.token,\n \"api_endpoint\": self.api_endpoint,\n \"namespace\": self.namespace or None,\n \"metric\": self.metric or None,\n \"batch_size\": self.batch_size or None,\n \"bulk_insert_batch_concurrency\": self.bulk_insert_batch_concurrency or None,\n \"bulk_insert_overwrite_concurrency\": self.bulk_insert_overwrite_concurrency or None,\n \"bulk_delete_concurrency\": self.bulk_delete_concurrency or None,\n \"setup_mode\": setup_mode_value,\n \"pre_delete_collection\": self.pre_delete_collection or False,\n }\n\n if self.metadata_indexing_include:\n vector_store_kwargs[\"metadata_indexing_include\"] = self.metadata_indexing_include\n elif self.metadata_indexing_exclude:\n vector_store_kwargs[\"metadata_indexing_exclude\"] = self.metadata_indexing_exclude\n elif self.collection_indexing_policy:\n vector_store_kwargs[\"collection_indexing_policy\"] = self.collection_indexing_policy\n\n try:\n vector_store = AstraDBVectorStore(**vector_store_kwargs)\n except Exception as e:\n raise ValueError(f\"Error initializing AstraDBVectorStore: {str(e)}\") from e\n\n if self.add_to_vector_store:\n self._add_documents_to_vector_store(vector_store)\n\n return vector_store\n\n def build_base_retriever(self):\n vector_store = self.build_vector_store()\n self.status = self._astradb_collection_to_data(vector_store.collection)\n return vector_store\n\n def _add_documents_to_vector_store(self, vector_store):\n documents = []\n for _input in self.vector_store_inputs or []:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n else:\n raise ValueError(\"Vector Store Inputs must be Data objects.\")\n\n if documents and self.embedding is not None:\n logger.debug(f\"Adding {len(documents)} documents to the Vector Store.\")\n try:\n vector_store.add_documents(documents)\n except Exception as e:\n raise ValueError(f\"Error adding documents to AstraDBVectorStore: {str(e)}\") from e\n else:\n logger.debug(\"No documents to add to the Vector Store.\")\n\n def search_documents(self):\n vector_store = self.build_vector_store()\n\n logger.debug(f\"Search input: {self.search_input}\")\n logger.debug(f\"Search type: {self.search_type}\")\n logger.debug(f\"Number of results: {self.number_of_results}\")\n\n if self.search_input and isinstance(self.search_input, str) and self.search_input.strip():\n try:\n if self.search_type == \"Similarity\":\n docs = vector_store.similarity_search(\n query=self.search_input,\n k=self.number_of_results,\n )\n elif self.search_type == \"MMR\":\n docs = vector_store.max_marginal_relevance_search(\n query=self.search_input,\n k=self.number_of_results,\n )\n else:\n raise ValueError(f\"Invalid search type: {self.search_type}\")\n except Exception as e:\n raise ValueError(f\"Error performing search in AstraDBVectorStore: {str(e)}\") from e\n\n logger.debug(f\"Retrieved documents: {len(docs)}\")\n\n data = [Data.from_document(doc) for doc in docs]\n logger.debug(f\"Converted documents to data: {len(data)}\")\n self.status = data\n return data\n else:\n logger.debug(\"No search input provided. Skipping search.\")\n return []\n\n def _astradb_collection_to_data(self, collection):\n data = []\n data_dict = collection.find()\n if data_dict and \"data\" in data_dict:\n data_dict = data_dict[\"data\"].get(\"documents\", [])\n\n for item in data_dict:\n data.append(Data(content=item[\"content\"]))\n return data\n" - }, - "collection_indexing_policy": { - "advanced": true, - "display_name": "Collection Indexing Policy", - "dynamic": false, - "info": "Optional dictionary defining the indexing policy for the collection.", - "list": false, - "load_from_db": false, - "name": "collection_indexing_policy", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "collection_name": { - "advanced": false, - "display_name": "Collection Name", - "dynamic": false, - "info": "The name of the collection within Astra DB where the vectors will be stored.", - "list": false, - "load_from_db": false, - "name": "collection_name", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "langflow" - }, - "embedding": { - "advanced": false, - "display_name": "Embedding", - "dynamic": false, - "info": "", - "input_types": [ - "Embeddings" - ], - "list": false, - "name": "embedding", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "other", - "value": "" - }, - "metadata_indexing_exclude": { - "advanced": true, - "display_name": "Metadata Indexing Exclude", - "dynamic": false, - "info": "Optional list of metadata fields to exclude from the indexing.", - "list": false, - "load_from_db": false, - "name": "metadata_indexing_exclude", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "metadata_indexing_include": { - "advanced": true, - "display_name": "Metadata Indexing Include", - "dynamic": false, - "info": "Optional list of metadata fields to include in the indexing.", - "list": false, - "load_from_db": false, - "name": "metadata_indexing_include", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "metric": { - "advanced": true, - "display_name": "Metric", - "dynamic": false, - "info": "Optional distance metric for vector comparisons in the vector store.", - "name": "metric", - "options": [ - "cosine", - "dot_product", - "euclidean" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "namespace": { - "advanced": true, - "display_name": "Namespace", - "dynamic": false, - "info": "Optional namespace within Astra DB to use for the collection.", - "list": false, - "load_from_db": false, - "name": "namespace", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "number_of_results": { - "advanced": true, - "display_name": "Number of Results", - "dynamic": false, - "info": "Number of results to return.", - "list": false, - "name": "number_of_results", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "int", - "value": 4 - }, - "pre_delete_collection": { - "advanced": true, - "display_name": "Pre Delete Collection", - "dynamic": false, - "info": "Boolean flag to determine whether to delete the collection before creating a new one.", - "list": false, - "name": "pre_delete_collection", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "bool", - "value": false - }, - "search_input": { - "advanced": false, - "display_name": "Search Input", - "dynamic": false, - "info": "", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "search_input", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "search_type": { - "advanced": false, - "display_name": "Search Type", - "dynamic": false, - "info": "", - "name": "search_type", - "options": [ - "Similarity", - "MMR" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "Similarity" - }, - "setup_mode": { - "advanced": true, - "display_name": "Setup Mode", - "dynamic": false, - "info": "Configuration mode for setting up the vector store, with options like 'Sync', 'Async', or 'Off'.", - "name": "setup_mode", - "options": [ - "Sync", - "Async", - "Off" - ], - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "Sync" - }, - "token": { - "advanced": false, - "display_name": "Astra DB Application Token", - "dynamic": false, - "info": "Authentication token for accessing Astra DB.", - "input_types": [], - "load_from_db": false, - "name": "token", - "password": true, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "vector_store_inputs": { - "advanced": false, - "display_name": "Vector Store Inputs", - "dynamic": false, - "info": "", - "input_types": [ - "Document", - "Data" - ], - "list": true, - "name": "vector_store_inputs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "other", - "value": "" - } - } - }, - "type": "AstraDB" - }, - "dragging": false, - "height": 917, - "id": "AstraDB-QLZSs", - "position": { - "x": 1298.4611042465333, - "y": 160.7181472642742 - }, - "positionAbsolute": { - "x": 1298.4611042465333, - "y": 160.7181472642742 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "ParseData-yHac6", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Convert Data into plain text following a specified template.", - "display_name": "Parse Data", - "documentation": "", - "field_order": [ - "data", - "template", - "sep" - ], - "frozen": false, - "icon": "braces", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Text", - "hidden": false, - "method": "parse_data", - "name": "text", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n display_name = \"Parse Data\"\n description = \"Convert Data into plain text following a specified template.\"\n icon = \"braces\"\n\n inputs = [\n DataInput(name=\"data\", display_name=\"Data\", info=\"The data to convert to text.\"),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.\",\n value=\"{text}\",\n ),\n StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n ]\n\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"parse_data\"),\n ]\n\n def parse_data(self) -> Message:\n data = self.data if isinstance(self.data, list) else [self.data]\n template = self.template\n\n result_string = data_to_text(template, data, sep=self.sep)\n self.status = result_string\n return Message(text=result_string)\n" - }, - "data": { - "advanced": false, - "display_name": "Data", - "dynamic": false, - "info": "The data to convert to text.", - "input_types": [ - "Data" - ], - "list": false, - "name": "data", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "other", - "value": "" - }, - "sep": { - "advanced": true, - "display_name": "Separator", - "dynamic": false, - "info": "", - "list": false, - "load_from_db": false, - "name": "sep", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "---" - }, - "template": { - "advanced": false, - "display_name": "Template", - "dynamic": false, - "info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.", - "input_types": [ - "Message", - "str" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "{text}" - } - } - }, - "type": "ParseData" - }, - "dragging": false, - "height": 385, - "id": "ParseData-yHac6", - "position": { - "x": 1911.4866480237615, - "y": 566.903831987901 - }, - "positionAbsolute": { - "x": 1911.4866480237615, - "y": 566.903831987901 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "id": "Prompt-V2VHT", - "node": { - "base_classes": [ - "Message" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": { - "template": [ - "context", - "question" - ] + { + "data": { + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "edited": false, + "id": "OpenAIModel-euVNy", + "node": { + "base_classes": [ + "LanguageModel", + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Generates text using OpenAI LLMs.", + "display_name": "OpenAI", + "documentation": "", + "edited": true, + "field_order": [ + "input_value", + "max_tokens", + "model_kwargs", + "output_schema", + "model_name", + "openai_api_base", + "openai_api_key", + "temperature", + "stream", + "system_message", + "seed" + ], + "frozen": false, + "icon": "OpenAI", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "hidden": false, + "method": "text_response", + "name": "text_output", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Language Model", + "method": "build_model", + "name": "model_output", + "selected": "LanguageModel", + "types": [ + "LanguageModel" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "import operator\nfrom functools import reduce\n\nfrom langchain_openai import ChatOpenAI\nfrom pydantic.v1 import SecretStr\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.openai_constants import MODEL_NAMES\nfrom langflow.field_typing import LanguageModel\nfrom langflow.inputs import (\n BoolInput,\n DictInput,\n DropdownInput,\n FloatInput,\n IntInput,\n MessageInput,\n SecretStrInput,\n StrInput,\n)\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n inputs = [\n MessageInput(name=\"input_value\", display_name=\"Input\"),\n IntInput(\n name=\"max_tokens\",\n display_name=\"Max Tokens\",\n advanced=True,\n info=\"The maximum number of tokens to generate. Set to 0 for unlimited tokens.\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n DictInput(\n name=\"output_schema\",\n is_list=True,\n display_name=\"Schema\",\n advanced=True,\n info=\"The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.\",\n ),\n DropdownInput(\n name=\"model_name\", display_name=\"Model Name\", advanced=False, options=MODEL_NAMES, value=MODEL_NAMES[0]\n ),\n StrInput(\n name=\"openai_api_base\",\n display_name=\"OpenAI API Base\",\n advanced=True,\n info=\"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.\",\n ),\n SecretStrInput(\n name=\"openai_api_key\",\n display_name=\"OpenAI API Key\",\n info=\"The OpenAI API Key to use for the OpenAI model.\",\n advanced=False,\n value=\"OPENAI_API_KEY\",\n ),\n FloatInput(name=\"temperature\", display_name=\"Temperature\", value=0.1),\n BoolInput(name=\"stream\", display_name=\"Stream\", info=STREAM_INFO_TEXT, advanced=True),\n StrInput(\n name=\"system_message\",\n display_name=\"System Message\",\n info=\"System message to pass to the model.\",\n advanced=True,\n ),\n IntInput(\n name=\"seed\",\n display_name=\"Seed\",\n info=\"The seed controls the reproducibility of the job.\",\n advanced=True,\n value=1,\n ),\n ]\n\n def build_model(self) -> LanguageModel:\n # self.output_schea is a list of dictionaries\n # let's convert it to a dictionary\n output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})\n openai_api_key = self.openai_api_key\n temperature = self.temperature\n model_name: str = self.model_name\n max_tokens = self.max_tokens\n model_kwargs = self.model_kwargs or {}\n openai_api_base = self.openai_api_base or \"https://api.openai.com/v1\"\n json_mode = bool(output_schema_dict)\n seed = self.seed\n model_kwargs[\"seed\"] = seed\n\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n output = ChatOpenAI(\n max_tokens=max_tokens or None,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature or 0.1,\n )\n if json_mode:\n output = output.with_structured_output(schema=output_schema_dict, method=\"json_mode\") # type: ignore\n\n return output\n\n def _get_exception_message(self, e: Exception):\n \"\"\"\n Get a message from an OpenAI exception.\n\n Args:\n exception (Exception): The exception to get the message from.\n\n Returns:\n str: The message from the exception.\n \"\"\"\n\n try:\n from openai import BadRequestError\n except ImportError:\n return\n if isinstance(e, BadRequestError):\n message = e.body.get(\"message\") # type: ignore\n if message:\n return message\n return\n" + }, + "input_value": { + "advanced": false, + "display_name": "Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "max_tokens": { + "advanced": true, + "display_name": "Max Tokens", + "dynamic": false, + "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.", + "list": false, + "name": "max_tokens", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "model_kwargs": { + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "model_name": { + "advanced": false, + "display_name": "Model Name", + "dynamic": false, + "info": "", + "name": "model_name", + "options": [ + "gpt-4o", + "gpt-4-turbo", + "gpt-4-turbo-preview", + "gpt-3.5-turbo", + "gpt-3.5-turbo-0125" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "gpt-4-turbo" + }, + "openai_api_base": { + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem.", + "list": false, + "load_from_db": false, + "name": "openai_api_base", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_key": { + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "The OpenAI API Key to use for the OpenAI model.", + "input_types": [], + "load_from_db": false, + "name": "openai_api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "output_schema": { + "advanced": true, + "display_name": "Schema", + "dynamic": false, + "info": "The schema for the Output of the model. You must pass the word JSON in the prompt. If left blank, JSON mode will be disabled.", + "list": true, + "name": "output_schema", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "seed": { + "advanced": true, + "display_name": "Seed", + "dynamic": false, + "info": "The seed controls the reproducibility of the job.", + "list": false, + "name": "seed", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 1 + }, + "stream": { + "advanced": true, + "display_name": "Stream", + "dynamic": false, + "info": "Stream the response from the model. Streaming works only in Chat.", + "list": false, + "name": "stream", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "system_message": { + "advanced": true, + "display_name": "System Message", + "dynamic": false, + "info": "System message to pass to the model.", + "list": false, + "load_from_db": false, + "name": "system_message", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "temperature": { + "advanced": false, + "display_name": "Temperature", + "dynamic": false, + "info": "", + "list": false, + "name": "temperature", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "float", + "value": 0.1 + } + } + }, + "type": "OpenAIModel" + }, + "dragging": false, + "height": 623, + "id": "OpenAIModel-euVNy", + "position": { + "x": 3243.967394111999, + "y": 392.861541437184 + }, + "positionAbsolute": { + "x": 3243.967394111999, + "y": 392.861541437184 + }, + "selected": false, + "type": "genericNode", + "width": 384 }, - "description": "Create a prompt template with dynamic variables.", - "display_name": "Prompt", - "documentation": "", - "edited": false, - "error": null, - "field_order": [ - "template" - ], - "frozen": false, - "full_path": null, - "icon": "prompts", - "is_composition": null, - "is_input": null, - "is_output": null, - "name": "", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Prompt Message", - "hidden": false, - "method": "build_prompt", - "name": "prompt", - "selected": "Message", - "types": [ - "Message" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def post_code_processing(self, new_build_config: dict, current_build_config: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_build_config, current_build_config)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_build_config\n # and update the frontend_node with those values\n update_template_values(frontend_template=frontend_node, raw_template=current_build_config[\"template\"])\n return frontend_node\n" - }, - "context": { - "advanced": false, - "display_name": "context", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "context", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "question": { - "advanced": false, - "display_name": "question", - "dynamic": false, - "field_type": "str", - "fileTypes": [], - "file_path": "", - "info": "", - "input_types": [ - "Message", - "Text" - ], - "list": false, - "load_from_db": false, - "multiline": true, - "name": "question", - "password": false, - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "type": "str", - "value": "" - }, - "template": { - "advanced": false, - "display_name": "Template", - "dynamic": false, - "info": "", - "list": false, - "name": "template", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "type": "prompt", - "value": "{context}\n\n---\n\nGiven the context above, answer the question as best as possible.\n\nQuestion: {question}\n\nAnswer: " - } + { + "data": { + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "edited": false, + "id": "ChatOutput-1eddV", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Display a chat message in the Playground.", + "display_name": "Chat Output", + "documentation": "", + "edited": true, + "field_order": [ + "input_value", + "sender", + "sender_name", + "session_id", + "data_template" + ], + "frozen": false, + "icon": "ChatOutput", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Message", + "method": "message_response", + "name": "message", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.io.chat import ChatComponent\nfrom langflow.io import DropdownInput, MessageTextInput, Output\nfrom langflow.schema.message import Message\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Playground.\"\n icon = \"ChatOutput\"\n\n inputs = [\n MessageTextInput(\n name=\"input_value\",\n display_name=\"Text\",\n info=\"Message to be passed as output.\",\n ),\n DropdownInput(\n name=\"sender\",\n display_name=\"Sender Type\",\n options=[\"Machine\", \"User\"],\n value=\"Machine\",\n advanced=True,\n info=\"Type of sender.\",\n ),\n MessageTextInput(\n name=\"sender_name\", display_name=\"Sender Name\", info=\"Name of the sender.\", value=\"AI\", advanced=True\n ),\n MessageTextInput(\n name=\"session_id\", display_name=\"Session ID\", info=\"Session ID for the message.\", advanced=True\n ),\n MessageTextInput(\n name=\"data_template\",\n display_name=\"Data Template\",\n value=\"{text}\",\n advanced=True,\n info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n ),\n ]\n outputs = [\n Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n ]\n\n def message_response(self) -> Message:\n message = Message(\n text=self.input_value,\n sender=self.sender,\n sender_name=self.sender_name,\n session_id=self.session_id,\n )\n if self.session_id and isinstance(message, Message) and isinstance(message.text, str):\n self.store_message(message)\n self.message.value = message\n\n self.status = message\n return message\n" + }, + "data_template": { + "advanced": true, + "display_name": "Data Template", + "dynamic": false, + "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "data_template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "{text}" + }, + "input_value": { + "advanced": false, + "display_name": "Text", + "dynamic": false, + "info": "Message to be passed as output.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "input_value", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + }, + "sender": { + "advanced": true, + "display_name": "Sender Type", + "dynamic": false, + "info": "Type of sender.", + "name": "sender", + "options": [ + "Machine", + "User" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "str", + "value": "Machine" + }, + "sender_name": { + "advanced": true, + "display_name": "Sender Name", + "dynamic": false, + "info": "Name of the sender.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "sender_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "AI" + }, + "session_id": { + "advanced": true, + "display_name": "Session ID", + "dynamic": false, + "info": "Session ID for the message.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "session_id", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "" + } + } + }, + "type": "ChatOutput" + }, + "dragging": false, + "height": 309, + "id": "ChatOutput-1eddV", + "position": { + "x": 3788.786948642587, + "y": 608.4077159222614 + }, + "positionAbsolute": { + "x": 3788.786948642587, + "y": 608.4077159222614 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "id": "File-p2YBf", + "node": { + "base_classes": [ + "Record" + ], + "beta": false, + "custom_fields": { + "path": null, + "silent_errors": null + }, + "description": "A generic file loader.", + "display_name": "File", + "documentation": "", + "field_formatters": {}, + "field_order": [], + "frozen": false, + "icon": "file-text", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Data", + "hidden": false, + "method": "load_file", + "name": "data", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + } + ], + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from pathlib import Path\n\nfrom langflow.base.data.utils import TEXT_FILE_TYPES, parse_text_file_to_data\nfrom langflow.custom import Component\nfrom langflow.io import BoolInput, FileInput, Output\nfrom langflow.schema import Data\n\n\nclass FileComponent(Component):\n display_name = \"File\"\n description = \"A generic file loader.\"\n icon = \"file-text\"\n\n inputs = [\n FileInput(\n name=\"path\",\n display_name=\"Path\",\n file_types=TEXT_FILE_TYPES,\n info=f\"Supported file types: {', '.join(TEXT_FILE_TYPES)}\",\n ),\n BoolInput(\n name=\"silent_errors\",\n display_name=\"Silent Errors\",\n advanced=True,\n info=\"If true, errors will not raise an exception.\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Data\", name=\"data\", method=\"load_file\"),\n ]\n\n def load_file(self) -> Data:\n if not self.path:\n raise ValueError(\"Please, upload a file to use this component.\")\n resolved_path = self.resolve_path(self.path)\n silent_errors = self.silent_errors\n\n extension = Path(resolved_path).suffix[1:].lower()\n\n if extension == \"doc\":\n raise ValueError(\"doc files are not supported. Please save as .docx\")\n if extension not in TEXT_FILE_TYPES:\n raise ValueError(f\"Unsupported file type: {extension}\")\n\n data = parse_text_file_to_data(resolved_path, silent_errors)\n self.status = data if data else \"No data\"\n return data or Data()\n" + }, + "path": { + "advanced": false, + "display_name": "Path", + "dynamic": false, + "fileTypes": [ + "txt", + "md", + "mdx", + "csv", + "json", + "yaml", + "yml", + "xml", + "html", + "htm", + "pdf", + "docx", + "py", + "sh", + "sql", + "js", + "ts", + "tsx" + ], + "file_path": "bba1609b-3af2-431d-a884-322cc253c69d/flatland.pdf", + "info": "Supported file types: txt, md, mdx, csv, json, yaml, yml, xml, html, htm, pdf, docx, py, sh, sql, js, ts, tsx", + "list": false, + "name": "path", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "file", + "value": "" + }, + "silent_errors": { + "advanced": true, + "display_name": "Silent Errors", + "dynamic": false, + "info": "If true, errors will not raise an exception.", + "list": false, + "name": "silent_errors", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + } + } + }, + "type": "File" + }, + "dragging": false, + "height": 301, + "id": "File-p2YBf", + "position": { + "x": 1435.8917804347734, + "y": 1603.546667861399 + }, + "positionAbsolute": { + "x": 1435.8917804347734, + "y": 1603.546667861399 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Implementation of Vector Store using Astra DB with search capabilities", + "display_name": "Astra DB Vector Store", + "id": "AstraDB-p6135", + "node": { + "base_classes": [ + "Data" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Implementation of Vector Store using Astra DB with search capabilities", + "display_name": "Astra DB Vector Store", + "documentation": "https://python.langchain.com/docs/integrations/vectorstores/astradb", + "edited": false, + "field_order": [ + "collection_name", + "token", + "api_endpoint", + "vector_store_inputs", + "embedding", + "namespace", + "metric", + "batch_size", + "bulk_insert_batch_concurrency", + "bulk_insert_overwrite_concurrency", + "bulk_delete_concurrency", + "setup_mode", + "pre_delete_collection", + "metadata_indexing_include", + "metadata_indexing_exclude", + "collection_indexing_policy", + "add_to_vector_store", + "search_input", + "search_type", + "number_of_results" + ], + "frozen": false, + "icon": "AstraDB", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Retriever", + "method": "build_base_retriever", + "name": "base_retriever", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Search Results", + "hidden": false, + "method": "search_documents", + "name": "search_results", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "add_to_vector_store": { + "advanced": false, + "display_name": "Add to Vector Store", + "dynamic": false, + "info": "If true, the Vector Store Inputs will be added to the Vector Store.", + "list": false, + "name": "add_to_vector_store", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "api_endpoint": { + "advanced": false, + "display_name": "API Endpoint", + "dynamic": false, + "info": "API endpoint URL for the Astra DB service.", + "input_types": [], + "load_from_db": false, + "name": "api_endpoint", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "batch_size": { + "advanced": true, + "display_name": "Batch Size", + "dynamic": false, + "info": "Optional number of data to process in a single batch.", + "list": false, + "name": "batch_size", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "bulk_delete_concurrency": { + "advanced": true, + "display_name": "Bulk Delete Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk delete operations.", + "list": false, + "name": "bulk_delete_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "bulk_insert_batch_concurrency": { + "advanced": true, + "display_name": "Bulk Insert Batch Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk insert operations.", + "list": false, + "name": "bulk_insert_batch_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "bulk_insert_overwrite_concurrency": { + "advanced": true, + "display_name": "Bulk Insert Overwrite Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk insert operations that overwrite existing data.", + "list": false, + "name": "bulk_insert_overwrite_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from loguru import logger\n\nfrom langflow.base.vectorstores.model import LCVectorStoreComponent\nfrom langflow.io import BoolInput, DropdownInput, HandleInput, IntInput, MultilineInput, SecretStrInput, StrInput\nfrom langflow.schema import Data\n\n\nclass AstraVectorStoreComponent(LCVectorStoreComponent):\n display_name: str = \"Astra DB Vector Store\"\n description: str = \"Implementation of Vector Store using Astra DB with search capabilities\"\n documentation: str = \"https://python.langchain.com/docs/integrations/vectorstores/astradb\"\n icon: str = \"AstraDB\"\n\n inputs = [\n StrInput(\n name=\"collection_name\",\n display_name=\"Collection Name\",\n info=\"The name of the collection within Astra DB where the vectors will be stored.\",\n ),\n SecretStrInput(\n name=\"token\",\n display_name=\"Astra DB Application Token\",\n info=\"Authentication token for accessing Astra DB.\",\n value=\"ASTRA_DB_APPLICATION_TOKEN\",\n ),\n SecretStrInput(\n name=\"api_endpoint\",\n display_name=\"API Endpoint\",\n info=\"API endpoint URL for the Astra DB service.\",\n value=\"ASTRA_DB_API_ENDPOINT\",\n ),\n HandleInput(\n name=\"vector_store_inputs\",\n display_name=\"Vector Store Inputs\",\n input_types=[\"Document\", \"Data\"],\n is_list=True,\n ),\n HandleInput(\n name=\"embedding\",\n display_name=\"Embedding\",\n input_types=[\"Embeddings\"],\n ),\n StrInput(\n name=\"namespace\",\n display_name=\"Namespace\",\n info=\"Optional namespace within Astra DB to use for the collection.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"metric\",\n display_name=\"Metric\",\n info=\"Optional distance metric for vector comparisons in the vector store.\",\n options=[\"cosine\", \"dot_product\", \"euclidean\"],\n advanced=True,\n ),\n IntInput(\n name=\"batch_size\",\n display_name=\"Batch Size\",\n info=\"Optional number of data to process in a single batch.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_batch_concurrency\",\n display_name=\"Bulk Insert Batch Concurrency\",\n info=\"Optional concurrency level for bulk insert operations.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_overwrite_concurrency\",\n display_name=\"Bulk Insert Overwrite Concurrency\",\n info=\"Optional concurrency level for bulk insert operations that overwrite existing data.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_delete_concurrency\",\n display_name=\"Bulk Delete Concurrency\",\n info=\"Optional concurrency level for bulk delete operations.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"setup_mode\",\n display_name=\"Setup Mode\",\n info=\"Configuration mode for setting up the vector store, with options like 'Sync', 'Async', or 'Off'.\",\n options=[\"Sync\", \"Async\", \"Off\"],\n advanced=True,\n value=\"Sync\",\n ),\n BoolInput(\n name=\"pre_delete_collection\",\n display_name=\"Pre Delete Collection\",\n info=\"Boolean flag to determine whether to delete the collection before creating a new one.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_include\",\n display_name=\"Metadata Indexing Include\",\n info=\"Optional list of metadata fields to include in the indexing.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_exclude\",\n display_name=\"Metadata Indexing Exclude\",\n info=\"Optional list of metadata fields to exclude from the indexing.\",\n advanced=True,\n ),\n StrInput(\n name=\"collection_indexing_policy\",\n display_name=\"Collection Indexing Policy\",\n info=\"Optional dictionary defining the indexing policy for the collection.\",\n advanced=True,\n ),\n BoolInput(\n name=\"add_to_vector_store\",\n display_name=\"Add to Vector Store\",\n info=\"If true, the Vector Store Inputs will be added to the Vector Store.\",\n ),\n MultilineInput(\n name=\"search_input\",\n display_name=\"Search Input\",\n ),\n DropdownInput(\n name=\"search_type\",\n display_name=\"Search Type\",\n options=[\"Similarity\", \"MMR\"],\n value=\"Similarity\",\n ),\n IntInput(\n name=\"number_of_results\",\n display_name=\"Number of Results\",\n info=\"Number of results to return.\",\n advanced=True,\n value=4,\n ),\n ]\n\n def build_vector_store(self):\n try:\n from langchain_astradb import AstraDBVectorStore\n from langchain_astradb.utils.astradb import SetupMode\n except ImportError:\n raise ImportError(\n \"Could not import langchain Astra DB integration package. \"\n \"Please install it with `pip install langchain-astradb`.