diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json index 90966fb38..4df8df96b 100644 --- a/.devcontainer/devcontainer.json +++ b/.devcontainer/devcontainer.json @@ -3,7 +3,7 @@ { "name": "Langflow Dev Container", // Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile - "image": "mcr.microsoft.com/devcontainers/python:1-3.10-bullseye", + "image": "mcr.microsoft.com/devcontainers/python:3.10", // Features to add to the dev container. More info: https://containers.dev/features. "features": { diff --git a/.github/workflows/pre-release-base.yml b/.github/workflows/pre-release-base.yml index 44ffc92ee..e0da58777 100644 --- a/.github/workflows/pre-release-base.yml +++ b/.github/workflows/pre-release-base.yml @@ -13,9 +13,12 @@ env: POETRY_VERSION: "1.8.2" jobs: - if_release: + release: + name: Release Langflow Base if: inputs.release_package == true runs-on: ubuntu-latest + outputs: + version: ${{ steps.check-version.outputs.version }} steps: - uses: actions/checkout@v4 - name: Install poetry @@ -49,6 +52,12 @@ jobs: POETRY_PYPI_TOKEN_PYPI: ${{ secrets.PYPI_API_TOKEN }} run: | make publish base=true + docker_build: + name: Build Docker Image + runs-on: ubuntu-latest + needs: release + steps: + - uses: actions/checkout@v4 - name: Set up QEMU uses: docker/setup-qemu-action@v3 - name: Set up Docker Buildx @@ -65,4 +74,4 @@ jobs: push: true file: ./build_and_push_base.Dockerfile tags: | - logspace/langflow:base-${{ steps.check-version.outputs.version }} + logspace/langflow:base-${{ needs.release.outputs.version }} diff --git a/.github/workflows/pre-release-langflow.yml b/.github/workflows/pre-release-langflow.yml index 4c0be75c9..116c2d7e6 100644 --- a/.github/workflows/pre-release-langflow.yml +++ b/.github/workflows/pre-release-langflow.yml @@ -17,9 +17,12 @@ env: POETRY_VERSION: "1.8.2" jobs: - if_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 @@ -49,6 +52,17 @@ jobs: POETRY_PYPI_TOKEN_PYPI: ${{ secrets.PYPI_API_TOKEN }} run: | make publish main=true + - name: Upload Artifact + uses: actions/upload-artifact@v2 + with: + name: dist + path: dist + + docker_build: + name: Build Docker Image + runs-on: ubuntu-latest + needs: release + steps: - name: Set up QEMU uses: docker/setup-qemu-action@v3 - name: Set up Docker Buildx @@ -65,9 +79,18 @@ jobs: push: true file: ./build_and_push.Dockerfile tags: | - logspace/langflow:${{ steps.check-version.outputs.version }} + logspace/langflow:${{ needs.release.outputs.version }} logspace/langflow:1.0-alpha + create_release: + name: Create Release + runs-on: ubuntu-latest + needs: [docker_build, release] + steps: + - uses: actions/download-artifact@v2 + with: + name: dist + path: dist - name: Create Release uses: ncipollo/release-action@v1 with: @@ -76,5 +99,5 @@ jobs: draft: false generateReleaseNotes: true prerelease: true - tag: v${{ steps.check-version.outputs.version }} + tag: v${{ needs.release.outputs.version }} commit: dev diff --git a/.github/workflows/typescript_test.yml b/.github/workflows/typescript_test.yml index a75327785..0cb3213d8 100644 --- a/.github/workflows/typescript_test.yml +++ b/.github/workflows/typescript_test.yml @@ -19,8 +19,8 @@ jobs: strategy: fail-fast: false matrix: - shardIndex: [1, 2, 3, 4] - shardTotal: [4] + shardIndex: [1] + shardTotal: [1] steps: - name: Checkout code uses: actions/checkout@v4 @@ -38,27 +38,6 @@ jobs: npm ci if: ${{ steps.setup-node.outputs.cache-hit != 'true' }} - # Attempt to restore the correct Playwright browser binaries based on the - # currently installed version of Playwright (The browser binary versions - # may change with Playwright versions). - # Note: Playwright's cache directory is hard coded because that's what it - # says to do in the docs. There doesn't appear to be a command that prints - # it out for us. - # - uses: actions/cache@v4 - # id: playwright-cache - # with: - # path: ${{ env.PLAYWRIGHT_BROWSERS_PATH }} - # key: "${{ runner.os }}-playwright-${{ hashFiles('src/frontend/package-lock.json') }}" - # # As a fallback, if the Playwright version has changed, try use the - # # most recently cached version. There's a good chance that at least one - # # of the browser binary versions haven't been updated, so Playwright can - # # skip installing that in the next step. - # # Note: When falling back to an old cache, `cache-hit` (used below) - # # will be `false`. This allows us to restore the potentially out of - # # date cache, but still let Playwright decide if it needs to download - # # new binaries or not. - # restore-keys: | - # ${{ runner.os }}-playwright- - name: Cache playwright binaries uses: actions/cache@v4 id: playwright-cache @@ -82,32 +61,26 @@ jobs: npx playwright install-deps if: steps.playwright-cache.outputs.cache-hit != 'true' - # If the Playwright browser binaries weren't able to be restored, we tell - # paywright to install everything for us. - # - name: Install Playwright's dependencies - # if: steps.playwright-cache.outputs.cache-hit != 'true' - # run: npx playwright install --with-deps - - - name: Install Poetry - run: pipx install "poetry==${{ env.POETRY_VERSION }}" - - - name: Set up Python - uses: actions/setup-python@v5 - id: setup-python + - name: Set up Python ${{ env.PYTHON_VERSION }} + Poetry ${{ env.POETRY_VERSION }} + uses: "./.github/actions/poetry_caching" with: python-version: ${{ env.PYTHON_VERSION }} - cache: "poetry" - + poetry-version: ${{ env.POETRY_VERSION }} + cache-key: ${{ runner.os }}-poetry-${{ env.POETRY_VERSION }}-${{ hashFiles('**/poetry.lock') }} - name: Install Python dependencies run: | poetry env use ${{ env.PYTHON_VERSION }} poetry install - if: ${{ steps.setup-python.outputs.cache-hit != 'true' }} + + - name: create .env + run: | + touch .env + echo "${{ secrets.ENV_VARS }}" > .env - name: Run Playwright Tests run: | cd src/frontend - npx playwright test --shard=${{ matrix.shardIndex }}/${{ matrix.shardTotal }} + npx playwright test - name: Upload blob report to GitHub Actions Artifacts if: always() diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md index 69376ded9..3b89f7faa 100644 --- a/CODE_OF_CONDUCT.md +++ b/CODE_OF_CONDUCT.md @@ -17,23 +17,23 @@ diverse, inclusive, and healthy community. Examples of behavior that contributes to a positive environment for our community include: -* Demonstrating empathy and kindness toward other people -* Being respectful of differing opinions, viewpoints, and experiences -* Giving and gracefully accepting constructive feedback -* Accepting responsibility and apologizing to those affected by our mistakes, +- Demonstrating empathy and kindness toward other people +- Being respectful of differing opinions, viewpoints, and experiences +- Giving and gracefully accepting constructive feedback +- Accepting responsibility and apologizing to those affected by our mistakes, and learning from the experience -* Focusing on what is best not just for us as individuals, but for the +- Focusing on what is best not just for us as individuals, but for the overall community Examples of unacceptable behavior include: -* The use of sexualized language or imagery, and sexual attention or +- The use of sexualized language or imagery, and sexual attention or advances of any kind -* Trolling, insulting or derogatory comments, and personal or political attacks -* Public or private harassment -* Publishing others' private information, such as a physical or email +- Trolling, insulting or derogatory comments, and personal or political attacks +- Public or private harassment +- Publishing others' private information, such as a physical or email address, without their explicit permission -* Other conduct which could reasonably be considered inappropriate in a +- Other conduct which could reasonably be considered inappropriate in a professional setting ## Enforcement Responsibilities @@ -60,7 +60,7 @@ representative at an online or offline event. Instances of abusive, harassing, or otherwise unacceptable behavior may be reported to the community leaders responsible for enforcement at -contact@logspace.ai. +contact@langflow.org. All complaints will be reviewed and investigated promptly and fairly. All community leaders are obligated to respect the privacy and security of the @@ -106,7 +106,7 @@ Violating these terms may lead to a permanent ban. ### 4. Permanent Ban **Community Impact**: Demonstrating a pattern of violation of community -standards, including sustained inappropriate behavior, harassment of an +standards, including sustained inappropriate behavior, harassment of an individual, or aggression toward or disparagement of classes of individuals. **Consequence**: A permanent ban from any sort of public interaction within diff --git a/GCP_DEPLOYMENT.md b/GCP_DEPLOYMENT.md index 12b6b0239..9f17e550b 100644 --- a/GCP_DEPLOYMENT.md +++ b/GCP_DEPLOYMENT.md @@ -6,7 +6,7 @@ This guide will help you set up a Langflow development VM in a Google Cloud Plat ## Standard VM -[![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial.md) +[![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts/gcp&shellonly=true&tutorial=walkthroughtutorial.md) This script sets up a Debian-based VM with the Langflow package, Nginx, and the necessary configurations to run the Langflow Dev environment. @@ -14,7 +14,7 @@ This script sets up a Debian-based VM with the Langflow package, Nginx, and the ## Spot/Preemptible Instance -[![Open in Cloud Shell - Spot Instance](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial_spot.md) +[![Open in Cloud Shell - Spot Instance](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts/gcp&shellonly=true&tutorial=walkthroughtutorial_spot.md) When running as a [spot (preemptible) instance](https://cloud.google.com/compute/docs/instances/preemptible), the code and VM will behave the same way as in a regular instance, executing the startup script to configure the environment, install necessary dependencies, and run the Langflow application. However, **due to the nature of spot instances, the VM may be terminated at any time if Google Cloud needs to reclaim the resources**. This makes spot instances suitable for fault-tolerant, stateless, or interruptible workloads that can handle unexpected terminations and restarts. diff --git a/LICENSE b/LICENSE index cd91750fb..ee3d6be71 100644 --- a/LICENSE +++ b/LICENSE @@ -1,6 +1,6 @@ MIT License -Copyright (c) 2024 Logspace +Copyright (c) 2024 Langflow Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal diff --git a/base.Dockerfile b/base.Dockerfile index 3946af99d..2325ece79 100644 --- a/base.Dockerfile +++ b/base.Dockerfile @@ -63,8 +63,10 @@ RUN --mount=type=cache,target=/root/.cache \ # copy project requirement files here to ensure they will be cached. WORKDIR $PYSETUP_PATH +# Copy just one file to avoid rebuilding the whole image COPY poetry.lock pyproject.toml ./ -COPY ./src/backend/langflow/main.py ./src/backend/langflow/main.py +COPY ./src/backend/langflow ./src/backend/langflow +COPY ./src/backend/base/pyproject.toml ./src/backend/base/pyproject.toml # Copy README.md to the build context COPY README.md . # install runtime deps - uses $POETRY_VIRTUALENVS_IN_PROJECT internally @@ -84,7 +86,7 @@ COPY --from=builder-base $POETRY_HOME $POETRY_HOME COPY --from=builder-base $PYSETUP_PATH $PYSETUP_PATH # Copy just one file to avoid rebuilding the whole image -COPY ./src/backend/langflow/__init__.py ./src/backend/langflow/__init__.py +COPY ./src/backend/langflow ./src/backend/langflow # quicker install as runtime deps are already installed RUN --mount=type=cache,target=/root/.cache \ poetry install --with=dev --extras deploy diff --git a/build_and_push.Dockerfile b/build_and_push.Dockerfile index 1c595e180..f552dd695 100644 --- a/build_and_push.Dockerfile +++ b/build_and_push.Dockerfile @@ -74,10 +74,11 @@ RUN $POETRY_HOME/bin/poetry build FROM python-base as final # Copy virtual environment and built .tar.gz from builder base +RUN useradd -m -u 1000 user COPY --from=builder-base /app/dist/*.tar.gz ./ - # Install the package from the .tar.gz -RUN pip install *.tar.gz +RUN python -m pip install *.tar.gz --user WORKDIR /app -CMD ["python", "-m", "langflow", "run", "--host", "0.0.0.0", "--port", "7860"] +ENTRYPOINT ["python", "-m", "langflow", "run"] +CMD ["--host", "0.0.0.0", "--port", "7860"] \ No newline at end of file diff --git a/build_and_push_base.Dockerfile b/build_and_push_base.Dockerfile index f5092c81c..db6d0cf58 100644 --- a/build_and_push_base.Dockerfile +++ b/build_and_push_base.Dockerfile @@ -82,10 +82,11 @@ RUN cd src/backend/base && $POETRY_HOME/bin/poetry build --format sdist FROM python-base as final # Copy virtual environment and built .tar.gz from builder base +RUN useradd -m -u 1000 user COPY --from=builder-base /app/src/backend/base/dist/*.tar.gz ./ - # Install the package from the .tar.gz -RUN pip install *.tar.gz +RUN pip install *.tar.gz --user WORKDIR /app -CMD ["python", "-m", "langflow", "run", "--host", "0.0.0.0", "--port", "7860"] +ENTRYPOINT ["python", "-m", "langflow", "run"] +CMD ["--host", "0.0.0.0", "--port", "7860"] \ No newline at end of file diff --git a/deploy/base.Dockerfile b/deploy/base.Dockerfile deleted file mode 100644 index 84b448e2d..000000000 --- a/deploy/base.Dockerfile +++ /dev/null @@ -1,92 +0,0 @@ - - -# syntax=docker/dockerfile:1 -# Keep this syntax directive! It's used to enable Docker BuildKit - -# Based on https://github.com/python-poetry/poetry/discussions/1879?sort=top#discussioncomment-216865 -# but I try to keep it updated (see history) - -################################ -# PYTHON-BASE -# Sets up all our shared environment variables -################################ -FROM python:3.10-slim as python-base - -# python -ENV PYTHONUNBUFFERED=1 \ - # prevents python creating .pyc files - PYTHONDONTWRITEBYTECODE=1 \ - \ - # pip - PIP_DISABLE_PIP_VERSION_CHECK=on \ - PIP_DEFAULT_TIMEOUT=100 \ - \ - # poetry - # https://python-poetry.org/docs/configuration/#using-environment-variables - POETRY_VERSION=1.8.2 \ - # make poetry install to this location - POETRY_HOME="/opt/poetry" \ - # make poetry create the virtual environment in the project's root - # it gets named `.venv` - POETRY_VIRTUALENVS_IN_PROJECT=true \ - # do