\"\n )\n\n try:\n if not self.setup_mode:\n self.setup_mode = self._inputs[\"setup_mode\"].options[0]\n\n setup_mode_value = SetupMode[self.setup_mode.upper()]\n except KeyError:\n raise ValueError(f\"Invalid setup mode: {self.setup_mode}\")\n\n vector_store_kwargs = {\n \"embedding\": self.embedding,\n \"collection_name\": self.collection_name,\n \"token\": self.token,\n \"api_endpoint\": self.api_endpoint,\n \"namespace\": self.namespace or None,\n \"metric\": self.metric or None,\n \"batch_size\": self.batch_size or None,\n \"bulk_insert_batch_concurrency\": self.bulk_insert_batch_concurrency or None,\n \"bulk_insert_overwrite_concurrency\": self.bulk_insert_overwrite_concurrency or None,\n \"bulk_delete_concurrency\": self.bulk_delete_concurrency or None,\n \"setup_mode\": setup_mode_value,\n \"pre_delete_collection\": self.pre_delete_collection or False,\n }\n\n if self.metadata_indexing_include:\n vector_store_kwargs[\"metadata_indexing_include\"] = self.metadata_indexing_include\n elif self.metadata_indexing_exclude:\n vector_store_kwargs[\"metadata_indexing_exclude\"] = self.metadata_indexing_exclude\n elif self.collection_indexing_policy:\n vector_store_kwargs[\"collection_indexing_policy\"] = self.collection_indexing_policy\n\n try:\n vector_store = AstraDBVectorStore(**vector_store_kwargs)\n except Exception as e:\n raise ValueError(f\"Error initializing AstraDBVectorStore: {str(e)}\") from e\n\n if self.add_to_vector_store:\n self._add_documents_to_vector_store(vector_store)\n\n return vector_store\n\n def build_base_retriever(self):\n vector_store = self.build_vector_store()\n self.status = self._astradb_collection_to_data(vector_store.collection)\n return vector_store\n\n def _add_documents_to_vector_store(self, vector_store):\n documents = []\n for _input in self.vector_store_inputs or []:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n else:\n raise ValueError(\"Vector Store Inputs must be Data objects.\")\n\n if documents and self.embedding is not None:\n logger.debug(f\"Adding {len(documents)} documents to the Vector Store.\")\n try:\n vector_store.add_documents(documents)\n except Exception as e:\n raise ValueError(f\"Error adding documents to AstraDBVectorStore: {str(e)}\") from e\n else:\n logger.debug(\"No documents to add to the Vector Store.\")\n\n def search_documents(self):\n vector_store = self.build_vector_store()\n\n logger.debug(f\"Search input: {self.search_input}\")\n logger.debug(f\"Search type: {self.search_type}\")\n logger.debug(f\"Number of results: {self.number_of_results}\")\n\n if self.search_input and isinstance(self.search_input, str) and self.search_input.strip():\n try:\n if self.search_type == \"Similarity\":\n docs = vector_store.similarity_search(\n query=self.search_input,\n k=self.number_of_results,\n )\n elif self.search_type == \"MMR\":\n docs = vector_store.max_marginal_relevance_search(\n query=self.search_input,\n k=self.number_of_results,\n )\n else:\n raise ValueError(f\"Invalid search type: {self.search_type}\")\n except Exception as e:\n raise ValueError(f\"Error performing search in AstraDBVectorStore: {str(e)}\") from e\n\n logger.debug(f\"Retrieved documents: {len(docs)}\")\n\n data = [Data.from_document(doc) for doc in docs]\n logger.debug(f\"Converted documents to data: {len(data)}\")\n self.status = data\n return data\n else:\n logger.debug(\"No search input provided. Skipping search.\")\n return []\n\n def _astradb_collection_to_data(self, collection):\n data = []\n data_dict = collection.find()\n if data_dict and \"data\" in data_dict:\n data_dict = data_dict[\"data\"].get(\"documents\", [])\n\n for item in data_dict:\n data.append(Data(content=item[\"content\"]))\n return data\n" + }, + "collection_indexing_policy": { + "advanced": true, + "display_name": "Collection Indexing Policy", + "dynamic": false, + "info": "Optional dictionary defining the indexing policy for the collection.", + "list": false, + "load_from_db": false, + "name": "collection_indexing_policy", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "collection_name": { + "advanced": false, + "display_name": "Collection Name", + "dynamic": false, + "info": "The name of the collection within Astra DB where the vectors will be stored.", + "list": false, + "load_from_db": false, + "name": "collection_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "langflow" + }, + "embedding": { + "advanced": false, + "display_name": "Embedding", + "dynamic": false, + "info": "", + "input_types": [ + "Embeddings" + ], + "list": false, + "name": "embedding", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "other", + "value": "" + }, + "metadata_indexing_exclude": { + "advanced": true, + "display_name": "Metadata Indexing Exclude", + "dynamic": false, + "info": "Optional list of metadata fields to exclude from the indexing.", + "list": false, + "load_from_db": false, + "name": "metadata_indexing_exclude", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "metadata_indexing_include": { + "advanced": true, + "display_name": "Metadata Indexing Include", + "dynamic": false, + "info": "Optional list of metadata fields to include in the indexing.", + "list": false, + "load_from_db": false, + "name": "metadata_indexing_include", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "metric": { + "advanced": true, + "display_name": "Metric", + "dynamic": false, + "info": "Optional distance metric for vector comparisons in the vector store.", + "name": "metric", + "options": [ + "cosine", + "dot_product", + "euclidean" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "namespace": { + "advanced": true, + "display_name": "Namespace", + "dynamic": false, + "info": "Optional namespace within Astra DB to use for the collection.", + "list": false, + "load_from_db": false, + "name": "namespace", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "number_of_results": { + "advanced": true, + "display_name": "Number of Results", + "dynamic": false, + "info": "Number of results to return.", + "list": false, + "name": "number_of_results", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 4 + }, + "pre_delete_collection": { + "advanced": true, + "display_name": "Pre Delete Collection", + "dynamic": false, + "info": "Boolean flag to determine whether to delete the collection before creating a new one.", + "list": false, + "name": "pre_delete_collection", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "search_input": { + "advanced": false, + "display_name": "Search Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "search_input", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "search_type": { + "advanced": false, + "display_name": "Search Type", + "dynamic": false, + "info": "", + "name": "search_type", + "options": [ + "Similarity", + "MMR" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "Similarity" + }, + "setup_mode": { + "advanced": true, + "display_name": "Setup Mode", + "dynamic": false, + "info": "Configuration mode for setting up the vector store, with options like 'Sync', 'Async', or 'Off'.", + "name": "setup_mode", + "options": [ + "Sync", + "Async", + "Off" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "Sync" + }, + "token": { + "advanced": false, + "display_name": "Astra DB Application Token", + "dynamic": false, + "info": "Authentication token for accessing Astra DB.", + "input_types": [], + "load_from_db": false, + "name": "token", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "vector_store_inputs": { + "advanced": false, + "display_name": "Vector Store Inputs", + "dynamic": false, + "info": "", + "input_types": [ + "Document", + "Data" + ], + "list": true, + "name": "vector_store_inputs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "other", + "value": "" + } + } + }, + "type": "AstraDB" + }, + "dragging": false, + "height": 917, + "id": "AstraDB-p6135", + "position": { + "x": 1298.4611042465333, + "y": 160.7181472642742 + }, + "positionAbsolute": { + "x": 1298.4611042465333, + "y": 160.7181472642742 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "id": "ParseData-9DrmC", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Convert Data into plain text following a specified template.", + "display_name": "Parse Data", + "documentation": "", + "field_order": [ + "data", + "template", + "sep" + ], + "frozen": false, + "icon": "braces", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Text", + "hidden": false, + "method": "parse_data", + "name": "text", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import DataInput, MultilineInput, Output, StrInput\nfrom langflow.schema.message import Message\n\n\nclass ParseDataComponent(Component):\n display_name = \"Parse Data\"\n description = \"Convert Data into plain text following a specified template.\"\n icon = \"braces\"\n\n inputs = [\n DataInput(name=\"data\", display_name=\"Data\", info=\"The data to convert to text.\"),\n MultilineInput(\n name=\"template\",\n display_name=\"Template\",\n info=\"The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.\",\n value=\"{text}\",\n ),\n StrInput(name=\"sep\", display_name=\"Separator\", advanced=True, value=\"\\n\"),\n ]\n\n outputs = [\n Output(display_name=\"Text\", name=\"text\", method=\"parse_data\"),\n ]\n\n def parse_data(self) -> Message:\n data = self.data if isinstance(self.data, list) else [self.data]\n template = self.template\n\n result_string = data_to_text(template, data, sep=self.sep)\n self.status = result_string\n return Message(text=result_string)\n" + }, + "data": { + "advanced": false, + "display_name": "Data", + "dynamic": false, + "info": "The data to convert to text.", + "input_types": [ + "Data" + ], + "list": false, + "name": "data", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "other", + "value": "" + }, + "sep": { + "advanced": true, + "display_name": "Separator", + "dynamic": false, + "info": "", + "list": false, + "load_from_db": false, + "name": "sep", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "---" + }, + "template": { + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "The template to use for formatting the data. It can contain the keys {text}, {data} or any other key in the Data.", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "{text}" + } + } + }, + "type": "ParseData" + }, + "dragging": false, + "height": 385, + "id": "ParseData-9DrmC", + "position": { + "x": 1911.4866480237615, + "y": 566.903831987901 + }, + "positionAbsolute": { + "x": 1911.4866480237615, + "y": 566.903831987901 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "id": "Prompt-EEXgw", + "node": { + "base_classes": [ + "Message" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": { + "template": [ + "context", + "question" + ] + }, + "description": "Create a prompt template with dynamic variables.", + "display_name": "Prompt", + "documentation": "", + "edited": false, + "error": null, + "field_order": [ + "template" + ], + "frozen": false, + "full_path": null, + "icon": "prompts", + "is_composition": null, + "is_input": null, + "is_output": null, + "name": "", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Prompt Message", + "hidden": false, + "method": "build_prompt", + "name": "prompt", + "selected": "Message", + "types": [ + "Message" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.io import Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\n trace_type = \"prompt\"\n\n inputs = [\n PromptInput(name=\"template\", display_name=\"Template\"),\n ]\n\n outputs = [\n Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n ]\n\n async def build_prompt(\n self,\n ) -> Message:\n prompt = await Message.from_template_and_variables(**self._attributes)\n self.status = prompt.text\n return prompt\n\n def post_code_processing(self, new_build_config: dict, current_build_config: dict):\n \"\"\"\n This function is called after the code validation is done.\n \"\"\"\n frontend_node = super().post_code_processing(new_build_config, current_build_config)\n template = frontend_node[\"template\"][\"template\"][\"value\"]\n _ = process_prompt_template(\n template=template,\n name=\"template\",\n custom_fields=frontend_node[\"custom_fields\"],\n frontend_node_template=frontend_node[\"template\"],\n )\n # Now that template is updated, we need to grab any values that were set in the current_build_config\n # and update the frontend_node with those values\n update_template_values(frontend_template=frontend_node, raw_template=current_build_config[\"template\"])\n return frontend_node\n" + }, + "context": { + "advanced": false, + "display_name": "context", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "context", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "question": { + "advanced": false, + "display_name": "question", + "dynamic": false, + "field_type": "str", + "fileTypes": [], + "file_path": "", + "info": "", + "input_types": [ + "Message", + "Text" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "question", + "password": false, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "template": { + "advanced": false, + "display_name": "Template", + "dynamic": false, + "info": "", + "list": false, + "name": "template", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "type": "prompt", + "value": "{context}\n\n---\n\nGiven the context above, answer the question as best as possible.\n\nQuestion: {question}\n\nAnswer: " + } + } + }, + "type": "Prompt" + }, + "dragging": false, + "height": 517, + "id": "Prompt-EEXgw", + "position": { + "x": 2537.8054430938064, + "y": 442.35183727527414 + }, + "positionAbsolute": { + "x": 2537.8054430938064, + "y": 442.35183727527414 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "data": { + "id": "SplitText-qI0jS", + "node": { + "base_classes": [ + "Data" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Split text into chunks based on specified criteria.", + "display_name": "Split Text", + "documentation": "", + "edited": false, + "field_order": [ + "data_inputs", + "chunk_overlap", + "chunk_size", + "separator" + ], + "frozen": false, + "icon": "scissors-line-dashed", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Chunks", + "hidden": false, + "method": "split_text", + "name": "chunks", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "chunk_overlap": { + "advanced": false, + "display_name": "Chunk Overlap", + "dynamic": false, + "info": "Number of characters to overlap between chunks.", + "list": false, + "name": "chunk_overlap", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 200 + }, + "chunk_size": { + "advanced": false, + "display_name": "Chunk Size", + "dynamic": false, + "info": "The maximum number of characters in each chunk.", + "list": false, + "name": "chunk_size", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "int", + "value": 1000 + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from typing import List\n\nfrom langchain_text_splitters import CharacterTextSplitter\n\nfrom langflow.custom import Component\nfrom langflow.io import HandleInput, IntInput, MessageTextInput, Output\nfrom langflow.schema import Data\nfrom langflow.utils.util import unescape_string\n\n\nclass SplitTextComponent(Component):\n display_name: str = \"Split Text\"\n description: str = \"Split text into chunks based on specified criteria.\"\n icon = \"scissors-line-dashed\"\n\n inputs = [\n HandleInput(\n name=\"data_inputs\",\n display_name=\"Data Inputs\",\n info=\"The data to split.\",\n input_types=[\"Data\"],\n is_list=True,\n ),\n IntInput(\n name=\"chunk_overlap\",\n display_name=\"Chunk Overlap\",\n info=\"Number of characters to overlap between chunks.\",\n value=200,\n ),\n IntInput(\n name=\"chunk_size\",\n display_name=\"Chunk Size\",\n info=\"The maximum number of characters in each chunk.\",\n value=1000,\n ),\n MessageTextInput(\n name=\"separator\",\n display_name=\"Separator\",\n info=\"The character to split on. Defaults to newline.\",\n value=\"\\n\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Chunks\", name=\"chunks\", method=\"split_text\"),\n ]\n\n def _docs_to_data(self, docs):\n data = []\n for doc in docs:\n data.append(Data(text=doc.page_content, data=doc.metadata))\n return data\n\n def split_text(self) -> List[Data]:\n separator = unescape_string(self.separator)\n\n documents = []\n for _input in self.data_inputs:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n\n splitter = CharacterTextSplitter(\n chunk_overlap=self.chunk_overlap,\n chunk_size=self.chunk_size,\n separator=separator,\n )\n docs = splitter.split_documents(documents)\n data = self._docs_to_data(docs)\n self.status = data\n return data\n" + }, + "data_inputs": { + "advanced": false, + "display_name": "Data Inputs", + "dynamic": false, + "info": "The data to split.", + "input_types": [ + "Data" + ], + "list": true, + "name": "data_inputs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_metadata": true, + "type": "other", + "value": "" + }, + "separator": { + "advanced": false, + "display_name": "Separator", + "dynamic": false, + "info": "The character to split on. Defaults to newline.", + "input_types": [ + "Message" + ], + "list": false, + "load_from_db": false, + "name": "separator", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "trace_as_input": true, + "trace_as_metadata": true, + "type": "str", + "value": "\n" + } + } + }, + "type": "SplitText" + }, + "dragging": false, + "height": 557, + "id": "SplitText-qI0jS", + "position": { + "x": 1992.5159478772907, + "y": 1190.8288727494814 + }, + "positionAbsolute": { + "x": 1992.5159478772907, + "y": 1190.8288727494814 + }, + "selected": false, + "type": "genericNode", + "width": 384 + }, + { + "id": "AstraDB-AX2Xz", + "type": "genericNode", + "position": { + "x": 2773.0562333179937, + "y": 1160.0660495763536 + }, + "data": { + "description": "Implementation of Vector Store using Astra DB with search capabilities", + "display_name": "Astra DB Vector Store", + "id": "AstraDB-AX2Xz", + "node": { + "base_classes": [ + "Data" + ], + "beta": false, + "conditional_paths": [], + "custom_fields": {}, + "description": "Implementation of Vector Store using Astra DB with search capabilities", + "display_name": "Astra DB Vector Store", + "documentation": "https://python.langchain.com/docs/integrations/vectorstores/astradb", + "edited": false, + "field_order": [ + "collection_name", + "token", + "api_endpoint", + "vector_store_inputs", + "embedding", + "namespace", + "metric", + "batch_size", + "bulk_insert_batch_concurrency", + "bulk_insert_overwrite_concurrency", + "bulk_delete_concurrency", + "setup_mode", + "pre_delete_collection", + "metadata_indexing_include", + "metadata_indexing_exclude", + "collection_indexing_policy", + "add_to_vector_store", + "search_input", + "search_type", + "number_of_results" + ], + "frozen": false, + "icon": "AstraDB", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Retriever", + "method": "build_base_retriever", + "name": "base_retriever", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + }, + { + "cache": true, + "display_name": "Search Results", + "hidden": false, + "method": "search_documents", + "name": "search_results", + "selected": "Data", + "types": [ + "Data" + ], + "value": "__UNDEFINED__" + } + ], + "pinned": false, + "template": { + "_type": "Component", + "add_to_vector_store": { + "advanced": false, + "display_name": "Add to Vector Store", + "dynamic": false, + "info": "If true, the Vector Store Inputs will be added to the Vector Store.", + "list": false, + "name": "add_to_vector_store", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": true + }, + "api_endpoint": { + "advanced": false, + "display_name": "API Endpoint", + "dynamic": false, + "info": "API endpoint URL for the Astra DB service.", + "input_types": [], + "load_from_db": false, + "name": "api_endpoint", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "batch_size": { + "advanced": true, + "display_name": "Batch Size", + "dynamic": false, + "info": "Optional number of data to process in a single batch.", + "list": false, + "name": "batch_size", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "bulk_delete_concurrency": { + "advanced": true, + "display_name": "Bulk Delete Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk delete operations.", + "list": false, + "name": "bulk_delete_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "bulk_insert_batch_concurrency": { + "advanced": true, + "display_name": "Bulk Insert Batch Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk insert operations.", + "list": false, + "name": "bulk_insert_batch_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "bulk_insert_overwrite_concurrency": { + "advanced": true, + "display_name": "Bulk Insert Overwrite Concurrency", + "dynamic": false, + "info": "Optional concurrency level for bulk insert operations that overwrite existing data.", + "list": false, + "name": "bulk_insert_overwrite_concurrency", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from loguru import logger\n\nfrom langflow.base.vectorstores.model import LCVectorStoreComponent\nfrom langflow.io import BoolInput, DropdownInput, HandleInput, IntInput, MultilineInput, SecretStrInput, StrInput\nfrom langflow.schema import Data\n\n\nclass AstraVectorStoreComponent(LCVectorStoreComponent):\n display_name: str = \"Astra DB Vector Store\"\n description: str = \"Implementation of Vector Store using Astra DB with search capabilities\"\n documentation: str = \"https://python.langchain.com/docs/integrations/vectorstores/astradb\"\n icon: str = \"AstraDB\"\n\n inputs = [\n StrInput(\n name=\"collection_name\",\n display_name=\"Collection Name\",\n info=\"The name of the collection within Astra DB where the vectors will be stored.\",\n ),\n SecretStrInput(\n name=\"token\",\n display_name=\"Astra DB Application Token\",\n info=\"Authentication token for accessing Astra DB.\",\n value=\"ASTRA_DB_APPLICATION_TOKEN\",\n ),\n SecretStrInput(\n name=\"api_endpoint\",\n display_name=\"API Endpoint\",\n info=\"API endpoint URL for the Astra DB service.\",\n value=\"ASTRA_DB_API_ENDPOINT\",\n ),\n HandleInput(\n name=\"vector_store_inputs\",\n display_name=\"Vector Store Inputs\",\n input_types=[\"Document\", \"Data\"],\n is_list=True,\n ),\n HandleInput(\n name=\"embedding\",\n display_name=\"Embedding\",\n input_types=[\"Embeddings\"],\n ),\n StrInput(\n name=\"namespace\",\n display_name=\"Namespace\",\n info=\"Optional namespace within Astra DB to use for the collection.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"metric\",\n display_name=\"Metric\",\n info=\"Optional distance metric for vector comparisons in the vector store.\",\n options=[\"cosine\", \"dot_product\", \"euclidean\"],\n advanced=True,\n ),\n IntInput(\n name=\"batch_size\",\n display_name=\"Batch Size\",\n info=\"Optional number of data to process in a single batch.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_batch_concurrency\",\n display_name=\"Bulk Insert Batch Concurrency\",\n info=\"Optional concurrency level for bulk insert operations.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_insert_overwrite_concurrency\",\n display_name=\"Bulk Insert Overwrite Concurrency\",\n info=\"Optional concurrency level for bulk insert operations that overwrite existing data.\",\n advanced=True,\n ),\n IntInput(\n name=\"bulk_delete_concurrency\",\n display_name=\"Bulk Delete Concurrency\",\n info=\"Optional concurrency level for bulk delete operations.\",\n advanced=True,\n ),\n DropdownInput(\n name=\"setup_mode\",\n display_name=\"Setup Mode\",\n info=\"Configuration mode for setting up the vector store, with options like 'Sync', 'Async', or 'Off'.\",\n options=[\"Sync\", \"Async\", \"Off\"],\n advanced=True,\n value=\"Sync\",\n ),\n BoolInput(\n name=\"pre_delete_collection\",\n display_name=\"Pre Delete Collection\",\n info=\"Boolean flag to determine whether to delete the collection before creating a new one.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_include\",\n display_name=\"Metadata Indexing Include\",\n info=\"Optional list of metadata fields to include in the indexing.\",\n advanced=True,\n ),\n StrInput(\n name=\"metadata_indexing_exclude\",\n display_name=\"Metadata Indexing Exclude\",\n info=\"Optional list of metadata fields to exclude from the indexing.\",\n advanced=True,\n ),\n StrInput(\n name=\"collection_indexing_policy\",\n display_name=\"Collection Indexing Policy\",\n info=\"Optional dictionary defining the indexing policy for the collection.\",\n advanced=True,\n ),\n BoolInput(\n name=\"add_to_vector_store\",\n display_name=\"Add to Vector Store\",\n info=\"If true, the Vector Store Inputs will be added to the Vector Store.\",\n ),\n MultilineInput(\n name=\"search_input\",\n display_name=\"Search Input\",\n ),\n DropdownInput(\n name=\"search_type\",\n display_name=\"Search Type\",\n options=[\"Similarity\", \"MMR\"],\n value=\"Similarity\",\n ),\n IntInput(\n name=\"number_of_results\",\n display_name=\"Number of Results\",\n info=\"Number of results to return.\",\n advanced=True,\n value=4,\n ),\n ]\n\n def build_vector_store(self):\n try:\n from langchain_astradb import AstraDBVectorStore\n from langchain_astradb.utils.astradb import SetupMode\n except ImportError:\n raise ImportError(\n \"Could not import langchain Astra DB integration package. \"\n \"Please install it with `pip install langchain-astradb`.\"\n )\n\n try:\n if not self.setup_mode:\n self.setup_mode = self._inputs[\"setup_mode\"].options[0]\n\n setup_mode_value = SetupMode[self.setup_mode.upper()]\n except KeyError:\n raise ValueError(f\"Invalid setup mode: {self.setup_mode}\")\n\n vector_store_kwargs = {\n \"embedding\": self.embedding,\n \"collection_name\": self.collection_name,\n \"token\": self.token,\n \"api_endpoint\": self.api_endpoint,\n \"namespace\": self.namespace or None,\n \"metric\": self.metric or None,\n \"batch_size\": self.batch_size or None,\n \"bulk_insert_batch_concurrency\": self.bulk_insert_batch_concurrency or None,\n \"bulk_insert_overwrite_concurrency\": self.bulk_insert_overwrite_concurrency or None,\n \"bulk_delete_concurrency\": self.bulk_delete_concurrency or None,\n \"setup_mode\": setup_mode_value,\n \"pre_delete_collection\": self.pre_delete_collection or False,\n }\n\n if self.metadata_indexing_include:\n vector_store_kwargs[\"metadata_indexing_include\"] = self.metadata_indexing_include\n elif self.metadata_indexing_exclude:\n vector_store_kwargs[\"metadata_indexing_exclude\"] = self.metadata_indexing_exclude\n elif self.collection_indexing_policy:\n vector_store_kwargs[\"collection_indexing_policy\"] = self.collection_indexing_policy\n\n try:\n vector_store = AstraDBVectorStore(**vector_store_kwargs)\n except Exception as e:\n raise ValueError(f\"Error initializing AstraDBVectorStore: {str(e)}\") from e\n\n if self.add_to_vector_store:\n self._add_documents_to_vector_store(vector_store)\n\n return vector_store\n\n def build_base_retriever(self):\n vector_store = self.build_vector_store()\n self.status = self._astradb_collection_to_data(vector_store.collection)\n return vector_store\n\n def _add_documents_to_vector_store(self, vector_store):\n documents = []\n for _input in self.vector_store_inputs or []:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n else:\n raise ValueError(\"Vector Store Inputs must be Data objects.\")\n\n if documents and self.embedding is not None:\n logger.debug(f\"Adding {len(documents)} documents to the Vector Store.\")\n try:\n vector_store.add_documents(documents)\n except Exception as e:\n raise ValueError(f\"Error adding documents to AstraDBVectorStore: {str(e)}\") from e\n else:\n logger.debug(\"No documents to add to the Vector Store.\")\n\n def search_documents(self):\n vector_store = self.build_vector_store()\n\n logger.debug(f\"Search input: {self.search_input}\")\n logger.debug(f\"Search type: {self.search_type}\")\n logger.debug(f\"Number of results: {self.number_of_results}\")\n\n if self.search_input and isinstance(self.search_input, str) and self.search_input.strip():\n try:\n if self.search_type == \"Similarity\":\n docs = vector_store.similarity_search(\n query=self.search_input,\n k=self.number_of_results,\n )\n elif self.search_type == \"MMR\":\n docs = vector_store.max_marginal_relevance_search(\n query=self.search_input,\n k=self.number_of_results,\n )\n else:\n raise ValueError(f\"Invalid search type: {self.search_type}\")\n except Exception as e:\n raise ValueError(f\"Error performing search in AstraDBVectorStore: {str(e)}\") from e\n\n logger.debug(f\"Retrieved documents: {len(docs)}\")\n\n data = [Data.from_document(doc) for doc in docs]\n logger.debug(f\"Converted documents to data: {len(data)}\")\n self.status = data\n return data\n else:\n logger.debug(\"No search input provided. Skipping search.\")\n return []\n\n def _astradb_collection_to_data(self, collection):\n data = []\n data_dict = collection.find()\n if data_dict and \"data\" in data_dict:\n data_dict = data_dict[\"data\"].get(\"documents\", [])\n\n for item in data_dict:\n data.append(Data(content=item[\"content\"]))\n return data\n" + }, + "collection_indexing_policy": { + "advanced": true, + "display_name": "Collection Indexing Policy", + "dynamic": false, + "info": "Optional dictionary defining the indexing policy for the collection.", + "list": false, + "load_from_db": false, + "name": "collection_indexing_policy", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "collection_name": { + "advanced": false, + "display_name": "Collection Name", + "dynamic": false, + "info": "The name of the collection within Astra DB where the vectors will be stored.", + "list": false, + "load_from_db": false, + "name": "collection_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "langflow" + }, + "embedding": { + "advanced": false, + "display_name": "Embedding", + "dynamic": false, + "info": "", + "input_types": [ + "Embeddings" + ], + "list": false, + "name": "embedding", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "other", + "value": "" + }, + "metadata_indexing_exclude": { + "advanced": true, + "display_name": "Metadata Indexing Exclude", + "dynamic": false, + "info": "Optional list of metadata fields to exclude from the indexing.", + "list": false, + "load_from_db": false, + "name": "metadata_indexing_exclude", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "metadata_indexing_include": { + "advanced": true, + "display_name": "Metadata Indexing Include", + "dynamic": false, + "info": "Optional list of metadata fields to include in the indexing.", + "list": false, + "load_from_db": false, + "name": "metadata_indexing_include", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "metric": { + "advanced": true, + "display_name": "Metric", + "dynamic": false, + "info": "Optional distance metric for vector comparisons in the vector store.", + "name": "metric", + "options": [ + "cosine", + "dot_product", + "euclidean" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "namespace": { + "advanced": true, + "display_name": "Namespace", + "dynamic": false, + "info": "Optional namespace within Astra DB to use for the collection.", + "list": false, + "load_from_db": false, + "name": "namespace", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "number_of_results": { + "advanced": true, + "display_name": "Number of Results", + "dynamic": false, + "info": "Number of results to return.", + "list": false, + "name": "number_of_results", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 4 + }, + "pre_delete_collection": { + "advanced": true, + "display_name": "Pre Delete Collection", + "dynamic": false, + "info": "Boolean flag to determine whether to delete the collection before creating a new one.", + "list": false, + "name": "pre_delete_collection", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "search_input": { + "advanced": false, + "display_name": "Search Input", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "multiline": true, + "name": "search_input", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "search_type": { + "advanced": false, + "display_name": "Search Type", + "dynamic": false, + "info": "", + "name": "search_type", + "options": [ + "Similarity", + "MMR" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "Similarity" + }, + "setup_mode": { + "advanced": true, + "display_name": "Setup Mode", + "dynamic": false, + "info": "Configuration mode for setting up the vector store, with options like 'Sync', 'Async', or 'Off'.", + "name": "setup_mode", + "options": [ + "Sync", + "Async", + "Off" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "Sync" + }, + "token": { + "advanced": false, + "display_name": "Astra DB Application Token", + "dynamic": false, + "info": "Authentication token for accessing Astra DB.", + "input_types": [], + "load_from_db": false, + "name": "token", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "vector_store_inputs": { + "advanced": false, + "display_name": "Vector Store Inputs", + "dynamic": false, + "info": "", + "input_types": [ + "Document", + "Data" + ], + "list": true, + "name": "vector_store_inputs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "other", + "value": "" + } + } + }, + "type": "AstraDB" + }, + "selected": false, + "width": 384, + "height": 917, + "positionAbsolute": { + "x": 2773.0562333179937, + "y": 1160.0660495763536 + }, + "dragging": false + }, + { + "id": "OpenAIEmbeddings-PQc6x", + "type": "genericNode", + "position": { + "x": 1992.590633037642, + "y": 1850.2707576021312 + }, + "data": { + "id": "OpenAIEmbeddings-PQc6x", + "node": { + "base_classes": [ + "Embeddings" + ], + "beta": false, + "custom_fields": { + "allowed_special": null, + "chunk_size": null, + "client": null, + "default_headers": null, + "default_query": null, + "deployment": null, + "disallowed_special": null, + "embedding_ctx_length": null, + "max_retries": null, + "model": null, + "model_kwargs": null, + "openai_api_base": null, + "openai_api_key": null, + "openai_api_type": null, + "openai_api_version": null, + "openai_organization": null, + "openai_proxy": null, + "request_timeout": null, + "show_progress_bar": null, + "skip_empty": null, + "tiktoken_enable": null, + "tiktoken_model_name": null + }, + "description": "Generate embeddings using OpenAI models.", + "display_name": "OpenAI Embeddings", + "documentation": "", + "field_formatters": {}, + "field_order": [], + "frozen": false, + "icon": "OpenAI", + "output_types": [], + "outputs": [ + { + "cache": true, + "display_name": "Embeddings", + "hidden": false, + "method": "build_embeddings", + "name": "embeddings", + "selected": "Embeddings", + "types": [ + "Embeddings" + ], + "value": "__UNDEFINED__" + } + ], + "template": { + "_type": "Component", + "chunk_size": { + "advanced": true, + "display_name": "Chunk Size", + "dynamic": false, + "info": "", + "list": false, + "name": "chunk_size", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 1000 + }, + "client": { + "advanced": true, + "display_name": "Client", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "client", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "code": { + "advanced": true, + "dynamic": true, + "fileTypes": [], + "file_path": "", + "info": "", + "list": false, + "load_from_db": false, + "multiline": true, + "name": "code", + "password": false, + "placeholder": "", + "required": true, + "show": true, + "title_case": false, + "type": "code", + "value": "from langchain_openai.embeddings.base import OpenAIEmbeddings\n\nfrom langflow.base.embeddings.model import LCEmbeddingsModel\nfrom langflow.field_typing import Embeddings\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, SecretStrInput, MessageTextInput\n\n\nclass OpenAIEmbeddingsComponent(LCEmbeddingsModel):\n display_name = \"OpenAI Embeddings\"\n description = \"Generate embeddings using OpenAI models.