not ask any interactive question - POETRY_NO_INTERACTION=1 \ - \ - # paths - # this is where our requirements + virtual environment will live - PYSETUP_PATH="/opt/pysetup" \ - VENV_PATH="/opt/pysetup/.venv" - - -# prepend poetry and venv to path -ENV PATH="$POETRY_HOME/bin:$VENV_PATH/bin:$PATH" - - -################################ -# BUILDER-BASE -# Used to build deps + create our virtual environment -################################ -FROM python-base as builder-base -RUN apt-get update \ - && apt-get install --no-install-recommends -y \ - # deps for installing poetry - curl \ - # deps for building python deps - build-essential - -# install poetry - respects $POETRY_VERSION & $POETRY_HOME -# The --mount will mount the buildx cache directory to where -# Poetry and Pip store their cache so that they can reuse it -RUN --mount=type=cache,target=/root/.cache \ - curl -sSL https://install.python-poetry.org | python3 - - -# copy project requirement files here to ensure they will be cached. -WORKDIR $PYSETUP_PATH -COPY ./poetry.lock ./pyproject.toml ./ -# Copy README.md to the build context -COPY ./README.md ./ -# install runtime deps - uses $POETRY_VIRTUALENVS_IN_PROJECT internally -RUN --mount=type=cache,target=/root/.cache \ - poetry install --without dev --extras deploy - - -################################ -# DEVELOPMENT -# Image used during development / testing -################################ -FROM python-base as development -WORKDIR $PYSETUP_PATH - -# copy in our built poetry + venv -COPY --from=builder-base $POETRY_HOME $POETRY_HOME -COPY --from=builder-base $PYSETUP_PATH $PYSETUP_PATH - -# Copy just one file to avoid rebuilding the whole image -COPY ./src/backend/langflow/__init__.py ./src/backend/langflow/__init__.py -# quicker install as runtime deps are already installed -RUN --mount=type=cache,target=/root/.cache \ - poetry install --with=dev --extras deploy - -# copy in our app code -COPY ./src/backend ./src/backend -COPY ./tests ./tests diff --git a/deploy/docker-compose.yml b/deploy/docker-compose.yml index 201f9bc97..c47871bf6 100644 --- a/deploy/docker-compose.yml +++ b/deploy/docker-compose.yml @@ -69,10 +69,7 @@ services: - traefik.http.routers.${STACK_NAME?Variable not set}-proxy-http.middlewares=${STACK_NAME?Variable not set}-www-redirect,${STACK_NAME?Variable not set}-https-redirect backend: &backend - image: "ogabrielluiz/langflow:latest" - build: - context: ../ - dockerfile: base.Dockerfile + image: "logspace/langflow:latest" depends_on: - db - broker @@ -143,9 +140,6 @@ services: <<: *backend env_file: - .env - build: - context: ../ - dockerfile: base.Dockerfile command: celery -A langflow.worker.celery_app worker --loglevel=INFO --concurrency=1 -n lf-worker@%h -P eventlet healthcheck: test: "exit 0" @@ -158,9 +152,6 @@ services: - .env networks: - default - build: - context: ../ - dockerfile: base.Dockerfile environment: - FLOWER_PORT=5555 diff --git a/docs/docs/deployment/gcp-deployment.md b/docs/docs/deployment/gcp-deployment.md index bd2b48968..e126e785c 100644 --- a/docs/docs/deployment/gcp-deployment.md +++ b/docs/docs/deployment/gcp-deployment.md @@ -8,7 +8,7 @@ This guide will help you set up a Langflow development VM in a Google Cloud Plat ## Standard VM -[![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial.md) +[![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/langflow-ai/langflow&working_dir=scripts/gcp&shellonly=true&tutorial=walkthroughtutorial.md) This script sets up a Debian-based VM with the Langflow package, Nginx, and the necessary configurations to run the Langflow Dev environment. @@ -16,7 +16,7 @@ This script sets up a Debian-based VM with the Langflow package, Nginx, and the ## Spot/Preemptible Instance -[![Open in Cloud Shell - Spot Instance](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/genome21/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial_spot.md) +[![Open in Cloud Shell - Spot Instance](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/genome21/langflow&working_dir=scripts/gcp&shellonly=true&tutorial=walkthroughtutorial_spot.md) When running as a [spot (preemptible) instance](https://cloud.google.com/compute/docs/instances/preemptible), the code and VM will behave the same way as in a regular instance, executing the startup script to configure the environment, install necessary dependencies, and run the Langflow application. However, **due to the nature of spot instances, the VM may be terminated at any time if Google Cloud needs to reclaim the resources**. This makes spot instances suitable for fault-tolerant, stateless, or interruptible workloads that can handle unexpected terminations and restarts. diff --git a/docs/docusaurus.config.js b/docs/docusaurus.config.js index f64b180c7..8f9302cfd 100644 --- a/docs/docusaurus.config.js +++ b/docs/docusaurus.config.js @@ -7,11 +7,11 @@ module.exports = { title: "Langflow Documentation", tagline: "Langflow is a GUI for LangChain, designed with react-flow", favicon: "img/favicon.ico", - url: "https://logspace-ai.github.io", + url: "https://langflow-ai.github.io", baseUrl: "/", onBrokenLinks: "throw", onBrokenMarkdownLinks: "warn", - organizationName: "logspace-ai", + organizationName: "langflow-ai", projectName: "langflow", trailingSlash: false, staticDirectories: ["static"], @@ -131,7 +131,7 @@ module.exports = { }, footer: { links: [], - copyright: `Copyright © ${new Date().getFullYear()} Logspace.`, + copyright: `Copyright © ${new Date().getFullYear()} Langflow.`, }, zoom: { selector: ".markdown :not(a) > img:not(.no-zoom)", diff --git a/poetry.lock b/poetry.lock index 4b2d4c912..feb0728da 100644 --- a/poetry.lock +++ b/poetry.lock @@ -2,87 +2,87 @@ [[package]] name = "aiohttp" -version = "3.9.4" +version = "3.9.5" description = "Async http client/server framework (asyncio)" optional = false python-versions = ">=3.8" files = [ - {file = "aiohttp-3.9.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:76d32588ef7e4a3f3adff1956a0ba96faabbdee58f2407c122dd45aa6e34f372"}, - {file = "aiohttp-3.9.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:56181093c10dbc6ceb8a29dfeea1e815e1dfdc020169203d87fd8d37616f73f9"}, - {file = "aiohttp-3.9.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c7a5b676d3c65e88b3aca41816bf72831898fcd73f0cbb2680e9d88e819d1e4d"}, - {file = "aiohttp-3.9.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d1df528a85fb404899d4207a8d9934cfd6be626e30e5d3a5544a83dbae6d8a7e"}, - {file = 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description = "A Python package with a built-in web application" -authors = ["Logspace "] +authors = ["Langflow "] maintainers = [ - "Carlos Coelho ", + "Carlos Coelho ", "Cristhian Zanforlin ", - "Gabriel Almeida ", + "Gabriel Almeida ", "Igor Carvalho ", "Lucas Eduoli ", "Otávio Anovazzi ", - "Rodrigo Nader ", + "Rodrigo Nader ", ] repository = "https://github.com/langflow-ai/langflow" license = "MIT" diff --git a/src/backend/base/langflow/alembic/versions/1a110b568907_replace_credential_table_with_variable.py b/src/backend/base/langflow/alembic/versions/1a110b568907_replace_credential_table_with_variable.py index e27d088d0..48d12ac30 100644 --- a/src/backend/base/langflow/alembic/versions/1a110b568907_replace_credential_table_with_variable.py +++ b/src/backend/base/langflow/alembic/versions/1a110b568907_replace_credential_table_with_variable.py @@ -5,6 +5,7 @@ Revises: 63b9c451fd30 Create Date: 2024-03-25 09:40:02.743453 """ + from typing import Sequence, Union import sqlalchemy as sa diff --git a/src/backend/base/langflow/alembic/versions/4e5980a44eaa_fix_date_times_again.py b/src/backend/base/langflow/alembic/versions/4e5980a44eaa_fix_date_times_again.py new file mode 100644 index 000000000..dc3e985ed --- /dev/null +++ b/src/backend/base/langflow/alembic/versions/4e5980a44eaa_fix_date_times_again.py @@ -0,0 +1,130 @@ +"""Fix date times again + +Revision ID: 4e5980a44eaa +Revises: 79e675cb6752 +Create Date: 2024-04-12 18:11:06.454037 + +""" + +from typing import Sequence, Union + +import sqlalchemy as sa +from alembic import op +from loguru import logger +from sqlalchemy.dialects import postgresql +from sqlalchemy.engine.reflection import Inspector + +# revision identifiers, used by Alembic. +revision: str = "4e5980a44eaa" +down_revision: Union[str, None] = "79e675cb6752" +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 + table_names = inspector.get_table_names() + # ### commands auto generated by Alembic - please adjust! ### + if "apikey" in table_names: + columns = inspector.get_columns("apikey") + created_at_column = next((column for column in columns if column["name"] == "created_at"), None) + if created_at_column is not None and isinstance(created_at_column["type"], postgresql.TIMESTAMP): + with op.batch_alter_table("apikey", schema=None) as batch_op: + batch_op.alter_column( + "created_at", + existing_type=postgresql.TIMESTAMP(), + type_=sa.DateTime(timezone=True), + existing_nullable=False, + ) + else: + if created_at_column is None: + logger.warning("Column 'created_at' not found in table 'apikey'") + else: + logger.warning(f"Column 'created_at' has type {created_at_column['type']} in table 'apikey'") + if "variable" in table_names: + columns = inspector.get_columns("variable") + created_at_column = next((column for column in columns if column["name"] == "created_at"), None) + updated_at_column = next((column for column in columns if column["name"] == "updated_at"), None) + with op.batch_alter_table("variable", schema=None) as batch_op: + if created_at_column is not None and isinstance(created_at_column["type"], postgresql.TIMESTAMP): + batch_op.alter_column( + "created_at", + existing_type=postgresql.TIMESTAMP(), + type_=sa.DateTime(timezone=True), + existing_nullable=True, + ) + else: + if created_at_column is None: + logger.warning("Column 'created_at' not found in table 'variable'") + else: + logger.warning(f"Column 'created_at' has type {created_at_column['type']} in table 'variable'") + if updated_at_column is not None and isinstance(updated_at_column["type"], postgresql.TIMESTAMP): + batch_op.alter_column( + "updated_at", + existing_type=postgresql.TIMESTAMP(), + type_=sa.DateTime(timezone=True), + existing_nullable=True, + ) + else: + if updated_at_column is None: + logger.warning("Column 'updated_at' not found in table 'variable'") + else: + logger.warning(f"Column 'updated_at' has type {updated_at_column['type']} in table 'variable'") + + # ### end Alembic commands ### + + +def downgrade() -> None: + conn = op.get_bind() + inspector = Inspector.from_engine(conn) # type: ignore + table_names = inspector.get_table_names() + # ### commands auto generated by Alembic - please adjust! ### + if "variable" in table_names: + columns = inspector.get_columns("variable") + created_at_column = next((column for column in columns if column["name"] == "created_at"), None) + updated_at_column = next((column for column in columns if column["name"] == "updated_at"), None) + with op.batch_alter_table("variable", schema=None) as batch_op: + if updated_at_column is not None and isinstance(updated_at_column["type"], sa.DateTime): + batch_op.alter_column( + "updated_at", + existing_type=sa.DateTime(timezone=True), + type_=postgresql.TIMESTAMP(), + existing_nullable=True, + ) + else: + if updated_at_column is None: + logger.warning("Column 'updated_at' not found in table 'variable'") + else: + logger.warning(f"Column 'updated_at' has type {updated_at_column['type']} in table 'variable'") + if created_at_column is not None and isinstance(created_at_column["type"], sa.DateTime): + batch_op.alter_column( + "created_at", + existing_type=sa.DateTime(timezone=True), + type_=postgresql.TIMESTAMP(), + existing_nullable=True, + ) + else: + if created_at_column is None: + logger.warning("Column 'created_at' not found in table 'variable'") + else: + logger.warning(f"Column 'created_at' has type {created_at_column['type']} in table 'variable'") + + if "apikey" in table_names: + columns = inspector.get_columns("apikey") + created_at_column = next((column for column in columns if column["name"] == "created_at"), None) + if created_at_column is not None and isinstance(created_at_column["type"], sa.DateTime): + with op.batch_alter_table("apikey", schema=None) as batch_op: + batch_op.alter_column( + "created_at", + existing_type=sa.DateTime(timezone=True), + type_=postgresql.TIMESTAMP(), + existing_nullable=False, + ) + else: + if created_at_column is None: + logger.warning("Column 'created_at' not found in table 'apikey'") + else: + logger.warning(f"Column 'created_at' has type {created_at_column['type']} in table 'apikey'") + + # ### end Alembic commands ### diff --git a/src/backend/base/langflow/alembic/versions/58b28437a398_modify_nullable.py b/src/backend/base/langflow/alembic/versions/58b28437a398_modify_nullable.py new file mode 100644 index 000000000..ead1ca30a --- /dev/null +++ b/src/backend/base/langflow/alembic/versions/58b28437a398_modify_nullable.py @@ -0,0 +1,66 @@ +"""Modify nullable + +Revision ID: 58b28437a398 +Revises: 4e5980a44eaa +Create Date: 2024-04-13 10:57:23.061709 + +""" + +from typing import Sequence, Union + +import sqlalchemy as sa +from alembic import op +from loguru import logger +from sqlalchemy.engine.reflection import Inspector + +down_revision: Union[str, None] = "4e5980a44eaa" +branch_labels: Union[str, Sequence[str], None] = None +depends_on: Union[str, Sequence[str], None] = None + +# Revision identifiers, used by Alembic. +revision = "58b28437a398" +down_revision = "4e5980a44eaa" +branch_labels = None +depends_on = None + + +def upgrade(): + conn = op.get_bind() + inspector = Inspector.from_engine(conn) + tables = ["apikey", "variable"] # List of tables to modify + + for table_name in tables: + modify_nullable(conn, inspector, table_name, upgrade=True) + + +def downgrade(): + conn = op.get_bind() + inspector = Inspector.from_engine(conn) + tables = ["apikey", "variable"] # List of tables to revert + + for table_name in tables: + modify_nullable(conn, inspector, table_name, upgrade=False) + + +def modify_nullable(conn, inspector, table_name, upgrade=True): + columns = inspector.get_columns(table_name) + nullable_changes = {"apikey": {"created_at": False}, "variable": {"created_at": True, "updated_at": True}} + + if table_name in columns: + with op.batch_alter_table(table_name, schema=None) as batch_op: + for column_name, nullable_setting in nullable_changes.get(table_name, {}).items(): + column_info = next((col for col in columns if col["name"] == column_name), None) + if column_info: + current_nullable = column_info["nullable"] + target_nullable = nullable_setting if upgrade else not nullable_setting + + if current_nullable != target_nullable: + batch_op.alter_column( + column_name, existing_type=sa.DateTime(timezone=True), nullable=target_nullable + ) + else: + logger.info( + f"Column '{column_name}' in table '{table_name}' already has nullable={target_nullable}" + ) + else: + logger.warning(f"Column '{column_name}' not found in table '{table_name}'") diff --git a/src/backend/base/langflow/alembic/versions/79e675cb6752_change_datetime_type.py b/src/backend/base/langflow/alembic/versions/79e675cb6752_change_datetime_type.py index 5f9de6034..0b6bc9218 100644 --- a/src/backend/base/langflow/alembic/versions/79e675cb6752_change_datetime_type.py +++ b/src/backend/base/langflow/alembic/versions/79e675cb6752_change_datetime_type.py @@ -5,13 +5,14 @@ Revises: e3bc869fa272 Create Date: 2024-04-11 19:23:10.697335 """ -from calendar import c + from typing import Sequence, Union import sqlalchemy as sa from alembic import op from sqlalchemy.dialects import postgresql from sqlalchemy.engine.reflection import Inspector +from loguru import logger # revision identifiers, used by Alembic. revision: str = "79e675cb6752" @@ -28,7 +29,7 @@ def upgrade() -> None: if "apikey" in table_names: columns = inspector.get_columns("apikey") created_at_column = next((column for column in columns if column["name"] == "created_at"), None) - if created_at_column is not None and created_at_column["type"] == postgresql.TIMESTAMP(): + if created_at_column is not None and isinstance(created_at_column["type"], postgresql.TIMESTAMP): with op.batch_alter_table("apikey", schema=None) as batch_op: batch_op.alter_column( "created_at", @@ -36,25 +37,40 @@ def upgrade() -> None: type_=sa.DateTime(timezone=True), existing_nullable=False, ) + else: + if created_at_column is None: + logger.warning("Column 'created_at' not found in table 'apikey'") + else: + logger.warning(f"Column 'created_at' has type {created_at_column['type']} in table 'apikey'") if "variable" in table_names: columns = inspector.get_columns("variable") created_at_column = next((column for column in columns if column["name"] == "created_at"), None) updated_at_column = next((column for column in columns if column["name"] == "updated_at"), None) with op.batch_alter_table("variable", schema=None) as batch_op: - if created_at_column is not None and created_at_column["type"] == postgresql.TIMESTAMP(): + if created_at_column is not None and isinstance(created_at_column["type"], postgresql.TIMESTAMP): batch_op.alter_column( "created_at", existing_type=postgresql.TIMESTAMP(), type_=sa.DateTime(timezone=True), existing_nullable=True, ) - if updated_at_column is not None and updated_at_column["type"] == postgresql.TIMESTAMP(): + else: + if created_at_column is None: + logger.warning("Column 'created_at' not found in table 'variable'") + else: + logger.warning(f"Column 'created_at' has type {created_at_column['type']} in table 'variable'") + if updated_at_column is not None and isinstance(updated_at_column["type"], postgresql.TIMESTAMP): batch_op.alter_column( "updated_at", existing_type=postgresql.TIMESTAMP(), type_=sa.DateTime(timezone=True), existing_nullable=True, ) + else: + if updated_at_column is None: + logger.warning("Column 'updated_at' not found in table 'variable'") + else: + logger.warning(f"Column 'updated_at' has type {updated_at_column['type']} in table 'variable'") # ### end Alembic commands ### @@ -69,25 +85,35 @@ def downgrade() -> None: created_at_column = next((column for column in columns if column["name"] == "created_at"), None) updated_at_column = next((column for column in columns if column["name"] == "updated_at"), None) with op.batch_alter_table("variable", schema=None) as batch_op: - if updated_at_column is not None and updated_at_column["type"] == sa.DateTime(timezone=True): + if updated_at_column is not None and isinstance(updated_at_column["type"], sa.DateTime): batch_op.alter_column( "updated_at", existing_type=sa.DateTime(timezone=True), type_=postgresql.TIMESTAMP(), existing_nullable=True, ) - if created_at_column is not None and created_at_column["type"] == sa.DateTime(timezone=True): + else: + if updated_at_column is None: + logger.warning("Column 'updated_at' not found in table 'variable'") + else: + logger.warning(f"Column 'updated_at' has type {updated_at_column['type']} in table 'variable'") + if created_at_column is not None and isinstance(created_at_column["type"], sa.DateTime): batch_op.alter_column( "created_at", existing_type=sa.DateTime(timezone=True), type_=postgresql.TIMESTAMP(), existing_nullable=True, ) + else: + if created_at_column is None: + logger.warning("Column 'created_at' not found in table 'variable'") + else: + logger.warning(f"Column 'created_at' has type {created_at_column['type']} in table 'variable'") if "apikey" in table_names: columns = inspector.get_columns("apikey") created_at_column = next((column for column in columns if column["name"] == "created_at"), None) - if created_at_column is not None and created_at_column["type"] == sa.DateTime(timezone=True): + if created_at_column is not None and isinstance(created_at_column["type"], sa.DateTime): with op.batch_alter_table("apikey", schema=None) as batch_op: batch_op.alter_column( "created_at", @@ -95,5 +121,10 @@ def downgrade() -> None: type_=postgresql.TIMESTAMP(), existing_nullable=False, ) + else: + if created_at_column is None: + logger.warning("Column 'created_at' not found in table 'apikey'") + else: + logger.warning(f"Column 'created_at' has type {created_at_column['type']} in table 'apikey'") # ### end Alembic commands ### diff --git a/src/backend/base/langflow/api/v1/endpoints.py b/src/backend/base/langflow/api/v1/endpoints.py index 1db888970..32faae472 100644 --- a/src/backend/base/langflow/api/v1/endpoints.py +++ b/src/backend/base/langflow/api/v1/endpoints.py @@ -109,6 +109,7 @@ async def simplified_run_flow( This endpoint provides a powerful interface for executing flows with enhanced flexibility and efficiency, supporting a wide range of applications by allowing for dynamic input and output configuration along with performance optimizations through session management and caching. """ session_id = input_request.session_id + try: task_result: List[RunOutputs] = [] artifacts = {} @@ -127,8 +128,9 @@ async def simplified_run_flow( if flow.data is None: raise ValueError(f"Flow {flow_id} has no data") graph_data = flow.data - graph_data = process_tweaks(graph_data, input_request.tweaks or {}) - graph = Graph.from_payload(graph_data, flow_id=flow_id) + + graph_data = process_tweaks(graph_data, input_request.tweaks or {}, stream=stream) + graph = Graph.from_payload(graph_data, flow_id=flow_id, user_id=api_key_user.id) inputs = [ InputValueRequest(components=[], input_value=input_request.input_value, type=input_request.input_type) ] diff --git a/src/backend/base/langflow/api/v1/store.py b/src/backend/base/langflow/api/v1/store.py index 313b0638b..7d0e9bff9 100644 --- a/src/backend/base/langflow/api/v1/store.py +++ b/src/backend/base/langflow/api/v1/store.py @@ -2,6 +2,7 @@ from typing import Annotated, List, Optional, Union from uuid import UUID from fastapi import APIRouter, Depends, HTTPException, Query +from loguru import logger from langflow.api.utils import check_langflow_version from langflow.services.auth import utils as auth_utils @@ -27,8 +28,11 @@ def get_user_store_api_key( ): if not user.store_api_key: raise HTTPException(status_code=400, detail="You must have a store API key set.") - decrypted = auth_utils.decrypt_api_key(user.store_api_key, settings_service) - return decrypted + try: + decrypted = auth_utils.decrypt_api_key(user.store_api_key, settings_service) + return decrypted + except Exception as e: + raise HTTPException(status_code=500, detail="Failed to decrypt API key. Please set a new one.") from e def get_optional_user_store_api_key( @@ -37,8 +41,12 @@ def get_optional_user_store_api_key( ): if not user.store_api_key: return None - decrypted = auth_utils.decrypt_api_key(user.store_api_key, settings_service) - return decrypted + try: + decrypted = auth_utils.decrypt_api_key(user.store_api_key, settings_service) + return decrypted + except Exception as e: + logger.error(f"Failed to decrypt API key: {e}") + return user.store_api_key @router.get("/check/") diff --git a/src/backend/base/langflow/base/agents/agent.py b/src/backend/base/langflow/base/agents/agent.py index 5ef498b66..ce40f1f51 100644 --- a/src/backend/base/langflow/base/agents/agent.py +++ b/src/backend/base/langflow/base/agents/agent.py @@ -1,13 +1,19 @@ from typing import List, Optional, Union, cast from langchain.agents import AgentExecutor, BaseMultiActionAgent, BaseSingleActionAgent +from langchain_core.messages import BaseMessage from langchain_core.runnables import Runnable +from langflow.base.agents.utils import get_agents_list, records_to_messages from langflow.custom import CustomComponent -from langflow.field_typing import BaseMemory, Text, Tool +from langflow.field_typing import Text, Tool +from langflow.schema.schema import Record class LCAgentComponent(CustomComponent): + def get_agents_list(self): + return get_agents_list() + def build_config(self): return { "lc": { @@ -42,9 +48,8 @@ class LCAgentComponent(CustomComponent): self, agent: Union[Runnable, BaseSingleActionAgent, BaseMultiActionAgent, AgentExecutor], inputs: str, - input_variables: list[str], tools: List[Tool], - memory: Optional[BaseMemory] = None, + message_history: Optional[List[Record]] = None, handle_parsing_errors: bool = True, output_key: str = "output", ) -> Text: @@ -55,13 +60,11 @@ class LCAgentComponent(CustomComponent): agent=agent, # type: ignore tools=tools, verbose=True, - memory=memory, handle_parsing_errors=handle_parsing_errors, ) - input_dict = {"input": inputs} - for var in input_variables: - if var not in ["agent_scratchpad", "input"]: - input_dict[var] = "" + input_dict: dict[str, str | list[BaseMessage]] = {"input": inputs} + if message_history: + input_dict["chat_history"] = records_to_messages(message_history) result = await runnable.ainvoke(input_dict) self.status = result if output_key in result: diff --git a/src/backend/base/langflow/base/agents/default_prompts.py b/src/backend/base/langflow/base/agents/default_prompts.py new file mode 100644 index 000000000..04e394813 --- /dev/null +++ b/src/backend/base/langflow/base/agents/default_prompts.py @@ -0,0 +1,23 @@ +XML_AGENT_PROMPT = """You are a helpful assistant. Help the user answer any questions. + + You have access to the following tools: + + {tools} + + In order to use a tool, you can use and tags. You will then get back a response in the form + For example, if you have a tool called 'search' that could run a google search, in order to search for the weather in SF you would respond: + + searchweather in SF + 64 degrees + + When you are done, respond with a final answer between . For example: + + The weather in SF is 64 degrees + + Begin! + + Previous Conversation: + {chat_history} + + Question: {input} + {agent_scratchpad}""" diff --git a/src/backend/base/langflow/base/agents/utils.py b/src/backend/base/langflow/base/agents/utils.py new file mode 100644 index 000000000..cb34d1cea --- /dev/null +++ b/src/backend/base/langflow/base/agents/utils.py @@ -0,0 +1,143 @@ +from typing import Any, Callable, Dict, List, Optional, Sequence, Union + +from langchain.agents import ( + create_json_chat_agent, + create_openai_tools_agent, + create_tool_calling_agent, + create_xml_agent, +) +from langchain.agents.xml.base import render_text_description +from langchain_core.language_models import BaseLanguageModel +from langchain_core.messages import BaseMessage +from langchain_core.prompts import BasePromptTemplate, ChatPromptTemplate +from langchain_core.tools import BaseTool +from pydantic import BaseModel + +from langflow.schema.schema import Record + +from .default_prompts import XML_AGENT_PROMPT + + +class AgentSpec(BaseModel): + func: Callable[ + [ + BaseLanguageModel, + Sequence[BaseTool], + BasePromptTemplate | ChatPromptTemplate, + Optional[Callable[[List[BaseTool]], str]], + Optional[Union[bool, List[str]]], + ], + Any, + ] + prompt: Optional[Any] = None + fields: List[str] + hub_repo: Optional[str] = None + + +def records_to_messages(records: List[Record]) -> List[BaseMessage]: + """ + Convert a list of records to a list of messages. + + Args: + records (List[Record]): The records to convert. + + Returns: + List[Message]: The records as messages. + """ + return [record.to_lc_message() for record in records] + + +def validate_and_create_xml_agent( + llm: BaseLanguageModel, + tools: Sequence[BaseTool], + prompt: BasePromptTemplate, + tools_renderer: Callable[[List[BaseTool]], str] = render_text_description, + *, + stop_sequence: Union[bool, List[str]] = True, +): + return create_xml_agent( + llm=llm, + tools=tools, + prompt=prompt, + tools_renderer=tools_renderer, + stop_sequence=stop_sequence, + ) + + +def validate_and_create_openai_tools_agent( + llm: BaseLanguageModel, + tools: Sequence[BaseTool], + prompt: ChatPromptTemplate, + tools_renderer: Callable[[List[BaseTool]], str] = render_text_description, + *, + stop_sequence: Union[bool, List[str]] = True, +): + return create_openai_tools_agent( + llm=llm, + tools=tools, + prompt=prompt, + ) + + +def validate_and_create_tool_calling_agent( + llm: BaseLanguageModel, + tools: Sequence[BaseTool], + prompt: ChatPromptTemplate, + tools_renderer: Callable[[List[BaseTool]], str] = render_text_description, + *, + stop_sequence: Union[bool, List[str]] = True, +): + return create_tool_calling_agent( + llm=llm, + tools=tools, + prompt=prompt, + ) + + +def validate_and_create_json_chat_agent( + llm: BaseLanguageModel, + tools: Sequence[BaseTool], + prompt: ChatPromptTemplate, + tools_renderer: Callable[[List[BaseTool]], str] = render_text_description, + *, + stop_sequence: Union[bool, List[str]] = True, +): + return create_json_chat_agent( + llm=llm, + tools=tools, + prompt=prompt, + tools_renderer=tools_renderer, + stop_sequence=stop_sequence, + ) + + +AGENTS: Dict[str, AgentSpec] = { + "Tool Calling Agent": AgentSpec( + func=validate_and_create_tool_calling_agent, + prompt=None, + fields=["llm", "tools", "prompt"], + hub_repo=None, + ), + "XML Agent": AgentSpec( + func=validate_and_create_xml_agent, + prompt=XML_AGENT_PROMPT, # Ensure XML_AGENT_PROMPT is properly defined and typed. + fields=["llm", "tools", "prompt", "tools_renderer", "stop_sequence"], + hub_repo="hwchase17/xml-agent-convo", + ), + "OpenAI Tools Agent": AgentSpec( + func=validate_and_create_openai_tools_agent, + prompt=None, + fields=["llm", "tools", "prompt"], + hub_repo=None, + ), + "JSON Chat Agent": AgentSpec( + func=validate_and_create_json_chat_agent, + prompt=None, + fields=["llm", "tools", "prompt", "tools_renderer", "stop_sequence"], + hub_repo="hwchase17/react-chat-json", + ), +} + + +def get_agents_list(): + return list(AGENTS.keys()) diff --git a/src/backend/base/langflow/base/constants.py b/src/backend/base/langflow/base/constants.py index c9a41a100..498b46f65 100644 --- a/src/backend/base/langflow/base/constants.py +++ b/src/backend/base/langflow/base/constants.py @@ -6,6 +6,7 @@ Constants: - NODE_FORMAT_ATTRIBUTES: A list of attributes used for formatting nodes. - FIELD_FORMAT_ATTRIBUTES: A list of attributes used for formatting fields. """ + STREAM_INFO_TEXT = "Stream the response from the model. Streaming works only in Chat." NODE_FORMAT_ATTRIBUTES = ["beta", "icon", "display_name", "description"] diff --git a/src/backend/base/langflow/base/models/model.py b/src/backend/base/langflow/base/models/model.py index b8ef38e07..977090818 100644 --- a/src/backend/base/langflow/base/models/model.py +++ b/src/backend/base/langflow/base/models/model.py @@ -2,7 +2,7 @@ from typing import Optional, Union from langchain_core.language_models.chat_models import BaseChatModel from langchain_core.language_models.llms import LLM -from langchain_core.messages import HumanMessage, SystemMessage +from langchain_core.messages import AIMessage, HumanMessage, SystemMessage from langflow.custom import CustomComponent @@ -31,6 +31,47 @@ class LCModelComponent(CustomComponent): self.status = result return result + def build_status_message(self, message: AIMessage): + """ + Builds a status message from an AIMessage object. + + Args: + message (AIMessage): The AIMessage object to build the status message from. + + Returns: + The status message. + """ + if message.response_metadata: + # Build a well formatted status message + content = message.content + response_metadata = message.response_metadata + openai_keys = ["token_usage", "model_name", "finish_reason"] + inner_openai_keys = ["completion_tokens", "prompt_tokens", "total_tokens"] + anthropic_keys = ["model", "usage", "stop_reason"] + inner_anthropic_keys = ["input_tokens", "output_tokens"] + if all(key in response_metadata for key in openai_keys) and all( + key in response_metadata["token_usage"] for key in inner_openai_keys + ): + token_usage = response_metadata["token_usage"] + completion_tokens = token_usage["completion_tokens"] + prompt_tokens = token_usage["prompt_tokens"] + total_tokens = token_usage["total_tokens"] + finish_reason = response_metadata["finish_reason"] + status_message = f"Tokens:\n- Input: {prompt_tokens}\nOutput: {completion_tokens}\nTotal Tokens: {total_tokens}\nStop Reason: {finish_reason}\nResponse: {content}" + elif all(key in response_metadata for key in anthropic_keys) and all( + key in response_metadata["usage"] for key in inner_anthropic_keys + ): + usage = response_metadata["usage"] + input_tokens = usage["input_tokens"] + output_tokens = usage["output_tokens"] + stop_reason = response_metadata["stop_reason"] + status_message = f"Tokens:\n- Input: {input_tokens}\n- Output: {output_tokens}\nStop Reason: {stop_reason}\nResponse: {content}" + else: + status_message = f"Response: {content}" + else: + status_message = f"Response: {message.content}" + return status_message + def get_chat_result( self, runnable: BaseChatModel, stream: bool, input_value: str, system_message: Optional[str] = None ): @@ -46,5 +87,9 @@ class LCModelComponent(CustomComponent): else: message = runnable.invoke(messages) result = message.content - self.status = result + if isinstance(message, AIMessage): + status_message = self.build_status_message(message) + self.status = status_message + else: + self.status = result return result diff --git a/src/backend/base/langflow/components/agents/ToolCallingAgent.py b/src/backend/base/langflow/components/agents/ToolCallingAgent.py new file mode 100644 index 000000000..b4a319e2f --- /dev/null +++ b/src/backend/base/langflow/components/agents/ToolCallingAgent.py @@ -0,0 +1,64 @@ +from typing import List, Optional + +from langchain.agents.tool_calling_agent.base import create_tool_calling_agent +from langchain_core.prompts import ChatPromptTemplate + +from langflow.base.agents.agent import LCAgentComponent +from langflow.field_typing import BaseLanguageModel, Text, Tool +from langflow.schema.schema import Record + + +class ToolCallingAgentComponent(LCAgentComponent): + display_name: str = "Tool Calling Agent" + description: str = "Agent that uses tools. Only models that are compatible with function calling are supported." + + def build_config(self): + return { + "llm": {"display_name": "LLM"}, + "tools": {"display_name": "Tools"}, + "user_prompt": { + "display_name": "Prompt", + "multiline": True, + "info": "This prompt must contain 'input' key.", + }, + "handle_parsing_errors": { + "display_name": "Handle Parsing Errors", + "info": "If True, the agent will handle parsing errors. If False, the agent will raise an error.", + "advanced": True, + }, + "memory": { + "display_name": "Memory", + "info": "Memory to use for the agent.", + }, + "input_value": { + "display_name": "Inputs", + "info": "Input text to pass to the agent.", + }, + } + + async def build( + self, + input_value: str, + llm: BaseLanguageModel, + tools: List[Tool], + user_prompt: str = "{input}", + message_history: Optional[List[Record]] = None, + system_message: str = "You are a helpful assistant", + handle_parsing_errors: bool = True, + ) -> Text: + if "input" not in user_prompt: + raise ValueError("Prompt must contain 'input' key.") + messages = [ + ("system", system_message), + ( + "placeholder", + "{chat_history}", + ), + ("human", user_prompt), + ("placeholder", "{agent_scratchpad}"), + ] + prompt = ChatPromptTemplate.from_messages(messages) + agent = create_tool_calling_agent(llm, tools, prompt) + result = await self.run_agent(agent, input_value, tools, message_history, handle_parsing_errors) + self.status = result + return result diff --git a/src/backend/base/langflow/components/agents/XMLAgent.py b/src/backend/base/langflow/components/agents/XMLAgent.py index 117399af9..76f96da53 100644 --- a/src/backend/base/langflow/components/agents/XMLAgent.py +++ b/src/backend/base/langflow/components/agents/XMLAgent.py @@ -1,10 +1,12 @@ from typing import List, Optional from langchain.agents import create_xml_agent -from langchain_core.prompts import PromptTemplate +from langchain_core.prompts import ChatPromptTemplate + from langflow.base.agents.agent import LCAgentComponent -from langflow.field_typing import BaseLanguageModel, BaseMemory, Text, Tool +from langflow.field_typing import BaseLanguageModel, Text, Tool +from langflow.schema.schema import Record class XMLAgentComponent(LCAgentComponent): @@ -15,7 +17,7 @@ class XMLAgentComponent(LCAgentComponent): return { "llm": {"display_name": "LLM"}, "tools": {"display_name": "Tools"}, - "prompt": { + "user_prompt": { "display_name": "Prompt", "multiline": True, "info": "This prompt must contain 'tools' and 'agent_scratchpad' keys.", @@ -43,6 +45,11 @@ class XMLAgentComponent(LCAgentComponent): Question: {input} {agent_scratchpad}""", }, + "system_message": { + "display_name": "System Message", + "info": "System message to be passed to the LLM.", + "advanced": True, + }, "tool_template": { "display_name": "Tool Template", "info": "Template for rendering tools in the prompt. Tools have 'name' and 'description' keys.", @@ -53,9 +60,9 @@ class XMLAgentComponent(LCAgentComponent): "info": "If True, the agent will handle parsing errors. If False, the agent will raise an error.", "advanced": True, }, - "memory": { - "display_name": "Memory", - "info": "Memory to use for the agent.", + "message_history": { + "display_name": "Message History", + "info": "Message history to pass to the agent.", }, "input_value": { "display_name": "Inputs", @@ -68,12 +75,13 @@ class XMLAgentComponent(LCAgentComponent): input_value: str, llm: BaseLanguageModel, tools: List[Tool], - prompt: str, - memory: Optional[BaseMemory] = None, + user_prompt: str = "{input}", + system_message: str = "You are a helpful assistant", + message_history: Optional[List[Record]] = None, tool_template: str = "{name}: {description}", handle_parsing_errors: bool = True, ) -> Text: - if "input" not in prompt: + if "input" not in user_prompt: raise ValueError("Prompt must contain 'input' key.") def render_tool_description(tools): @@ -81,9 +89,23 @@ class XMLAgentComponent(LCAgentComponent): [tool_template.format(name=tool.name, description=tool.description, args=tool.args) for tool in tools] ) - prompt_template = PromptTemplate.from_template(prompt) - input_variables = prompt_template.input_variables - agent = create_xml_agent(llm, tools, prompt_template, tools_renderer=render_tool_description) - result = await self.run_agent(agent, input_value, input_variables, tools, memory, handle_parsing_errors) + messages = [ + ("system", system_message), + ( + "placeholder", + "{chat_history}", + ), + ("human", user_prompt), + ("placeholder", "{agent_scratchpad}"), + ] + prompt = ChatPromptTemplate.from_messages(messages) + agent = create_xml_agent(llm, tools, prompt, tools_renderer=render_tool_description) + result = await self.run_agent( + agent=agent, + inputs=input_value, + tools=tools, + message_history=message_history, + handle_parsing_errors=handle_parsing_errors, + ) self.status = result return result diff --git a/src/backend/base/langflow/components/experimental/AgentComponent.py b/src/backend/base/langflow/components/experimental/AgentComponent.py new file mode 100644 index 000000000..9a6840a41 --- /dev/null +++ b/src/backend/base/langflow/components/experimental/AgentComponent.py @@ -0,0 +1,185 @@ +from typing import Any, List, Optional, cast + +from langchain_core.prompts import ChatPromptTemplate +from langchain_core.prompts.chat import HumanMessagePromptTemplate, SystemMessagePromptTemplate + +from langflow.base.agents.agent import LCAgentComponent +from langflow.base.agents.utils import AGENTS, AgentSpec, get_agents_list +from langflow.field_typing import BaseLanguageModel, Text, Tool +from langflow.schema.dotdict import dotdict +from langflow.schema.schema import Record + + +class AgentComponent(LCAgentComponent): + display_name = "Agent" + description = "Run any LangChain agent using a simplified interface." + field_order = [ + "agent_name", + "llm", + "tools", + "prompt", + "tool_template", + "handle_parsing_errors", + "memory", + "input_value", + ] + + def build_config(self): + return { + "agent_name": { + "display_name": "Agent", + "info": "The agent to use.", + "refresh_button": True, + "real_time_refresh": True, + "options": get_agents_list(), + }, + "llm": {"display_name": "LLM"}, + "tools": {"display_name": "Tools"}, + "user_prompt": { + "display_name": "Prompt", + "multiline": True, + "info": "This prompt must contain 'tools' and 'agent_scratchpad' keys.", + }, + "system_message": { + "display_name": "System Message", + "info": "System message to be passed to the LLM.", + "advanced": True, + }, + "tool_template": { + "display_name": "Tool Template", + "info": "Template for rendering tools in the prompt. Tools have 'name' and 'description' keys.", + "advanced": True, + }, + "handle_parsing_errors": { + "display_name": "Handle Parsing Errors", + "info": "If True, the agent will handle parsing errors. If False, the agent will raise an error.", + "advanced": True, + }, + "message_history": { + "display_name": "Message History", + "info": "Message history to pass to the agent.", + }, + "input_value": { + "display_name": "Input", + "info": "Input text to pass to the agent.", + }, + "langchain_hub_api_key": { + "display_name": "LangChain Hub API Key", + "info": "API key to use for LangChain Hub. If provided, prompts will be fetched from LangChain Hub.", + "advanced": True, + }, + } + + def get_system_and_user_message_from_prompt(self, prompt: Any): + """ + Extracts the system message and user prompt from a given prompt object. + + Args: + prompt (Any): The prompt object from which to extract the system message and user prompt. + + Returns: + Tuple[Optional[str], Optional[str]]: A tuple containing the system message and user prompt. + If the prompt object does not have any messages, both values will be None. + """ + if hasattr(prompt, "messages"): + system_message = None + user_prompt = None + for message in prompt.messages: + if isinstance(message, SystemMessagePromptTemplate): + s_prompt = message.prompt + if isinstance(s_prompt, list): + s_template = " ".join([cast(str, s.template) for s in s_prompt if hasattr(s, "template")]) + elif hasattr(s_prompt, "template"): + s_template = s_prompt.template + system_message = s_template + elif isinstance(message, HumanMessagePromptTemplate): + h_prompt = message.prompt + if isinstance(h_prompt, list): + h_template = " ".join([cast(str, h.template) for h in h_prompt if hasattr(h, "template")]) + elif hasattr(h_prompt, "template"): + h_template = h_prompt.template + user_prompt = h_template + return system_message, user_prompt + return None, None + + def update_build_config(self, build_config: dotdict, field_value: Any, field_name: Text | None = None): + """ + Updates the build configuration based on the provided field value and field name. + + Args: + build_config (dotdict): The build configuration to be updated. + field_value (Any): The value of the field being updated. + field_name (Text | None, optional): The name of the field being updated. Defaults to None. + + Returns: + dotdict: The updated build configuration. + """ + if field_name == "agent": + build_config["agent"]["options"] = get_agents_list() + if field_value in AGENTS: + # if langchain_hub_api_key is provided, fetch the prompt from LangChain Hub + if build_config["langchain_hub_api_key"]["value"] and AGENTS[field_value].hub_repo: + from langchain import hub + + hub_repo: str | None = AGENTS[field_value].hub_repo + if hub_repo: + hub_api_key: str = build_config["langchain_hub_api_key"]["value"] + prompt = hub.pull(hub_repo, api_key=hub_api_key) + system_message, user_prompt = self.get_system_and_user_message_from_prompt(prompt) + if system_message: + build_config["system_message"]["value"] = system_message + if user_prompt: + build_config["user_prompt"]["value"] = user_prompt + + if AGENTS[field_value].prompt: + build_config["user_prompt"]["value"] = AGENTS[field_value].prompt + else: + build_config["user_prompt"]["value"] = "{input}" + fields = AGENTS[field_value].fields + for field in ["llm", "tools", "prompt", "tools_renderer"]: + if field not in fields: + build_config[field]["show"] = False + return build_config + + async def build( + self, + agent_name: str, + input_value: str, + llm: BaseLanguageModel, + tools: List[Tool], + system_message: str = "You are a helpful assistant. Help the user answer any questions.", + user_prompt: str = "{input}", + message_history: Optional[List[Record]] = None, + tool_template: str = "{name}: {description}", + handle_parsing_errors: bool = True, + ) -> Text: + agent_spec: Optional[AgentSpec] = AGENTS.get(agent_name) + if agent_spec is None: + raise ValueError(f"{agent_name} not found.") + + def render_tool_description(tools): + return "\n".join( + [tool_template.format(name=tool.name, description=tool.description, args=tool.args) for tool in tools] + ) + + messages = [ + ("system", system_message), + ( + "placeholder", + "{chat_history}", + ), + ("human", user_prompt), + ("placeholder", "{agent_scratchpad}"), + ] + prompt = ChatPromptTemplate.from_messages(messages) + agent_func = agent_spec.func + agent = agent_func(llm, tools, prompt, render_tool_description, True) + result = await self.run_agent( + agent=agent, + inputs=input_value, + tools=tools, + message_history=message_history, + handle_parsing_errors=handle_parsing_errors, + ) + self.status = result + return result diff --git a/src/backend/base/langflow/components/experimental/__init__.py b/src/backend/base/langflow/components/experimental/__init__.py index 54ca60a3b..a8e83125c 100644 --- a/src/backend/base/langflow/components/experimental/__init__.py +++ b/src/backend/base/langflow/components/experimental/__init__.py @@ -10,8 +10,10 @@ from .RunFlow import RunFlowComponent from .RunnableExecutor import RunnableExecComponent from .SQLExecutor import SQLExecutorComponent from .SubFlow import SubFlowComponent +from .AgentComponent import AgentComponent __all__ = [ + "AgentComponent", "ClearMessageHistoryComponent", "ExtractKeyFromRecordComponent", "FlowToolComponent", diff --git a/src/backend/base/langflow/components/models/AzureOpenAIModel.py b/src/backend/base/langflow/components/models/AzureOpenAIModel.py index 1440df4d0..b6d3607f3 100644 --- a/src/backend/base/langflow/components/models/AzureOpenAIModel.py +++ b/src/backend/base/langflow/components/models/AzureOpenAIModel.py @@ -105,7 +105,7 @@ class AzureChatOpenAIComponent(LCModelComponent): system_message: Optional[str] = None, max_tokens: Optional[int] = 1000, stream: bool = False, - ) -> BaseLanguageModel: + ) -> Text: if api_key: secret_api_key = SecretStr(api_key) else: diff --git a/src/backend/base/langflow/components/models/ChatLiteLLMModel.py b/src/backend/base/langflow/components/models/ChatLiteLLMModel.py index 5266c6935..23ac483cb 100644 --- a/src/backend/base/langflow/components/models/ChatLiteLLMModel.py +++ b/src/backend/base/langflow/components/models/ChatLiteLLMModel.py @@ -142,7 +142,7 @@ class ChatLiteLLMModelComponent(LCModelComponent): max_retries: int = 6, verbose: bool = False, system_message: Optional[str] = None, - ) -> BaseLanguageModel: + ) -> Text: try: import litellm # type: ignore diff --git a/src/backend/base/langflow/components/models/OpenAIModel.py b/src/backend/base/langflow/components/models/OpenAIModel.py index 1997170f5..641eeb755 100644 --- a/src/backend/base/langflow/components/models/OpenAIModel.py +++ b/src/backend/base/langflow/components/models/OpenAIModel.py @@ -40,6 +40,7 @@ class OpenAIModelComponent(LCModelComponent): "display_name": "Model Name", "advanced": False, "options": [ + "gpt-4-turbo-2024-04-09", "gpt-4-turbo-preview", "gpt-3.5-turbo", "gpt-4-0125-preview", diff --git a/src/backend/base/langflow/components/vectorstores/AstraDB.py b/src/backend/base/langflow/components/vectorstores/AstraDB.py index 47fa2a881..3425c3a4e 100644 --- a/src/backend/base/langflow/components/vectorstores/AstraDB.py +++ b/src/backend/base/langflow/components/vectorstores/AstraDB.py @@ -1,5 +1,6 @@ -from typing import List, Optional +from typing import List, Optional, Union +from langchain.schema import BaseRetriever from langchain_astradb import AstraDBVectorStore from langchain_astradb.utils.astradb import SetupMode @@ -110,7 +111,7 @@ class AstraDBVectorStoreComponent(CustomComponent): metadata_indexing_include: Optional[List[str]] = None, metadata_indexing_exclude: Optional[List[str]] = None, collection_indexing_policy: Optional[dict] = None, - ) -> VectorStore: + ) -> Union[VectorStore, BaseRetriever]: try: setup_mode_value = SetupMode[setup_mode.upper()] except KeyError: diff --git a/src/backend/base/langflow/graph/graph/base.py b/src/backend/base/langflow/graph/graph/base.py index cccb1739e..a0661f4f2 100644 --- a/src/backend/base/langflow/graph/graph/base.py +++ b/src/backend/base/langflow/graph/graph/base.py @@ -1,5 +1,7 @@ import asyncio +import uuid from collections import defaultdict, deque +from functools import partial from itertools import chain from typing import TYPE_CHECKING, Callable, Coroutine, Dict, Generator, List, Optional, Type, Union @@ -16,6 +18,7 @@ from langflow.graph.vertex.types import ChatVertex, FileToolVertex, LLMVertex, R from langflow.interface.tools.constants import FILE_TOOLS from langflow.schema import Record from langflow.schema.schema import INPUT_FIELD_NAME, InputType +from langflow.services.deps import get_chat_service if TYPE_CHECKING: from langflow.graph.schema import ResultData @@ -29,6 +32,7 @@ class Graph: nodes: List[Dict], edges: List[Dict[str, str]], flow_id: Optional[str] = None, + user_id: Optional[str] = None, ) -> None: """ Initializes a new instance of the Graph class. @@ -44,6 +48,7 @@ class Graph: self._runs = 0 self._updates = 0 self.flow_id = flow_id + self.user_id = user_id self._is_input_vertices: List[str] = [] self._is_output_vertices: List[str] = [] self._is_state_vertices: List[str] = [] @@ -164,13 +169,14 @@ class Graph: raise ValueError("Run ID not set") return self._run_id - def set_run_id(self, run_id: str): + def set_run_id(self, run_id: str | uuid.UUID): """ Sets the ID of the current run. Args: run_id (str): The run ID. """ + run_id = str(run_id) for vertex in self.vertices: self.state_manager.subscribe(run_id, vertex.update_graph_state) self._run_id = run_id @@ -446,7 +452,7 @@ class Graph: self.__init__(**state) @classmethod - def from_payload(cls, payload: Dict, flow_id: Optional[str] = None) -> "Graph": + def from_payload(cls, payload: Dict, flow_id: Optional[str] = None, user_id: Optional[str] = None) -> "Graph": """ Creates a graph from a payload. @@ -461,7 +467,7 @@ class Graph: try: vertices = payload["nodes"] edges = payload["edges"] - return cls(vertices, edges, flow_id) + return cls(vertices, edges, flow_id, user_id) except KeyError as exc: logger.exception(exc) if "nodes" not in payload and "edges" not in payload: @@ -748,31 +754,53 @@ class Graph: async def process(self, start_component_id: Optional[str] = None) -> "Graph": """Processes the graph with vertices in each layer run in parallel.""" - self.sort_vertices(start_component_id=start_component_id) - vertices_layers = self.sorted_vertices_layers + first_layer = self.sort_vertices(start_component_id=start_component_id) vertex_task_run_count: Dict[str, int] = {} - for layer_index, layer in enumerate(vertices_layers): + to_process = deque(first_layer) + layer_index = 0 + chat_service = get_chat_service() + run_id = uuid.uuid4() + self.set_run_id(run_id) + while to_process: + current_batch = list(to_process) # Copy current deque items to a list + to_process.clear() # Clear the deque for new items tasks = [] - for vertex_id in layer: + for vertex_id in current_batch: vertex = self.get_vertex(vertex_id) + lock = chat_service._cache_locks[self.run_id] + set_cache_coro = partial(chat_service.set_cache, flow_id=self.run_id) task = asyncio.create_task( - vertex.build(), + self.build_vertex( + lock=lock, + set_cache_coro=set_cache_coro, + vertex_id=vertex_id, + user_id=self.user_id, + inputs_dict={}, + ), name=f"{vertex.display_name} Run {vertex_task_run_count.get(vertex_id, 0)}", ) tasks.append(task) vertex_task_run_count[vertex_id] = vertex_task_run_count.get(vertex_id, 0) + 1 + logger.debug(f"Running layer {layer_index} with {len(tasks)} tasks") - await self._execute_tasks(tasks) + next_runnable_vertices = await self._execute_tasks(tasks) + to_process.extend(next_runnable_vertices) + logger.debug("Graph processing complete") return self - async def _execute_tasks(self, tasks): + async def _execute_tasks(self, tasks: List[asyncio.Task]) -> List[str]: """Executes tasks in parallel, handling exceptions for each task.""" results = [] for i, task in enumerate(asyncio.as_completed(tasks)): try: result = await task - results.append(result) + if isinstance(result, tuple) and len(result) == 7: + # Get the next runnable vertices + next_runnable_vertices = result[0] + results.extend(next_runnable_vertices) + else: + raise ValueError(f"Invalid result: {result}") except Exception as e: # Log the exception along with the task name for easier debugging # task_name = task.get_name() 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 fa049eec2..fce13f449 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 @@ -161,7 +161,7 @@ "list": false, "show": true, "multiline": true, - "value": "from typing import Optional\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.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n field_order = [\n \"max_tokens\",\n \"model_kwargs\",\n \"model_name\",\n \"openai_api_base\",\n \"openai_api_key\",\n \"temperature\",\n \"input_value\",\n \"system_message\",\n \"stream\",\n ]\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": True,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"options\": [\n \"gpt-4-turbo-preview\",\n \"gpt-3.5-turbo\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n \"value\": \"gpt-4-turbo-preview\",\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": True,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"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 \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"value\": 0.1,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": STREAM_INFO_TEXT,\n \"advanced\": True,\n },\n \"system_message\": {\n \"display_name\": \"System Message\",\n \"info\": \"System message to pass to the model.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n openai_api_key: str,\n temperature: float,\n model_name: str,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n stream: bool = False,\n system_message: Optional[str] = None,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n\n return self.get_chat_result(output, stream, input_value, system_message)\n", + "value": "from typing import Optional\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.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n field_order = [\n \"max_tokens\",\n \"model_kwargs\",\n \"model_name\",\n \"openai_api_base\",\n \"openai_api_key\",\n \"temperature\",\n \"input_value\",\n \"system_message\",\n \"stream\",\n ]\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": True,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"options\": [\n \"gpt-4-turbo-2024-04-09\",\n \"gpt-4-turbo-preview\",\n \"gpt-3.5-turbo\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n \"value\": \"gpt-4-turbo-preview\",\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": True,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"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 \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"value\": 0.1,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": STREAM_INFO_TEXT,\n \"advanced\": True,\n },\n \"system_message\": {\n \"display_name\": \"System Message\",\n \"info\": \"System message to pass to the model.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n openai_api_key: str,\n temperature: float,\n model_name: str,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n stream: bool = False,\n system_message: Optional[str] = None,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n\n return self.get_chat_result(output, stream, input_value, system_message)\n", "fileTypes": [], "file_path": "", "password": false, @@ -222,6 +222,7 @@ "file_path": "", "password": false, "options": [ + "gpt-4-turbo-2024-04-09", "gpt-4-turbo-preview", "gpt-3.5-turbo", "gpt-4-0125-preview", diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Blog Writter.json b/src/backend/base/langflow/initial_setup/starter_projects/Langflow Blog Writter.json index 6be06dd5d..8aa19c3df 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Blog Writter.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Langflow Blog Writter.json @@ -494,7 +494,7 @@ "list": false, "show": true, "multiline": true, - "value": "from typing import Optional\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.