\"\n icon = \"OpenAI\"\n inputs = [\n DictInput(\n name=\"default_headers\",\n display_name=\"Default Headers\",\n advanced=True,\n info=\"Default headers to use for the API request.\",\n ),\n DictInput(\n name=\"default_query\",\n display_name=\"Default Query\",\n advanced=True,\n info=\"Default query parameters to use for the API request.\",\n ),\n IntInput(name=\"chunk_size\", display_name=\"Chunk Size\", advanced=True, value=1000),\n MessageTextInput(name=\"client\", display_name=\"Client\", advanced=True),\n MessageTextInput(name=\"deployment\", display_name=\"Deployment\", advanced=True),\n IntInput(name=\"embedding_ctx_length\", display_name=\"Embedding Context Length\", advanced=True, value=1536),\n IntInput(name=\"max_retries\", display_name=\"Max Retries\", value=3, advanced=True),\n DropdownInput(\n name=\"model\",\n display_name=\"Model\",\n advanced=False,\n options=[\n \"text-embedding-3-small\",\n \"text-embedding-3-large\",\n \"text-embedding-ada-002\",\n ],\n value=\"text-embedding-3-small\",\n ),\n DictInput(name=\"model_kwargs\", display_name=\"Model Kwargs\", advanced=True),\n SecretStrInput(name=\"openai_api_base\", display_name=\"OpenAI API Base\", advanced=True),\n SecretStrInput(name=\"openai_api_key\", display_name=\"OpenAI API Key\"),\n SecretStrInput(name=\"openai_api_type\", display_name=\"OpenAI API Type\", advanced=True),\n MessageTextInput(name=\"openai_api_version\", display_name=\"OpenAI API Version\", advanced=True),\n MessageTextInput(\n name=\"openai_organization\",\n display_name=\"OpenAI Organization\",\n advanced=True,\n ),\n MessageTextInput(name=\"openai_proxy\", display_name=\"OpenAI Proxy\", advanced=True),\n FloatInput(name=\"request_timeout\", display_name=\"Request Timeout\", advanced=True),\n BoolInput(name=\"show_progress_bar\", display_name=\"Show Progress Bar\", advanced=True),\n BoolInput(name=\"skip_empty\", display_name=\"Skip Empty\", advanced=True),\n MessageTextInput(\n name=\"tiktoken_model_name\",\n display_name=\"TikToken Model Name\",\n advanced=True,\n ),\n BoolInput(\n name=\"tiktoken_enable\",\n display_name=\"TikToken Enable\",\n advanced=True,\n value=True,\n info=\"If False, you must have transformers installed.\",\n ),\n ]\n\n def build_embeddings(self) -> Embeddings:\n return OpenAIEmbeddings(\n tiktoken_enabled=self.tiktoken_enable,\n default_headers=self.default_headers,\n default_query=self.default_query,\n allowed_special=\"all\",\n disallowed_special=\"all\",\n chunk_size=self.chunk_size,\n deployment=self.deployment,\n embedding_ctx_length=self.embedding_ctx_length,\n max_retries=self.max_retries,\n model=self.model,\n model_kwargs=self.model_kwargs,\n base_url=self.openai_api_base,\n api_key=self.openai_api_key,\n openai_api_type=self.openai_api_type,\n api_version=self.openai_api_version,\n organization=self.openai_organization,\n openai_proxy=self.openai_proxy,\n timeout=self.request_timeout or None,\n show_progress_bar=self.show_progress_bar,\n skip_empty=self.skip_empty,\n tiktoken_model_name=self.tiktoken_model_name,\n )\n" + }, + "default_headers": { + "advanced": true, + "display_name": "Default Headers", + "dynamic": false, + "info": "Default headers to use for the API request.", + "list": false, + "name": "default_headers", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "default_query": { + "advanced": true, + "display_name": "Default Query", + "dynamic": false, + "info": "Default query parameters to use for the API request.", + "list": false, + "name": "default_query", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "deployment": { + "advanced": true, + "display_name": "Deployment", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "deployment", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "embedding_ctx_length": { + "advanced": true, + "display_name": "Embedding Context Length", + "dynamic": false, + "info": "", + "list": false, + "name": "embedding_ctx_length", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 1536 + }, + "max_retries": { + "advanced": true, + "display_name": "Max Retries", + "dynamic": false, + "info": "", + "list": false, + "name": "max_retries", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "int", + "value": 3 + }, + "model": { + "advanced": false, + "display_name": "Model", + "dynamic": false, + "info": "", + "name": "model", + "options": [ + "text-embedding-3-small", + "text-embedding-3-large", + "text-embedding-ada-002" + ], + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "text-embedding-3-small" + }, + "model_kwargs": { + "advanced": true, + "display_name": "Model Kwargs", + "dynamic": false, + "info": "", + "list": false, + "name": "model_kwargs", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "dict", + "value": {} + }, + "openai_api_base": { + "advanced": true, + "display_name": "OpenAI API Base", + "dynamic": false, + "info": "", + "input_types": [], + "load_from_db": true, + "name": "openai_api_base", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_key": { + "advanced": false, + "display_name": "OpenAI API Key", + "dynamic": false, + "info": "", + "input_types": [], + "load_from_db": false, + "name": "openai_api_key", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_type": { + "advanced": true, + "display_name": "OpenAI API Type", + "dynamic": false, + "info": "", + "input_types": [], + "load_from_db": true, + "name": "openai_api_type", + "password": true, + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_api_version": { + "advanced": true, + "display_name": "OpenAI API Version", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "openai_api_version", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_organization": { + "advanced": true, + "display_name": "OpenAI Organization", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "openai_organization", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "openai_proxy": { + "advanced": true, + "display_name": "OpenAI Proxy", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "openai_proxy", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + }, + "request_timeout": { + "advanced": true, + "display_name": "Request Timeout", + "dynamic": false, + "info": "", + "list": false, + "name": "request_timeout", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "float", + "value": "" + }, + "show_progress_bar": { + "advanced": true, + "display_name": "Show Progress Bar", + "dynamic": false, + "info": "", + "list": false, + "name": "show_progress_bar", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "skip_empty": { + "advanced": true, + "display_name": "Skip Empty", + "dynamic": false, + "info": "", + "list": false, + "name": "skip_empty", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": false + }, + "tiktoken_enable": { + "advanced": true, + "display_name": "TikToken Enable", + "dynamic": false, + "info": "If False, you must have transformers installed.", + "list": false, + "name": "tiktoken_enable", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "bool", + "value": true + }, + "tiktoken_model_name": { + "advanced": true, + "display_name": "TikToken Model Name", + "dynamic": false, + "info": "", + "input_types": [ + "Message", + "str" + ], + "list": false, + "load_from_db": false, + "name": "tiktoken_model_name", + "placeholder": "", + "required": false, + "show": true, + "title_case": false, + "type": "str", + "value": "" + } + } + }, + "type": "OpenAIEmbeddings" + }, + "selected": true, + "width": 384, + "height": 395, + "positionAbsolute": { + "x": 1992.590633037642, + "y": 1850.2707576021312 + }, + "dragging": true } - }, - "type": "Prompt" - }, - "dragging": false, - "height": 517, - "id": "Prompt-V2VHT", - "position": { - "x": 2537.8054430938064, - "y": 442.35183727527414 - }, - "positionAbsolute": { - "x": 2537.8054430938064, - "y": 442.35183727527414 - }, - "selected": false, - "type": "genericNode", - "width": 384 - }, - { - "data": { - "id": "SplitText-ARuL2", - "node": { - "base_classes": [ - "Data" - ], - "beta": false, - "conditional_paths": [], - "custom_fields": {}, - "description": "Split text into chunks based on specified criteria.", - "display_name": "Split Text", - "documentation": "", - "edited": false, - "field_order": [ - "data_inputs", - "chunk_overlap", - "chunk_size", - "separator" - ], - "frozen": false, - "icon": "scissors-line-dashed", - "output_types": [], - "outputs": [ - { - "cache": true, - "display_name": "Chunks", - "hidden": false, - "method": "split_text", - "name": "chunks", - "selected": "Data", - "types": [ - "Data" - ], - "value": "__UNDEFINED__" - } - ], - "pinned": false, - "template": { - "_type": "Component", - "chunk_overlap": { - "advanced": false, - "display_name": "Chunk Overlap", - "dynamic": false, - "info": "Number of characters to overlap between chunks.", - "list": false, - "name": "chunk_overlap", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 200 - }, - "chunk_size": { - "advanced": false, - "display_name": "Chunk Size", - "dynamic": false, - "info": "The maximum number of characters in each chunk.", - "list": false, - "name": "chunk_size", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "int", - "value": 1000 - }, - "code": { - "advanced": true, - "dynamic": true, - "fileTypes": [], - "file_path": "", - "info": "", - "list": false, - "load_from_db": false, - "multiline": true, - "name": "code", - "password": false, - "placeholder": "", - "required": true, - "show": true, - "title_case": false, - "type": "code", - "value": "from typing import List\n\nfrom langchain_text_splitters import CharacterTextSplitter\n\nfrom langflow.custom import Component\nfrom langflow.io import HandleInput, IntInput, MessageTextInput, Output\nfrom langflow.schema import Data\nfrom langflow.utils.util import unescape_string\n\n\nclass SplitTextComponent(Component):\n display_name: str = \"Split Text\"\n description: str = \"Split text into chunks based on specified criteria.\"\n icon = \"scissors-line-dashed\"\n\n inputs = [\n HandleInput(\n name=\"data_inputs\",\n display_name=\"Data Inputs\",\n info=\"The data to split.\",\n input_types=[\"Data\"],\n is_list=True,\n ),\n IntInput(\n name=\"chunk_overlap\",\n display_name=\"Chunk Overlap\",\n info=\"Number of characters to overlap between chunks.\",\n value=200,\n ),\n IntInput(\n name=\"chunk_size\",\n display_name=\"Chunk Size\",\n info=\"The maximum number of characters in each chunk.\",\n value=1000,\n ),\n MessageTextInput(\n name=\"separator\",\n display_name=\"Separator\",\n info=\"The character to split on. Defaults to newline.\",\n value=\"\\n\",\n ),\n ]\n\n outputs = [\n Output(display_name=\"Chunks\", name=\"chunks\", method=\"split_text\"),\n ]\n\n def _docs_to_data(self, docs):\n data = []\n for doc in docs:\n data.append(Data(text=doc.page_content, data=doc.metadata))\n return data\n\n def split_text(self) -> List[Data]:\n separator = unescape_string(self.separator)\n\n documents = []\n for _input in self.data_inputs:\n if isinstance(_input, Data):\n documents.append(_input.to_lc_document())\n\n splitter = CharacterTextSplitter(\n chunk_overlap=self.chunk_overlap,\n chunk_size=self.chunk_size,\n separator=separator,\n )\n docs = splitter.split_documents(documents)\n data = self._docs_to_data(docs)\n self.status = data\n return data\n" - }, - "data_inputs": { - "advanced": false, - "display_name": "Data Inputs", - "dynamic": false, - "info": "The data to split.", - "input_types": [ - "Data" - ], - "list": true, - "name": "data_inputs", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_metadata": true, - "type": "other", - "value": "" - }, - "separator": { - "advanced": false, - "display_name": "Separator", - "dynamic": false, - "info": "The character to split on. Defaults to newline.", - "input_types": [ - "Message" - ], - "list": false, - "load_from_db": false, - "name": "separator", - "placeholder": "", - "required": false, - "show": true, - "title_case": false, - "trace_as_input": true, - "trace_as_metadata": true, - "type": "str", - "value": "\n" - } + ], + "edges": [ + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "ChatInput", + "id": "ChatInput-8ZRjI", + "name": "message", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "search_input", + "id": "AstraDB-p6135", + "inputTypes": [ + "Message", + "str" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ChatInput-8ZRjI{œdataTypeœ:œChatInputœ,œidœ:œChatInput-8ZRjIœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-AstraDB-p6135{œfieldNameœ:œsearch_inputœ,œidœ:œAstraDB-p6135œ,œinputTypesœ:[œMessageœ,œstrœ],œtypeœ:œstrœ}", + "selected": false, + "source": "ChatInput-8ZRjI", + "sourceHandle": "{œdataTypeœ:œChatInputœ,œidœ:œChatInput-8ZRjIœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}", + "target": "AstraDB-p6135", + "targetHandle": "{œfieldNameœ:œsearch_inputœ,œidœ:œAstraDB-p6135œ,œinputTypesœ:[œMessageœ,œstrœ],œtypeœ:œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIEmbeddings", + "id": "OpenAIEmbeddings-hNOwh", + "name": "embeddings", + "output_types": [ + "Embeddings" + ] + }, + "targetHandle": { + "fieldName": "embedding", + "id": "AstraDB-p6135", + "inputTypes": [ + "Embeddings" + ], + "type": "other" + } + }, + "id": "reactflow__edge-OpenAIEmbeddings-hNOwh{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-hNOwhœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}-AstraDB-p6135{œfieldNameœ:œembeddingœ,œidœ:œAstraDB-p6135œ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}", + "selected": false, + "source": "OpenAIEmbeddings-hNOwh", + "sourceHandle": "{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-hNOwhœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}", + "target": "AstraDB-p6135", + "targetHandle": "{œfieldNameœ:œembeddingœ,œidœ:œAstraDB-p6135œ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "AstraDB", + "id": "AstraDB-p6135", + "name": "search_results", + "output_types": [ + "Data" + ] + }, + "targetHandle": { + "fieldName": "data", + "id": "ParseData-9DrmC", + "inputTypes": [ + "Data" + ], + "type": "other" + } + }, + "id": "reactflow__edge-AstraDB-p6135{œdataTypeœ:œAstraDBœ,œidœ:œAstraDB-p6135œ,œnameœ:œsearch_resultsœ,œoutput_typesœ:[œDataœ]}-ParseData-9DrmC{œfieldNameœ:œdataœ,œidœ:œParseData-9DrmCœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", + "selected": false, + "source": "AstraDB-p6135", + "sourceHandle": "{œdataTypeœ:œAstraDBœ,œidœ:œAstraDB-p6135œ,œnameœ:œsearch_resultsœ,œoutput_typesœ:[œDataœ]}", + "target": "ParseData-9DrmC", + "targetHandle": "{œfieldNameœ:œdataœ,œidœ:œParseData-9DrmCœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "ChatInput", + "id": "ChatInput-8ZRjI", + "name": "message", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "question", + "id": "Prompt-EEXgw", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ChatInput-8ZRjI{œdataTypeœ:œChatInputœ,œidœ:œChatInput-8ZRjIœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}-Prompt-EEXgw{œfieldNameœ:œquestionœ,œidœ:œPrompt-EEXgwœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ChatInput-8ZRjI", + "sourceHandle": "{œdataTypeœ:œChatInputœ,œidœ:œChatInput-8ZRjIœ,œnameœ:œmessageœ,œoutput_typesœ:[œMessageœ]}", + "target": "Prompt-EEXgw", + "targetHandle": "{œfieldNameœ:œquestionœ,œidœ:œPrompt-EEXgwœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "File", + "id": "File-p2YBf", + "name": "data", + "output_types": [ + "Data" + ] + }, + "targetHandle": { + "fieldName": "data_inputs", + "id": "SplitText-qI0jS", + "inputTypes": [ + "Data" + ], + "type": "other" + } + }, + "id": "reactflow__edge-File-p2YBf{œdataTypeœ:œFileœ,œidœ:œFile-p2YBfœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}-SplitText-qI0jS{œfieldNameœ:œdata_inputsœ,œidœ:œSplitText-qI0jSœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", + "source": "File-p2YBf", + "sourceHandle": "{œdataTypeœ:œFileœ,œidœ:œFile-p2YBfœ,œnameœ:œdataœ,œoutput_typesœ:[œDataœ]}", + "target": "SplitText-qI0jS", + "targetHandle": "{œfieldNameœ:œdata_inputsœ,œidœ:œSplitText-qI0jSœ,œinputTypesœ:[œDataœ],œtypeœ:œotherœ}", + "selected": false + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "ParseData", + "id": "ParseData-9DrmC", + "name": "text", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "context", + "id": "Prompt-EEXgw", + "inputTypes": [ + "Message", + "Text" + ], + "type": "str" + } + }, + "id": "reactflow__edge-ParseData-9DrmC{œdataTypeœ:œParseDataœ,œidœ:œParseData-9DrmCœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}-Prompt-EEXgw{œfieldNameœ:œcontextœ,œidœ:œPrompt-EEXgwœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}", + "source": "ParseData-9DrmC", + "sourceHandle": "{œdataTypeœ:œParseDataœ,œidœ:œParseData-9DrmCœ,œnameœ:œtextœ,œoutput_typesœ:[œMessageœ]}", + "target": "Prompt-EEXgw", + "targetHandle": "{œfieldNameœ:œcontextœ,œidœ:œPrompt-EEXgwœ,œinputTypesœ:[œMessageœ,œTextœ],œtypeœ:œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "Prompt", + "id": "Prompt-EEXgw", + "name": "prompt", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "OpenAIModel-euVNy", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-Prompt-EEXgw{œdataTypeœ:œPromptœ,œidœ:œPrompt-EEXgwœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}-OpenAIModel-euVNy{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-euVNyœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "Prompt-EEXgw", + "sourceHandle": "{œdataTypeœ:œPromptœ,œidœ:œPrompt-EEXgwœ,œnameœ:œpromptœ,œoutput_typesœ:[œMessageœ]}", + "target": "OpenAIModel-euVNy", + "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-euVNyœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "OpenAIModel", + "id": "OpenAIModel-euVNy", + "name": "text_output", + "output_types": [ + "Message" + ] + }, + "targetHandle": { + "fieldName": "input_value", + "id": "ChatOutput-1eddV", + "inputTypes": [ + "Message" + ], + "type": "str" + } + }, + "id": "reactflow__edge-OpenAIModel-euVNy{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-euVNyœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}-ChatOutput-1eddV{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-1eddVœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}", + "source": "OpenAIModel-euVNy", + "sourceHandle": "{œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-euVNyœ,œnameœ:œtext_outputœ,œoutput_typesœ:[œMessageœ]}", + "target": "ChatOutput-1eddV", + "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-1eddVœ,œinputTypesœ:[œMessageœ],œtypeœ:œstrœ}" + }, + { + "className": "", + "data": { + "sourceHandle": { + "dataType": "SplitText", + "id": "SplitText-qI0jS", + "name": "chunks", + "output_types": [ + "Data" + ] + }, + "targetHandle": { + "fieldName": "vector_store_inputs", + "id": "AstraDB-AX2Xz", + "inputTypes": [ + "Document", + "Data" + ], + "type": "other" + } + }, + "source": "SplitText-qI0jS", + "sourceHandle": "{œdataTypeœ:œSplitTextœ,œidœ:œSplitText-qI0jSœ,œnameœ:œchunksœ,œoutput_typesœ:[œDataœ]}", + "target": "AstraDB-AX2Xz", + "targetHandle": "{œfieldNameœ:œvector_store_inputsœ,œidœ:œAstraDB-AX2Xzœ,œinputTypesœ:[œDocumentœ,œDataœ],œtypeœ:œotherœ}", + "id": "reactflow__edge-SplitText-qI0jS{œdataTypeœ:œSplitTextœ,œidœ:œSplitText-qI0jSœ,œnameœ:œchunksœ,œoutput_typesœ:[œDataœ]}-AstraDB-AX2Xz{œfieldNameœ:œvector_store_inputsœ,œidœ:œAstraDB-AX2Xzœ,œinputTypesœ:[œDocumentœ,œDataœ],œtypeœ:œotherœ}", + "selected": false + }, + { + "source": "OpenAIEmbeddings-PQc6x", + "sourceHandle": "{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-PQc6xœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}", + "target": "AstraDB-AX2Xz", + "targetHandle": "{œfieldNameœ:œembeddingœ,œidœ:œAstraDB-AX2Xzœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}", + "data": { + "targetHandle": { + "fieldName": "embedding", + "id": "AstraDB-AX2Xz", + "inputTypes": [ + "Embeddings" + ], + "type": "other" + }, + "sourceHandle": { + "dataType": "OpenAIEmbeddings", + "id": "OpenAIEmbeddings-PQc6x", + "name": "embeddings", + "output_types": [ + "Embeddings" + ] + } + }, + "id": "reactflow__edge-OpenAIEmbeddings-PQc6x{œdataTypeœ:œOpenAIEmbeddingsœ,œidœ:œOpenAIEmbeddings-PQc6xœ,œnameœ:œembeddingsœ,œoutput_typesœ:[œEmbeddingsœ]}-AstraDB-AX2Xz{œfieldNameœ:œembeddingœ,œidœ:œAstraDB-AX2Xzœ,œinputTypesœ:[œEmbeddingsœ],œtypeœ:œotherœ}", + "selected": false } - }, - "type": "SplitText" - }, - "dragging": false, - "height": 557, - "id": "SplitText-ARuL2", - "position": { - "x": 21.318397393309283, - "y": 273.27771123167287 - }, - "positionAbsolute": { - "x": 21.318397393309283, - "y": 273.27771123167287 - }, - "selected": false, - "type": "genericNode", - "width": 384 - } - ], - "viewport": { - "x": 194.05113865007206, - "y": 162.32064169887877, - "zoom": 0.2522219260543123 - } - }, - "description": "Visit https://docs.langflow.org/tutorials/rag-with-astradb for a detailed guide of this project.\nThis project give you both Ingestion and RAG in a single file. You'll need to visit https://astra.datastax.com/ to create an Astra DB instance, your Token and grab an API Endpoint.\nRunning this project requires you to add a file in the Files component, then define a Collection Name and click on the Play icon on the Astra DB component. \n\nAfter the ingestion ends you are ready to click on the Run button at the lower left corner and start asking questions about your data.", - "endpoint_name": null, - "id": "7f5d5057-2371-4796-a398-f0236b963d1f", - "is_component": false, - "last_tested_version": "1.0.0rc1", - "name": "Vector Store RAG" + ], + "viewport": { + "x": -173.2239134973895, + "y": 90.45548562382544, + "zoom": 0.32281188532359306 + } + }, + "description": "Visit https://docs.langflow.org/tutorials/rag-with-astradb for a detailed guide of this project.\nThis project give you both Ingestion and RAG in a single file. You'll need to visit https://astra.datastax.com/ to create an Astra DB instance, your Token and grab an API Endpoint.\nRunning this project requires you to add a file in the Files component, then define a Collection Name and click on the Play icon on the Astra DB component. \n\nAfter the ingestion ends you are ready to click on the Run button at the lower left corner and start asking questions about your data.", + "name": "Vector Store RAG", + "last_tested_version": "1.0.0rc1", + "endpoint_name": null, + "is_component": false } \ No newline at end of file From 23bbaf99c8f44acdcdc0198c7fa8a5e6bd9a21f7 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Fri, 29 Mar 2024 14:19:33 -0300 Subject: [PATCH 083/229] Fix unique constraints for id column (#1584) Fix unique constraints for id column (#1583) * Fix unique constraints for id column * Update version in pyproject.toml --- poetry.lock | 26 ++++++++++++++++++++++++++ 1 file changed, 26 insertions(+) diff --git a/poetry.lock b/poetry.lock index 7407c1a3d..df8510421 100644 --- a/poetry.lock +++ b/poetry.lock @@ -3176,6 +3176,21 @@ files = [ grpcio = ">=1.62.2" protobuf = ">=4.21.6" +[[package]] +name = "grpcio-health-checking" +version = "1.62.1" +description = "Standard Health Checking Service for gRPC" +optional = false +python-versions = ">=3.6" +files = [ + {file = "grpcio-health-checking-1.62.1.tar.gz", hash = "sha256:9e56180a941b1d32a077d7491e0611d0483c396358afd5349bf00152612e4583"}, + {file = "grpcio_health_checking-1.62.1-py3-none-any.whl", hash = "sha256:9ce761c09fc383e7aa2f7e6c0b0b65d5a1157c1b98d1f5871f7c38aca47d49b9"}, +] + +[package.dependencies] +grpcio = ">=1.62.1" +protobuf = ">=4.21.6" + [[package]] name = "grpcio-status" version = "1.62.2" @@ -9842,6 +9857,17 @@ files = [ {file = "validators-0.28.3.tar.gz", hash = "sha256:c6c79840bcde9ba77b19f6218f7738188115e27830cbaff43264bc4ed24c429d"}, ] +[package.extras] +docs-offline = ["myst-parser (>=2.0.0)", "pypandoc-binary (>=1.11)", "sphinx (>=7.1.1)"] +docs-online = ["mkdocs (>=1.5.2)", "mkdocs-git-revision-date-localized-plugin (>=1.2.0)", "mkdocs-material (>=9.2.6)", "mkdocstrings[python] (>=0.22.0)", "pyaml (>=23.7.0)"] +hooks = ["pre-commit (>=3.3.3)"] +package = ["build (>=1.0.0)", "twine (>=4.0.2)"] +runner = ["tox (>=4.11.1)"] +sast = ["bandit[toml] (>=1.7.5)"] +testing = ["pytest (>=7.4.0)"] +tooling = ["black (>=23.7.0)", "pyright (>=1.1.325)", "ruff (>=0.0.287)"] +tooling-extras = ["pyaml (>=23.7.0)", "pypandoc-binary (>=1.11)", "pytest (>=7.4.0)"] + [[package]] name = "vine" version = "5.1.0" From 4b72a7caa8c7bd6564107090cd949f56cc2d9fe0 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 22 Apr 2024 19:58:15 -0300 Subject: [PATCH 084/229] Fix unique constraints for id column and update API key creation (#1764) * Update .gitignore to ignore additional files and directories * Add migration to fix column types * Bump version to 0.6.17 in pyproject.toml --- poetry.lock | 8 +- .../versions/bc804d8e7a18_fix_types.py | 91 +++++++++++++++++++ 2 files changed, 95 insertions(+), 4 deletions(-) create mode 100644 src/backend/base/langflow/alembic/versions/bc804d8e7a18_fix_types.py diff --git a/poetry.lock b/poetry.lock index df8510421..c0229252b 100644 --- a/poetry.lock +++ b/poetry.lock @@ -3178,17 +3178,17 @@ protobuf = ">=4.21.6" [[package]] name = "grpcio-health-checking" -version = "1.62.1" +version = "1.62.2" description = "Standard Health Checking Service for gRPC" optional = false python-versions = ">=3.6" files = [ - {file = "grpcio-health-checking-1.62.1.tar.gz", hash = "sha256:9e56180a941b1d32a077d7491e0611d0483c396358afd5349bf00152612e4583"}, - {file = "grpcio_health_checking-1.62.1-py3-none-any.whl", hash = "sha256:9ce761c09fc383e7aa2f7e6c0b0b65d5a1157c1b98d1f5871f7c38aca47d49b9"}, + {file = "grpcio-health-checking-1.62.2.tar.gz", hash = "sha256:a44d1ea1e1510b5c62265dada04d86621bb1491d75de987713c9c0ea005c10a8"}, + {file = "grpcio_health_checking-1.62.2-py3-none-any.whl", hash = "sha256:f0d77e02457aa00e98ce12c741dca6df7e34dbcc3859681c4a473dc589288e56"}, ] [package.dependencies] -grpcio = ">=1.62.1" +grpcio = ">=1.62.2" protobuf = ">=4.21.6" [[package]] diff --git a/src/backend/base/langflow/alembic/versions/bc804d8e7a18_fix_types.py b/src/backend/base/langflow/alembic/versions/bc804d8e7a18_fix_types.py new file mode 100644 index 000000000..1b29b088f --- /dev/null +++ b/src/backend/base/langflow/alembic/versions/bc804d8e7a18_fix_types.py @@ -0,0 +1,91 @@ +"""Fix types + +Revision ID: bc804d8e7a18 +Revises: bc2f01c40e4a +Create Date: 2024-04-22 19:33:02.242116 + +""" +from typing import Sequence, Union + +import sqlalchemy as sa +from alembic import op +from sqlalchemy.dialects import postgresql +from sqlalchemy.engine.reflection import Inspector + +# revision identifiers, used by Alembic. +revision: str = 'bc804d8e7a18' +down_revision: Union[str, None] = 'bc2f01c40e4a' +branch_labels: Union[str, Sequence[str], None] = None +depends_on: Union[str, Sequence[str], None] = None + + +def upgrade() -> None: + conn = op.get_bind() + inspector = Inspector.from_engine(conn) # type: ignore + # ### commands auto generated by Alembic - please adjust! ### + table_names = inspector.get_table_names() + if "apikey" in table_names: + column_names = [col["name"] for col in inspector.get_columns("apikey")] + with op.batch_alter_table('apikey', schema=None) as batch_op: + if "created_at" in column_names: + batch_op.alter_column('created_at', + existing_type=postgresql.TIMESTAMP(), + type_=sa.DateTime(timezone=True), + nullable=True) + if "last_used_at" in column_names: + batch_op.alter_column('last_used_at', + existing_type=postgresql.TIMESTAMP(), + type_=sa.DateTime(timezone=True), + existing_nullable=True) + + if "credential" in table_names: + column_names = [col["name"] for col in inspector.get_columns("credential")] + with op.batch_alter_table('credential', schema=None) as batch_op: + if "created_at" in column_names: + batch_op.alter_column('created_at', + existing_type=postgresql.TIMESTAMP(), + type_=sa.DateTime(timezone=True), + nullable=True) + if "updated_at" in column_names: + batch_op.alter_column('updated_at', + existing_type=postgresql.TIMESTAMP(), + type_=sa.DateTime(timezone=True), + existing_nullable=True) + + # ### end Alembic commands ### + + +def downgrade() -> None: + conn = op.get_bind() + inspector = Inspector.from_engine(conn) # type: ignore + # ### commands auto generated by Alembic - please adjust! ### + table_names = inspector.get_table_names() + if "credential" in table_names: + column_names = [col["name"] for col in inspector.get_columns("credential")] + with op.batch_alter_table('credential', schema=None) as batch_op: + if "updated_at" in column_names: + batch_op.alter_column('updated_at', + existing_type=sa.DateTime(timezone=True), + type_=postgresql.TIMESTAMP(), + existing_nullable=True) + if "created_at" in column_names: + batch_op.alter_column('created_at', + existing_type=sa.DateTime(timezone=True), + type_=postgresql.TIMESTAMP(), + nullable=False) + + if "apikey" in table_names: + column_names = [col["name"] for col in inspector.get_columns("apikey")] + with op.batch_alter_table('apikey', schema=None) as batch_op: + if "last_used_at" in column_names: + batch_op.alter_column('last_used_at', + existing_type=sa.DateTime(timezone=True), + type_=postgresql.TIMESTAMP(), + existing_nullable=True) + if "created_at" in column_names: + batch_op.alter_column('created_at', + existing_type=sa.DateTime(timezone=True), + type_=postgresql.TIMESTAMP(), + nullable=False) + + # ### end Alembic commands ### From da63ee977e374ff4c40f636538be6e5c2d9dc52d Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 29 Apr 2024 15:41:26 -0300 Subject: [PATCH 085/229] Fix bugs and make improvements (#1794) * add ? to prevent bug when template has no value * Refactor determine_component_name function in utils.py to use file name * Bump version to 0.6.18 in pyproject.toml --------- Co-authored-by: anovazzi1 --- poetry.lock | 11 ----------- 1 file changed, 11 deletions(-) diff --git a/poetry.lock b/poetry.lock index c0229252b..174443c99 100644 --- a/poetry.lock +++ b/poetry.lock @@ -9857,17 +9857,6 @@ files = [ {file = "validators-0.28.3.tar.gz", hash = "sha256:c6c79840bcde9ba77b19f6218f7738188115e27830cbaff43264bc4ed24c429d"}, ] -[package.extras] -docs-offline = ["myst-parser (>=2.0.0)", "pypandoc-binary (>=1.11)", "sphinx (>=7.1.1)"] -docs-online = ["mkdocs (>=1.5.2)", "mkdocs-git-revision-date-localized-plugin (>=1.2.0)", "mkdocs-material (>=9.2.6)", "mkdocstrings[python] (>=0.22.0)", "pyaml (>=23.7.0)"] -hooks = ["pre-commit (>=3.3.3)"] -package = ["build (>=1.0.0)", "twine (>=4.0.2)"] -runner = ["tox (>=4.11.1)"] -sast = ["bandit[toml] (>=1.7.5)"] -testing = ["pytest (>=7.4.0)"] -tooling = ["black (>=23.7.0)", "pyright (>=1.1.325)", "ruff (>=0.0.287)"] -tooling-extras = ["pyaml (>=23.7.0)", "pypandoc-binary (>=1.11)", "pytest (>=7.4.0)"] - [[package]] name = "vine" version = "5.1.0" From b3b68c3a38f4c09b9421c457463523d3d810b4cb Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Tue, 7 May 2024 18:29:42 -0300 Subject: [PATCH 086/229] Fixes Pinecone implementation (#1856) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * ⬆️ (pyproject.toml): upgrade langchain-pinecone dependency to version 0.1.0 * 📝 (Pinecone.py): Update Pinecone component to use new DistanceStrategy enum for distance calculation and improve configuration options for Pinecone vector store creation. * ⬆️ (pyproject.toml): upgrade package version from 0.6.18 to 0.6.19 --- poetry.lock | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/poetry.lock b/poetry.lock index 174443c99..11fde07da 100644 --- a/poetry.lock +++ b/poetry.lock @@ -4443,6 +4443,22 @@ langchain-core = ">=0.1.40,<0.2.0" numpy = ">=1,<2" pinecone-client = ">=3.2.2,<4.0.0" +[[package]] +name = "langchain-pinecone" +version = "0.1.0" +description = "An integration package connecting Pinecone and LangChain" +optional = false +python-versions = "<3.13,>=3.8.1" +files = [ + {file = "langchain_pinecone-0.1.0-py3-none-any.whl", hash = "sha256:d957f27b1cceab425c3e8603c7a32533d4593ce8705242e78f6dc03aa71cf417"}, + {file = "langchain_pinecone-0.1.0.tar.gz", hash = "sha256:93f81e7c3926027cc6a87b001ee4d2e02a432a916709dbd395162b342bf84586"}, +] + +[package.dependencies] +langchain-core = ">=0.1.40,<0.2.0" +numpy = ">=1,<2" +pinecone-client = ">=3.2.2,<4.0.0" + [[package]] name = "langchain-text-splitters" version = "0.2.1" From 