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n field_order = [\n \"max_tokens\",\n \"model_kwargs\",\n \"model_name\",\n \"openai_api_base\",\n \"openai_api_key\",\n \"temperature\",\n \"input_value\",\n \"system_message\",\n \"stream\",\n ]\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": True,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"options\": [\n \"gpt-4-turbo-preview\",\n \"gpt-3.5-turbo\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n \"value\": \"gpt-4-turbo-preview\",\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": True,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"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 \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"value\": 0.1,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": STREAM_INFO_TEXT,\n \"advanced\": True,\n },\n \"system_message\": {\n \"display_name\": \"System Message\",\n \"info\": \"System message to pass to the model.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n openai_api_key: str,\n temperature: float,\n model_name: str,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n stream: bool = False,\n system_message: Optional[str] = None,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n\n return self.get_chat_result(output, stream, input_value, system_message)\n", + "value": "from typing import Optional\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.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n field_order = [\n \"max_tokens\",\n \"model_kwargs\",\n \"model_name\",\n \"openai_api_base\",\n \"openai_api_key\",\n \"temperature\",\n \"input_value\",\n \"system_message\",\n \"stream\",\n ]\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": True,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"options\": [\n \"gpt-4-turbo-2024-04-09\",\n \"gpt-4-turbo-preview\",\n \"gpt-3.5-turbo\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n \"value\": \"gpt-4-turbo-preview\",\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": True,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"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 \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"value\": 0.1,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": STREAM_INFO_TEXT,\n \"advanced\": True,\n },\n \"system_message\": {\n \"display_name\": \"System Message\",\n \"info\": \"System message to pass to the model.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n openai_api_key: str,\n temperature: float,\n model_name: str,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n stream: bool = False,\n system_message: Optional[str] = None,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n\n return self.get_chat_result(output, stream, input_value, system_message)\n", "fileTypes": [], "file_path": "", "password": false, @@ -555,6 +555,7 @@ "file_path": "", "password": false, "options": [ + "gpt-4-turbo-2024-04-09", "gpt-4-turbo-preview", "gpt-3.5-turbo", "gpt-4-0125-preview", 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 index 592c05fac..8291b96b4 100644 --- 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 @@ -651,7 +651,7 @@ "list": false, "show": true, "multiline": true, - "value": "from typing import Optional\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.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n field_order = [\n \"max_tokens\",\n \"model_kwargs\",\n \"model_name\",\n \"openai_api_base\",\n \"openai_api_key\",\n \"temperature\",\n \"input_value\",\n \"system_message\",\n \"stream\",\n ]\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": True,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"options\": [\n \"gpt-4-turbo-preview\",\n \"gpt-3.5-turbo\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n \"value\": \"gpt-4-turbo-preview\",\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": True,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"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 \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"value\": 0.1,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": STREAM_INFO_TEXT,\n \"advanced\": True,\n },\n \"system_message\": {\n \"display_name\": \"System Message\",\n \"info\": \"System message to pass to the model.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n openai_api_key: str,\n temperature: float,\n model_name: str,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n stream: bool = False,\n system_message: Optional[str] = None,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n\n return self.get_chat_result(output, stream, input_value, system_message)\n", + "value": "from typing import Optional\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.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n field_order = [\n \"max_tokens\",\n \"model_kwargs\",\n \"model_name\",\n \"openai_api_base\",\n \"openai_api_key\",\n \"temperature\",\n \"input_value\",\n \"system_message\",\n \"stream\",\n ]\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": True,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"options\": [\n \"gpt-4-turbo-2024-04-09\",\n \"gpt-4-turbo-preview\",\n \"gpt-3.5-turbo\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n \"value\": \"gpt-4-turbo-preview\",\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": True,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"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 \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"value\": 0.1,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": STREAM_INFO_TEXT,\n \"advanced\": True,\n },\n \"system_message\": {\n \"display_name\": \"System Message\",\n \"info\": \"System message to pass to the model.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n openai_api_key: str,\n temperature: float,\n model_name: str,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n stream: bool = False,\n system_message: Optional[str] = None,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n\n return self.get_chat_result(output, stream, input_value, system_message)\n", "fileTypes": [], "file_path": "", "password": false, @@ -712,6 +712,7 @@ "file_path": "", "password": false, "options": [ + "gpt-4-turbo-2024-04-09", "gpt-4-turbo-preview", "gpt-3.5-turbo", "gpt-4-0125-preview", diff --git a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Memory Conversation.json b/src/backend/base/langflow/initial_setup/starter_projects/Langflow Memory Conversation.json index d424b97bc..10cb1d8c2 100644 --- a/src/backend/base/langflow/initial_setup/starter_projects/Langflow Memory Conversation.json +++ b/src/backend/base/langflow/initial_setup/starter_projects/Langflow Memory Conversation.json @@ -751,7 +751,7 @@ "list": false, "show": true, "multiline": true, - "value": "from typing import Optional\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.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n field_order = [\n \"max_tokens\",\n \"model_kwargs\",\n \"model_name\",\n \"openai_api_base\",\n \"openai_api_key\",\n \"temperature\",\n \"input_value\",\n \"system_message\",\n \"stream\",\n ]\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": True,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"options\": [\n \"gpt-4-turbo-preview\",\n \"gpt-3.5-turbo\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n \"value\": \"gpt-4-turbo-preview\",\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": True,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"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 \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"value\": 0.1,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": STREAM_INFO_TEXT,\n \"advanced\": True,\n },\n \"system_message\": {\n \"display_name\": \"System Message\",\n \"info\": \"System message to pass to the model.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n openai_api_key: str,\n temperature: float,\n model_name: str,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n stream: bool = False,\n system_message: Optional[str] = None,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n\n return self.get_chat_result(output, stream, input_value, system_message)\n", + "value": "from typing import Optional\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.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n field_order = [\n \"max_tokens\",\n \"model_kwargs\",\n \"model_name\",\n \"openai_api_base\",\n \"openai_api_key\",\n \"temperature\",\n \"input_value\",\n \"system_message\",\n \"stream\",\n ]\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": True,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"options\": [\n \"gpt-4-turbo-2024-04-09\",\n \"gpt-4-turbo-preview\",\n \"gpt-3.5-turbo\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n \"value\": \"gpt-4-turbo-preview\",\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": True,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"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 \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"value\": 0.1,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": STREAM_INFO_TEXT,\n \"advanced\": True,\n },\n \"system_message\": {\n \"display_name\": \"System Message\",\n \"info\": \"System message to pass to the model.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n openai_api_key: str,\n temperature: float,\n model_name: str,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n stream: bool = False,\n system_message: Optional[str] = None,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n\n return self.get_chat_result(output, stream, input_value, system_message)\n", "fileTypes": [], "file_path": "", "password": false, @@ -812,6 +812,7 @@ "file_path": "", "password": false, "options": [ + "gpt-4-turbo-2024-04-09", "gpt-4-turbo-preview", "gpt-3.5-turbo", "gpt-4-0125-preview", 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 index 3b2411fec..690c22e1e 100644 --- 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 @@ -884,7 +884,7 @@ "list": false, "show": true, "multiline": true, - "value": "from typing import Optional\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.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n field_order = [\n \"max_tokens\",\n \"model_kwargs\",\n \"model_name\",\n \"openai_api_base\",\n \"openai_api_key\",\n \"temperature\",\n \"input_value\",\n \"system_message\",\n \"stream\",\n ]\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": True,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"options\": [\n \"gpt-4-turbo-preview\",\n \"gpt-3.5-turbo\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n \"value\": \"gpt-4-turbo-preview\",\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": True,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"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 \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"value\": 0.1,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": STREAM_INFO_TEXT,\n \"advanced\": True,\n },\n \"system_message\": {\n \"display_name\": \"System Message\",\n \"info\": \"System message to pass to the model.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n openai_api_key: str,\n temperature: float,\n model_name: str,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n stream: bool = False,\n system_message: Optional[str] = None,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n\n return self.get_chat_result(output, stream, input_value, system_message)\n", + "value": "from typing import Optional\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.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n field_order = [\n \"max_tokens\",\n \"model_kwargs\",\n \"model_name\",\n \"openai_api_base\",\n \"openai_api_key\",\n \"temperature\",\n \"input_value\",\n \"system_message\",\n \"stream\",\n ]\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": True,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"options\": [\n \"gpt-4-turbo-2024-04-09\",\n \"gpt-4-turbo-preview\",\n \"gpt-3.5-turbo\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n \"value\": \"gpt-4-turbo-preview\",\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": True,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"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 \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"value\": 0.1,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": STREAM_INFO_TEXT,\n \"advanced\": True,\n },\n \"system_message\": {\n \"display_name\": \"System Message\",\n \"info\": \"System message to pass to the model.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n openai_api_key: str,\n temperature: float,\n model_name: str,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n stream: bool = False,\n system_message: Optional[str] = None,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n\n return self.get_chat_result(output, stream, input_value, system_message)\n", "fileTypes": [], "file_path": "", "password": false, @@ -945,6 +945,7 @@ "file_path": "", "password": false, "options": [ + "gpt-4-turbo-2024-04-09", "gpt-4-turbo-preview", "gpt-3.5-turbo", "gpt-4-0125-preview", @@ -1270,7 +1271,7 @@ "list": false, "show": true, "multiline": true, - "value": "from typing import Optional\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.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n field_order = [\n \"max_tokens\",\n \"model_kwargs\",\n \"model_name\",\n \"openai_api_base\",\n \"openai_api_key\",\n \"temperature\",\n \"input_value\",\n \"system_message\",\n \"stream\",\n ]\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": True,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"options\": [\n \"gpt-4-turbo-preview\",\n \"gpt-3.5-turbo\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n \"value\": \"gpt-4-turbo-preview\",\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": True,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"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 \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"value\": 0.1,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": STREAM_INFO_TEXT,\n \"advanced\": True,\n },\n \"system_message\": {\n \"display_name\": \"System Message\",\n \"info\": \"System message to pass to the model.