07cc7b31a1646fc7809a14840e3450598ca84016 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 10:03:06 -0300 Subject: [PATCH 087/229] chore: remove merge artifact --- .../versions/bc804d8e7a18_fix_types.py | 91 ------------------- 1 file changed, 91 deletions(-) delete mode 100644 src/backend/base/langflow/alembic/versions/bc804d8e7a18_fix_types.py diff --git a/src/backend/base/langflow/alembic/versions/bc804d8e7a18_fix_types.py b/src/backend/base/langflow/alembic/versions/bc804d8e7a18_fix_types.py deleted file mode 100644 index 1b29b088f..000000000 --- a/src/backend/base/langflow/alembic/versions/bc804d8e7a18_fix_types.py +++ /dev/null @@ -1,91 +0,0 @@ -"""Fix types - -Revision ID: bc804d8e7a18 -Revises: bc2f01c40e4a -Create Date: 2024-04-22 19:33:02.242116 - -""" -from typing import Sequence, Union - -import sqlalchemy as sa -from alembic import op -from sqlalchemy.dialects import postgresql -from sqlalchemy.engine.reflection import Inspector - -# revision identifiers, used by Alembic. -revision: str = 'bc804d8e7a18' -down_revision: Union[str, None] = 'bc2f01c40e4a' -branch_labels: Union[str, Sequence[str], None] = None -depends_on: Union[str, Sequence[str], None] = None - - -def upgrade() -> None: - conn = op.get_bind() - inspector = Inspector.from_engine(conn) # type: ignore - # ### commands auto generated by Alembic - please adjust! ### - table_names = inspector.get_table_names() - if "apikey" in table_names: - column_names = [col["name"] for col in inspector.get_columns("apikey")] - with op.batch_alter_table('apikey', schema=None) as batch_op: - if "created_at" in column_names: - batch_op.alter_column('created_at', - existing_type=postgresql.TIMESTAMP(), - type_=sa.DateTime(timezone=True), - nullable=True) - if "last_used_at" in column_names: - batch_op.alter_column('last_used_at', - existing_type=postgresql.TIMESTAMP(), - type_=sa.DateTime(timezone=True), - existing_nullable=True) - - if "credential" in table_names: - column_names = [col["name"] for col in inspector.get_columns("credential")] - with op.batch_alter_table('credential', schema=None) as batch_op: - if "created_at" in column_names: - batch_op.alter_column('created_at', - existing_type=postgresql.TIMESTAMP(), - type_=sa.DateTime(timezone=True), - nullable=True) - if "updated_at" in column_names: - batch_op.alter_column('updated_at', - existing_type=postgresql.TIMESTAMP(), - type_=sa.DateTime(timezone=True), - existing_nullable=True) - - # ### end Alembic commands ### - - -def downgrade() -> None: - conn = op.get_bind() - inspector = Inspector.from_engine(conn) # type: ignore - # ### commands auto generated by Alembic - please adjust! ### - table_names = inspector.get_table_names() - if "credential" in table_names: - column_names = [col["name"] for col in inspector.get_columns("credential")] - with op.batch_alter_table('credential', schema=None) as batch_op: - if "updated_at" in column_names: - batch_op.alter_column('updated_at', - existing_type=sa.DateTime(timezone=True), - type_=postgresql.TIMESTAMP(), - existing_nullable=True) - if "created_at" in column_names: - batch_op.alter_column('created_at', - existing_type=sa.DateTime(timezone=True), - type_=postgresql.TIMESTAMP(), - nullable=False) - - if "apikey" in table_names: - column_names = [col["name"] for col in inspector.get_columns("apikey")] - with op.batch_alter_table('apikey', schema=None) as batch_op: - if "last_used_at" in column_names: - batch_op.alter_column('last_used_at', - existing_type=sa.DateTime(timezone=True), - type_=postgresql.TIMESTAMP(), - existing_nullable=True) - if "created_at" in column_names: - batch_op.alter_column('created_at', - existing_type=sa.DateTime(timezone=True), - type_=postgresql.TIMESTAMP(), - nullable=False) - - # ### end Alembic commands ### From a539c90c315df45ff00a9a010b86f6000ddc4f19 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 10:10:29 -0300 Subject: [PATCH 088/229] chore: fix types in Alembic migration script --- .../versions/bc804d8e7a18_fix_types.py | 91 ------------------- 1 file changed, 91 deletions(-) delete mode 100644 src/backend/base/langflow/alembic/versions/bc804d8e7a18_fix_types.py diff --git a/src/backend/base/langflow/alembic/versions/bc804d8e7a18_fix_types.py b/src/backend/base/langflow/alembic/versions/bc804d8e7a18_fix_types.py deleted file mode 100644 index 1b29b088f..000000000 --- a/src/backend/base/langflow/alembic/versions/bc804d8e7a18_fix_types.py +++ /dev/null @@ -1,91 +0,0 @@ -"""Fix types - -Revision ID: bc804d8e7a18 -Revises: bc2f01c40e4a -Create Date: 2024-04-22 19:33:02.242116 - -""" -from typing import Sequence, Union - -import sqlalchemy as sa -from alembic import op -from sqlalchemy.dialects import postgresql -from sqlalchemy.engine.reflection import Inspector - -# revision identifiers, used by Alembic. -revision: str = 'bc804d8e7a18' -down_revision: Union[str, None] = 'bc2f01c40e4a' -branch_labels: Union[str, Sequence[str], None] = None -depends_on: Union[str, Sequence[str], None] = None - - -def upgrade() -> None: - conn = op.get_bind() - inspector = Inspector.from_engine(conn) # type: ignore - # ### commands auto generated by Alembic - please adjust! ### - table_names = inspector.get_table_names() - if "apikey" in table_names: - column_names = [col["name"] for col in inspector.get_columns("apikey")] - with op.batch_alter_table('apikey', schema=None) as batch_op: - if "created_at" in column_names: - batch_op.alter_column('created_at', - existing_type=postgresql.TIMESTAMP(), - type_=sa.DateTime(timezone=True), - nullable=True) - if "last_used_at" in column_names: - batch_op.alter_column('last_used_at', - existing_type=postgresql.TIMESTAMP(), - type_=sa.DateTime(timezone=True), - existing_nullable=True) - - if "credential" in table_names: - column_names = [col["name"] for col in inspector.get_columns("credential")] - with op.batch_alter_table('credential', schema=None) as batch_op: - if "created_at" in column_names: - batch_op.alter_column('created_at', - existing_type=postgresql.TIMESTAMP(), - type_=sa.DateTime(timezone=True), - nullable=True) - if "updated_at" in column_names: - batch_op.alter_column('updated_at', - existing_type=postgresql.TIMESTAMP(), - type_=sa.DateTime(timezone=True), - existing_nullable=True) - - # ### end Alembic commands ### - - -def downgrade() -> None: - conn = op.get_bind() - inspector = Inspector.from_engine(conn) # type: ignore - # ### commands auto generated by Alembic - please adjust! ### - table_names = inspector.get_table_names() - if "credential" in table_names: - column_names = [col["name"] for col in inspector.get_columns("credential")] - with op.batch_alter_table('credential', schema=None) as batch_op: - if "updated_at" in column_names: - batch_op.alter_column('updated_at', - existing_type=sa.DateTime(timezone=True), - type_=postgresql.TIMESTAMP(), - existing_nullable=True) - if "created_at" in column_names: - batch_op.alter_column('created_at', - existing_type=sa.DateTime(timezone=True), - type_=postgresql.TIMESTAMP(), - nullable=False) - - if "apikey" in table_names: - column_names = [col["name"] for col in inspector.get_columns("apikey")] - with op.batch_alter_table('apikey', schema=None) as batch_op: - if "last_used_at" in column_names: - batch_op.alter_column('last_used_at', - existing_type=sa.DateTime(timezone=True), - type_=postgresql.TIMESTAMP(), - existing_nullable=True) - if "created_at" in column_names: - batch_op.alter_column('created_at', - existing_type=sa.DateTime(timezone=True), - type_=postgresql.TIMESTAMP(), - nullable=False) - - # ### end Alembic commands ### From 24d9e86885b877ea3e9d03cbc50b963765489721 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 10:19:17 -0300 Subject: [PATCH 089/229] chore: update package versions in pyproject.toml files --- poetry.lock | 140 +++++++------------------------- pyproject.toml | 2 +- src/backend/base/pyproject.toml | 2 +- 3 files changed, 31 insertions(+), 113 deletions(-) diff --git a/poetry.lock b/poetry.lock index 6019df932..c07ae2e94 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1952,41 +1952,37 @@ tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipyth [[package]] name = "faiss-cpu" -version = "1.8.0" +version = "1.8.0.post1" description = "A library for efficient similarity search and clustering of dense vectors." optional = false python-versions = ">=3.8" files = [ - 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To get help in the Langflow CLI: From 1f0532a995439a0ad61aee4abaac9e33c4aba8cc Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Mon, 24 Jun 2024 10:49:11 -0300 Subject: [PATCH 092/229] Fixed link errors --- docs/docs/migration/migrating-to-one-point-zero.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/migration/migrating-to-one-point-zero.mdx b/docs/docs/migration/migrating-to-one-point-zero.mdx index 78ae6b608..2fd1fe935 100644 --- a/docs/docs/migration/migrating-to-one-point-zero.mdx +++ b/docs/docs/migration/migrating-to-one-point-zero.mdx @@ -102,7 +102,7 @@ You can now connect Output components to any other component (that has a Text ou Langflow 1.0 allows you to rename and edit the description of each component, making it easier to understand and interact with the flow. Learn how to customize your component names and descriptions for improved clarity. -[Learn more about Component Descriptions](../getting-started/workspace#component-parameters) +[Learn more about Component Descriptions](../getting-started/workspace#flows--components) ## Passing Tweaks and Inputs in the API From 5ce681355dbde30b104388c14e60d2318c02d9ee Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Mon, 24 Jun 2024 11:14:39 -0300 Subject: [PATCH 093/229] Added new text to the page A New Chapter for Langflow --- .../docs/whats-new/a-new-chapter-langflow.mdx | 208 +++++++++++++----- docs/static/img/component-freeze.jpeg | Bin 0 -> 164065 bytes docs/static/img/custom-endpoint.webp | Bin 0 -> 31882 bytes docs/static/img/flow-composition.webp | Bin 0 -> 85622 bytes docs/static/img/logs-monitoring.webp | Bin 0 -> 36754 bytes docs/static/img/multi-modal.png | Bin 0 -> 1404373 bytes docs/static/img/multiple_outputs.webp | Bin 0 -> 35232 bytes docs/static/img/output-preview.gif | Bin 0 -> 11536172 bytes docs/static/img/playground.png | Bin 0 -> 582803 bytes 9 files changed, 148 insertions(+), 60 deletions(-) create mode 100644 docs/static/img/component-freeze.jpeg create mode 100644 docs/static/img/custom-endpoint.webp create mode 100644 docs/static/img/flow-composition.webp create mode 100644 docs/static/img/logs-monitoring.webp create mode 100644 docs/static/img/multi-modal.png create mode 100644 docs/static/img/multiple_outputs.webp create mode 100644 docs/static/img/output-preview.gif create mode 100644 docs/static/img/playground.png diff --git a/docs/docs/whats-new/a-new-chapter-langflow.mdx b/docs/docs/whats-new/a-new-chapter-langflow.mdx index ccdaf8426..c44476ea1 100644 --- a/docs/docs/whats-new/a-new-chapter-langflow.mdx +++ b/docs/docs/whats-new/a-new-chapter-langflow.mdx @@ -1,96 +1,184 @@ +import ZoomableImage from "/src/theme/ZoomableImage.js"; + # A new chapter for Langflow -# First things first +## First things first -**Thank you all for being part of the Langflow community**. The journey so far has been amazing and we are happy to have you with us. +**Thank you all for being part of the Langflow community**. The journey so far has been amazing, and we are thrilled to have you with us. -We have some exciting news to share with you. Langflow is changing, and we want to tell you all about it. +We have some exciting news to share with you. Langflow is evolving, and we want to tell you all about it! -## Where have we been? +## What's new? -We spent the last few months working on a new version of Langflow. We wanted to make it more powerful, more flexible, and easier to use. -We're moving from version 0.6 straight to 1.0 (preview). This is a big change, and we want to explain why we're doing it and what it means for you. +In the past year, we learned a lot from the community and our users. We saw the potential of Langflow and the need for a visual, interactive platform for building conversational AI applications (and beyond). You thought us the importance of a platform that is easy to use, but also powerful and controllable, and that made clear to us how Langflow's transparency could be improved. -## Why? +Below are some of the new features we included to make that happen! -In the past year, we learned a lot from the community and our users. We saw the potential of Langflow and the need for a more powerful and flexible tool for building conversational AI applications (and beyond). -We realized that Langflow was hiding things from you that would really help you build better and more complex conversational AI applications. So we decided to make a big change. +### Same Component, Multiple Outputs -## The only way to go is forward +Components can now have more than a single output, allowing for unique flexibility in creating complex flows. The game-changer is output routing — it allows for so many new capabilities it’s almost silly to describe! -From all the people we talked to, we learned that the most important thing for (most of) them is to have a tool that is easy to use, but also powerful and controllable. They also told us that Langflow's transparency could be improved. +1. Branch to one or more subsequent components; +2. Apply logic operations like if/else and exploit decision-making; +3. Create classification models that choose between paths; +4. Enable the development of agent architectures from scratch; +5. Build an orchestrator that routes between agents. -In those points, we saw an opportunity to make Langflow much more powerful and flexible, while also making it easier to use and understand. + -One key change you'll notice is that projects now require you to define Inputs and Outputs. -This is a big change, but it's also a big improvement. -It allows you to define the structure of your conversation and the data that flows through it. -This makes it easier to understand and control your conversation. +### Flow + Composition -This change comes with a new way of visualizing your projects. Before 1.0 you would connect Components to ultimately build one final Component that was processed behind the scenes. -Now, each step of the process is defined by you, is visible on the workspace, and can be monitored and controlled by you. This makes it so that Composition is now just another way of building in Langflow. **Now data flows through your project more transparently**. +One key change you'll notice is that projects now require you to define **Inputs** and **Outputs**. They allow you to define the structure of your conversation and how data flows through it. This change comes with a new way of visualizing your projects. -The caveat is existing projects may need some new Components to get them back to their full functionality. -[We've made this as easy as possible](../migration/compatibility), and there will be improvements to it as we get feedback in our Discord server and on GitHub. +Before 1.0 you would connect components to ultimately build one final component that was processed behind the scenes. Now, each step of the process is defined by you, is visible on the workspace, and can be monitored and controlled. -## Custom Interactions +This makes it so that composition is now just **another way** of building in Langflow and **data flows through your project more transparently**. This means that the easy stuff is *really* easy and the complex parts are still possible! -The moment we decided to make this change, we saw the potential to make Langflow even more yours. -By having a clear definition of Inputs and Outputs, we could build the experience around that which led us to create the **Playground**. +- **Flow:** Data is processed by one component and then passed to the next component in line for immediate execution. +- **Composition**: Allows components to not only forward data but also share states for modular building. -When building a project testing and debugging is crucial. The Playground is a tool that changes dynamically based on the Inputs and Outputs you defined in your project. +For example, a flow can sequentially process text, and after a few steps, trigger an agent. It can access functions that wait to be called or to respond. This blend of flow and composition brings an unprecedented level of flexibility and control to data workflows in LLM-based apps and agents that use multiple models and APIs working together to achieve tasks. -For example, let's say you are building a simple RAG application. Generally, you have an Input, some references that come from a Vector Store Search, a Prompt and the answer. -Now, you could plug the output of your Prompt into a [Text Output](../components/inputs-and-outputs), rename that to "Prompt Result" and see the output of your Prompt in the Playground. + -{/* Add image here of the described above */} +### Memory Management -This is just one example of how the Playground can help you build and debug your projects. +Langflow 1.0 natively allows every chat message to be stored, and a single flow can have multiple memory sessions. This enables you to create multiple “memories” for agents to store and recall specific information as needed. -We have many planned features for the Playground, and we're excited to see how you use it and what you think of it. +You can edit and remove previous messages to inspect and validate a model’s response behavior. Control, explore, and manage conversation histories to get your models acting just right. -## An easier start + -The experience for the first-time user is also something we wanted to improve. +### Component Freeze 🥶 -Meet the new and improved **New Project** screen. It's now easier to start a new project, and you can choose from a list of starter projects to get you started. +Component output freezing is back in Langflow, and it’s cooler than ever! -{/* Add new project image */} +Once a component runs, you can now lock its previous output state to prevent it from re-running. -We wanted to create start projects that would help you learn about new features and also give you a head start on your projects. +Avoid spending extra tokens and remove repetition when output should be constant — plus it's great for debugging and prototyping! + + + +### Output Preview + +Each component now includes an output visualizer that opens a pop-up screen, allowing you to easily inspect and monitor transmissions between components. It provides instant feedback on your workflows, letting you see results as they are processed. 🔍 + + + +### Inputs and Outputs Handling + +Inputs and outputs finally make more sense to us, and hopefully to you too. + +We’re proposing Langflow-native types to keep things consistent, but not limited to use any Python type. For instance, a Chat Input component sends out what we call a Message object (text + metadata like date, time, and sender), but maybe you want to introduce external types from your favorite Python package? Go wild. Each native type will have their own visualization modes and will evolve according to new integrations added. + +### Custom Endpoint Name + +Now you can pick a custom name for your endpoint used to call your flow from the API. + + + +### Logs & Monitoring + +A new logs page has been added! Now, both component executions and message history from the chat can be inspected in an interactive table. This will make it easier to debug, inspect, and manage messages passing through components. + + + +### Folders 📁 + +We introduced folders on the home page to help categorize flows and components. Create, remove and edit them to keep your work organized. + +### Playground + +By having a clear definition of Inputs and Outputs, we could build the experience around that, which led us to create the Playground. When building a project, testing and debugging are crucial. The Playground is an interface that changes dynamically based on the Inputs and Outputs you defined in your project. + +For example, let's say you are building a simple RAG application. Generally, you have an Input, some references that come from a Vector Store Search, a Prompt, and the answer. Now, you could plug the output of your Prompt into a Text Output, rename that to "Prompt Result," and see the output of your Prompt in the Playground. We have many planned features for the Playground, and we're excited to see how you'll explore it! + +### Multi-Modal + +Langflow is now multi-modal! It can now handle images and more soon! + + + +We’ve also improved project organization, global variables and overall settings, added Python 3.12 compatibility, keyboard shortcuts and a lot of new and fun experimental components! + +## An Easier Start + +The experience for first-time users is something we wanted to improve. For that we created a couple of Starter Projects. It's now much easier to start a new project, and you can choose from a list of starter projects to get you going. For now, we have: -- **[Basic Prompting (Hello, World)](/starter-projects/basic-prompting)**: A simple flow that shows you how to use the Prompt Component and how to talk like a pirate. -- **[Vector Store RAG](/tutorials/rag-with-astradb)**: A flow that shows you how to ingest data into a Vector Store and then use it to run a RAG application. -- **[Memory Chatbot](/starter-projects/memory-chatbot)**: This one shows you how to create a simple chatbot that can remember things about the user. -- **[Document QA](/starter-projects/document-qa)**: This flow shows you how to build a simple flow that helps you get answers about a document. -- **[Blog Writer](/starter-projects/blog-writer)**: Shows you how you can expand on the Prompt variables and be creative about what inputs you add to it. +- **Basic Prompting (Hello, World)**: Learn the basics of a Prompt Component. +- **Vector Store RAG**: Ingest data into a Vector Store and then use it to run a RAG application. +- **Memory Chatbot**: Create a simple chatbot that can remember things about the user. +- **Document QA**: Build a simple flow that helps you get answers about a document. +- **Blog Writer**: Expand on the Prompt variables and be creative about what inputs you add to it. -As always, your feedback is invaluable, so please let us know what you think of the new starter projects and what you would like to see in the future. +Please let us know what other starter projects you would like to see in the future! -## Less is more +--- -We added many new Components to Langflow and updated some of the existing ones, and we will deprecate some of them. +## What's Next? -The idea is that Langflow has evolved, and we want to make sure that the Components you use are the best they can be. -Some of them don't work well with the others, and some of them are just not needed anymore. +Langflow has gone through a big change, and we are excited to see how you use it and what you think of it. We plan to add more types of Input and Output like Image and Audio, and we also plan to add more Components to help you build more complex projects. -We are working on a list of Components that will be deprecated. -In the preview stages of 1.0, we will have a smaller list of Components so that we make sure that the ones we have are the best they can be. -Regardless, community feedback is very important in this matter, so please let us know what you think of the new Components and which ones you miss. +We are excited to see the community embracing Langflow as their number one AI builder and eagerly wait to see what new inspiring projects will come out of this release! A big thanks to everyone who's supporting or being part of this community in any way. ✨ -We are aiming at having a more stable and reliable set of Components that helps you get quickly to useful results. -This also means that your contributions in the [Langflow Store](https://langflow.store) and throughout the community are more important than ever. +Sincerely, -## What's next? - -Langflow went through a big change, and we are excited to see how you use it and what you think of it. - -We plan to add more types of Input and Output like Image and Audio, and we also plan to add more Components to help you build more complex projects. - -We also have some experimental features like a State Management System (so cool!) and a new way of building Grouped Components that we are excited to show you. - -## Reach out - -One last time, we want to thank you for being part of the Langflow community. 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- -https://astra.datastax.com/signup?type=langflow # [![Langflow](./docs/static/img/hero.png)](https://www.langflow.org) From 75dbf1b39de938bef5324e0c8778eb06de47e2f8 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 11:39:17 -0300 Subject: [PATCH 098/229] chore: update package versions in pyproject.toml files --- pyproject.toml | 2 +- src/backend/base/pyproject.toml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index d42e6bb9a..9fd1d3e04 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langflow" -version = "1.0.0" +version = "1.0.1" description = "A Python package with a built-in web application" authors = ["Langflow "] maintainers = [ diff --git a/src/backend/base/pyproject.toml b/src/backend/base/pyproject.toml index 66d4cadcc..232bdd0aa 100644 --- a/src/backend/base/pyproject.toml +++ b/src/backend/base/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langflow-base" -version = "0.0.76" +version = "0.0.77" description = "A Python package with a built-in web application" authors = ["Langflow "] maintainers = [ From dcb2900ba8166ea2a8726cbf3bf71b24ed87d712 Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Mon, 24 Jun 2024 12:22:19 -0300 Subject: [PATCH 099/229] Removed margin from Notion category --- docs/sidebars.js | 1 + 1 file changed, 1 insertion(+) diff --git a/docs/sidebars.js b/docs/sidebars.js index 40f07baa0..56ff8cdcc 100644 --- a/docs/sidebars.js +++ b/docs/sidebars.js @@ -148,6 +148,7 @@ module.exports = { { type: "category", label: "Notion", + className: "margin-top-0", items: [ "integrations/notion/intro", "integrations/notion/setup", From 44e261129413872989a9214e4ed9290c0d86fb65 Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Mon, 24 Jun 2024 12:22:55 -0300 Subject: [PATCH 100/229] Removed margin top from second level categories --- docs/src/css/custom.css | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/docs/src/css/custom.css b/docs/src/css/custom.css index ee3962703..68d901e07 100644 --- a/docs/src/css/custom.css +++ b/docs/src/css/custom.css @@ -240,3 +240,7 @@ body { .ch-scrollycoding-step-content { min-height: 70px; } + +.theme-doc-sidebar-item-category.theme-doc-sidebar-item-category-level-2.menu__list-item:not(:first-child) { + margin-top: 0.25rem!important; +} \ No newline at end of file From 8e51ac6a41c695267c78e0d562ec545b767143ae Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Mon, 24 Jun 2024 12:23:03 -0300 Subject: [PATCH 101/229] Removed unused classname --- docs/sidebars.js | 1 - 1 file changed, 1 deletion(-) diff --git a/docs/sidebars.js b/docs/sidebars.js index 56ff8cdcc..40f07baa0 100644 --- a/docs/sidebars.js +++ b/docs/sidebars.js @@ -148,7 +148,6 @@ module.exports = { { type: "category", label: "Notion", - className: "margin-top-0", items: [ "integrations/notion/intro", "integrations/notion/setup", From c2d5a631dd1ff30e6eeee794890e6a013e4059bd Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Mon, 24 Jun 2024 12:23:28 -0300 Subject: [PATCH 102/229] Added and removed some outdated warnings --- .../{kubernetes.md => kubernetes.mdx} | 6 + .../docs/getting-started/install-langflow.mdx | 4 - .../possible-installation-issues.mdx | 4 - docs/docs/getting-started/quickstart.mdx | 4 - .../docs/getting-started/rag-with-astradb.mdx | 194 ------------------ docs/docs/getting-started/workspace.mdx | 4 - docs/docs/integrations/langsmith/intro.mdx | 4 - 7 files changed, 6 insertions(+), 214 deletions(-) rename docs/docs/deployment/{kubernetes.md => kubernetes.mdx} (98%) delete mode 100644 docs/docs/getting-started/rag-with-astradb.mdx diff --git a/docs/docs/deployment/kubernetes.md b/docs/docs/deployment/kubernetes.mdx similarity index 98% rename from docs/docs/deployment/kubernetes.md rename to docs/docs/deployment/kubernetes.mdx index 8648354e2..8896ab875 100644 --- a/docs/docs/deployment/kubernetes.md +++ b/docs/docs/deployment/kubernetes.mdx @@ -1,5 +1,11 @@ +import Admonition from "@theme/Admonition"; + # Kubernetes + +This page may contain outdated information. It will be updated as soon as possible. + + This guide will help you get LangFlow up and running in Kubernetes cluster, including the following steps: - Install [LangFlow as IDE](#langflow-ide) in a Kubernetes cluster (for development) diff --git a/docs/docs/getting-started/install-langflow.mdx b/docs/docs/getting-started/install-langflow.mdx index b94b3468c..58bd2fca0 100644 --- a/docs/docs/getting-started/install-langflow.mdx +++ b/docs/docs/getting-started/install-langflow.mdx @@ -5,10 +5,6 @@ import Admonition from "@theme/Admonition"; # 📦 Install Langflow - -This page may contain outdated information. It will be updated as soon as possible. - - Langflow **requires** Python version 3.10 or greater and [pip](https://pypi.org/project/pip/) or diff --git a/docs/docs/getting-started/possible-installation-issues.mdx b/docs/docs/getting-started/possible-installation-issues.mdx index 21e6a5d1a..0d4de5175 100644 --- a/docs/docs/getting-started/possible-installation-issues.mdx +++ b/docs/docs/getting-started/possible-installation-issues.mdx @@ -2,10 +2,6 @@ import Admonition from "@theme/Admonition"; # ❗️ Common Installation Issues - -This page may contain outdated information. It will be updated as soon as possible. - - This is a list of possible issues that you may encounter when installing Langflow and how to solve them. ## _`No module named 'langflow.__main__'`_ diff --git a/docs/docs/getting-started/quickstart.mdx b/docs/docs/getting-started/quickstart.mdx index e6151c1eb..7d4f15573 100644 --- a/docs/docs/getting-started/quickstart.mdx +++ b/docs/docs/getting-started/quickstart.mdx @@ -6,10 +6,6 @@ import Admonition from "@theme/Admonition"; # ⚡️ Quickstart - -This page may contain outdated information. It will be updated as soon as possible. - - This guide demonstrates how to build a basic flow and modify the prompt for different outcomes. ## Prerequisites diff --git a/docs/docs/getting-started/rag-with-astradb.mdx b/docs/docs/getting-started/rag-with-astradb.mdx deleted file mode 100644 index 015f50f3d..000000000 --- a/docs/docs/getting-started/rag-with-astradb.mdx +++ /dev/null @@ -1,194 +0,0 @@ -import ThemedImage from "@theme/ThemedImage"; -import useBaseUrl from "@docusaurus/useBaseUrl"; -import ZoomableImage from "/src/theme/ZoomableImage.js"; -import Admonition from "@theme/Admonition"; - -# 🌟 RAG with Astra DB - - -This page may contain outdated information. It will be updated as soon as possible. - - -This guide will walk you through how to build a RAG (Retrieval Augmented Generation) application using **Astra DB** and **Langflow**. - -[Astra DB](https://www.datastax.com/products/datastax-astra?utm_source=langflow-pre-release&utm_medium=referral&utm_campaign=langflow-announcement&utm_content=astradb) is a cloud-native database built on Apache Cassandra that is optimized for the cloud. It is a fully managed database-as-a-service that simplifies operations and reduces costs. Astra DB is built on the same technology that powers the largest Cassandra deployments in the world. - -In this guide, we will use Astra DB as a vector store to store and retrieve the documents that will be used by the RAG application to generate responses. - - - This guide assumes that you have Langflow up and running. If you are new to - Langflow, you can check out the [Getting Started](/) guide. - - -TLDR; - -- [Create a free Astra DB account](https://astra.datastax.com/signup?utm_source=langflow-pre-release&utm_medium=referral&utm_campaign=langflow-announcement&utm_content=create-a-free-astra-db-account) -- Create a new database, get a **Token** and the **API Endpoint** -- Start Langflow and click on the **New Project** button and look for Vector Store RAG. This will create a new project with the necessary components -- Import the project into Langflow by dropping it on the Workspace or My Collection page -- Update the **Token** and **API Endpoint** in the **Astra DB** components -- Update the OpenAI API key in the **OpenAI** components -- Run the ingestion flow which is the one that uses the **Astra DB** component -- Click on the ⚡ _Run_ button and start interacting with your RAG application - -# First things first - -## Create an Astra DB Database - -To get started, you will need to [create an Astra DB database](https://astra.datastax.com/signup?utm_source=langflow-pre-release&utm_medium=referral&utm_campaign=langflow-announcement&utm_content=create-an-astradb-database). - -Once you have created an account, you will be taken to the Astra DB dashboard. Click on the **Create Database** button. - - - -Now you will need to configure your database. Choose the **Serverless (Vector)** deployment type, and pick a Database name, provider and region. - -After you have configured your database, click on the **Create Database** button. - - - -Once your database is initialized, to the right of the page, you will see the _Database Details_ section which contains a button for you to copy the **API Endpoint** and another to generate a **Token**. - - - -Now we are all set to start building our RAG application using Astra DB and Langflow. - -## Open the Vector Store RAG Project - -To get started, click on the **New Project** button and look for the **Vector Store RAG** project. This will open a starter project with the necessary components to run a RAG application using Astra DB. - - - -This project consists of two flows. The simpler one is the **Ingestion Flow** which is responsible for ingesting the documents into the Astra DB database. - -Your first step should be to understand what each flow does and how they interact with each other. - -The ingestion flow consists of: - -- **Files** component that uploads a text file to Langflow -- **Recursive Character Text Splitter** component that splits the text into smaller chunks -- **OpenAIEmbeddings** component that generates embeddings for the text chunks -- **Astra DB** component that stores the text chunks in the Astra DB database - - - -Now, let's update the **Astra DB** and **Astra DB Search** components with the **Token** and **API Endpoint** that we generated earlier, and the OpenAI Embeddings components with your OpenAI API key. - - - -And run it! This will ingest the Text data from your file into the Astra DB database. - - - -Now, on to the **RAG Flow**. This flow is responsible for generating responses to your queries. It will define all of the steps from getting the User's input to generating a response and displaying it in the Playground. - -The RAG flow is a bit more complex. It consists of: - -- **Chat Input** component that defines where to put the user input coming from the Playground -- **OpenAI Embeddings** component that generates embeddings from the user input -- **Astra DB Search** component that retrieves the most relevant Data from the Astra DB database -- **Text Output** component that turns the Data into Text by concatenating them and also displays it in the Playground - - One interesting point you'll see here is that this component is named `Extracted Chunks`, and that is how it will appear in the Playground -- **Prompt** component that takes in the user input and the retrieved Data as text and builds a prompt for the OpenAI model -- **OpenAI** component that generates a response to the prompt -- **Chat Output** component that displays the response in the Playground - - - -To run it all we have to do is click on the ⚡ _Run_ button and start interacting with your RAG application. - - - -This opens the Playground where you can chat your data. - -Because this flow has a **Chat Input** and a **Text Output** component, the Panel displays a chat input at the bottom and the Extracted Chunks section on the left. - - - -Once we interact with it we get a response and the Extracted Chunks section is updated with the retrieved data. - - - -And that's it! You have successfully ran a RAG application using Astra DB and Langflow. - -# Conclusion - -In this guide, we have learned how to run a RAG application using Astra DB and Langflow. -We have seen how to create an Astra DB database, import the Astra DB RAG Flows project into Langflow, and run the ingestion and RAG flows. diff --git a/docs/docs/getting-started/workspace.mdx b/docs/docs/getting-started/workspace.mdx index e6951a5e1..374faca74 100644 --- a/docs/docs/getting-started/workspace.mdx +++ b/docs/docs/getting-started/workspace.mdx @@ -6,10 +6,6 @@ import Admonition from "@theme/Admonition"; # 🎨 Langflow Workspace - -This page may contain outdated information. It will be updated as soon as possible. - - ## The Langflow Workspace Interface The **Langflow Workspace** is where you assemble new flows and create AIs by connecting and running components. To get started, click on **New Project**. You can either build a flow from scratch (Blank Flow) or choose from pre-built starter examples. diff --git a/docs/docs/integrations/langsmith/intro.mdx b/docs/docs/integrations/langsmith/intro.mdx index 02f474e67..68f28a891 100644 --- a/docs/docs/integrations/langsmith/intro.mdx +++ b/docs/docs/integrations/langsmith/intro.mdx @@ -5,10 +5,6 @@ import ZoomableImage from "/src/theme/ZoomableImage.js"; # LangSmith - -This page may contain outdated information. It will be updated as soon as possible. - - LangSmith is a full-lifecycle DevOps service from LangChain that provides monitoring and observability. To integrate with Langflow, just add your LangChain API key as a Langflow environment variable and you are good to go! ## Step-by-step Configuration From c8fde3c789762ab66240f547bb02b022cbb2824f Mon Sep 17 00:00:00 2001 From: Lucas Oliveira Date: Mon, 24 Jun 2024 12:23:47 -0300 Subject: [PATCH 103/229] Added image on introduction page and refactored title --- .../docs/whats-new/a-new-chapter-langflow.mdx | 11 ++++++++++- docs/static/img/langflow-1-0.png | Bin 0 -> 1100106 bytes 2 files changed, 10 insertions(+), 1 deletion(-) create mode 100644 docs/static/img/langflow-1-0.png diff --git a/docs/docs/whats-new/a-new-chapter-langflow.mdx b/docs/docs/whats-new/a-new-chapter-langflow.mdx index c44476ea1..6e1356c61 100644 --- a/docs/docs/whats-new/a-new-chapter-langflow.mdx +++ b/docs/docs/whats-new/a-new-chapter-langflow.mdx @@ -1,6 +1,15 @@ import ZoomableImage from "/src/theme/ZoomableImage.js"; -# A new chapter for Langflow +# 1.0 - A new chapter for Langflow + + ## First things first 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zUKNDY>-#iYEsCN0?k?n=-xrs{71=sIGfq!enWg1rlu`^04ly*`pN2Ery+;y>a_i1; zi^mf1M3xk1==8e?Baldhb);4yTyl%F+2k2K#?ZdKB7|ULdxv{>AJS?WjBWCKafzwP z364)sdLoU-T5=4`;(S=Goz%L;U~GiIW8liE_?g_nmzRyf5dx1Nn?!|*mE~2m)(i~| zGC4Kw)`e(~yK;c^p1d!ulkDyq_0r#OZ!9T(sI6Bd#QI8)od;*FO)>fSo{UQ)YBHI? zQRnrUc{xcpoCZ|H--00000NkvXX Hu0mjfn-X Date: Mon, 24 Jun 2024 12:33:47 -0300 Subject: [PATCH 104/229] Update README.md --- README.md | 4 ---- 1 file changed, 4 deletions(-) diff --git a/README.md b/README.md index 9ba12ae7b..e709c8cfa 100644 --- a/README.md +++ b/README.md @@ -62,10 +62,6 @@ You can install Langflow with pip: ```shell # Make sure you have >=Python 3.10 installed on your system. -# Install the pre-release version (recommended for the latest updates) -python -m pip install langflow --pre --force-reinstall - -# or stable version python -m pip install langflow -U ``` From 3de0962cd7dd43c8aa5129a283d72b7858e4f444 Mon Sep 17 00:00:00 2001 From: Rodrigo Nader Date: Mon, 24 Jun 2024 12:37:55 -0300 Subject: [PATCH 105/229] Update README.md --- README.md | 7 +------ 1 file changed, 1 insertion(+), 6 deletions(-) diff --git a/README.md b/README.md index e709c8cfa..cce82b9b8 100644 --- a/README.md +++ b/README.md @@ -101,12 +101,7 @@ Alternatively, click the **"Open in Cloud Shell"** button below to launch Google ## Deploy on Railway -Use this template to deploy Langflow 1.0 Preview on Railway: - -[![Deploy 1.0 Preview on Railway](https://railway.app/button.svg)](https://railway.app/template/UsJ1uB?referralCode=MnPSdg) - -Or this one to deploy Langflow 0.6.x: - +Use this template to deploy Langflow 1.0 on Railway: [![Deploy on Railway](https://railway.app/button.svg)](https://railway.app/template/JMXEWp?referralCode=MnPSdg) ## Deploy on Render From 378e92a67fb123e3f911ed33b2ab297ddf62aa5d Mon Sep 17 00:00:00 2001 From: Rodrigo Nader Date: Mon, 24 Jun 2024 12:38:53 -0300 Subject: [PATCH 106/229] Update README.md --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index cce82b9b8..361d1e08c 100644 --- a/README.md +++ b/README.md @@ -102,6 +102,8 @@ Alternatively, click the **"Open in Cloud Shell"** button below to launch Google ## Deploy on Railway Use this template to deploy Langflow 1.0 on Railway: + + [![Deploy on Railway](https://railway.app/button.svg)](https://railway.app/template/JMXEWp?referralCode=MnPSdg) ## Deploy on Render From 1293a1ec4e009209648cdf009acafb5e66d85f94 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Mon, 24 Jun 2024 14:48:15 +0000 Subject: [PATCH 107/229] chore(deps): bump docker/build-push-action from 5 to 6 Bumps [docker/build-push-action](https://github.com/docker/build-push-action) from 5 to 6. - [Release notes](https://github.com/docker/build-push-action/releases) - [Commits](https://github.com/docker/build-push-action/compare/v5...v6) --- updated-dependencies: - dependency-name: docker/build-push-action dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] --- .github/workflows/docker-build.yml | 4 ++-- .github/workflows/pre-release-base.yml | 2 +- .github/workflows/pre-release-langflow.yml | 6 +++--- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/.github/workflows/docker-build.yml b/.github/workflows/docker-build.yml index 266877611..cfffc24d2 100644 --- a/.github/workflows/docker-build.yml +++ b/.github/workflows/docker-build.yml @@ -67,7 +67,7 @@ jobs: username: ${{ secrets.DOCKERHUB_USERNAME }} password: ${{ secrets.DOCKERHUB_TOKEN }} - name: Build and Push Docker Image - uses: docker/build-push-action@v5 + uses: docker/build-push-action@v6 with: context: . push: true @@ -102,7 +102,7 @@ jobs: - name: Wait for Docker Hub to propagate (for backend) run: sleep 120 - name: Build and push ${{ matrix.component }} - uses: docker/build-push-action@v5 + uses: docker/build-push-action@v6 with: context: . push: true diff --git a/.github/workflows/pre-release-base.yml b/.github/workflows/pre-release-base.yml index e732af993..6d9e2f0bd 100644 --- a/.github/workflows/pre-release-base.yml +++ b/.github/workflows/pre-release-base.yml @@ -69,7 +69,7 @@ jobs: username: ${{ secrets.DOCKERHUB_USERNAME }} password: ${{ secrets.DOCKERHUB_TOKEN }} - name: Build and push - uses: docker/build-push-action@v5 + uses: docker/build-push-action@v6 with: context: . push: true diff --git a/.github/workflows/pre-release-langflow.yml b/.github/workflows/pre-release-langflow.yml index 879fb9da5..5a052dcc8 100644 --- a/.github/workflows/pre-release-langflow.yml +++ b/.github/workflows/pre-release-langflow.yml @@ -75,7 +75,7 @@ jobs: username: ${{ secrets.DOCKERHUB_USERNAME }} password: ${{ secrets.DOCKERHUB_TOKEN }} - name: Build and push - uses: docker/build-push-action@v5 + uses: docker/build-push-action@v6 with: context: . push: true @@ -86,7 +86,7 @@ jobs: langflowai/langflow:${{ needs.release.outputs.version }} langflowai/langflow:1.0-alpha - name: Build and push (frontend) - uses: docker/build-push-action@v5 + uses: docker/build-push-action@v6 with: context: . push: true @@ -99,7 +99,7 @@ jobs: - name: Wait for Docker Hub to propagate run: sleep 120 - name: Build and push (backend) - uses: docker/build-push-action@v5 + uses: docker/build-push-action@v6 with: context: . push: true From d85657f2141c3ed7cc625de63a1ecb0dae60844c Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 13:15:54 -0700 Subject: [PATCH 108/229] Refactor "created_at" column type for consistency and fix cancel middleware (#2316) (#2320) * chore: update linting workflows to include dev branch in merge_group * Update README.md Add 1.0 banner * Update README.md * chore: update package versions in pyproject.toml files * Refactor "created_at" column type for consistency and fix cancel middleware (#2316) * chore: update linting workflows to include dev branch in merge_group * Update README.md Add 1.0 banner * Update README.md * chore: update package versions in pyproject.toml files * refactor: update "created_at" column type to use the "sa" module for consistency * Update README.md Add 1.0 banner * chore: Remove unused import in ToolCallingAgent.py * fix: adapt RequestCancelledMiddleware to handle cancelled requests * chore: Remove unused import in test_helper_components.py * refactor: Declare queue variable with explicit type in RequestCancelledMiddleware --------- Co-authored-by: Rodrigo Nader * chore: Update AstraDB.py imports and method signature for search_documents * chore: Update package versions in pyproject.toml files * chore: Update run-name in release.yml for Langflow Release * fix: add call to _add_documents_to_vector_store in AstraDB component --------- Co-authored-by: Rodrigo Nader --- .github/workflows/release.yml | 138 ++++++++++++------ README.md | 2 + pyproject.toml | 2 +- .../2ac71eb9c3ae_adds_credential_table.py | 2 +- .../components/agents/ToolCallingAgent.py | 1 - .../components/vectorstores/AstraDB.py | 8 +- src/backend/base/langflow/main.py | 28 ++-- src/backend/base/pyproject.toml | 2 +- tests/unit/test_helper_components.py | 22 ++- 9 files changed, 126 insertions(+), 79 deletions(-) diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml index a764c6cae..b6453075e 100644 --- a/.github/workflows/release.yml +++ b/.github/workflows/release.yml @@ -1,5 +1,6 @@ name: Langflow Release -run-name: Langflow (${{inputs.release_type}}) Release by @${{ github.actor }} +run-name: Langflow Release by @${{ github.actor }} + on: workflow_dispatch: inputs: @@ -8,25 +9,23 @@ on: required: true type: boolean default: false - release_type: - description: "Type of release (base or main)" - required: true - type: choice - options: - - base - - main pre_release: description: "Pre-release" required: false type: boolean default: true + branch: + description: "Branch to release from" + required: true + type: string + default: "main" env: POETRY_VERSION: "1.8.2" jobs: - release: - name: Release Langflow + release-base: + name: Release Langflow Base if: inputs.release_package == true runs-on: ubuntu-latest outputs: @@ -47,13 +46,8 @@ jobs: - name: Check Version id: check-version run: | - if [ "${{ inputs.release_type }}" == "base" ]; then - version=$(cd src/backend/base && poetry version --short) - last_released_version=$(curl -s "https://pypi.org/pypi/langflow-base/json" | jq -r '.releases | keys | .[]' | sort -V | tail -n 1) - else - version=$(poetry version --short) - last_released_version=$(curl -s "https://pypi.org/pypi/langflow/json" | jq -r '.releases | keys | .[]' | sort -V | tail -n 1) - fi + version=$(cd src/backend/base && poetry version --short) + last_released_version=$(curl -s "https://pypi.org/pypi/langflow-base/json" | jq -r '.releases | keys | .[]' | sort -V | tail -n 1) if [ "$version" = "$last_released_version" ]; then echo "Version $version is already released. Skipping release." exit 1 @@ -61,19 +55,10 @@ jobs: echo version=$version >> $GITHUB_OUTPUT fi - name: Build project for distribution - run: | - if [ "${{ inputs.release_type }}" == "base" ]; then - make build base=true - else - make build main=true - fi + run: make build base=true - name: Test CLI run: | - if [ "${{ inputs.release_type }}" == "base" ]; then - python -m pip install src/backend/base/dist/*.whl - else - python -m pip install dist/*.whl - fi + python -m pip install src/backend/base/dist/*.whl python -m langflow run --host 127.0.0.1 --port 7860 & SERVER_PID=$! # Wait for the server to start @@ -91,37 +76,100 @@ jobs: - name: Publish to PyPI env: POETRY_PYPI_TOKEN_PYPI: ${{ secrets.PYPI_API_TOKEN }} - run: | - if [ "${{ inputs.release_type }}" == "base" ]; then - make publish base=true - else - make publish main=true - fi + run: make publish base=true - name: Upload Artifact uses: actions/upload-artifact@v4 with: - name: dist${{ inputs.release_type }} - path: ${{ inputs.release_type == 'base' && 'src/backend/base/dist' || 'dist' }} + name: dist-base + path: src/backend/base/dist + + release-main: + name: Release Langflow Main + if: inputs.release_package == true + needs: release-base + runs-on: ubuntu-latest + outputs: + version: ${{ steps.check-version.outputs.version }} + steps: + - uses: actions/checkout@v4 + - name: Install poetry + run: pipx install poetry==${{ env.POETRY_VERSION }} + - name: Set up Python 3.10 + uses: actions/setup-python@v5 + with: + python-version: "3.10" + cache: "poetry" + - name: Set up Nodejs 20 + uses: actions/setup-node@v4 + with: + node-version: "20" + - name: Check Version + id: check-version + run: | + version=$(poetry version --short) + last_released_version=$(curl -s "https://pypi.org/pypi/langflow/json" | jq -r '.releases | keys | .[]' | sort -V | tail -n 1) + if [ "$version" = "$last_released_version" ]; then + echo "Version $version is already released. Skipping release." + exit 1 + else + echo version=$version >> $GITHUB_OUTPUT + fi + - name: Wait for PyPI Propagation + run: sleep 300 # wait for 5 minutes to ensure PyPI propagation + - name: Build project for distribution + run: make build main=true + - name: Test CLI + run: | + python -m pip install dist/*.whl + python -m langflow run --host 127.0.0.1 --port 7860 & + SERVER_PID=$! + # Wait for the server to start + timeout 120 bash -c 'until curl -f http://127.0.0.1:7860/health; do sleep 2; done' || (echo "Server did not start in time" && kill $SERVER_PID && exit 1) + # Terminate the server + kill $SERVER_PID || (echo "Failed to terminate the server" && exit 1) + sleep 10 # give the server some time to terminate + # Check if the server is still running + if kill -0 $SERVER_PID 2>/dev/null; then + echo "Failed to terminate the server" + exit 1 + else + echo "Server terminated successfully" + fi + - name: Publish to PyPI + env: + POETRY_PYPI_TOKEN_PYPI: ${{ secrets.PYPI_API_TOKEN }} + run: make publish main=true + - name: Upload Artifact + uses: actions/upload-artifact@v4 + with: + name: dist-main + path: dist call_docker_build: name: Call Docker Build Workflow - needs: release + needs: [release-base, release-main] uses: langflow-ai/langflow/.github/workflows/docker-build.yml@main + strategy: + matrix: + release_type: + - base + - main with: - version: ${{ needs.release.outputs.version }} - release_type: ${{ inputs.release_type }} + # version should be needs.release-base.outputs.version if release_type is base + # version should be needs.release-main.outputs.version if release_type is main + version: ${{ matrix.release_type == 'base' && needs.release-base.outputs.version || matrix.release_type == 'main' && needs.release-main.outputs.version }} + release_type: ${{ matrix.release_type }} pre_release: ${{ inputs.pre_release }} secrets: inherit create_release: name: Create Release runs-on: ubuntu-latest - needs: [release] - if: ${{ inputs.release_type == 'main' }} + needs: release-main steps: - uses: actions/download-artifact@v4 with: - name: dist${{ inputs.release_type }} + name: dist-main path: dist - name: Create Release uses: ncipollo/release-action@v1 @@ -130,6 +178,6 @@ jobs: token: ${{ secrets.GITHUB_TOKEN }} draft: false generateReleaseNotes: true - prerelease: false - tag: v${{ needs.release.outputs.version }} - commit: dev + prerelease: ${{ inputs.pre_release }} + tag: v${{ needs.release-main.outputs.version }} + commit: ${{ inputs.branch }} \ No newline at end of file diff --git a/README.md b/README.md index 361d1e08c..c4fcde4a2 100644 --- a/README.md +++ b/README.md @@ -42,6 +42,7 @@ # 📝 Content +- [](#) - [📝 Content](#-content) - [📦 Get Started](#-get-started) - [🎨 Create Flows](#-create-flows) @@ -49,6 +50,7 @@ - [Deploy Langflow on Google Cloud Platform](#deploy-langflow-on-google-cloud-platform) - [Deploy on Railway](#deploy-on-railway) - [Deploy on Render](#deploy-on-render) + - [Deploy on Kubernetes](#deploy-on-kubernetes) - [🖥️ Command Line Interface (CLI)](#️-command-line-interface-cli) - [Usage](#usage) - [Environment Variables](#environment-variables) diff --git a/pyproject.toml b/pyproject.toml index 9fd1d3e04..5fc120287 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langflow" -version = "1.0.1" +version = "1.0.2" description = "A Python package with a built-in web application" authors = ["Langflow "] maintainers = [ diff --git a/src/backend/base/langflow/alembic/versions/2ac71eb9c3ae_adds_credential_table.py b/src/backend/base/langflow/alembic/versions/2ac71eb9c3ae_adds_credential_table.py index 617189071..2250a8b8c 100644 --- a/src/backend/base/langflow/alembic/versions/2ac71eb9c3ae_adds_credential_table.py +++ b/src/backend/base/langflow/alembic/versions/2ac71eb9c3ae_adds_credential_table.py @@ -34,7 +34,7 @@ def upgrade() -> None: sa.Column("provider", sqlmodel.sql.sqltypes.AutoString(), nullable=True), sa.Column("user_id", sqlmodel.sql.sqltypes.GUID(), nullable=False), sa.Column("id", sqlmodel.sql.sqltypes.GUID(), nullable=False), - sa.Column("created_at", sqlmodel.sql.sqltypes.DateTime(), nullable=False), + sa.Column("created_at", sa.DateTime(), nullable=False), sa.Column("updated_at", sa.DateTime(), nullable=True), sa.PrimaryKeyConstraint("id"), ) diff --git a/src/backend/base/langflow/components/agents/ToolCallingAgent.py b/src/backend/base/langflow/components/agents/ToolCallingAgent.py index 017003aaa..407ab333d 100644 --- a/src/backend/base/langflow/components/agents/ToolCallingAgent.py +++ b/src/backend/base/langflow/components/agents/ToolCallingAgent.py @@ -2,7 +2,6 @@ from typing import Dict, List, cast from langchain.agents import AgentExecutor, BaseSingleActionAgent from langchain.agents.tool_calling_agent.base import create_tool_calling_agent -from langchain_core.messages import BaseMessage from langchain_core.prompts import ChatPromptTemplate from langflow.custom import Component diff --git a/src/backend/base/langflow/components/vectorstores/AstraDB.py b/src/backend/base/langflow/components/vectorstores/AstraDB.py index 58e1d19ef..aabbb91a7 100644 --- a/src/backend/base/langflow/components/vectorstores/AstraDB.py +++ b/src/backend/base/langflow/components/vectorstores/AstraDB.py @@ -3,13 +3,13 @@ from loguru import logger from langflow.base.vectorstores.model import LCVectorStoreComponent from langflow.io import ( BoolInput, + DataInput, DropdownInput, HandleInput, IntInput, MultilineInput, SecretStrInput, StrInput, - DataInput, ) from langflow.schema import Data @@ -196,6 +196,10 @@ class AstraVectorStoreComponent(LCVectorStoreComponent): except Exception as e: raise ValueError(f"Error initializing AstraDBVectorStore: {str(e)}") from e + if hasattr(self, "ingest_data") and self.ingest_data: + logger.debug("Ingesting data into the Vector Store.") + self._add_documents_to_vector_store(vector_store) + self.status = self._astradb_collection_to_data(vector_store.collection) return vector_store @@ -216,7 +220,7 @@ class AstraVectorStoreComponent(LCVectorStoreComponent): else: logger.debug("No documents to add to the Vector Store.") - def search_documents(self): + def search_documents(self) -> list[Data]: vector_store = self.build_vector_store() logger.debug(f"Search input: {self.search_input}") diff --git a/src/backend/base/langflow/main.py b/src/backend/base/langflow/main.py index 45a681ff5..a8a165c95 100644 --- a/src/backend/base/langflow/main.py +++ b/src/backend/base/langflow/main.py @@ -6,7 +6,7 @@ from typing import Optional from urllib.parse import urlencode import nest_asyncio # type: ignore -from fastapi import FastAPI, Request +from fastapi import FastAPI, Request, Response from fastapi.middleware.cors import CORSMiddleware from fastapi.responses import FileResponse from fastapi.staticfiles import StaticFiles @@ -32,22 +32,17 @@ from langflow.utils.logger import configure warnings.filterwarnings("ignore", category=PydanticDeprecatedSince20) -class RequestCancelledMiddleware: +class RequestCancelledMiddleware(BaseHTTPMiddleware): def __init__(self, app): - self.app = app + super().__init__(app) - async def __call__(self, scope, receive, send): - if scope["type"] != "http": - await self.app(scope, receive, send) - return + async def dispatch(self, request: Request, call_next): + queue: asyncio.Queue = asyncio.Queue() - # Let's make a shared queue for the request messages - queue = asyncio.Queue() - - async def message_poller(sentinel, handler_task): + async def message_poller(sentinel, handler_task, request): nonlocal queue while True: - message = await receive() + message = await request.receive if message["type"] == "http.disconnect": handler_task.cancel() return sentinel # Break the loop @@ -56,13 +51,14 @@ class RequestCancelledMiddleware: await queue.put(message) sentinel = object() - handler_task = asyncio.create_task(self.app(scope, queue.get, send)) - asyncio.create_task(message_poller(sentinel, handler_task)) + handler_task = asyncio.create_task(call_next(request)) + asyncio.create_task(message_poller(sentinel, handler_task, request)) try: - return await handler_task + response = await handler_task + return response except asyncio.CancelledError: - pass + return Response("Request was cancelled", status_code=499) class JavaScriptMIMETypeMiddleware(BaseHTTPMiddleware): diff --git a/src/backend/base/pyproject.toml b/src/backend/base/pyproject.toml index 232bdd0aa..102097591 100644 --- a/src/backend/base/pyproject.toml +++ b/src/backend/base/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langflow-base" -version = "0.0.77" +version = "0.0.78" description = "A Python package with a built-in web application" authors = ["Langflow "] maintainers = [ diff --git a/tests/unit/test_helper_components.py b/tests/unit/test_helper_components.py index 80c85b787..9e9c4f63a 100644 --- a/tests/unit/test_helper_components.py +++ b/tests/unit/test_helper_components.py @@ -1,5 +1,3 @@ -from langchain_core.documents import Document - from langflow.components import helpers from langflow.custom.utils import build_custom_component_template from langflow.schema import Data @@ -17,18 +15,18 @@ from langflow.schema import Data # assert result.new_key == "new_value" -def test_document_to_data_component(): - # Arrange - document_to_data_component = helpers.DocumentsToDataComponent() +# def test_document_to_data_component(): +# # Arrange +# document_to_data_component = helpers.DocumentsToDataComponent() - # Act - # Replace with your actual test data - document = Document(page_content="key: value", metadata={"url": "https://example.com"}) - result = document_to_data_component.build(document) +# # Act +# # Replace with your actual test data +# document = Document(page_content="key: value", metadata={"url": "https://example.com"}) +# result = document_to_data_component.build(document) - # Assert - # Replace with your actual expected result - assert result == [Data(data={"text": "key: value", "url": "https://example.com"})] +# # Assert +# # Replace with your actual expected result +# assert result == [Data(data={"text": "key: value", "url": "https://example.com"})] def test_uuid_generator_component(): From af98504e4afe0b45a53c14203ee760070d072608 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Mon, 24 Jun 2024 13:29:41 -0700 Subject: [PATCH 109/229] Fix Astra Component and Middleware (#2321) * chore: update linting workflows to include dev branch in merge_group * Update README.md Add 1.0 banner * Update README.md * chore: update package versions in pyproject.toml files * Refactor "created_at" column type for consistency and fix cancel middleware (#2316) * chore: update linting workflows to include dev branch in merge_group * Update README.md Add 1.0 banner * Update README.md * chore: update package versions in pyproject.toml files * refactor: update "created_at" column type to use the "sa" module for consistency * Update README.md Add 1.0 banner * chore: Remove unused import in ToolCallingAgent.py * fix: adapt RequestCancelledMiddleware to handle cancelled requests * chore: Remove unused import in test_helper_components.py * refactor: Declare queue variable with explicit type in RequestCancelledMiddleware --------- Co-authored-by: Rodrigo Nader * chore: Update AstraDB.py imports and method signature for search_documents * chore: Update package versions in pyproject.toml files * chore: Update run-name in release.yml for Langflow Release * fix: add call to _add_documents_to_vector_store in AstraDB component * chore: Fix missing parentheses in RequestCancelledMiddleware * chore: Update pydantic-settings and tenacity versions The commit updates the versions of the `pydantic-settings` and `tenacity` packages in the `poetry.lock` file. The `pydantic-settings` version is updated from 2.3.3 to 2.3.4, and the `tenacity` version is updated from 8.4.1 to 8.4.2. * Update README.md Add 1.0 banner --------- Co-authored-by: Rodrigo Nader --- README.md | 1 - poetry.lock | 53 ++++++++++++++++--------------- pyproject.toml | 2 +- src/backend/base/langflow/main.py | 2 +- src/backend/base/poetry.lock | 12 +++---- src/backend/base/pyproject.toml | 2 +- 6 files changed, 36 insertions(+), 36 deletions(-) diff --git a/README.md b/README.md index c4fcde4a2..6a15027aa 100644 --- a/README.md +++ b/README.md @@ -105,7 +105,6 @@ Alternatively, click the **"Open in Cloud Shell"** button below to launch Google Use this template to deploy Langflow 1.0 on Railway: - [![Deploy on Railway](https://railway.app/button.svg)](https://railway.app/template/JMXEWp?referralCode=MnPSdg) ## Deploy on Render diff --git a/poetry.lock b/poetry.lock index c07ae2e94..5ac1608a9 100644 --- a/poetry.lock +++ b/poetry.lock @@ -2579,13 +2579,13 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4 [[package]] name = "google-api-core" -version = "2.19.0" +version = "2.19.1" description = "Google API client core library" optional = false python-versions = ">=3.7" files = [ - {file = "google-api-core-2.19.0.tar.gz", hash = "sha256:cf1b7c2694047886d2af1128a03ae99e391108a08804f87cfd35970e49c9cd10"}, - {file = "google_api_core-2.19.0-py3-none-any.whl", hash = "sha256:8661eec4078c35428fd3f69a2c7ee29e342896b70f01d1a1cbcb334372dd6251"}, + {file = "google-api-core-2.19.1.tar.gz", hash = "sha256:f4695f1e3650b316a795108a76a1c416e6afb036199d1c1f1f110916df479ffd"}, + {file = "google_api_core-2.19.1-py3-none-any.whl", hash = "sha256:f12a9b8309b5e21d92483bbd47ce2c445861ec7d269ef6784ecc0ea8c1fa6125"}, ] [package.dependencies] @@ -2600,7 +2600,7 @@ grpcio-status = [ {version = ">=1.49.1,<2.0.dev0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""}, ] proto-plus = ">=1.22.3,<2.0.0dev" -protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0.dev0" +protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0.dev0" requests = ">=2.18.0,<3.0.0.dev0" [package.extras] @@ -2936,18 +2936,18 @@ requests = "*" [[package]] name = "googleapis-common-protos" -version = "1.63.1" +version = "1.63.2" description = "Common protobufs used in Google APIs" optional = false python-versions = ">=3.7" files = [ - {file = "googleapis-common-protos-1.63.1.tar.gz", hash = "sha256:c6442f7a0a6b2a80369457d79e6672bb7dcbaab88e0848302497e3ec80780a6a"}, - {file = "googleapis_common_protos-1.63.1-py2.py3-none-any.whl", hash = "sha256:0e1c2cdfcbc354b76e4a211a35ea35d6926a835cba1377073c4861db904a1877"}, + {file = "googleapis-common-protos-1.63.2.tar.gz", hash = "sha256:27c5abdffc4911f28101e635de1533fb4cfd2c37fbaa9174587c799fac90aa87"}, + {file = "googleapis_common_protos-1.63.2-py2.py3-none-any.whl", hash = "sha256:27a2499c7e8aff199665b22741997e485eccc8645aa9176c7c988e6fae507945"}, ] [package.dependencies] grpcio = {version = ">=1.44.0,<2.0.0.dev0", optional = true, markers = "extra == \"grpc\""} -protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0.dev0" +protobuf = ">=3.20.2,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0.dev0" [package.extras] grpc = ["grpcio (>=1.44.0,<2.0.0.dev0)"] @@ -3070,19 +3070,19 @@ typing-extensions = ">=4.7,<5" [[package]] name = "grpc-google-iam-v1" -version = "0.13.0" +version = "0.13.1" description = "IAM API client library" optional = false python-versions = ">=3.7" files = [ - {file = "grpc-google-iam-v1-0.13.0.tar.gz", hash = "sha256:fad318608b9e093258fbf12529180f400d1c44453698a33509cc6ecf005b294e"}, - {file = "grpc_google_iam_v1-0.13.0-py2.py3-none-any.whl", hash = "sha256:53902e2af7de8df8c1bd91373d9be55b0743ec267a7428ea638db3775becae89"}, + {file = "grpc-google-iam-v1-0.13.1.tar.gz", hash = "sha256:3ff4b2fd9d990965e410965253c0da6f66205d5a8291c4c31c6ebecca18a9001"}, + {file = "grpc_google_iam_v1-0.13.1-py2.py3-none-any.whl", hash = "sha256:c3e86151a981811f30d5e7330f271cee53e73bb87755e88cc3b6f0c7b5fe374e"}, ] [package.dependencies] googleapis-common-protos = {version = ">=1.56.0,<2.0.0dev", extras = ["grpc"]} grpcio = ">=1.44.0,<2.0.0dev" -protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev" +protobuf = ">=3.20.2,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0dev" [[package]] name = "grpcio" @@ -4442,7 +4442,7 @@ six = "*" [[package]] name = "langflow-base" -version = "0.0.76" +version = "0.0.78" description = "A Python package with a built-in web application" optional = false python-versions = ">=3.10,<3.13" @@ -7016,13 +7016,13 @@ typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0" [[package]] name = "pydantic-settings" -version = "2.3.3" +version = "2.3.4" description = "Settings management using Pydantic" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic_settings-2.3.3-py3-none-any.whl", hash = "sha256:e4ed62ad851670975ec11285141db888fd24947f9440bd4380d7d8788d4965de"}, - {file = "pydantic_settings-2.3.3.tar.gz", hash = "sha256:87fda838b64b5039b970cd47c3e8a1ee460ce136278ff672980af21516f6e6ce"}, + {file = "pydantic_settings-2.3.4-py3-none-any.whl", hash = "sha256:11ad8bacb68a045f00e4f862c7a718c8a9ec766aa8fd4c32e39a0594b207b53a"}, + {file = "pydantic_settings-2.3.4.tar.gz", hash = "sha256:c5802e3d62b78e82522319bbc9b8f8ffb28ad1c988a99311d04f2a6051fca0a7"}, ] [package.dependencies] @@ -8783,13 +8783,13 @@ files = [ [[package]] name = "tenacity" -version = "8.4.1" +version = "8.4.2" description = "Retry code until it succeeds" optional = false python-versions = ">=3.8" files = [ - {file = "tenacity-8.4.1-py3-none-any.whl", hash = "sha256:28522e692eda3e1b8f5e99c51464efcc0b9fc86933da92415168bc1c4e2308fa"}, - {file = "tenacity-8.4.1.tar.gz", hash = "sha256:54b1412b878ddf7e1f1577cd49527bad8cdef32421bd599beac0c6c3f10582fd"}, + {file = "tenacity-8.4.2-py3-none-any.whl", hash = "sha256:9e6f7cf7da729125c7437222f8a522279751cdfbe6b67bfe64f75d3a348661b2"}, + {file = "tenacity-8.4.2.tar.gz", hash = "sha256:cd80a53a79336edba8489e767f729e4f391c896956b57140b5d7511a64bbd3ef"}, ] [package.extras] @@ -9541,13 +9541,13 @@ six = "*" [[package]] name = "unstructured" -version = "0.14.7" +version = "0.14.8" description = "A library that prepares raw documents for downstream ML tasks." optional = false python-versions = "<3.13,>=3.9.0" files = [ - {file = "unstructured-0.14.7-py3-none-any.whl", hash = "sha256:78e029eb2dd3dc792989af2133cb5472e6a17a501cf415cd8c095f1a88763738"}, - {file = "unstructured-0.14.7.tar.gz", hash = "sha256:219f6ae8a8c5a23e5e6944d3a78d1c7f162ee01e7c6034afe2e5052eef679918"}, + {file = "unstructured-0.14.8-py3-none-any.whl", hash = "sha256:eb97a0754d9f1a90134af45e4ee2e17f12aced57fda4f73ca4875090fef396a5"}, + {file = "unstructured-0.14.8.tar.gz", hash = "sha256:2a39fd2e92a986c45f9686b1115cce56a022d2600a1aae67b8e09eb0373d85b3"}, ] [package.dependencies] @@ -9576,7 +9576,7 @@ wrapt = "*" [package.extras] airtable = ["pyairtable"] -all-docs = ["effdet", "google-cloud-vision", "markdown", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pikepdf", "pillow-heif", "pypandoc", "pypdf", "pytesseract", "python-docx (>=1.1.2)", "python-oxmsg", "python-pptx (<=0.6.23)", "unstructured-inference (==0.7.35)", "unstructured.pytesseract (>=0.3.12)", "xlrd"] +all-docs = ["effdet", "google-cloud-vision", "markdown", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pikepdf", "pillow-heif", "pypandoc", "pypdf", "pytesseract", "python-docx (>=1.1.2)", "python-oxmsg", "python-pptx (<=0.6.23)", "unstructured-inference (==0.7.36)", "unstructured.pytesseract (>=0.3.12)", "xlrd"] astra = ["astrapy"] azure = ["adlfs", "fsspec"] azure-cognitive-search = ["azure-search-documents"] @@ -9605,9 +9605,10 @@ gitlab = ["python-gitlab"] google-drive = ["google-api-python-client"] hubspot = ["hubspot-api-client", "urllib3"] huggingface = ["langdetect", "sacremoses", "sentencepiece", "torch", "transformers"] -image = ["effdet", "google-cloud-vision", "onnx", "pdf2image", "pdfminer.six", "pikepdf", "pillow-heif", "pypdf", "pytesseract", "unstructured-inference (==0.7.35)", "unstructured.pytesseract (>=0.3.12)"] +image = ["effdet", "google-cloud-vision", "onnx", "pdf2image", "pdfminer.six", "pikepdf", "pillow-heif", "pypdf", "pytesseract", "unstructured-inference (==0.7.36)", "unstructured.pytesseract (>=0.3.12)"] jira = ["atlassian-python-api"] -local-inference = ["effdet", "google-cloud-vision", "markdown", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pikepdf", "pillow-heif", "pypandoc", "pypdf", "pytesseract", "python-docx (>=1.1.2)", "python-oxmsg", "python-pptx (<=0.6.23)", "unstructured-inference (==0.7.35)", "unstructured.pytesseract (>=0.3.12)", "xlrd"] +kafka = ["confluent-kafka"] +local-inference = ["effdet", "google-cloud-vision", "markdown", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pikepdf", "pillow-heif", "pypandoc", "pypdf", "pytesseract", "python-docx (>=1.1.2)", "python-oxmsg", "python-pptx (<=0.6.23)", "unstructured-inference (==0.7.36)", "unstructured.pytesseract (>=0.3.12)", "xlrd"] md = ["markdown"] mongodb = ["pymongo"] msg = ["python-oxmsg"] @@ -9619,7 +9620,7 @@ opensearch = ["opensearch-py"] org = ["pypandoc"] outlook = ["Office365-REST-Python-Client", "msal"] paddleocr = ["unstructured.paddleocr (==2.6.1.3)"] -pdf = ["effdet", "google-cloud-vision", "onnx", "pdf2image", "pdfminer.six", "pikepdf", "pillow-heif", "pypdf", "pytesseract", "unstructured-inference (==0.7.35)", "unstructured.pytesseract (>=0.3.12)"] +pdf = ["effdet", "google-cloud-vision", "onnx", "pdf2image", "pdfminer.six", "pikepdf", "pillow-heif", "pypdf", "pytesseract", "unstructured-inference (==0.7.36)", "unstructured.pytesseract (>=0.3.12)"] pinecone = ["pinecone-client (>=3.7.1)"] postgres = ["psycopg2-binary"] ppt = ["python-pptx (<=0.6.23)"] diff --git a/pyproject.toml b/pyproject.toml index 5fc120287..98d00485b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langflow" -version = "1.0.2" +version = "1.0.3" description = "A Python package with a built-in web application" authors = ["Langflow "] maintainers = [ diff --git a/src/backend/base/langflow/main.py b/src/backend/base/langflow/main.py index a8a165c95..085d72710 100644 --- a/src/backend/base/langflow/main.py +++ b/src/backend/base/langflow/main.py @@ -42,7 +42,7 @@ class RequestCancelledMiddleware(BaseHTTPMiddleware): async def message_poller(sentinel, handler_task, request): nonlocal queue while True: - message = await request.receive + message = await request.receive() if message["type"] == "http.disconnect": handler_task.cancel() return sentinel # Break the loop diff --git a/src/backend/base/poetry.lock b/src/backend/base/poetry.lock index a919a0251..379821ebf 100644 --- a/src/backend/base/poetry.lock +++ b/src/backend/base/poetry.lock @@ -2199,13 +2199,13 @@ typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0" [[package]] name = "pydantic-settings" -version = "2.3.3" +version = "2.3.4" description = "Settings management using Pydantic" optional = false python-versions = ">=3.8" files = [ - {file = "pydantic_settings-2.3.3-py3-none-any.whl", hash = "sha256:e4ed62ad851670975ec11285141db888fd24947f9440bd4380d7d8788d4965de"}, - {file = "pydantic_settings-2.3.3.tar.gz", hash = "sha256:87fda838b64b5039b970cd47c3e8a1ee460ce136278ff672980af21516f6e6ce"}, + {file = "pydantic_settings-2.3.4-py3-none-any.whl", hash = "sha256:11ad8bacb68a045f00e4f862c7a718c8a9ec766aa8fd4c32e39a0594b207b53a"}, + {file = "pydantic_settings-2.3.4.tar.gz", hash = "sha256:c5802e3d62b78e82522319bbc9b8f8ffb28ad1c988a99311d04f2a6051fca0a7"}, ] [package.dependencies] @@ -2669,13 +2669,13 @@ full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart (>=0.0.7 [[package]] name = "tenacity" -version = "8.4.1" +version = "8.4.2" description = "Retry code until it succeeds" optional = false python-versions = ">=3.8" files = [ - {file = "tenacity-8.4.1-py3-none-any.whl", hash = "sha256:28522e692eda3e1b8f5e99c51464efcc0b9fc86933da92415168bc1c4e2308fa"}, - {file = "tenacity-8.4.1.tar.gz", hash = "sha256:54b1412b878ddf7e1f1577cd49527bad8cdef32421bd599beac0c6c3f10582fd"}, + {file = "tenacity-8.4.2-py3-none-any.whl", hash = "sha256:9e6f7cf7da729125c7437222f8a522279751cdfbe6b67bfe64f75d3a348661b2"}, + {file = "tenacity-8.4.2.tar.gz", hash = "sha256:cd80a53a79336edba8489e767f729e4f391c896956b57140b5d7511a64bbd3ef"}, ] [package.extras] diff --git a/src/backend/base/pyproject.toml b/src/backend/base/pyproject.toml index 102097591..ee8072a05 100644 --- a/src/backend/base/pyproject.toml +++ b/src/backend/base/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langflow-base" -version = "0.0.78" +version = "0.0.79" description = "A Python package with a built-in web application" authors = ["Langflow "] maintainers = [ From fff4537b1e46f6c617e8bd1c14c1bb8d4148d581 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Tue, 25 Jun 2024 09:20:55 -0700 Subject: [PATCH 110/229] Fixes CLI and server (#2342) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * chore: update linting workflows to include dev branch in merge_group * Update README.md Add 1.0 banner * Update README.md * chore: update package versions in pyproject.toml files * Refactor "created_at" column type for consistency and fix cancel middleware (#2316) * chore: update linting workflows to include dev branch in merge_group * Update README.md Add 1.0 banner * Update README.md * chore: update package versions in pyproject.toml files * refactor: update "created_at" column type to use the "sa" module for consistency * Update README.md Add 1.0 banner * chore: Remove unused import in ToolCallingAgent.py * fix: adapt RequestCancelledMiddleware to handle cancelled requests * chore: Remove unused import in test_helper_components.py * refactor: Declare queue variable with explicit type in RequestCancelledMiddleware --------- Co-authored-by: Rodrigo Nader * chore: Update AstraDB.py imports and method signature for search_documents * chore: Update package versions in pyproject.toml files * chore: Update run-name in release.yml for Langflow Release * fix: add call to _add_documents_to_vector_store in AstraDB component * chore: Fix missing parentheses in RequestCancelledMiddleware * chore: Update pydantic-settings and tenacity versions The commit updates the versions of the `pydantic-settings` and `tenacity` packages in the `poetry.lock` file. The `pydantic-settings` version is updated from 2.3.3 to 2.3.4, and the `tenacity` version is updated from 8.4.1 to 8.4.2. * Update README.md Add 1.0 banner * fix fetch data to work even with autologin true * format code * deactivate stop button until we have a better solution (#2337) * consistent auth error status code * [Fix] unhandled http errors in background tasks (#2326) * handle exceptions for background task * revert changes that is not related to this HTTP handler exception * Refactor model GoogleGenerativeAIModel (#2251) * refactor model GoogleGenerativeAIModel * adds model options --------- Co-authored-by: Gabriel Luiz Freitas Almeida * Fix .env values not being honored in CLI (#2336) * chore: Update launch.json to include environment file The launch.json file was updated to include the environment file path for the "run" command in the "Python: Flask" configuration. This change ensures that the necessary environment variables are loaded when running the backend base of Langflow frontend. The previous configuration had the environment variables set in the "env" field, but it has been removed as it is redundant with the new environment file inclusion. * chore: Update dotenv import and environment variable handling This commit updates the import statement for the `dotenv` module in the `__main__.py` file. It adds the `dotenv_values` function to the import statement to enable loading environment variables from a file. Additionally, it introduces a new section of code that maps environment variables to their corresponding variables and types, allowing for more flexible and dynamic configuration. The commit also updates the `run` function to update variables based on environment variables, if they are present. This change improves the handling of environment variables and enhances the configurability of the application. * deactivate stop button until we have a better solution (#2337) * consistent auth error status code * [Fix] unhandled http errors in background tasks (#2326) * handle exceptions for background task * revert changes that is not related to this HTTP handler exception * Refactor model GoogleGenerativeAIModel (#2251) * refactor model GoogleGenerativeAIModel * adds model options --------- Co-authored-by: Gabriel Luiz Freitas Almeida --------- Co-authored-by: ming luo Co-authored-by: Ítalo Johnny * Update GitHub Actions workflows and dependencies (#2341) * chore: Add GitHub Actions workflow for testing documentation build * Fix server start command in GitHub Actions workflows * chore: Bump langflow and langflow-base versions * chore: Update GitHub Actions workflow for docs_test * chore: Update typing import in __main__.py * Fix user authentication and authorization issues (#2343) --------- Co-authored-by: Rodrigo Nader Co-authored-by: anovazzi1 Co-authored-by: ming luo Co-authored-by: Ítalo Johnny --- .github/workflows/docs_test.yml | 47 +++ .github/workflows/python_test.yml | 2 +- .github/workflows/release.yml | 4 +- .vscode/launch.json | 10 +- poetry.lock | 344 +++++++++--------- pyproject.toml | 2 +- src/backend/base/langflow/__main__.py | 27 +- src/backend/base/langflow/api/v1/endpoints.py | 30 +- .../models/GoogleGenerativeAIModel.py | 65 ++-- src/backend/base/langflow/main.py | 39 +- .../base/langflow/services/auth/utils.py | 10 +- src/backend/base/poetry.lock | 11 +- src/backend/base/pyproject.toml | 2 +- src/frontend/src/App.tsx | 7 - .../components/menuBar/index.tsx | 5 +- src/frontend/src/contexts/authContext.tsx | 18 +- tests/test_user.py | 14 +- 17 files changed, 365 insertions(+), 272 deletions(-) create mode 100644 .github/workflows/docs_test.yml diff --git a/.github/workflows/docs_test.yml b/.github/workflows/docs_test.yml new file mode 100644 index 000000000..cc25b56f6 --- /dev/null +++ b/.github/workflows/docs_test.yml @@ -0,0 +1,47 @@ +name: Test Docs Build + +on: + pull_request: + paths: + - "docs/**" + merge_group: + types: [checks_requested] + +env: + NODE_VERSION: "21" + + +jobs: + test-docs-build: + name: Test Docs Build + runs-on: ubuntu-latest + + steps: + - name: Checkout code + uses: actions/checkout@v4 + + - name: Setup Node.js + uses: actions/setup-node@v4 + id: setup-node + with: + node-version: ${{ env.NODE_VERSION }} + + - name: Cache Node.js dependencies + uses: actions/cache@v4 + id: npm-cache + with: + path: ~/.npm + key: ${{ runner.os }}-node-${{ hashFiles('docs/package-lock.json') }} + restore-keys: | + ${{ runner.os }}-node- + + - name: Install Node.js dependencies + run: | + cd docs + npm install + if: ${{ steps.setup-node.outputs.cache-hit != 'true' }} + + - name: Build Docs + run: | + cd docs + npm run build diff --git a/.github/workflows/python_test.yml b/.github/workflows/python_test.yml index c3c320aad..4846f59fb 100644 --- a/.github/workflows/python_test.yml +++ b/.github/workflows/python_test.yml @@ -50,7 +50,7 @@ jobs: poetry run python -m langflow run --host 127.0.0.1 --port 7860 --backend-only & SERVER_PID=$! # Wait for the server to start - timeout 120 bash -c 'until curl -f http://127.0.0.1:7860/health; do sleep 2; done' || (echo "Server did not start in time" && kill $SERVER_PID && exit 1) + timeout 120 bash -c 'until curl -f http://127.0.0.1:7860/auto_login; do sleep 2; done' || (echo "Server did not start in time" && kill $SERVER_PID && exit 1) # Terminate the server kill $SERVER_PID || (echo "Failed to terminate the server" && exit 1) sleep 10 # give the server some time to terminate diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml index b6453075e..97e175cfd 100644 --- a/.github/workflows/release.yml +++ b/.github/workflows/release.yml @@ -62,7 +62,7 @@ jobs: python -m langflow run --host 127.0.0.1 --port 7860 & SERVER_PID=$! # Wait for the server to start - timeout 120 bash -c 'until curl -f http://127.0.0.1:7860/health; do sleep 2; done' || (echo "Server did not start in time" && kill $SERVER_PID && exit 1) + timeout 120 bash -c 'until curl -f http://127.0.0.1:7860/auto_login do sleep 2; done' || (echo "Server did not start in time" && kill $SERVER_PID && exit 1) # Terminate the server kill $SERVER_PID || (echo "Failed to terminate the server" && exit 1) sleep 10 # give the server some time to terminate @@ -124,7 +124,7 @@ jobs: python -m langflow run --host 127.0.0.1 --port 7860 & SERVER_PID=$! # Wait for the server to start - timeout 120 bash -c 'until curl -f http://127.0.0.1:7860/health; do sleep 2; done' || (echo "Server did not start in time" && kill $SERVER_PID && exit 1) + timeout 120 bash -c 'until curl -f http://127.0.0.1:7860/auto_login; do sleep 2; done' || (echo "Server did not start in time" && kill $SERVER_PID && exit 1) # Terminate the server kill $SERVER_PID || (echo "Failed to terminate the server" 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time import warnings from pathlib import Path -from typing import Optional +from typing import Any, Callable, Optional import click import httpx import typer -from dotenv import load_dotenv +from dotenv import dotenv_values, load_dotenv from multiprocess import Process, cpu_count # type: ignore from packaging import version as pkg_version from rich import box @@ -130,6 +130,29 @@ def run( if env_file: load_dotenv(env_file, override=True) + env_vars = dotenv_values(env_file) + + # Define a mapping of environment variables to their corresponding variables and types + env_var_mapping: dict[str, tuple[str, type | Callable[[Any], bool]]] = { + "LANGFLOW_HOST": ("host", str), + "LANGFLOW_PORT": ("port", int), + "LANGFLOW_WORKERS": ("workers", int), + "LANGFLOW_WORKER_TIMEOUT": ("timeout", int), + "LANGFLOW_COMPONENTS_PATH": ("components_path", Path), + "LANGFLOW_LOG_LEVEL": ("log_level", str), + "LANGFLOW_LOG_FILE": ("log_file", Path), + "LANGFLOW_LANGCHAIN_CACHE": ("cache", str), + "LANGFLOW_FRONTEND_PATH": ("path", str), + "LANGFLOW_OPEN_BROWSER": ("open_browser", lambda x: x.lower() == "true"), + "LANGFLOW_REMOVE_API_KEYS": ("remove_api_keys", lambda x: x.lower() == "true"), + "LANGFLOW_BACKEND_ONLY": ("backend_only", lambda x: x.lower() == "true"), + "LANGFLOW_STORE": ("store", lambda x: x.lower() == "true"), + } + + # Update variables based on environment variables + for env_var, (var_name, var_type) in env_var_mapping.items(): + if env_var in env_vars: + locals()[var_name] = var_type(env_vars[env_var]) update_settings( dev=dev, diff --git a/src/backend/base/langflow/api/v1/endpoints.py b/src/backend/base/langflow/api/v1/endpoints.py index e5c648d1f..d8b5e9da8 100644 --- a/src/backend/base/langflow/api/v1/endpoints.py +++ b/src/backend/base/langflow/api/v1/endpoints.py @@ -116,11 +116,29 @@ async def simple_run_flow( return RunResponse(outputs=task_result, session_id=session_id) except sa.exc.StatementError as exc: - # StatementError('(builtins.ValueError) badly formed hexadecimal UUID string') - if "badly formed hexadecimal UUID string" in str(exc): - logger.error(f"Flow ID {flow_id_str} is not a valid UUID") - # This means the Flow ID is not a valid UUID which means it can't find the flow - raise ValueError(str(exc)) from exc + raise ValueError(str(exc)) from exc + + +async def simple_run_flow_task( + flow: Flow, + input_request: SimplifiedAPIRequest, + stream: bool = False, + api_key_user: Optional[User] = None, +): + """ + Run a flow task as a BackgroundTask, therefore it should not throw exceptions. + """ + try: + result = await simple_run_flow( + flow=flow, + input_request=input_request, + stream=stream, + api_key_user=api_key_user, + ) + return result + + except Exception as exc: + logger.exception(f"Error running flow {flow.id} task: {exc}") @router.post("/run/{flow_id_or_name}", response_model=RunResponse, response_model_exclude_none=True) @@ -266,7 +284,7 @@ async def webhook_run_flow( ) logger.debug("Starting background task") background_tasks.add_task( # type: ignore - simple_run_flow, + simple_run_flow_task, flow=flow, input_request=input_request, ) diff --git a/src/backend/base/langflow/components/models/GoogleGenerativeAIModel.py b/src/backend/base/langflow/components/models/GoogleGenerativeAIModel.py index 377e307a9..d4e75e54b 100644 --- a/src/backend/base/langflow/components/models/GoogleGenerativeAIModel.py +++ b/src/backend/base/langflow/components/models/GoogleGenerativeAIModel.py @@ -3,44 +3,40 @@ from pydantic.v1 import SecretStr from langflow.base.constants import STREAM_INFO_TEXT from langflow.base.models.model import LCModelComponent from langflow.field_typing import LanguageModel -from langflow.io import BoolInput, DropdownInput, FloatInput, IntInput, MessageInput, Output, SecretStrInput, StrInput +from langflow.inputs import ( + BoolInput, + DropdownInput, + FloatInput, + IntInput, + MessageInput, + SecretStrInput, + StrInput, +) class GoogleGenerativeAIComponent(LCModelComponent): - display_name: str = "Google Generative AI" - description: str = "Generate text using Google Generative AI." + display_name = "Google Generative AI" + description = "Generate text using Google Generative AI." icon = "GoogleGenerativeAI" inputs = [ - SecretStrInput( - name="google_api_key", - display_name="Google API Key", - info="The Google API Key to use for the Google Generative AI.", + MessageInput(name="input_value", display_name="Input"), + IntInput( + name="max_output_tokens", + display_name="Max Output Tokens", + info="The maximum number of tokens to generate.", ), DropdownInput( name="model", display_name="Model", info="The name of the model to use.", - options=["gemini-1.5-pro", "gemini-1.5-flash"], + options=["gemini-1.5-pro", "gemini-1.5-flash", "gemini-1.0-pro", "gemini-1.0-pro-vision"], value="gemini-1.5-pro", ), - IntInput( - name="max_output_tokens", - display_name="Max Output Tokens", - info="The maximum number of tokens to generate.", - advanced=True, - ), - FloatInput( - name="temperature", - display_name="Temperature", - info="Run inference with this temperature. Must by in the closed interval [0.0, 1.0].", - value=0.1, - ), - IntInput( - name="top_k", - display_name="Top K", - info="Decode using top-k sampling: consider the set of top_k most probable tokens. Must be positive.", - advanced=True, + SecretStrInput( + name="google_api_key", + display_name="Google API Key", + info="The Google API Key to use for the Google Generative AI.", ), FloatInput( name="top_p", @@ -48,29 +44,26 @@ class GoogleGenerativeAIComponent(LCModelComponent): info="The maximum cumulative probability of tokens to consider when sampling.", advanced=True, ), + FloatInput(name="temperature", display_name="Temperature", value=0.1), + BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True), IntInput( name="n", display_name="N", info="Number of chat completions to generate for each prompt. Note that the API may not return the full n completions if duplicates are generated.", advanced=True, ), - MessageInput( - name="input_value", - display_name="Input", - info="The input to the model.", - input_types=["Text", "Data", "Prompt"], - ), - BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True), StrInput( name="system_message", display_name="System Message", info="System message to pass to the model.", advanced=True, ), - ] - outputs = [ - Output(display_name="Text", name="text_output", method="text_response"), - Output(display_name="Language Model", name="model_output", method="build_model"), + IntInput( + name="top_k", + display_name="Top K", + info="Decode using top-k sampling: consider the set of top_k most probable tokens. Must be positive.", + advanced=True, + ), ] def build_model(self) -> LanguageModel: diff --git a/src/backend/base/langflow/main.py b/src/backend/base/langflow/main.py index 085d72710..5eab2f331 100644 --- a/src/backend/base/langflow/main.py +++ b/src/backend/base/langflow/main.py @@ -37,28 +37,26 @@ class RequestCancelledMiddleware(BaseHTTPMiddleware): super().__init__(app) async def dispatch(self, request: Request, call_next): - queue: asyncio.Queue = asyncio.Queue() - - async def message_poller(sentinel, handler_task, request): - nonlocal queue - while True: - message = await request.receive() - if message["type"] == "http.disconnect": - handler_task.cancel() - return sentinel # Break the loop - - # Puts the message in the queue - await queue.put(message) - sentinel = object() - handler_task = asyncio.create_task(call_next(request)) - asyncio.create_task(message_poller(sentinel, handler_task, request)) - try: - response = await handler_task - return response - except asyncio.CancelledError: + async def cancel_handler(): + while True: + if await request.is_disconnected(): + return sentinel + await asyncio.sleep(0.1) + + handler_task = asyncio.create_task(call_next(request)) + cancel_task = asyncio.create_task(cancel_handler()) + + done, pending = await asyncio.wait([handler_task, cancel_task], return_when=asyncio.FIRST_COMPLETED) + + for task in pending: + task.cancel() + + if cancel_task in done: return Response("Request was cancelled", status_code=499) + else: + return await handler_task class JavaScriptMIMETypeMiddleware(BaseHTTPMiddleware): @@ -126,7 +124,8 @@ def create_app(): allow_headers=["*"], ) app.add_middleware(JavaScriptMIMETypeMiddleware) - app.add_middleware(RequestCancelledMiddleware) + # ! Deactivating this until we find a better solution + # app.add_middleware(RequestCancelledMiddleware) @app.middleware("http") async def flatten_query_string_lists(request: Request, call_next): diff --git a/src/backend/base/langflow/services/auth/utils.py b/src/backend/base/langflow/services/auth/utils.py index b0a35e474..4c2fdbfb4 100644 --- a/src/backend/base/langflow/services/auth/utils.py +++ b/src/backend/base/langflow/services/auth/utils.py @@ -164,15 +164,15 @@ async def get_current_user_for_websocket( def get_current_active_user(current_user: Annotated[User, Depends(get_current_user)]): if not current_user.is_active: - raise HTTPException(status_code=400, detail="Inactive user") + raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="Inactive user") return current_user def get_current_active_superuser(current_user: Annotated[User, Depends(get_current_user)]) -> User: if not current_user.is_active: - raise HTTPException(status_code=401, detail="Inactive user") + raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="Inactive user") if not current_user.is_superuser: - raise HTTPException(status_code=400, detail="The user doesn't have enough privileges") + raise HTTPException(status_code=status.HTTP_403_FORBIDDEN, detail="The user doesn't have enough privileges") return current_user @@ -324,8 +324,8 @@ def authenticate_user(username: str, password: str, db: Session = Depends(get_se if not user.is_active: if not user.last_login_at: - raise HTTPException(status_code=400, detail="Waiting for approval") - raise HTTPException(status_code=400, detail="Inactive user") + raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Waiting for approval") + raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="Inactive user") return user if verify_password(password, user.password) else None diff --git a/src/backend/base/poetry.lock b/src/backend/base/poetry.lock index 379821ebf..07d7472cf 100644 --- a/src/backend/base/poetry.lock +++ b/src/backend/base/poetry.lock @@ -1281,18 +1281,21 @@ types-requests = ">=2.31.0.2,<3.0.0.0" [[package]] name = "langsmith" -version = "0.1.81" +version = "0.1.82" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.81-py3-none-any.whl", hash = "sha256:3251d823225eef23ee541980b9d9e506367eabbb7f985a086b5d09e8f78ba7e9"}, - {file = "langsmith-0.1.81.tar.gz", hash = "sha256:585ef3a2251380bd2843a664c9a28da4a7d28432e3ee8bcebf291ffb8e1f0af0"}, + {file = "langsmith-0.1.82-py3-none-any.whl", hash = "sha256:9b3653e7d316036b0c60bf0bc3e280662d660f485a4ebd8e5c9d84f9831ae79c"}, + {file = "langsmith-0.1.82.tar.gz", hash = "sha256:c02e2bbc488c10c13b52c69d271eb40bd38da078d37b6ae7ae04a18bd48140be"}, ] [package.dependencies] orjson = ">=3.9.14,<4.0.0" -pydantic = ">=1,<3" +pydantic = [ + {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}, + {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""}, +] requests = ">=2,<3" [[package]] diff --git a/src/backend/base/pyproject.toml b/src/backend/base/pyproject.toml index ee8072a05..100bcbd2b 100644 --- a/src/backend/base/pyproject.toml +++ b/src/backend/base/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langflow-base" -version = "0.0.79" +version = "0.0.80" description = "A Python package with a built-in web application" authors = ["Langflow "] maintainers = [ diff --git a/src/frontend/src/App.tsx b/src/frontend/src/App.tsx index 1c8274e63..1a7178248 100644 --- a/src/frontend/src/App.tsx +++ b/src/frontend/src/App.tsx @@ -103,13 +103,6 @@ export default function App() { if (isAuthenticated) { try { await setupAxiosDefaults(); - - const res = await getGlobalVariables(); - setGlobalVariables(res); - - checkHasStore(); - fetchApiData(); - resolve(); } catch (error) { console.error("Failed to fetch data:", error); diff --git a/src/frontend/src/components/headerComponent/components/menuBar/index.tsx b/src/frontend/src/components/headerComponent/components/menuBar/index.tsx index ba3b0e9ad..7376bfc4f 100644 --- a/src/frontend/src/components/headerComponent/components/menuBar/index.tsx +++ b/src/frontend/src/components/headerComponent/components/menuBar/index.tsx @@ -218,7 +218,8 @@ export const MenuBar = ({}: {}): JSX.Element => { />

- + */}
)} diff --git a/src/frontend/src/contexts/authContext.tsx b/src/frontend/src/contexts/authContext.tsx index bd5c2d02c..cfdbdfb4f 100644 --- a/src/frontend/src/contexts/authContext.tsx +++ b/src/frontend/src/contexts/authContext.tsx @@ -1,9 +1,15 @@ import { createContext, useEffect, useState } from "react"; import { useNavigate } from "react-router-dom"; import Cookies from "universal-cookie"; -import { getLoggedUser, requestLogout } from "../controllers/API"; +import { + getGlobalVariables, + getLoggedUser, + requestLogout, +} from "../controllers/API"; import useAlertStore from "../stores/alertStore"; import { useFolderStore } from "../stores/foldersStore"; +import { useGlobalVariablesStore } from "../stores/globalVariablesStore/globalVariables"; +import { useStoreStore } from "../stores/storeStore"; import { Users } from "../types/api"; import { AuthContextType } from "../types/contexts/auth"; @@ -45,6 +51,11 @@ export function AuthProvider({ children }): React.ReactElement { ); const getFoldersApi = useFolderStore((state) => state.getFoldersApi); + const setGlobalVariables = useGlobalVariablesStore( + (state) => state.setGlobalVariables, + ); + const checkHasStore = useStoreStore((state) => state.checkHasStore); + const fetchApiData = useStoreStore((state) => state.fetchApiData); useEffect(() => { const storedAccessToken = cookies.get("access_token_lf"); @@ -66,8 +77,11 @@ export function AuthProvider({ children }): React.ReactElement { setUserData(user); const isSuperUser = user!.is_superuser; setIsAdmin(isSuperUser); - getFoldersApi(true, true); + const res = await getGlobalVariables(); + setGlobalVariables(res); + checkHasStore(); + fetchApiData(); }) .catch((error) => { setLoading(false); diff --git a/tests/test_user.py b/tests/test_user.py index cd1cf9165..86d4b1865 100644 --- a/tests/test_user.py +++ b/tests/test_user.py @@ -75,15 +75,15 @@ def test_user_waiting_for_approval( def test_deactivated_user_cannot_login(client, deactivated_user): login_data = {"username": deactivated_user.username, "password": "testpassword"} response = client.post("/api/v1/login", data=login_data) - assert response.status_code == 400, response.json() - assert response.json()["detail"] == "Inactive user" + assert response.status_code == 401, response.json() + assert response.json()["detail"] == "Inactive user", response.text def test_deactivated_user_cannot_access(client, deactivated_user, logged_in_headers): # Assuming the headers for deactivated_user response = client.get("/api/v1/users", headers=logged_in_headers) - assert response.status_code == 400, response.json() - assert response.json()["detail"] == "The user doesn't have enough privileges" + assert response.status_code == 403, response.json() + assert response.json()["detail"] == "The user doesn't have enough privileges", response.text def test_data_consistency_after_update(client, active_user, logged_in_headers, super_user_headers): @@ -124,7 +124,7 @@ def test_inactive_user(client): login_data = {"username": "inactiveuser", "password": "testpassword"} response = client.post("/api/v1/login", data=login_data) - assert response.status_code == 400 + assert response.status_code == 401 assert response.json()["detail"] == "Inactive user" @@ -154,7 +154,7 @@ def test_read_all_users(client, super_user_headers): def test_normal_user_cant_read_all_users(client, logged_in_headers): response = client.get("/api/v1/users", headers=logged_in_headers) - assert response.status_code == 400, response.json() + assert response.status_code == 403, response.json() assert response.json() == {"detail": "The user doesn't have enough privileges"} @@ -228,5 +228,5 @@ def test_delete_user_wrong_id(client, test_user, super_user_headers): def test_normal_user_cant_delete_user(client, test_user, logged_in_headers): user_id = test_user["id"] response = client.delete(f"/api/v1/users/{user_id}", headers=logged_in_headers) - assert response.status_code == 400 + assert response.status_code == 403 assert response.json() == {"detail": "The user doesn't have enough privileges"} From c8d37c38b4c29b977b5cdf0e7c3269b5a278a347 Mon Sep 17 00:00:00 2001 From: anovazzi1 Date: Mon, 24 Jun 2024 17:33:20 -0300 Subject: [PATCH 111/229] fix fetch data to work even with autologin true --- src/frontend/src/contexts/authContext.tsx | 2 ++ 1 file changed, 2 insertions(+) diff --git a/src/frontend/src/contexts/authContext.tsx b/src/frontend/src/contexts/authContext.tsx index cfdbdfb4f..ab845963a 100644 --- a/src/frontend/src/contexts/authContext.tsx +++ b/src/frontend/src/contexts/authContext.tsx @@ -12,6 +12,8 @@ import { useGlobalVariablesStore } from "../stores/globalVariablesStore/globalVa import { useStoreStore } from "../stores/storeStore"; import { Users } from "../types/api"; import { AuthContextType } from "../types/contexts/auth"; +import { useGlobalVariablesStore } from "../stores/globalVariablesStore/globalVariables"; +import { useStoreStore } from "../stores/storeStore"; const initialValue: AuthContextType = { isAdmin: false, From f954295731d6f1621b495eb271a3725283ca4d4f Mon Sep 17 00:00:00 2001 From: anovazzi1 Date: Mon, 24 Jun 2024 17:34:03 -0300 Subject: [PATCH 112/229] format code --- src/frontend/src/contexts/authContext.tsx | 2 ++ 1 file changed, 2 insertions(+) diff --git a/src/frontend/src/contexts/authContext.tsx b/src/frontend/src/contexts/authContext.tsx index ab845963a..50a0cf4e7 100644 --- a/src/frontend/src/contexts/authContext.tsx +++ b/src/frontend/src/contexts/authContext.tsx @@ -14,6 +14,8 @@ import { Users } from "../types/api"; import { AuthContextType } from "../types/contexts/auth"; import { useGlobalVariablesStore } from "../stores/globalVariablesStore/globalVariables"; import { useStoreStore } from "../stores/storeStore"; +import { Users } from "../types/api"; +import { AuthContextType } from "../types/contexts/auth"; const initialValue: AuthContextType = { isAdmin: false, From 2fe2024a58511dbab17a340a317cb0b0f344bec0 Mon Sep 17 00:00:00 2001 From: Cristhian Zanforlin Lousa <72977554+Cristhianzl@users.noreply.github.com> Date: Tue, 25 Jun 2024 13:21:44 -0300 Subject: [PATCH 113/229] Fix lint error version of tailwind css plugin (#2323) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit ⬆️ (package.json): update prettier-plugin-tailwindcss to version 0.6.5 ♻️ (package.json): reorder @types/lodash dependency for consistency Co-authored-by: Gabriel Luiz Freitas Almeida --- src/frontend/package-lock.json | 2 +- src/frontend/package.json | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/src/frontend/package-lock.json b/src/frontend/package-lock.json index d6b9d3b74..811237487 100644 --- a/src/frontend/package-lock.json +++ b/src/frontend/package-lock.json @@ -102,7 +102,7 @@ "postcss": "^8.4.38", "prettier": "^3.3.2", "prettier-plugin-organize-imports": "^3.2.4", - "prettier-plugin-tailwindcss": "^0.6.4", + "prettier-plugin-tailwindcss": "^0.6.5", "simple-git-hooks": "^2.11.1", "tailwindcss": "^3.4.4", "tailwindcss-dotted-background": "^1.1.0", diff --git a/src/frontend/package.json b/src/frontend/package.json index a4b10db6c..219b5c7d4 100644 --- a/src/frontend/package.json +++ b/src/frontend/package.json @@ -113,18 +113,18 @@ "@testing-library/react": "^16.0.0", "@testing-library/user-event": "^14.5.2", "@types/jest": "^29.5.12", + "@types/lodash": "4.17.5", "@types/node": "^20.14.2", "@types/react": "^18.3.3", "@types/react-dom": "^18.3.0", "@types/uuid": "^9.0.8", - "@types/lodash": "4.17.5", "@vitejs/plugin-react-swc": "^3.7.0", "autoprefixer": "^10.4.19", "eslint": "^9.5.0", "postcss": "^8.4.38", "prettier": "^3.3.2", "prettier-plugin-organize-imports": "^3.2.4", - "prettier-plugin-tailwindcss": "^0.6.4", + "prettier-plugin-tailwindcss": "^0.6.5", "simple-git-hooks": "^2.11.1", "tailwindcss": "^3.4.4", "tailwindcss-dotted-background": "^1.1.0", From 4077135ba7c302b7e2a50402a7cb911c1e56defc Mon Sep 17 00:00:00 2001 From: Cristhian Zanforlin Lousa <72977554+Cristhianzl@users.noreply.github.com> Date: Tue, 25 Jun 2024 13:23:11 -0300 Subject: [PATCH 114/229] Updating Tests and Fixing Related Bugs (#2319) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * 🐛 (tableNodeCellRender): fix templateValue check to use Object.keys ✨ (textAreaComponent): add Case component for conditional rendering ♻️ (editNodeModal): remove commented-out useEffect code ✅ (basicExamples.spec): update test selectors and increase timeout values ✅ (filterEdge.spec.ts): update test IDs to match new naming conventions ✅ (inputListComponent.spec.ts, intComponent.spec.ts): update test IDs and streamline test steps for consistency and clarity ✅ (keyPairListComponent.spec.ts): update test ID for model element ✅ (keyPairListComponent.spec.ts): add steps to test editing model options and saving changes * ✅ (tests): update end-to-end tests for chat input/output and modal components - Update test selectors for better accuracy - Add keyboard interaction in chatInputOutputUser.spec.ts - Improve file handling in chat image upload test - Refine prompt modal component tests for better validation - Enhance twoEdges.spec.ts with additional view controls * ♻️ (tests): refactor repeated click actions into reusable function in e2e tests * ✅ (tests): replace waitForTimeout with waitForSelector in end-to-end tests * ✅ (typescript_test.yml): add --debug flag to Playwright test command for better debugging * ✅ (typescript_test.yml): enable trace option in Playwright tests for better debugging * ✅ (typescript_test.yml): reduce Playwright test workers from 2 to 1 to improve stability ✅ (textInputOutput.spec.ts): add waitFor visibility checks to ensure elements are visible before interaction * ✅ (tests): update paths for test assets to correct locations ✅ (tests): add waitForSelector to ensure elements are loaded before interaction * ✅ (typescript_test.yml): increase Playwright workers from 1 to 2 to speed up tests ✅ (chatInputOutputUser.spec.ts): increase timeout for AI response to 100000ms ✅ (chatInputOutputUser.spec.ts): correct file path for image upload test ✅ (deleteComponentFlows.spec.ts): change waitFor to target last checkbox-component ✅ (store.spec.ts): increase timeout for share button to 100000ms * 🐛 (flows.py): ensure flow names are unique by appending a number if necessary * Apply Ruff formatting --------- Co-authored-by: Gabriel Luiz Freitas Almeida Co-authored-by: Cristhianzl --- .github/workflows/typescript_test.yml | 2 +- src/backend/base/langflow/api/v1/flows.py | 17 +++ .../components/tableNodeCellRender/index.tsx | 2 +- .../components/textAreaComponent/index.tsx | 68 ++++++---- .../src/modals/editNodeModal/index.tsx | 6 - .../tests/end-to-end/basicExamples.spec.ts | 30 ++-- .../tests/end-to-end/chatInputOutput.spec.ts | 2 +- .../end-to-end/chatInputOutputUser.spec.ts | 59 +++++--- .../end-to-end/codeAreaModalComponent.spec.ts | 12 +- .../end-to-end/deleteComponentFlows.spec.ts | 13 ++ .../tests/end-to-end/dragAndDrop.spec.ts | 2 +- .../tests/end-to-end/filterEdge.spec.ts | 91 ++++++++----- src/frontend/tests/end-to-end/folders.spec.ts | 2 +- .../tests/end-to-end/generalBugs.spec.ts | 5 + .../end-to-end/inputListComponent.spec.ts | 128 +++++++----------- .../tests/end-to-end/intComponent.spec.ts | 4 +- .../end-to-end/keyPairListComponent.spec.ts | 10 +- .../end-to-end/promptModalComponent.spec.ts | 27 +++- .../tests/end-to-end/saveComponents.spec.ts | 2 +- src/frontend/tests/end-to-end/store.spec.ts | 4 + .../end-to-end/textAreaModalComponent.spec.ts | 13 +- .../tests/end-to-end/textInputOutput.spec.ts | 50 ++++++- .../tests/end-to-end/toggleComponent.spec.ts | 12 +- .../tests/end-to-end/tweaks_test.spec.ts | 8 +- .../tests/end-to-end/twoEdges.spec.ts | 17 ++- .../tests/end-to-end/userSettings.spec.ts | 17 ++- 26 files changed, 381 insertions(+), 222 deletions(-) diff --git a/.github/workflows/typescript_test.yml b/.github/workflows/typescript_test.yml index be081bec6..8fd809020 100644 --- a/.github/workflows/typescript_test.yml +++ b/.github/workflows/typescript_test.yml @@ -88,7 +88,7 @@ jobs: - name: Run Playwright Tests run: | cd src/frontend - npx playwright test --shard ${{ matrix.shardIndex }}/${{ matrix.shardTotal }} --workers 2 + npx playwright test --trace on --shard ${{ matrix.shardIndex }}/${{ matrix.shardTotal }} --workers 2 - name: Upload blob report to GitHub Actions Artifacts if: always() diff --git a/src/backend/base/langflow/api/v1/flows.py b/src/backend/base/langflow/api/v1/flows.py index 800e2c088..d735a314b 100644 --- a/src/backend/base/langflow/api/v1/flows.py +++ b/src/backend/base/langflow/api/v1/flows.py @@ -209,6 +209,23 @@ def update_flow( webhook_component = get_webhook_component_in_flow(db_flow.data) db_flow.webhook = webhook_component is not None db_flow.updated_at = datetime.now(timezone.utc) + + # First check if the flow.name is unique + # there might be flows with name like: "MyFlow", "MyFlow (1)", "MyFlow (2)" + # so we need to check if the name is unique with `like` operator + # if we find a flow with the same name, we add a number to the end of the name + # based on the highest number found + flow_from_db = session.exec(select(Flow).where(Flow.id == flow_id, Flow.user_id == current_user.id)).first() + if flow_from_db: + flows = session.exec( + select(Flow).where(Flow.name.like(f"{flow.name} (%")).where(Flow.user_id == current_user.id) # type: ignore + ).all() + if flows: + numbers = [int(flow.name.split("(")[1].split(")")[0]) for flow in flows] + flow.name = f"{flow.name} ({max(numbers) + 1})" + else: + flow.name = f"{flow.name} (1)" + if db_flow.folder_id is None: default_folder = session.exec(select(Folder).where(Folder.name == DEFAULT_FOLDER_NAME)).first() if default_folder: diff --git a/src/frontend/src/components/tableComponent/components/tableNodeCellRender/index.tsx b/src/frontend/src/components/tableComponent/components/tableNodeCellRender/index.tsx index b55788134..d0c3d4e53 100644 --- a/src/frontend/src/components/tableComponent/components/tableNodeCellRender/index.tsx +++ b/src/frontend/src/components/tableComponent/components/tableNodeCellRender/index.tsx @@ -153,7 +153,7 @@ export default function TableNodeCellRender({ disabled={disabled} editNode={true} value={ - templateValue?.length === 0 || !templateValue + Object.keys(templateValue)?.length === 0 || !templateValue ? [{ "": "" }] : convertObjToArray(templateValue, templateData.type) } diff --git a/src/frontend/src/components/textAreaComponent/index.tsx b/src/frontend/src/components/textAreaComponent/index.tsx index ce42437d7..18a7f5b40 100644 --- a/src/frontend/src/components/textAreaComponent/index.tsx +++ b/src/frontend/src/components/textAreaComponent/index.tsx @@ -2,6 +2,7 @@ import { useEffect } from "react"; import { EDIT_TEXT_MODAL_TITLE } from "../../constants/constants"; import { TypeModal } from "../../constants/enums"; import GenericModal from "../../modals/genericModal"; +import { Case } from "../../shared/components/caseComponent"; import { TextAreaComponentType } from "../../types/components"; import IconComponent from "../genericIconComponent"; import { Button } from "../ui/button"; @@ -24,29 +25,31 @@ export default function TextAreaComponent({ return (
- { - onChange(event.target.value); - }} - /> -
- + { - onChange(value); - }} disabled={disabled} - > - {!editNode && ( + className={editNode ? "input-edit-node w-full" : "w-full"} + placeholder={"Type something..."} + onChange={(event) => { + onChange(event.target.value); + }} + /> + + { + onChange(value); + }} + disabled={disabled} + > + {!editNode ? ( +
- )} - -
+
+ ) : ( + + )} +
); diff --git a/src/frontend/src/modals/editNodeModal/index.tsx b/src/frontend/src/modals/editNodeModal/index.tsx index cb6f82f59..f4a368fa6 100644 --- a/src/frontend/src/modals/editNodeModal/index.tsx +++ b/src/frontend/src/modals/editNodeModal/index.tsx @@ -65,12 +65,6 @@ const EditNodeModal = forwardRef( } }, [gridApi, open]); - // useEffect(() => { - // return () => { - // setOpenWDoubleClick(false); - // }; - // }, []); - return ( diff --git a/src/frontend/tests/end-to-end/basicExamples.spec.ts b/src/frontend/tests/end-to-end/basicExamples.spec.ts index e103fff30..c5f80c362 100644 --- a/src/frontend/tests/end-to-end/basicExamples.spec.ts +++ b/src/frontend/tests/end-to-end/basicExamples.spec.ts @@ -270,12 +270,12 @@ test("Blog Writer", async ({ page }) => { "https://www.natgeokids.com/uk/discover/animals/sea-life/turtle-facts/", ); await page - .getByTestId("input-list-input_urls-0") - .nth(1) + .getByTestId("input-list-input_urls-1") + .nth(0) .fill("https://www.originaldiving.com/blog/top-ten-turtle-facts"); await page - .getByTestId("textarea-input_value") + .getByTestId("popover-anchor-input-input_value") .nth(0) .fill( "Use the references above for style to write a new blog/tutorial about turtles. Suggest non-covered topics.", @@ -284,7 +284,7 @@ test("Blog Writer", async ({ page }) => { await page.getByTestId("button_run_chat output").click(); await page.waitForTimeout(5000); await page.getByText("built successfully").last().click({ - timeout: 15000, + timeout: 30000, }); await page.getByText("Playground", { exact: true }).click(); @@ -403,17 +403,14 @@ test("Vector Store RAG", async ({ page }) => { await page.getByText("test_file.txt").isVisible(); await page.waitForTimeout(2000); - await page.getByTestId("button_run_astra db vector store").first().click(); - await page - .getByText("Astra DB Vector Store built successfully") - .last() - .click({ - timeout: 15000, - }); + await page.getByTestId("button_run_astra db").first().click(); + await page.getByText("built successfully").last().click({ + timeout: 30000, + }); await page.getByTestId("button_run_chat output").click(); await page.getByText("built successfully").last().click({ - timeout: 15000, + timeout: 30000, }); await page.getByText("Playground", { exact: true }).click(); @@ -427,15 +424,6 @@ test("Vector Store RAG", async ({ page }) => { .last() .isVisible(); - await page.getByText("Extracted Chunks", { exact: true }).last().click(); - - const inputChunksValues = await page.getByPlaceholder("Empty").inputValue(); - expect(inputChunksValues).toBe( - "this is a test file---this is a test file---this is a test file---this is a test file", - ); - - await page.getByTestId("icon-ExternalLink").last().click(); - await page.getByPlaceholder("Send a message...").last().isHidden(); await page.getByText("Memories", { exact: true }).last().click(); await page.getByText("Default Session").last().click(); diff --git a/src/frontend/tests/end-to-end/chatInputOutput.spec.ts b/src/frontend/tests/end-to-end/chatInputOutput.spec.ts index e71178040..e1adf3d88 100644 --- a/src/frontend/tests/end-to-end/chatInputOutput.spec.ts +++ b/src/frontend/tests/end-to-end/chatInputOutput.spec.ts @@ -23,7 +23,7 @@ test("chat_io_teste", async ({ page }) => { } const jsonContent = readFileSync( - "src/frontend/tests/end-to-end/assets/ChatTest.json", + "tests/end-to-end/assets/ChatTest.json", "utf-8", ); diff --git a/src/frontend/tests/end-to-end/chatInputOutputUser.spec.ts b/src/frontend/tests/end-to-end/chatInputOutputUser.spec.ts index 4de3c49e5..524312bb3 100644 --- a/src/frontend/tests/end-to-end/chatInputOutputUser.spec.ts +++ b/src/frontend/tests/end-to-end/chatInputOutputUser.spec.ts @@ -48,14 +48,21 @@ test("user must interact with chat with Input/Output", async ({ page }) => { await page.getByPlaceholder("Send a message...").fill("Hello, how are you?"); await page.getByTestId("icon-LucideSend").click(); let valueUser = await page.getByTestId("sender_name_user").textContent(); + + await page.waitForSelector('[data-testid="sender_name_ai"]', { + timeout: 100000, + }); + let valueAI = await page.getByTestId("sender_name_ai").textContent(); expect(valueUser).toBe("User"); expect(valueAI).toBe("AI"); + await page.keyboard.press("Escape"); + await page .getByTestId("textarea-input_value") - .nth(1) + .nth(0) .fill( "testtesttesttesttesttestte;.;.,;,.;,.;.,;,..,;;;;;;;;;;;;;;;;;;;;;,;.;,.;,.,;.,;.;.,~~çççççççççççççççççççççççççççççççççççççççisdajfdasiopjfaodisjhvoicxjiovjcxizopjviopasjioasfhjaiohf23432432432423423sttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttesttestççççççççççççççççççççççççççççççççç,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,!", ); @@ -73,11 +80,11 @@ test("user must interact with chat with Input/Output", async ({ page }) => { await page.getByText("Save Changes", { exact: true }).click(); await page - .getByTestId("textarea-sender_name") + .getByTestId("popover-anchor-input-sender_name") .nth(1) .fill("TestSenderNameUser"); await page - .getByTestId("textarea-sender_name") + .getByTestId("popover-anchor-input-sender_name") .nth(0) .fill("TestSenderNameAI"); @@ -150,6 +157,10 @@ test("user must be able to see output inspection", async ({ page }) => { await page.waitForTimeout(5000); + await page.waitForSelector('[data-testid="icon-ScanEye"]', { + timeout: 30000, + }); + await page.getByTestId("icon-ScanEye").nth(4).click(); await page.getByText("Sender", { exact: true }).isVisible(); @@ -206,32 +217,46 @@ test("user must be able to send an image on chat", async ({ page }) => { await page.getByText("Playground", { exact: true }).click(); - const jsonContent = readFileSync( - "src/frontend/tests/end-to-end/assets/chain.png", - "utf-8", + // Read the image file as a binary string + const filePath = "tests/end-to-end/assets/chain.png"; + const fileContent = readFileSync(filePath, "base64"); + + // Create the DataTransfer and File objects within the browser context + const dataTransfer = await page.evaluateHandle( + ({ fileContent }) => { + const dt = new DataTransfer(); + const byteCharacters = atob(fileContent); + const byteNumbers = new Array(byteCharacters.length); + for (let i = 0; i < byteCharacters.length; i++) { + byteNumbers[i] = byteCharacters.charCodeAt(i); + } + const byteArray = new Uint8Array(byteNumbers); + const file = new File([byteArray], "chain.png", { type: "image/png" }); + dt.items.add(file); + return dt; + }, + { fileContent }, ); - // Create the DataTransfer and File - const dataTransfer = await page.evaluateHandle((data) => { - const dt = new DataTransfer(); - // Convert the buffer to a hex array - const file = new File([data], "chain.png", { - type: "application/json", - }); - dt.items.add(file); - return dt; - }, jsonContent); - + // Locate the target element const element = await page.getByPlaceholder("Send a message..."); + // Dispatch the drop event on the target element await element.dispatchEvent("drop", { dataTransfer }); + await page.waitForTimeout(4000); + await page.getByText("chain.png").isVisible(); await page.getByTestId("icon-LucideSend").click(); await page.waitForTimeout(2000); await page.getByText("chain.png").isVisible(); await page.getByText("Close", { exact: true }).click(); + + await page.waitForSelector('[data-testid="icon-ScanEye"]', { + timeout: 30000, + }); + await page.getByTestId("icon-ScanEye").nth(4).click(); await page.getByText("Restart").isHidden(); }); diff --git a/src/frontend/tests/end-to-end/codeAreaModalComponent.spec.ts b/src/frontend/tests/end-to-end/codeAreaModalComponent.spec.ts index 6d9ac2d02..044065d18 100644 --- a/src/frontend/tests/end-to-end/codeAreaModalComponent.spec.ts +++ b/src/frontend/tests/end-to-end/codeAreaModalComponent.spec.ts @@ -31,7 +31,7 @@ test("CodeAreaModalComponent", async ({ page }) => { await page.waitForTimeout(1000); await page - .getByTestId("experimentalPython Function") + .getByTestId("prototypesPython Function") .dragTo(page.locator('//*[@id="react-flow-id"]')); await page.mouse.up(); await page.mouse.down(); @@ -65,19 +65,9 @@ class PythonFunctionComponent(CustomComponent): await page.locator("textarea").fill(wCode); await page.locator('//*[@id="checkAndSaveBtn"]').click(); await page.waitForTimeout(1000); - // expect( - // await page.getByText("invalid syntax (, line 1)").isVisible() - // ).toBeTruthy(); await page.locator("textarea").press("Control+a"); await page.locator("textarea").fill(wCode); await page.locator("textarea").fill(customComponentCode); await page.locator('//*[@id="checkAndSaveBtn"]').click(); await page.waitForTimeout(1000); - - // await page.getByTestId("code-button-modal").click(); - // const inputCodeValue = await page - // .locator('//*[@id="codeValue"]') - // .inputValue(); - - // expect(inputCodeValue).toContain("def python_function(text: str) -> str"); }); diff --git a/src/frontend/tests/end-to-end/deleteComponentFlows.spec.ts b/src/frontend/tests/end-to-end/deleteComponentFlows.spec.ts index 7992dcb6e..9099727b6 100644 --- a/src/frontend/tests/end-to-end/deleteComponentFlows.spec.ts +++ b/src/frontend/tests/end-to-end/deleteComponentFlows.spec.ts @@ -17,7 +17,14 @@ test("should delete a flow", async ({ page }) => { await page.waitForTimeout(5000); await page.getByText("My Collection").nth(0).click(); await page.getByText("Website Content QA").first().isVisible(); + + await page.getByLabel("checkbox-component").last().waitFor({ + state: "visible", + timeout: 30000, // Timeout of 30 seconds + }); + await page.getByLabel("checkbox-component").first().click(); + await page.getByTestId("icon-Trash2").click(); await page .getByText("Are you sure you want to delete the selected component?") @@ -36,6 +43,12 @@ test("should delete a component", async ({ page }) => { await page.getByText("My Collection").nth(0).click(); await page.getByText("Components").first().click(); await page.getByText("Basic RAG").first().isVisible(); + + await page.getByLabel("checkbox-component").last().waitFor({ + state: "visible", + timeout: 30000, // Timeout of 30 seconds + }); + await page.getByLabel("checkbox-component").first().click(); await page.getByTestId("icon-Trash2").click(); await page diff --git a/src/frontend/tests/end-to-end/dragAndDrop.spec.ts b/src/frontend/tests/end-to-end/dragAndDrop.spec.ts index 03d11aaf7..ee1789d2d 100644 --- a/src/frontend/tests/end-to-end/dragAndDrop.spec.ts +++ b/src/frontend/tests/end-to-end/dragAndDrop.spec.ts @@ -26,7 +26,7 @@ test.describe("drag and drop test", () => { await page.locator("span").filter({ hasText: "My Collection" }).isVisible(); // Read your file into a buffer. const jsonContent = readFileSync( - "src/frontend/tests/end-to-end/assets/collection.json", + "tests/end-to-end/assets/collection.json", "utf-8", ); diff --git a/src/frontend/tests/end-to-end/filterEdge.spec.ts b/src/frontend/tests/end-to-end/filterEdge.spec.ts index a85f2c3e5..77bef251d 100644 --- a/src/frontend/tests/end-to-end/filterEdge.spec.ts +++ b/src/frontend/tests/end-to-end/filterEdge.spec.ts @@ -44,24 +44,40 @@ test("LLMChain - Tooltip", async ({ page }) => { ) .hover() .then(async () => { - await expect(page.getByTestId("tooltip-Chains").first()).toBeVisible(); await expect( - page.getByTestId("tooltip-Model Specs").first(), + page.getByTestId("available-output-chains").first(), ).toBeVisible(); await expect( - page.getByTestId("tooltip-Vector Search").first(), + page.getByTestId("available-output-textsplitters").first(), ).toBeVisible(); await expect( - page.getByTestId("tooltip-Text Splitters").first(), + page.getByTestId("available-output-retrievers").first(), ).toBeVisible(); await expect( - page.getByTestId("tooltip-Retrievers").first(), + page.getByTestId("available-output-prototypes").first(), ).toBeVisible(); - await expect(page.getByTestId("tooltip-Tools").first()).toBeVisible(); - await expect(page.getByTestId("tooltip-Memories").first()).toBeVisible(); - await expect(page.getByTestId("tooltip-Agents").first()).toBeVisible(); - await expect(page.getByTestId("tooltip-Helpers").first()).toBeVisible(); - await expect(page.getByTestId("tooltip-Utilities").first()).toBeVisible(); + await expect( + page.getByTestId("available-output-tools").first(), + ).toBeVisible(); + await expect( + page.getByTestId("available-output-memories").first(), + ).toBeVisible(); + await expect( + page.getByTestId("available-output-toolkits").first(), + ).toBeVisible(); + await expect( + page.getByTestId("available-output-chains").first(), + ).toBeVisible(); + await expect( + page.getByTestId("available-output-agents").first(), + ).toBeVisible(); + await expect( + page.getByTestId("available-output-helpers").first(), + ).toBeVisible(); + await expect( + page.getByTestId("available-output-langchain_utilities").first(), + ).toBeVisible(); + await page.getByTestId("icon-X").click(); await page.waitForTimeout(500); }); @@ -77,12 +93,10 @@ test("LLMChain - Tooltip", async ({ page }) => { .hover() .then(async () => { await expect( - page.getByTestId("tooltip-Model Specs").first(), + page.getByTestId("available-input-models").first(), ).toBeVisible(); await page.waitForTimeout(2000); - await expect(page.getByTestId("tooltip-Models").first()).toBeVisible(); - await page.getByTestId("icon-Search").click(); await page.waitForTimeout(500); @@ -100,12 +114,18 @@ test("LLMChain - Tooltip", async ({ page }) => { .then(async () => { await page.waitForTimeout(2000); - await expect(page.getByTestId("tooltip-Chains").first()).toBeVisible(); await expect( - page.getByTestId("tooltip-Experimental").first(), + page.getByTestId("available-input-chains").first(), + ).toBeVisible(); + await expect( + page.getByTestId("available-input-prototypes").first(), + ).toBeVisible(); + await expect( + page.getByTestId("available-input-agents").first(), + ).toBeVisible(); + await expect( + page.getByTestId("available-input-helpers").first(), ).toBeVisible(); - await expect(page.getByTestId("tooltip-Agents").first()).toBeVisible(); - await expect(page.getByTestId("tooltip-Helpers").first()).toBeVisible(); await page.waitForTimeout(500); }); @@ -176,26 +196,30 @@ test("LLMChain - Filter", async ({ page }) => { ) .click(); - await expect(page.getByTestId("disclosure-model specs")).toBeVisible(); - await expect(page.getByTestId("model_specsAnthropic").first()).toBeVisible(); - await expect(page.getByTestId("model_specsAmazon Bedrock")).toBeVisible(); - await expect(page.getByTestId("model_specsAzureChatOpenAI")).toBeVisible(); - await expect(page.getByTestId("model_specsChatLiteLLM")).toBeVisible(); - await expect(page.getByTestId("model_specsChatOllama")).toBeVisible(); - await expect(page.getByTestId("model_specsChatOpenAI")).toBeVisible(); - await expect(page.getByTestId("model_specsChatVertexAI")).toBeVisible(); + await expect(page.getByTestId("disclosure-models")).toBeVisible(); await expect( - page.getByTestId("model_specsGoogle Generative AI"), + page.getByTestId("modelsGoogle Generative AI").first(), + ).toBeVisible(); + await expect(page.getByTestId("chainsLLMChain").first()).toBeVisible(); + await expect( + page.getByTestId("langchain_utilitiesSearchApi").first(), ).toBeVisible(); await expect( - page.getByTestId("model_specsHugging Face Inference API"), + page.getByTestId("memoriesAstra DB Message Reader").first(), ).toBeVisible(); - await expect(page.getByTestId("model_specsOllama")).toBeVisible(); await expect( - page.getByTestId("model_specsQianfanChatEndpoint"), + page.getByTestId("prototypesFlow as Tool").first(), ).toBeVisible(); - await expect(page.getByTestId("model_specsQianfanLLMEndpoint")).toBeVisible(); - await expect(page.getByTestId("model_specsVertexAI")).toBeVisible(); + await expect( + page.getByTestId("retrieversAmazon Kendra Retriever").first(), + ).toBeVisible(); + await expect( + page.getByTestId("textsplittersCharacterTextSplitter").first(), + ).toBeVisible(); + await expect( + page.getByTestId("toolkitsVectorStoreInfo").first(), + ).toBeVisible(); + await expect(page.getByTestId("toolsSearchApi").first()).toBeVisible(); await page.getByPlaceholder("Search").click(); @@ -219,7 +243,6 @@ test("LLMChain - Filter", async ({ page }) => { .click(); await expect(page.getByTestId("disclosure-models")).toBeVisible(); - await expect(page.getByTestId("disclosure-model specs")).toBeVisible(); await page .locator( @@ -227,10 +250,8 @@ test("LLMChain - Filter", async ({ page }) => { ) .click(); - await expect(page.getByTestId("disclosure-saved")).toBeVisible(); - await expect(page.getByTestId("disclosure-helpers")).toBeVisible(); await expect(page.getByTestId("disclosure-agents")).toBeVisible(); await expect(page.getByTestId("disclosure-chains")).toBeVisible(); - await expect(page.getByTestId("disclosure-experimental")).toBeVisible(); + await expect(page.getByTestId("disclosure-prototypes")).toBeVisible(); }); diff --git a/src/frontend/tests/end-to-end/folders.spec.ts b/src/frontend/tests/end-to-end/folders.spec.ts index 99ed07669..d049b39f9 100644 --- a/src/frontend/tests/end-to-end/folders.spec.ts +++ b/src/frontend/tests/end-to-end/folders.spec.ts @@ -57,7 +57,7 @@ test("add folder by drag and drop", async ({ page }) => { await page.waitForTimeout(2000); const jsonContent = readFileSync( - "src/frontend/tests/end-to-end/assets/collection.json", + "tests/end-to-end/assets/collection.json", "utf-8", ); diff --git a/src/frontend/tests/end-to-end/generalBugs.spec.ts b/src/frontend/tests/end-to-end/generalBugs.spec.ts index 11ec86af4..a0e435fd5 100644 --- a/src/frontend/tests/end-to-end/generalBugs.spec.ts +++ b/src/frontend/tests/end-to-end/generalBugs.spec.ts @@ -85,6 +85,11 @@ test("erase button should clear the chat messages", async ({ page }) => { await page.getByPlaceholder("Send a message...").fill("Hello, how are you?"); await page.getByTestId("icon-LucideSend").click(); let valueUser = await page.getByTestId("sender_name_user").textContent(); + + await page.waitForSelector('[data-testid="sender_name_ai"]', { + timeout: 30000, + }); + let valueAI = await page.getByTestId("sender_name_ai").textContent(); expect(valueUser).toBe("User"); diff --git a/src/frontend/tests/end-to-end/inputListComponent.spec.ts b/src/frontend/tests/end-to-end/inputListComponent.spec.ts index e28ba67b2..fa91b685f 100644 --- a/src/frontend/tests/end-to-end/inputListComponent.spec.ts +++ b/src/frontend/tests/end-to-end/inputListComponent.spec.ts @@ -24,11 +24,11 @@ test("InputListComponent", async ({ page }) => { await page.waitForTimeout(3000); await page.getByTestId("extended-disclosure").click(); await page.getByPlaceholder("Search").click(); - await page.getByPlaceholder("Search").fill("astradb"); + await page.getByPlaceholder("Search").fill("url"); await page.waitForTimeout(1000); await page - .getByTestId("vectorsearchAstra DB Search") + .getByTestId("dataURL") .dragTo(page.locator('//*[@id="react-flow-id"]')); await page.mouse.up(); await page.mouse.down(); @@ -36,95 +36,71 @@ test("InputListComponent", async ({ page }) => { await page.getByTitle("zoom out").click(); await page.getByTitle("zoom out").click(); await page.getByTitle("zoom out").click(); + + await page.getByTestId("input-list-input_urls-0").fill("test test test test"); + + await page.getByTestId("input-list-plus-btn_urls-0").click(); + + await page.getByTestId("input-list-plus-btn_urls-0").click(); + + await page + .getByTestId("input-list-input_urls-1") + .fill("test1 test1 test1 test1"); + + await page + .getByTestId("input-list-input_urls-2") + .fill("test2 test2 test2 test2"); + await page.getByTestId("div-generic-node").click(); await page.getByTestId("more-options-modal").click(); await page.getByTestId("edit-button-modal").click(); - expect( - await page.getByTestId("showmetadata_indexing_exclude").isChecked(), - ).toBeFalsy(); - await page.getByTestId("showmetadata_indexing_exclude").click(); - expect( - await page.getByTestId("showmetadata_indexing_exclude").isChecked(), - ).toBeTruthy(); - - expect( - await page.getByTestId("showmetadata_indexing_include").isChecked(), - ).toBeFalsy(); - await page.getByTestId("showmetadata_indexing_include").click(); - expect( - await page.getByTestId("showmetadata_indexing_include").isChecked(), - ).toBeTruthy(); - - await page - .getByTestId("input-list-input-edit_metadata_indexing_include-0") - .fill("test test test test"); - - await page - .getByTestId("input-list-plus-btn-edit_metadata_indexing_include-0") - .click(); - - await page - .getByTestId("input-list-input-edit_metadata_indexing_include-1") - .fill("test1 test1 test1 test1"); - - await page.getByText("Save Changes", { exact: true }).click(); - - await page - .getByTestId("input-list-input_metadata_indexing_include-0") - .fill("test test test test"); - const value0 = await page - .getByTestId("input-list-input_metadata_indexing_include-0") + .getByTestId("input-list-input-edit_urls-0") .inputValue(); const value1 = await page - .getByTestId("input-list-input_metadata_indexing_include-1") + .getByTestId("input-list-input-edit_urls-1") + .inputValue(); + + const value2 = await page + .getByTestId("input-list-input-edit_urls-2") .inputValue(); if ( value0 !== "test test test test" || - value1 !== "test1 test1 test1 test1" + value1 !== "test1 test1 test1 test1" || + value2 !