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n openai_api_key: str,\n temperature: float,\n model_name: str,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n stream: bool = False,\n system_message: Optional[str] = None,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n\n return self.get_chat_result(output, stream, input_value, system_message)\n", + "value": "from typing import Optional\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.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n field_order = [\n \"max_tokens\",\n \"model_kwargs\",\n \"model_name\",\n \"openai_api_base\",\n \"openai_api_key\",\n \"temperature\",\n \"input_value\",\n \"system_message\",\n \"stream\",\n ]\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": True,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"options\": [\n \"gpt-4-turbo-2024-04-09\",\n \"gpt-4-turbo-preview\",\n \"gpt-3.5-turbo\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n \"value\": \"gpt-4-turbo-preview\",\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": True,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"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 \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"value\": 0.1,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": STREAM_INFO_TEXT,\n \"advanced\": True,\n },\n \"system_message\": {\n \"display_name\": \"System Message\",\n \"info\": \"System message to pass to the model.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n openai_api_key: str,\n temperature: float,\n model_name: str,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n stream: bool = False,\n system_message: Optional[str] = None,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n\n return self.get_chat_result(output, stream, input_value, system_message)\n", "fileTypes": [], "file_path": "", "password": false, @@ -1331,6 +1332,7 @@ "file_path": "", "password": false, "options": [ + "gpt-4-turbo-2024-04-09", "gpt-4-turbo-preview", "gpt-3.5-turbo", "gpt-4-0125-preview", 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 4aabe3717..69ac26c77 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 @@ -851,7 +851,7 @@ "list": false, "show": true, "multiline": true, - "value": "from typing import Optional\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.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n field_order = [\n \"max_tokens\",\n \"model_kwargs\",\n \"model_name\",\n \"openai_api_base\",\n \"openai_api_key\",\n \"temperature\",\n \"input_value\",\n \"system_message\",\n \"stream\",\n ]\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": True,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"options\": [\n \"gpt-4-turbo-preview\",\n \"gpt-3.5-turbo\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n \"value\": \"gpt-4-turbo-preview\",\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": True,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"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 \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"value\": 0.1,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": STREAM_INFO_TEXT,\n \"advanced\": True,\n },\n \"system_message\": {\n \"display_name\": \"System Message\",\n \"info\": \"System message to pass to the model.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n openai_api_key: str,\n temperature: float,\n model_name: str,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n stream: bool = False,\n system_message: Optional[str] = None,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n\n return self.get_chat_result(output, stream, input_value, system_message)\n", + "value": "from typing import Optional\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.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI LLMs.\"\n icon = \"OpenAI\"\n\n field_order = [\n \"max_tokens\",\n \"model_kwargs\",\n \"model_name\",\n \"openai_api_base\",\n \"openai_api_key\",\n \"temperature\",\n \"input_value\",\n \"system_message\",\n \"stream\",\n ]\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": True,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"options\": [\n \"gpt-4-turbo-2024-04-09\",\n \"gpt-4-turbo-preview\",\n \"gpt-3.5-turbo\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n \"value\": \"gpt-4-turbo-preview\",\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": True,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"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 \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"value\": 0.1,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": STREAM_INFO_TEXT,\n \"advanced\": True,\n },\n \"system_message\": {\n \"display_name\": \"System Message\",\n \"info\": \"System message to pass to the model.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n openai_api_key: str,\n temperature: float,\n model_name: str,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n stream: bool = False,\n system_message: Optional[str] = None,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\n if openai_api_key:\n api_key = SecretStr(openai_api_key)\n else:\n api_key = None\n\n output = ChatOpenAI(\n max_tokens=max_tokens,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=api_key,\n temperature=temperature,\n )\n\n return self.get_chat_result(output, stream, input_value, system_message)\n", "fileTypes": [], "file_path": "", "password": false, @@ -912,6 +912,7 @@ "file_path": "", "password": false, "options": [ + "gpt-4-turbo-2024-04-09", "gpt-4-turbo-preview", "gpt-3.5-turbo", "gpt-4-0125-preview", @@ -2302,7 +2303,7 @@ "list": false, "show": true, "multiline": true, - "value": "from typing import List, Optional\n\nfrom langchain_astradb import AstraDBVectorStore\nfrom langchain_astradb.utils.astradb import SetupMode\n\nfrom langflow.custom import CustomComponent\nfrom langflow.field_typing import Embeddings, VectorStore\nfrom langflow.schema import Record\n\n\nclass AstraDBVectorStoreComponent(CustomComponent):\n display_name = \"Astra DB\"\n description = \"Builds or loads an Astra DB Vector Store.\"\n icon = \"AstraDB\"\n field_order = [\"token\", \"api_endpoint\", \"collection_name\", \"inputs\", \"embedding\"]\n\n def build_config(self):\n return {\n \"inputs\": {\n \"display_name\": \"Inputs\",\n \"info\": \"Optional list of records to be processed and stored in the vector store.\",\n },\n \"embedding\": {\"display_name\": \"Embedding\", \"info\": \"Embedding to use\"},\n \"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 \"token\": {\n \"display_name\": \"Token\",\n \"info\": \"Authentication token for accessing Astra DB.\",\n \"password\": True,\n },\n \"api_endpoint\": {\n \"display_name\": \"API Endpoint\",\n \"info\": \"API endpoint URL for the Astra DB service.\",\n },\n \"namespace\": {\n \"display_name\": \"Namespace\",\n \"info\": \"Optional namespace within Astra DB to use for the collection.\",\n \"advanced\": True,\n },\n \"metric\": {\n \"display_name\": \"Metric\",\n \"info\": \"Optional distance metric for vector comparisons in the vector store.\",\n \"advanced\": True,\n },\n \"batch_size\": {\n \"display_name\": \"Batch Size\",\n \"info\": \"Optional number of records to process in a single batch.\",\n \"advanced\": True,\n },\n \"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 \"bulk_insert_overwrite_concurrency\": {\n \"display_name\": \"Bulk Insert Overwrite Concurrency\",\n \"info\": \"Optional concurrency level for bulk insert operations that overwrite existing records.\",\n \"advanced\": True,\n },\n \"bulk_delete_concurrency\": {\n \"display_name\": \"Bulk Delete Concurrency\",\n \"info\": \"Optional concurrency level for bulk delete operations.\",\n \"advanced\": True,\n },\n \"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 },\n \"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 \"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 \"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 \"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 }\n\n def build(\n self,\n embedding: Embeddings,\n token: str,\n api_endpoint: str,\n collection_name: str,\n inputs: Optional[List[Record]] = None,\n namespace: Optional[str] = None,\n metric: Optional[str] = None,\n batch_size: Optional[int] = None,\n bulk_insert_batch_concurrency: Optional[int] = None,\n bulk_insert_overwrite_concurrency: Optional[int] = None,\n bulk_delete_concurrency: Optional[int] = None,\n setup_mode: str = \"Sync\",\n pre_delete_collection: bool = False,\n metadata_indexing_include: Optional[List[str]] = None,\n metadata_indexing_exclude: Optional[List[str]] = None,\n collection_indexing_policy: Optional[dict] = None,\n ) -> VectorStore:\n try:\n setup_mode_value = SetupMode[setup_mode.upper()]\n except KeyError:\n raise ValueError(f\"Invalid setup mode: {setup_mode}\")\n if inputs:\n documents = [_input.to_lc_document() for _input in inputs]\n\n vector_store = AstraDBVectorStore.from_documents(\n documents=documents,\n embedding=embedding,\n collection_name=collection_name,\n token=token,\n api_endpoint=api_endpoint,\n namespace=namespace,\n metric=metric,\n batch_size=batch_size,\n bulk_insert_batch_concurrency=bulk_insert_batch_concurrency,\n bulk_insert_overwrite_concurrency=bulk_insert_overwrite_concurrency,\n bulk_delete_concurrency=bulk_delete_concurrency,\n setup_mode=setup_mode_value,\n pre_delete_collection=pre_delete_collection,\n metadata_indexing_include=metadata_indexing_include,\n metadata_indexing_exclude=metadata_indexing_exclude,\n collection_indexing_policy=collection_indexing_policy,\n )\n else:\n vector_store = AstraDBVectorStore(\n embedding=embedding,\n collection_name=collection_name,\n token=token,\n api_endpoint=api_endpoint,\n namespace=namespace,\n metric=metric,\n batch_size=batch_size,\n bulk_insert_batch_concurrency=bulk_insert_batch_concurrency,\n bulk_insert_overwrite_concurrency=bulk_insert_overwrite_concurrency,\n bulk_delete_concurrency=bulk_delete_concurrency,\n setup_mode=setup_mode_value,\n pre_delete_collection=pre_delete_collection,\n metadata_indexing_include=metadata_indexing_include,\n metadata_indexing_exclude=metadata_indexing_exclude,\n collection_indexing_policy=collection_indexing_policy,\n )\n\n return vector_store\n", + "value": "from typing import List, Optional, Union\n\nfrom langchain.schema import BaseRetriever\nfrom langchain_astradb import AstraDBVectorStore\nfrom langchain_astradb.utils.astradb import SetupMode\n\nfrom langflow.custom import CustomComponent\nfrom langflow.field_typing import Embeddings, VectorStore\nfrom langflow.schema import Record\n\n\nclass AstraDBVectorStoreComponent(CustomComponent):\n display_name = \"Astra DB\"\n description = \"Builds or loads an Astra DB Vector Store.\"\n icon = \"AstraDB\"\n field_order = [\"token\", \"api_endpoint\", \"collection_name\", \"inputs\", \"embedding\"]\n\n def build_config(self):\n return {\n \"inputs\": {\n \"display_name\": \"Inputs\",\n \"info\": \"Optional list of records to be processed and stored in the vector store.\",\n },\n \"embedding\": {\"display_name\": \"Embedding\", \"info\": \"Embedding to use\"},\n \"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 \"token\": {\n \"display_name\": \"Token\",\n \"info\": \"Authentication token for accessing Astra DB.\",\n \"password\": True,\n },\n \"api_endpoint\": {\n \"display_name\": \"API Endpoint\",\n \"info\": \"API endpoint URL for the Astra DB service.\",\n },\n \"namespace\": {\n \"display_name\": \"Namespace\",\n \"info\": \"Optional namespace within Astra DB to use for the collection.\",\n \"advanced\": True,\n },\n \"metric\": {\n \"display_name\": \"Metric\",\n \"info\": \"Optional distance metric for vector comparisons in the vector store.\",\n \"advanced\": True,\n },\n \"batch_size\": {\n \"display_name\": \"Batch Size\",\n \"info\": \"Optional number of records to process in a single batch.\",\n \"advanced\": True,\n },\n \"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 \"bulk_insert_overwrite_concurrency\": {\n \"display_name\": \"Bulk Insert Overwrite Concurrency\",\n \"info\": \"Optional concurrency level for bulk insert operations that overwrite existing records.\",\n \"advanced\": True,\n },\n \"bulk_delete_concurrency\": {\n \"display_name\": \"Bulk Delete Concurrency\",\n \"info\": \"Optional concurrency level for bulk delete operations.