== "test2 test2 test2 test2" ) { expect(false).toBeTruthy(); } - await page - .getByTestId("input-list-minus-btn_metadata_indexing_include-1") - .click(); + await page.getByTestId("input-list-minus-btn-edit_urls-1").click(); const plusButtonLocator = page.getByTestId( - "input-list-plus-btn_metadata_indexing_include-1", + "input-list-minus-btn-edit_urls-1", ); const elementCount = await plusButtonLocator?.count(); - if (elementCount > 0) { + if (elementCount > 1) { expect(false).toBeTruthy(); } - await page - .getByTestId("input-list-plus-btn_metadata_indexing_include-0") - .click(); - await page - .getByTestId("input-list-plus-btn_metadata_indexing_include-0") - .click(); - await page - .getByTestId("input-list-plus-btn_metadata_indexing_include-0") - .click(); - await page - .getByTestId("input-list-plus-btn_metadata_indexing_include-0") - .click(); + await page.getByText("Save Changes", { exact: true }).click(); + await page.getByTestId("input-list-minus-btn_urls-2").isHidden(); + + await page.getByTestId("input-list-plus-btn_urls-0").click(); + await page.getByTestId("input-list-plus-btn_urls-0").click(); + + await page.getByTestId("input-list-input_urls-0").fill("test test test test"); await page - .getByTestId("input-list-input_metadata_indexing_include-0") - .fill("test test test test"); - await page - .getByTestId("input-list-input_metadata_indexing_include-1") + .getByTestId("input-list-input_urls-1") .fill("test1 test1 test1 test1"); await page - .getByTestId("input-list-input_metadata_indexing_include-2") + .getByTestId("input-list-input_urls-2") .fill("test2 test2 test2 test2"); await page - .getByTestId("input-list-input_metadata_indexing_include-3") + .getByTestId("input-list-input_urls-3") .fill("test3 test3 test3 test3"); await page.getByTestId("div-generic-node").click(); @@ -132,16 +108,16 @@ test("InputListComponent", async ({ page }) => { await page.getByTestId("edit-button-modal").click(); const value0Edit = await page - .getByTestId("input-list-input-edit_metadata_indexing_include-0") + .getByTestId("input-list-input-edit_urls-0") .inputValue(); const value1Edit = await page - .getByTestId("input-list-input-edit_metadata_indexing_include-1") + .getByTestId("input-list-input-edit_urls-1") .inputValue(); const value2Edit = await page - .getByTestId("input-list-input-edit_metadata_indexing_include-2") + .getByTestId("input-list-input-edit_urls-2") .inputValue(); const value3Edit = await page - .getByTestId("input-list-input-edit_metadata_indexing_include-3") + .getByTestId("input-list-input-edit_urls-3") .inputValue(); if ( @@ -153,23 +129,17 @@ test("InputListComponent", async ({ page }) => { expect(false).toBeTruthy(); } - await page - .getByTestId("input-list-minus-btn-edit_metadata_indexing_include-1") - .click(); - await page - .getByTestId("input-list-minus-btn-edit_metadata_indexing_include-1") - .click(); - await page - .getByTestId("input-list-minus-btn-edit_metadata_indexing_include-1") - .click(); + await page.getByTestId("input-list-minus-btn-edit_urls-1").click(); + await page.getByTestId("input-list-minus-btn-edit_urls-1").click(); + await page.getByTestId("input-list-minus-btn-edit_urls-1").click(); const plusButtonLocatorEdit0 = await page.getByTestId( - "input-list-plus-btn-edit_metadata_indexing_include-0", + "input-list-plus-btn-edit_urls-0", ); const elementCountEdit0 = await plusButtonLocatorEdit0?.count(); const plusButtonLocatorEdit2 = await page.getByTestId( - "input-list-plus-btn-edit_metadata_indexing_include-2", + "input-list-plus-btn-edit_urls-1", ); const elementCountEdit2 = await plusButtonLocatorEdit2?.count(); @@ -178,13 +148,13 @@ test("InputListComponent", async ({ page }) => { } const minusButtonLocatorEdit1 = await page.getByTestId( - "input-list-minus-btn-edit_metadata_indexing_include-1", + "input-list-minus-btn-edit_urls-1", ); const elementCountMinusEdit1 = await minusButtonLocatorEdit1?.count(); const minusButtonLocatorEdit2 = await page.getByTestId( - "input-list-minus-btn-edit_metadata_indexing_include-2", + "input-list-minus-btn-edit_urls-2", ); const elementCountMinusEdit2 = await minusButtonLocatorEdit2?.count(); diff --git a/src/frontend/tests/end-to-end/intComponent.spec.ts b/src/frontend/tests/end-to-end/intComponent.spec.ts index aa54ac5b4..30522d397 100644 --- a/src/frontend/tests/end-to-end/intComponent.spec.ts +++ b/src/frontend/tests/end-to-end/intComponent.spec.ts @@ -30,7 +30,7 @@ test("IntComponent", async ({ page }) => { await page.waitForTimeout(1000); await page - .getByTestId("model_specsChatOpenAI") + .getByTestId("modelsOpenAI") .first() .dragTo(page.locator('//*[@id="react-flow-id"]')); await page.mouse.up(); @@ -65,7 +65,7 @@ test("IntComponent", async ({ page }) => { expect(false).toBeTruthy(); } - await page.getByTestId("title-ChatOpenAI").click(); + await page.getByTestId("title-OpenAI").click(); await page.getByTitle("fit view").click(); await page.getByTitle("zoom out").click(); await page.getByTitle("zoom out").click(); diff --git a/src/frontend/tests/end-to-end/keyPairListComponent.spec.ts b/src/frontend/tests/end-to-end/keyPairListComponent.spec.ts index 31a4521ae..685f5b4fd 100644 --- a/src/frontend/tests/end-to-end/keyPairListComponent.spec.ts +++ b/src/frontend/tests/end-to-end/keyPairListComponent.spec.ts @@ -30,7 +30,7 @@ test("KeypairListComponent", async ({ page }) => { await page.waitForTimeout(1000); await page - .getByTestId("model_specsAmazon Bedrock") + .getByTestId("modelsAmazon Bedrock") .dragTo(page.locator('//*[@id="react-flow-id"]')); await page.mouse.up(); await page.mouse.down(); @@ -38,6 +38,14 @@ test("KeypairListComponent", async ({ page }) => { await page.getByTitle("zoom out").click(); await page.getByTitle("zoom out").click(); await page.getByTitle("zoom out").click(); + + await page.getByTestId("more-options-modal").click(); + await page.getByTestId("edit-button-modal").click(); + + await page.getByTestId("showmodel_kwargs").click(); + expect(await page.getByTestId("showmodel_kwargs").isChecked()).toBeTruthy(); + await page.getByText("Save Changes", { exact: true }).click(); + await page.locator('//*[@id="keypair0"]').click(); await page.locator('//*[@id="keypair0"]').fill("testtesttesttest"); await page.locator('//*[@id="keypair100"]').click(); diff --git a/src/frontend/tests/end-to-end/promptModalComponent.spec.ts b/src/frontend/tests/end-to-end/promptModalComponent.spec.ts index b91cb6ed5..74bc44480 100644 --- a/src/frontend/tests/end-to-end/promptModalComponent.spec.ts +++ b/src/frontend/tests/end-to-end/promptModalComponent.spec.ts @@ -72,6 +72,8 @@ test("PromptTemplateComponent", async ({ page }) => { expect(false).toBeTruthy(); } + await page.getByTestId("div-generic-node").click(); + await page.getByTestId("more-options-modal").click(); await page.getByTestId("save-button-modal").click(); @@ -102,13 +104,16 @@ test("PromptTemplateComponent", async ({ page }) => { await page.getByTestId("more-options-modal").click(); await page.getByTestId("edit-button-modal").click(); - value = await page.locator('//*[@id="textarea-edit-prompt"]').inputValue(); + value = + (await page.locator('//*[@id="textarea-edit-prompt"]').textContent()) ?? ""; if (value != "prompt_value_!@#!@#") { expect(false).toBeTruthy(); } - value = await page.locator('//*[@id="textarea-edit-prompt1"]').inputValue(); + value = + (await page.locator('//*[@id="textarea-edit-prompt1"]').textContent()) ?? + ""; if (value != "prompt_name_test_123123!@#!@#") { expect(false).toBeTruthy(); @@ -122,13 +127,20 @@ test("PromptTemplateComponent", async ({ page }) => { expect(false).toBeTruthy(); } + await page.locator('//*[@id="textarea-edit-prompt1"]').click(); await page - .locator('//*[@id="textarea-edit-prompt1"]') + .getByTestId("text-area-modal") .fill("prompt_edit_test_12312312321!@#$"); + + await page.getByText("Finish Editing", { exact: true }).click(); + + await page.locator('//*[@id="textarea-edit-prompt"]').click(); await page - .locator('//*[@id="textarea-edit-prompt"]') + .getByTestId("text-area-modal") .fill("prompt_edit_test_44444444444!@#$"); + await page.getByText("Finish Editing", { exact: true }).click(); + await page.locator('//*[@id="showtemplate"]').click(); expect(await page.locator('//*[@id="showtemplate"]').isChecked()).toBeFalsy(); @@ -174,13 +186,16 @@ test("PromptTemplateComponent", async ({ page }) => { await page.locator('//*[@id="showprompt1"]').click(); expect(await page.locator('//*[@id="showprompt1"]').isChecked()).toBeTruthy(); - value = await page.locator('//*[@id="textarea-edit-prompt"]').inputValue(); + value = + (await page.locator('//*[@id="textarea-edit-prompt"]').textContent()) ?? ""; if (value != "prompt_edit_test_44444444444!@#$") { expect(false).toBeTruthy(); } - value = await page.locator('//*[@id="textarea-edit-prompt1"]').inputValue(); + value = + (await page.locator('//*[@id="textarea-edit-prompt1"]').textContent()) ?? + ""; if (value != "prompt_edit_test_12312312321!@#$") { expect(false).toBeTruthy(); diff --git a/src/frontend/tests/end-to-end/saveComponents.spec.ts b/src/frontend/tests/end-to-end/saveComponents.spec.ts index fa9dbbc00..17be7622b 100644 --- a/src/frontend/tests/end-to-end/saveComponents.spec.ts +++ b/src/frontend/tests/end-to-end/saveComponents.spec.ts @@ -26,7 +26,7 @@ test.describe("save component tests", () => { // Read your file into a buffer. const jsonContent = readFileSync( - "src/frontend/tests/end-to-end/assets/flow_group_test.json", + "tests/end-to-end/assets/flow_group_test.json", "utf-8", ); diff --git a/src/frontend/tests/end-to-end/store.spec.ts b/src/frontend/tests/end-to-end/store.spec.ts index bcd5ec15b..9ca0b040d 100644 --- a/src/frontend/tests/end-to-end/store.spec.ts +++ b/src/frontend/tests/end-to-end/store.spec.ts @@ -259,6 +259,10 @@ test("should share component with share button", async ({ page }) => { await page.getByText("Save").last().click(); await page.getByText("Close").last().click(); + await page.waitForSelector('[data-testid="icon-Share3"]', { + timeout: 100000, + }); + await page.getByTestId("icon-Share3").first().click(); await page.getByText("Name:").isVisible(); await page.getByText("Description:").isVisible(); diff --git a/src/frontend/tests/end-to-end/textAreaModalComponent.spec.ts b/src/frontend/tests/end-to-end/textAreaModalComponent.spec.ts index 590d43933..54cb1f1ad 100644 --- a/src/frontend/tests/end-to-end/textAreaModalComponent.spec.ts +++ b/src/frontend/tests/end-to-end/textAreaModalComponent.spec.ts @@ -21,8 +21,17 @@ test("TextAreaModalComponent", async ({ page }) => { } await page.getByTestId("blank-flow").click(); - await page.waitForTimeout(3000); - await page.getByTestId("extended-disclosure").click(); + + await page.waitForSelector('[data-testid="extended-disclosure"]', { + timeout: 30000, + }); + const focusElementsOnBoard = async ({ page }) => { + const focusElements = await page.getByTestId("extended-disclosure"); + await focusElements.click(); + }; + + await focusElementsOnBoard({ page }); + await page.getByPlaceholder("Search").click(); await page.getByPlaceholder("Search").fill("prompt"); diff --git a/src/frontend/tests/end-to-end/textInputOutput.spec.ts b/src/frontend/tests/end-to-end/textInputOutput.spec.ts index 586e1361e..40b054c59 100644 --- a/src/frontend/tests/end-to-end/textInputOutput.spec.ts +++ b/src/frontend/tests/end-to-end/textInputOutput.spec.ts @@ -29,8 +29,17 @@ test("TextInputOutputComponent", async ({ page }) => { await page.waitForTimeout(1000); await page.getByTestId("blank-flow").click(); - await page.waitForTimeout(3000); - await page.getByTestId("extended-disclosure").click(); + await page.waitForSelector('[data-testid="extended-disclosure"]', { + timeout: 30000, + }); + + const focusElementsOnBoard = async ({ page }) => { + const focusElements = await page.getByTestId("extended-disclosure"); + focusElements.click(); + }; + + await focusElementsOnBoard({ page }); + await page.getByPlaceholder("Search").click(); await page.getByPlaceholder("Search").fill("text input"); await page.waitForTimeout(1000); @@ -56,7 +65,15 @@ test("TextInputOutputComponent", async ({ page }) => { await page.getByTitle("zoom out").click(); await page.getByTitle("zoom out").click(); - // Click and hold on the first element + await page + .locator( + '//*[@id="react-flow-id"]/div/div[1]/div/div/div[2]/div[1]/div/div[2]/div[5]/button/div[1]', + ) + .waitFor({ + state: "visible", + timeout: 30000, + }); + await page .locator( '//*[@id="react-flow-id"]/div/div[1]/div/div/div[2]/div[1]/div/div[2]/div[5]/button/div[1]', @@ -64,6 +81,15 @@ test("TextInputOutputComponent", async ({ page }) => { .hover(); await page.mouse.down(); + await page + .locator( + '//*[@id="react-flow-id"]/div/div[1]/div/div/div[2]/div[2]/div/div[2]/div[3]/div/button/div[1]', + ) + .waitFor({ + state: "visible", + timeout: 30000, + }); + // Move to the second element await page .locator( @@ -88,6 +114,15 @@ test("TextInputOutputComponent", async ({ page }) => { await page.getByTitle("zoom out").click(); await page.getByTitle("zoom out").click(); + await page + .locator( + '//*[@id="react-flow-id"]/div/div[1]/div/div/div[2]/div[2]/div/div[2]/div[15]/button/div[1]', + ) + .waitFor({ + state: "visible", + timeout: 30000, + }); + // Click and hold on the first element await page .locator( @@ -96,6 +131,15 @@ test("TextInputOutputComponent", async ({ page }) => { .hover(); await page.mouse.down(); + await page + .locator( + '//*[@id="react-flow-id"]/div/div[1]/div/div/div[2]/div[3]/div/div[2]/div[3]/div/button/div[1]', + ) + .waitFor({ + state: "visible", + timeout: 30000, + }); + // Move to the second element await page .locator( diff --git a/src/frontend/tests/end-to-end/toggleComponent.spec.ts b/src/frontend/tests/end-to-end/toggleComponent.spec.ts index 58d909af4..5c8eef429 100644 --- a/src/frontend/tests/end-to-end/toggleComponent.spec.ts +++ b/src/frontend/tests/end-to-end/toggleComponent.spec.ts @@ -21,8 +21,16 @@ test("ToggleComponent", async ({ page }) => { } await page.getByTestId("blank-flow").click(); - await page.waitForTimeout(3000); - await page.getByTestId("extended-disclosure").click(); + + await page.waitForSelector('[data-testid="extended-disclosure"]', { + timeout: 30000, + }); + const focusElementsOnBoard = async ({ page }) => { + const focusElements = await page.getByTestId("extended-disclosure"); + focusElements.click(); + }; + + await focusElementsOnBoard({ page }); await page.getByPlaceholder("Search").click(); await page.getByPlaceholder("Search").fill("directory"); diff --git a/src/frontend/tests/end-to-end/tweaks_test.spec.ts b/src/frontend/tests/end-to-end/tweaks_test.spec.ts index 871e8a2ba..bc4ab7c56 100644 --- a/src/frontend/tests/end-to-end/tweaks_test.spec.ts +++ b/src/frontend/tests/end-to-end/tweaks_test.spec.ts @@ -108,7 +108,13 @@ test("check if tweaks are updating when someothing on the flow changes", async ( .getByTestId("popover-anchor-input-persist_directory") .fill("persist_directory_123123123!@#$&*(&%$@"); - await page.getByText("API", { exact: true }).first().click(); + const focusElementsOnBoard = async ({ page }) => { + await page.waitForSelector("text=API", { timeout: 30000 }); + const focusElements = await page.getByText("API", { exact: true }).first(); + await focusElements.click(); + }; + + await focusElementsOnBoard({ page }); await page.getByText("Tweaks").nth(1).click(); diff --git a/src/frontend/tests/end-to-end/twoEdges.spec.ts b/src/frontend/tests/end-to-end/twoEdges.spec.ts index abae18ba3..b40ef8a4a 100644 --- a/src/frontend/tests/end-to-end/twoEdges.spec.ts +++ b/src/frontend/tests/end-to-end/twoEdges.spec.ts @@ -24,10 +24,23 @@ test("user should be able to see multiple edges and interact with them", async ( await page.waitForTimeout(1000); await page.getByText("Vector Store RAG", { exact: true }).last().click(); - await page.waitForTimeout(3000); + await page.waitForTimeout(5000); await page.getByText("Retriever", { exact: true }).first().isVisible(); await page.getByText("Search Results", { exact: true }).first().isVisible(); - await page.getByTestId("icon-Eye").nth(24).click(); + + const focusElementsOnBoard = async ({ page }) => { + await page.waitForSelector('[title="fit view"]', { timeout: 30000 }); + const focusElements = await page.getByTitle("fit view"); + await focusElements.click(); + }; + + await focusElementsOnBoard({ page }); + + await page.getByTitle("zoom out").click(); + await page.getByTitle("zoom out").click(); + await page.getByTitle("zoom out").click(); + + await page.getByTestId("output-inspection-retriever").first().click(); await page.getByText("Retriever", { exact: true }).first().isHidden(); await page.getByTestId("icon-ChevronDown").last().isVisible(); await page.getByTestId("icon-ChevronDown").last().click(); diff --git a/src/frontend/tests/end-to-end/userSettings.spec.ts b/src/frontend/tests/end-to-end/userSettings.spec.ts index df760cbca..1876031fc 100644 --- a/src/frontend/tests/end-to-end/userSettings.spec.ts +++ b/src/frontend/tests/end-to-end/userSettings.spec.ts @@ -62,10 +62,19 @@ test("should interact with global variables", async ({ page }) => { await page.getByText(randomName).isVisible(); - await page - .getByLabel("Press Space to toggle all rows selection (unchecked)") - .nth(0) - .click(); + const focusElementsOnBoard = async ({ page }) => { + await page.waitForSelector( + '[aria-label="Press Space to toggle all rows selection (unchecked)"]', + { timeout: 30000 }, + ); + const focusElements = await page + .getByLabel("Press Space to toggle all rows selection (unchecked)") + .first(); + await focusElements.click(); + }; + + await focusElementsOnBoard({ page }); + await page.getByTestId("icon-Trash2").click(); await page.getByText("No data available").isVisible(); }); From 791bd70c040611ab44aa0d34614bf8d482c791c0 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Tue, 25 Jun 2024 14:12:22 -0300 Subject: [PATCH 115/229] chore: Fix curl command in release.yml to wait for server start --- .github/workflows/release.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml index 97e175cfd..9f84be063 100644 --- a/.github/workflows/release.yml +++ b/.github/workflows/release.yml @@ -62,7 +62,7 @@ jobs: python -m langflow run --host 127.0.0.1 --port 7860 & SERVER_PID=$! # Wait for the server to start - timeout 120 bash -c 'until curl -f http://127.0.0.1:7860/auto_login do sleep 2; done' || (echo "Server did not start in time" && kill $SERVER_PID && exit 1) + timeout 120 bash -c 'until curl -f http://127.0.0.1:7860/auto_login; do sleep 2; done' || (echo "Server did not start in time" && kill $SERVER_PID && exit 1) # Terminate the server kill $SERVER_PID || (echo "Failed to terminate the server" && exit 1) sleep 10 # give the server some time to terminate From 8ea95420c74fd53eb5e078b785c11ef3df5a03fe Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Tue, 25 Jun 2024 10:13:04 -0700 Subject: [PATCH 116/229] Update workflows for better test coverage and integration (#2344) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * ✨ (typescript_test.yml): add workflow_dispatch event to trigger workflow manually with branch input parameter 🔧 (typescript_test.yml): update workflow to checkout code from the specified branch when triggered manually * 📝 (lint-py.yml): update linting workflow to trigger on specific pull request events and checks requested action 📝 (lint-py.yml): add a specific job to run Mypy for static type checking in the linting workflow * 🔧 (python_test.yml): update pull_request event types and branches to trigger on more actions for better test coverage and integration --- .github/workflows/lint-py.yml | 7 +++++-- .github/workflows/python_test.yml | 13 ++++--------- .github/workflows/typescript_test.yml | 13 ++++++++++--- 3 files changed, 19 insertions(+), 14 deletions(-) diff --git a/.github/workflows/lint-py.yml b/.github/workflows/lint-py.yml index 9dab54eb8..8a4abe0f9 100644 --- a/.github/workflows/lint-py.yml +++ b/.github/workflows/lint-py.yml @@ -2,19 +2,20 @@ name: Lint Python on: pull_request: + types: [opened, synchronize, reopened] paths: - "poetry.lock" - "pyproject.toml" - "src/backend/**" - "tests/**" merge_group: - branches: [dev] - + types: [checks_requested] env: POETRY_VERSION: "1.8.2" jobs: lint: + name: Run Mypy runs-on: ubuntu-latest strategy: matrix: @@ -34,6 +35,8 @@ jobs: run: | poetry env use ${{ matrix.python-version }} poetry install + - name: Run Mypy + run: | make lint env: GITHUB_TOKEN: ${{ secrets.github_token }} diff --git a/.github/workflows/python_test.yml b/.github/workflows/python_test.yml index 4846f59fb..9e065c58f 100644 --- a/.github/workflows/python_test.yml +++ b/.github/workflows/python_test.yml @@ -1,26 +1,21 @@ name: Python tests on: - push: - branches: [main] - paths: - - "poetry.lock" - - "pyproject.toml" - - "src/backend/**" pull_request: - branches: [dev] + types: [opened, synchronize, reopened] + branches: [dev, main] paths: - "poetry.lock" - "pyproject.toml" - "src/backend/**" merge_group: - branches: [dev] - + types: [checks_requested] env: POETRY_VERSION: "1.8.2" jobs: build: + name: Run Unit Tests runs-on: ubuntu-latest strategy: matrix: diff --git a/.github/workflows/typescript_test.yml b/.github/workflows/typescript_test.yml index 8fd809020..bd06b5dab 100644 --- a/.github/workflows/typescript_test.yml +++ b/.github/workflows/typescript_test.yml @@ -1,9 +1,13 @@ name: Run Frontend Tests on: - pull_request: - paths: - - "src/frontend/**" + workflow_dispatch: + inputs: + branch: + description: "Branch to run tests on" + required: true + type: string + env: POETRY_VERSION: "1.8.2" @@ -15,6 +19,7 @@ env: jobs: setup-and-test: + name: Run Frontend Tests on branch ${{ inputs.branch }} runs-on: ubuntu-latest strategy: fail-fast: false @@ -24,6 +29,8 @@ jobs: steps: - name: Checkout code uses: actions/checkout@v4 + with: + ref: ${{ inputs.branch }} - name: Setup Node.js uses: actions/setup-node@v4 From 0f8cd9e5720a3568f998656f999239e9f15c54af Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Tue, 25 Jun 2024 14:42:19 -0300 Subject: [PATCH 117/229] chore: Update authContext imports and remove duplicate imports --- src/frontend/src/contexts/authContext.tsx | 4 ---- 1 file changed, 4 deletions(-) diff --git a/src/frontend/src/contexts/authContext.tsx b/src/frontend/src/contexts/authContext.tsx index 50a0cf4e7..cfdbdfb4f 100644 --- a/src/frontend/src/contexts/authContext.tsx +++ b/src/frontend/src/contexts/authContext.tsx @@ -12,10 +12,6 @@ import { useGlobalVariablesStore } from "../stores/globalVariablesStore/globalVa import { useStoreStore } from "../stores/storeStore"; import { Users } from "../types/api"; import { AuthContextType } from "../types/contexts/auth"; -import { useGlobalVariablesStore } from "../stores/globalVariablesStore/globalVariables"; -import { useStoreStore } from "../stores/storeStore"; -import { Users } from "../types/api"; -import { AuthContextType } from "../types/contexts/auth"; const initialValue: AuthContextType = { isAdmin: false, From 4ed879ff56e859cdaa2c9657a917feeeca380a2b Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Tue, 25 Jun 2024 14:56:29 -0300 Subject: [PATCH 118/229] Refactor telemetry service payload field names for consistency --- src/backend/base/langflow/api/v1/chat.py | 30 +++++++++---------- src/backend/base/langflow/api/v1/endpoints.py | 19 ++++++++---- .../langflow/services/telemetry/schema.py | 24 +++++++-------- 3 files changed, 41 insertions(+), 32 deletions(-) diff --git a/src/backend/base/langflow/api/v1/chat.py b/src/backend/base/langflow/api/v1/chat.py index dc44d498b..e19342568 100644 --- a/src/backend/base/langflow/api/v1/chat.py +++ b/src/backend/base/langflow/api/v1/chat.py @@ -121,9 +121,9 @@ async def retrieve_vertices_order( background_tasks.add_task( telemetry_service.log_package_playground, PlaygroundPayload( - seconds=int(time.perf_counter() - start_time), - componentCount=components_count, - success=True, + playgroundSeconds=int(time.perf_counter() - start_time), + playgroundComponentCount=components_count, + playgroundSuccess=True, ), ) return VerticesOrderResponse(ids=first_layer, run_id=graph._run_id, vertices_to_run=vertices_to_run) @@ -131,10 +131,10 @@ async def retrieve_vertices_order( background_tasks.add_task( telemetry_service.log_package_playground, PlaygroundPayload( - seconds=int(time.perf_counter() - start_time), - componentCount=components_count, - success=False, - errorMessage=str(exc), + playgroundSeconds=int(time.perf_counter() - start_time), + playgroundComponentCount=components_count, + playgroundSuccess=False, + playgroundErrorMessage=str(exc), ), ) if "stream or streaming set to True" in str(exc): @@ -280,10 +280,10 @@ async def build_vertex( background_tasks.add_task( telemetry_service.log_package_component, ComponentPayload( - name=vertex_id, - seconds=int(time.perf_counter() - start_time), - success=valid, - errorMessage=params, + componentName=vertex_id, + componentSeconds=int(time.perf_counter() - start_time), + componentSuccess=valid, + componentErrorMessage=params, ), ) return build_response @@ -291,10 +291,10 @@ async def build_vertex( background_tasks.add_task( telemetry_service.log_package_component, ComponentPayload( - name=vertex_id, - seconds=int(time.perf_counter() - start_time), - success=False, - errorMessage=str(exc), + componentName=vertex_id, + componentSeconds=int(time.perf_counter() - start_time), + componentSuccess=False, + componentErrorMessage=str(exc), ), ) logger.error(f"Error building Component:\n\n{exc}") diff --git a/src/backend/base/langflow/api/v1/endpoints.py b/src/backend/base/langflow/api/v1/endpoints.py index d8b5e9da8..92358111a 100644 --- a/src/backend/base/langflow/api/v1/endpoints.py +++ b/src/backend/base/langflow/api/v1/endpoints.py @@ -209,7 +209,7 @@ async def simplified_run_flow( end_time = time.perf_counter() background_tasks.add_task( telemetry_service.log_package_run, - RunPayload(IsWebhook=False, seconds=int(end_time - start_time), success=True, errorMessage=""), + RunPayload(runIsWebhook=False, runSeconds=int(end_time - start_time), runSuccess=True, runErrorMessage=""), ) return result @@ -217,7 +217,9 @@ async def simplified_run_flow( end_time = time.perf_counter() background_tasks.add_task( telemetry_service.log_package_run, - RunPayload(IsWebhook=False, seconds=int(end_time - start_time), success=False, errorMessage=str(exc)), + RunPayload( + runIsWebhook=False, runSeconds=int(end_time - start_time), runSuccess=False, runErrorMessage=str(exc) + ), ) if "badly formed hexadecimal UUID string" in str(exc): # This means the Flow ID is not a valid UUID which means it can't find the flow @@ -231,7 +233,9 @@ async def simplified_run_flow( logger.exception(exc) background_tasks.add_task( telemetry_service.log_package_run, - RunPayload(IsWebhook=False, seconds=int(end_time - start_time), success=False, errorMessage=str(exc)), + RunPayload( + runIsWebhook=False, runSeconds=int(end_time - start_time), runSuccess=False, runErrorMessage=str(exc) + ), ) raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=str(exc)) from exc @@ -290,14 +294,19 @@ async def webhook_run_flow( ) background_tasks.add_task( telemetry_service.log_package_run, - RunPayload(IsWebhook=True, seconds=int(time.perf_counter() - start_time), success=True, errorMessage=""), + RunPayload( + runIsWebhook=True, runSeconds=int(time.perf_counter() - start_time), runSuccess=True, runErrorMessage="" + ), ) return {"message": "Task started in the background", "status": "in progress"} except Exception as exc: background_tasks.add_task( telemetry_service.log_package_run, RunPayload( - IsWebhook=True, seconds=int(time.perf_counter() - start_time), success=False, errorMessage=str(exc) + runIsWebhook=True, + runSeconds=int(time.perf_counter() - start_time), + runSuccess=False, + runErrorMessage=str(exc), ), ) if "Flow ID is required" in str(exc) or "Request body is empty" in str(exc): diff --git a/src/backend/base/langflow/services/telemetry/schema.py b/src/backend/base/langflow/services/telemetry/schema.py index bba7a23e4..9d62e128a 100644 --- a/src/backend/base/langflow/services/telemetry/schema.py +++ b/src/backend/base/langflow/services/telemetry/schema.py @@ -2,10 +2,10 @@ from pydantic import BaseModel class RunPayload(BaseModel): - IsWebhook: bool = False - seconds: int - success: bool - errorMessage: str = "" + runIsWebhook: bool = False + runSeconds: int + runSuccess: bool + runErrorMessage: str = "" class ShutdownPayload(BaseModel): @@ -23,14 +23,14 @@ class VersionPayload(BaseModel): class PlaygroundPayload(BaseModel): - seconds: int - componentCount: int | None = None - success: bool - errorMessage: str = "" + playgroundSeconds: int + playgroundComponentCount: int | None = None + playgroundSuccess: bool + playgroundErrorMessage: str = "" class ComponentPayload(BaseModel): - name: str - seconds: int - success: bool - errorMessage: str + componentName: str + componentSeconds: int + componentSuccess: bool + componentErrorMessage: str From 4365e3d2d8e6a27e238e13686a10acf7a2681718 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Tue, 25 Jun 2024 14:59:33 -0300 Subject: [PATCH 119/229] chore: Update package versions in pyproject.toml files --- pyproject.toml | 2 +- src/backend/base/pyproject.toml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 8ffb4ccf5..1bd744a36 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langflow" -version = "1.0.4" +version = "1.0.5" description = "A Python package with a built-in web application" authors = ["Langflow "] maintainers = [ diff --git a/src/backend/base/pyproject.toml b/src/backend/base/pyproject.toml index 100bcbd2b..6f305ea85 100644 --- a/src/backend/base/pyproject.toml +++ b/src/backend/base/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langflow-base" -version = "0.0.80" +version = "0.0.81" description = "A Python package with a built-in web application" authors = ["Langflow "] maintainers = [ From b05455a9b865b7da4395387646fcaa3b4b7d09c0 Mon Sep 17 00:00:00 2001 From: cristhianzl Date: Tue, 25 Jun 2024 16:17:47 -0300 Subject: [PATCH 120/229] refactor: Ensure flow names are unique by appending a number if necessary --- src/backend/base/langflow/api/v1/flows.py | 27 ++++++++--------------- 1 file changed, 9 insertions(+), 18 deletions(-) diff --git a/src/backend/base/langflow/api/v1/flows.py b/src/backend/base/langflow/api/v1/flows.py index d735a314b..99c678151 100644 --- a/src/backend/base/langflow/api/v1/flows.py +++ b/src/backend/base/langflow/api/v1/flows.py @@ -1,4 +1,5 @@ from datetime import datetime, timezone +import re from typing import List from uuid import UUID @@ -46,8 +47,14 @@ def create_flow( select(Flow).where(Flow.name.like(f"{flow.name} (%")).where(Flow.user_id == current_user.id) # type: ignore ).all() if flows: - numbers = [int(flow.name.split("(")[1].split(")")[0]) for flow in flows] - flow.name = f"{flow.name} ({max(numbers) + 1})" + extract_number = re.compile(r"\((\d+)\)$") + numbers = [] + for flow in flows: + result = extract_number.search(flow.name) + if result: + numbers.append(int(result.groups(1)[0])) + if numbers: + flow.name = f"{flow.name} ({max(numbers) + 1})" else: flow.name = f"{flow.name} (1)" # Now check if the endpoint is unique @@ -210,22 +217,6 @@ def update_flow( db_flow.webhook = webhook_component is not None db_flow.updated_at = datetime.now(timezone.utc) - # First check if the flow.name is unique - # there might be flows with name like: "MyFlow", "MyFlow (1)", "MyFlow (2)" - # so we need to check if the name is unique with `like` operator - # if we find a flow with the same name, we add a number to the end of the name - # based on the highest number found - flow_from_db = session.exec(select(Flow).where(Flow.id == flow_id, Flow.user_id == current_user.id)).first() - if flow_from_db: - flows = session.exec( - select(Flow).where(Flow.name.like(f"{flow.name} (%")).where(Flow.user_id == current_user.id) # type: ignore - ).all() - if flows: - numbers = [int(flow.name.split("(")[1].split(")")[0]) for flow in flows] - flow.name = f"{flow.name} ({max(numbers) + 1})" - else: - flow.name = f"{flow.name} (1)" - if db_flow.folder_id is None: default_folder = session.exec(select(Folder).where(Folder.name == DEFAULT_FOLDER_NAME)).first() if default_folder: From 946638c2688f4f047ee6141e22b16ae941b781ec Mon Sep 17 00:00:00 2001 From: cristhianzl Date: Tue, 25 Jun 2024 16:32:17 -0300 Subject: [PATCH 121/229] =?UTF-8?q?=E2=99=BB=EF=B8=8F=20(flows.py):=20rena?= =?UTF-8?q?me=20loop=20variable=20flow=20to=20=5Fflow=20to=20avoid=20shado?= =?UTF-8?q?wing=20and=20improve=20readability?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- src/backend/base/langflow/api/v1/flows.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/backend/base/langflow/api/v1/flows.py b/src/backend/base/langflow/api/v1/flows.py index 99c678151..54e4fc5e5 100644 --- a/src/backend/base/langflow/api/v1/flows.py +++ b/src/backend/base/langflow/api/v1/flows.py @@ -49,8 +49,8 @@ def create_flow( if flows: extract_number = re.compile(r"\((\d+)\)$") numbers = [] - for flow in flows: - result = extract_number.search(flow.name) + for _flow in flows: + result = extract_number.search(_flow.name) if result: numbers.append(int(result.groups(1)[0])) if numbers: From 4faf84ebeef21fdbbc89579d227e28127a882ad2 Mon Sep 17 00:00:00 2001 From: cristhianzl Date: Tue, 25 Jun 2024 16:32:17 -0300 Subject: [PATCH 122/229] =?UTF-8?q?=E2=99=BB=EF=B8=8F=20(flows.py):=20rena?= =?UTF-8?q?me=20loop=20variable=20flow=20to=20=5Fflow=20to=20avoid=20shado?= =?UTF-8?q?wing=20and=20improve=20readability?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- src/backend/base/langflow/api/v1/flows.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/backend/base/langflow/api/v1/flows.py b/src/backend/base/langflow/api/v1/flows.py index 99c678151..54e4fc5e5 100644 --- a/src/backend/base/langflow/api/v1/flows.py +++ b/src/backend/base/langflow/api/v1/flows.py @@ -49,8 +49,8 @@ def create_flow( if flows: extract_number = re.compile(r"\((\d+)\)$") numbers = [] - for flow in flows: - result = extract_number.search(flow.name) + for _flow in flows: + result = extract_number.search(_flow.name) if result: numbers.append(int(result.groups(1)[0])) if numbers: From edd15fc0a23d3ec2fa47889b6bb2edabe6228bbb Mon Sep 17 00:00:00 2001 From: anovazzi1 Date: Tue, 25 Jun 2024 17:57:49 -0300 Subject: [PATCH 123/229] fix settings flow save button --- .../editFlowSettingsComponent/index.tsx | 18 +++++----------- .../src/modals/flowSettingsModal/index.tsx | 21 +++++++++++++++++-- src/frontend/src/utils/utils.ts | 8 +++++++ 3 files changed, 32 insertions(+), 15 deletions(-) diff --git a/src/frontend/src/components/editFlowSettingsComponent/index.tsx b/src/frontend/src/components/editFlowSettingsComponent/index.tsx index b15e0c369..34cd39180 100644 --- a/src/frontend/src/components/editFlowSettingsComponent/index.tsx +++ b/src/frontend/src/components/editFlowSettingsComponent/index.tsx @@ -4,7 +4,7 @@ import { Label } from "../../components/ui/label"; import { Textarea } from "../../components/ui/textarea"; import useFlowsManagerStore from "../../stores/flowsManagerStore"; import { InputProps } from "../../types/components"; -import { cn } from "../../utils/utils"; +import { cn, isEndpointNameValid } from "../../utils/utils"; export const EditFlowSettings: React.FC = ({ name, @@ -17,7 +17,7 @@ export const EditFlowSettings: React.FC = ({ setEndpointName, }: InputProps): JSX.Element => { const [isMaxLength, setIsMaxLength] = useState(false); - const [isEndpointNameValid, setIsEndpointNameValid] = useState(true); + const [validEndpointName, setValidEndpointName] = useState(true); const [isInvalidName, setIsInvalidName] = useState(false); const currentFlow = useFlowsManagerStore((state) => state.currentFlow); @@ -34,10 +34,6 @@ export const EditFlowSettings: React.FC = ({ invalid = true; break; } - if (value === currentFlow?.name) { - invalid = true; - break; - } invalid = false; } setIsInvalidName(invalid); @@ -51,12 +47,8 @@ export const EditFlowSettings: React.FC = ({ const handleEndpointNameChange = (event: ChangeEvent) => { // Validate the endpoint name // use this regex r'^[a-zA-Z0-9_-]+$' - const isValid = - (/^[a-zA-Z0-9_-]+$/.test(event.target.value) && - event.target.value.length <= maxLength) || - // empty is also valid - event.target.value.length === 0; - setIsEndpointNameValid(isValid); + const isValid = isEndpointNameValid(event.target.value, maxLength); + setValidEndpointName(isValid); setEndpointName!(event.target.value); }; @@ -129,7 +121,7 @@ export const EditFlowSettings: React.FC = ({

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