\",\n \"advanced\": True,\n },\n \"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 },\n \"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 \"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 \"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 \"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 }\n\n def build(\n self,\n embedding: Embeddings,\n token: str,\n api_endpoint: str,\n collection_name: str,\n inputs: Optional[List[Record]] = None,\n namespace: Optional[str] = None,\n metric: Optional[str] = None,\n batch_size: Optional[int] = None,\n bulk_insert_batch_concurrency: Optional[int] = None,\n bulk_insert_overwrite_concurrency: Optional[int] = None,\n bulk_delete_concurrency: Optional[int] = None,\n setup_mode: str = \"Sync\",\n pre_delete_collection: bool = False,\n metadata_indexing_include: Optional[List[str]] = None,\n metadata_indexing_exclude: Optional[List[str]] = None,\n collection_indexing_policy: Optional[dict] = None,\n ) -> Union[VectorStore, BaseRetriever]:\n try:\n setup_mode_value = SetupMode[setup_mode.upper()]\n except KeyError:\n raise ValueError(f\"Invalid setup mode: {setup_mode}\")\n if inputs:\n documents = [_input.to_lc_document() for _input in inputs]\n\n vector_store = AstraDBVectorStore.from_documents(\n documents=documents,\n embedding=embedding,\n collection_name=collection_name,\n token=token,\n api_endpoint=api_endpoint,\n namespace=namespace,\n metric=metric,\n batch_size=batch_size,\n bulk_insert_batch_concurrency=bulk_insert_batch_concurrency,\n bulk_insert_overwrite_concurrency=bulk_insert_overwrite_concurrency,\n bulk_delete_concurrency=bulk_delete_concurrency,\n setup_mode=setup_mode_value,\n pre_delete_collection=pre_delete_collection,\n metadata_indexing_include=metadata_indexing_include,\n metadata_indexing_exclude=metadata_indexing_exclude,\n collection_indexing_policy=collection_indexing_policy,\n )\n else:\n vector_store = AstraDBVectorStore(\n embedding=embedding,\n collection_name=collection_name,\n token=token,\n api_endpoint=api_endpoint,\n namespace=namespace,\n metric=metric,\n batch_size=batch_size,\n bulk_insert_batch_concurrency=bulk_insert_batch_concurrency,\n bulk_insert_overwrite_concurrency=bulk_insert_overwrite_concurrency,\n bulk_delete_concurrency=bulk_delete_concurrency,\n setup_mode=setup_mode_value,\n pre_delete_collection=pre_delete_collection,\n metadata_indexing_include=metadata_indexing_include,\n metadata_indexing_exclude=metadata_indexing_exclude,\n collection_indexing_policy=collection_indexing_policy,\n )\n\n return vector_store\n", "fileTypes": [], "file_path": "", "password": false, diff --git a/src/backend/base/langflow/interface/run.py b/src/backend/base/langflow/interface/run.py index 2327b8725..283c752e8 100644 --- a/src/backend/base/langflow/interface/run.py +++ b/src/backend/base/langflow/interface/run.py @@ -1,9 +1,5 @@ -from typing import Dict, Tuple - from loguru import logger -from langflow.graph import Graph - def get_memory_key(langchain_object): """ diff --git a/src/backend/base/langflow/main.py b/src/backend/base/langflow/main.py index 1a369649e..81797dc80 100644 --- a/src/backend/base/langflow/main.py +++ b/src/backend/base/langflow/main.py @@ -11,6 +11,7 @@ from fastapi.responses import FileResponse from fastapi.staticfiles import StaticFiles from loguru import logger from rich import print as rprint +from starlette.middleware.base import BaseHTTPMiddleware from langflow.api import router from langflow.initial_setup.setup import create_or_update_starter_projects @@ -20,15 +21,38 @@ from langflow.services.utils import initialize_services, teardown_services from langflow.utils.logger import configure +class JavaScriptMIMETypeMiddleware(BaseHTTPMiddleware): + async def dispatch(self, request: Request, call_next): + try: + response = await call_next(request) + except Exception as exc: + logger.error(exc) + raise exc + if "files/" not in request.url.path and request.url.path.endswith(".js") and response.status_code == 200: + response.headers["Content-Type"] = "text/javascript" + return response + + def get_lifespan(fix_migration=False, socketio_server=None): + from langflow.version import __version__ # type: ignore + @asynccontextmanager async def lifespan(app: FastAPI): nest_asyncio.apply() - initialize_services(fix_migration=fix_migration, socketio_server=socketio_server) - setup_llm_caching() - LangfuseInstance.update() - create_or_update_starter_projects() - yield + # Startup message + if __version__: + rprint(f"[bold green]Starting Langflow v{__version__}...[/bold green]") + else: + rprint("[bold green]Starting Langflow...[/bold green]") + try: + initialize_services(fix_migration=fix_migration, socketio_server=socketio_server) + setup_llm_caching() + LangfuseInstance.update() + create_or_update_starter_projects() + yield + except Exception as exc: + if "langflow migration --fix" not in str(exc): + logger.error(exc) # Shutdown message rprint("[bold red]Shutting down Langflow...[/bold red]") teardown_services() @@ -52,6 +76,7 @@ def create_app(): allow_methods=["*"], allow_headers=["*"], ) + app.add_middleware(JavaScriptMIMETypeMiddleware) @app.middleware("http") async def flatten_query_string_lists(request: Request, call_next): diff --git a/src/backend/base/langflow/processing/process.py b/src/backend/base/langflow/processing/process.py index bd35527b4..bfaff74d5 100644 --- a/src/backend/base/langflow/processing/process.py +++ b/src/backend/base/langflow/processing/process.py @@ -243,7 +243,6 @@ def apply_tweaks(node: Dict[str, Any], node_tweaks: Dict[str, Any]) -> None: for tweak_name, tweak_value in node_tweaks.items(): if tweak_name not in template_data: - logger.warning(f"Node {node.get('id')} does not have a tweak named {tweak_name}") continue if tweak_name in template_data: key = "file_path" if template_data[tweak_name]["type"] == "file" else "value" @@ -256,21 +255,24 @@ def apply_tweaks_on_vertex(vertex: Vertex, node_tweaks: Dict[str, Any]) -> None: vertex.params[tweak_name] = tweak_value -def process_tweaks(graph_data: Dict[str, Any], tweaks: Union["Tweaks", Dict[str, Dict[str, Any]]]) -> Dict[str, Any]: +def process_tweaks( + graph_data: Dict[str, Any], tweaks: Union["Tweaks", Dict[str, Dict[str, Any]]], stream: bool = False +) -> Dict[str, Any]: """ This function is used to tweak the graph data using the node id and the tweaks dict. :param graph_data: The dictionary containing the graph data. It must contain a 'data' key with 'nodes' as its child or directly contain 'nodes' key. Each node should have an 'id' and 'data'. :param tweaks: The dictionary containing the tweaks. The keys can be the node id or the name of the tweak. - The values can be a dictionary containing the tweaks for the node or the value of the tweak. + The values can be a dictionary containing the tweaks for the node or the value of the tweak. + :param stream: A boolean flag indicating whether streaming should be deactivated across all components or not. Default is False. :return: The modified graph_data dictionary. - :raises ValueError: If the input is not in the expected format. """ if not isinstance(tweaks, dict): tweaks = tweaks.model_dump() - + if "stream" not in tweaks: + tweaks["stream"] = stream nodes = validate_input(graph_data, tweaks) nodes_map = {node.get("id"): node for node in nodes} nodes_display_name_map = {node.get("data", {}).get("node", {}).get("display_name"): node for node in nodes} diff --git a/src/backend/base/langflow/schema/schema.py b/src/backend/base/langflow/schema/schema.py index a48e72339..979c78920 100644 --- a/src/backend/base/langflow/schema/schema.py +++ b/src/backend/base/langflow/schema/schema.py @@ -2,7 +2,9 @@ import copy from typing import Literal, Optional from langchain_core.documents import Document +from langchain_core.messages import BaseMessage from pydantic import BaseModel, model_validator +from langchain_core.messages import HumanMessage, AIMessage, BaseMessage class Record(BaseModel): @@ -54,6 +56,21 @@ class Record(BaseModel): data["text"] = document.page_content return cls(data=data, text_key="text") + @classmethod + def from_lc_message(cls, message: BaseMessage) -> "Record": + """ + Converts a BaseMessage to a Record. + + Args: + message (BaseMessage): The BaseMessage to convert. + + Returns: + Record: The converted Record. + """ + data = {"text": message.content} + data["metadata"] = message.to_json() + return cls(data=data, text_key="text") + def __add__(self, other: "Record") -> "Record": """ Combines the data of two records by attempting to add values for overlapping keys @@ -85,6 +102,26 @@ class Record(BaseModel): text = self.data.pop(self.text_key, self.default_value) return Document(page_content=text, metadata=self.data) + def to_lc_message(self) -> BaseMessage: + """ + Converts the Record to a BaseMessage. + + Returns: + BaseMessage: The converted BaseMessage. + """ + # The idea of this function is to be a helper to convert a Record to a BaseMessage + # It will use the "sender" key to determine if the message is Human or AI + # If the key is not present, it will default to AI + # But first we check if all required keys are present in the data dictionary + # they are: "text", "sender" + if not all(key in self.data for key in ["text", "sender"]): + raise ValueError(f"Missing required keys ('text', 'sender') in Record: {self.data}") + sender = self.data.get("sender", "Machine") + text = self.data.get("text", "") + if sender == "User": + return HumanMessage(content=text) + return AIMessage(content=text) + def __getattr__(self, key): """ Allows attribute-like access to the data dictionary. diff --git a/src/backend/base/langflow/services/database/models/api_key/crud.py b/src/backend/base/langflow/services/database/models/api_key/crud.py index 33bdc7579..37fe08cd1 100644 --- a/src/backend/base/langflow/services/database/models/api_key/crud.py +++ b/src/backend/base/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/base/langflow/services/database/models/api_key/model.py b/src/backend/base/langflow/services/database/models/api_key/model.py index e110258b9..ee0d1e71d 100644 --- a/src/backend/base/langflow/services/database/models/api_key/model.py +++ b/src/backend/base/langflow/services/database/models/api_key/model.py @@ -3,17 +3,18 @@ from typing import TYPE_CHECKING, Optional from uuid import UUID, uuid4 from pydantic import field_validator, validator -from sqlmodel import Field, Relationship, SQLModel, Column, func, DateTime +from sqlmodel import Column, DateTime, Field, Relationship, SQLModel, func if TYPE_CHECKING: from langflow.services.database.models.user import User +def utc_now(): + return datetime.now(timezone.utc) + + class ApiKeyBase(SQLModel): name: Optional[str] = Field(index=True, nullable=True, default=None) - created_at: datetime = Field( - default=None, sa_column=Column(DateTime(timezone=True), server_default=func.now(), nullable=False) - ) last_used_at: Optional[datetime] = Field(default=None, nullable=True) total_uses: int = Field(default=0) is_active: bool = Field(default=True) @@ -21,7 +22,9 @@ class ApiKeyBase(SQLModel): class ApiKey(ApiKeyBase, table=True): id: UUID = Field(default_factory=uuid4, primary_key=True, unique=True) - + created_at: datetime = Field( + default=None, sa_column=Column(DateTime(timezone=True), server_default=func.now(), nullable=False) + ) api_key: str = Field(index=True, unique=True) # User relationship # Delete API keys when user is deleted @@ -34,10 +37,11 @@ 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=utc_now) @field_validator("created_at", mode="before") def set_created_at(cls, v): - return v or datetime.now(timezone.utc) + return v or utc_now() class UnmaskedApiKeyRead(ApiKeyBase): diff --git a/src/backend/base/langflow/services/database/service.py b/src/backend/base/langflow/services/database/service.py index 876f9f30e..5ca20c642 100644 --- a/src/backend/base/langflow/services/database/service.py +++ b/src/backend/base/langflow/services/database/service.py @@ -133,7 +133,7 @@ class DatabaseService(Service): alembic_cfg = Config(stdout=buffer) # alembic_cfg.attributes["connection"] = session alembic_cfg.set_main_option("script_location", str(self.script_location)) - alembic_cfg.set_main_option("sqlalchemy.url", self.database_url) + alembic_cfg.set_main_option("sqlalchemy.url", self.database_url.replace('%', '%%')) should_initialize_alembic = False with Session(self.engine) as session: diff --git a/src/backend/base/langflow/services/settings/base.py b/src/backend/base/langflow/services/settings/base.py index 97f69c6c7..db6ba1022 100644 --- a/src/backend/base/langflow/services/settings/base.py +++ b/src/backend/base/langflow/services/settings/base.py @@ -121,7 +121,7 @@ class Settings(BaseSettings): # Define the app name and author app_name = "langflow" - app_author = "logspace" + app_author = "langflow" # Get the cache directory for the application cache_dir = user_cache_dir(app_name, app_author) diff --git a/src/backend/base/langflow/services/utils.py b/src/backend/base/langflow/services/utils.py index 34b3415ad..3d2be2f6d 100644 --- a/src/backend/base/langflow/services/utils.py +++ b/src/backend/base/langflow/services/utils.py @@ -163,7 +163,6 @@ def initialize_services(fix_migration: bool = False, socketio_server=None): try: initialize_database(fix_migration=fix_migration) except Exception as exc: - logger.error(exc) raise exc setup_superuser(get_service(ServiceType.SETTINGS_SERVICE), next(get_session())) try: diff --git a/src/backend/base/langflow/utils/logger.py b/src/backend/base/langflow/utils/logger.py index bc81eaa77..48783710a 100644 --- a/src/backend/base/langflow/utils/logger.py +++ b/src/backend/base/langflow/utils/logger.py @@ -54,22 +54,24 @@ def configure(log_level: Optional[str] = None, log_file: Optional[Path] = None, if not log_file: cache_dir = Path(user_cache_dir("langflow")) + logger.debug(f"Cache directory: {cache_dir}") log_file = cache_dir / "langflow.log" + logger.debug(f"Log file: {log_file}") + try: + log_file = Path(log_file) + log_file.parent.mkdir(parents=True, exist_ok=True) - log_file = Path(log_file) - log_file.parent.mkdir(parents=True, exist_ok=True) - - logger.add( - sink=str(log_file), - level=log_level.upper(), - format=log_format, - rotation="10 MB", # Log rotation based on file size - serialize=True, - ) + logger.add( + sink=str(log_file), + level=log_level.upper(), + format=log_format, + rotation="10 MB", # Log rotation based on file size + serialize=True, + ) + except Exception as exc: + logger.error(f"Error setting up log file: {exc}") logger.debug(f"Logger set up with log level: {log_level}") - if log_file: - logger.debug(f"Log file: {log_file}") setup_uvicorn_logger() setup_gunicorn_logger() diff --git a/src/backend/base/poetry.lock b/src/backend/base/poetry.lock index 40cc1669a..7a8067103 100644 --- a/src/backend/base/poetry.lock +++ b/src/backend/base/poetry.lock @@ -2,87 +2,87 @@ [[package]] name = "aiohttp" -version = "3.9.4" +version = "3.9.5" description = "Async http client/server framework (asyncio)" optional = false python-versions = ">=3.8" files = [ - {file = "aiohttp-3.9.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:76d32588ef7e4a3f3adff1956a0ba96faabbdee58f2407c122dd45aa6e34f372"}, - {file = "aiohttp-3.9.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:56181093c10dbc6ceb8a29dfeea1e815e1dfdc020169203d87fd8d37616f73f9"}, - {file = "aiohttp-3.9.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c7a5b676d3c65e88b3aca41816bf72831898fcd73f0cbb2680e9d88e819d1e4d"}, - {file = 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{file = "langsmith-0.1.45-py3-none-any.whl", hash = "sha256:5a5b7fafe767fa28826c925f175875c09bf5368bfdb141286381a94bf737e6ef"}, - {file = "langsmith-0.1.45.tar.gz", hash = "sha256:713206107df636db1edf30867d64b92495afb1f09d2fee0857a77b7a8ee083d5"}, + {file = "langsmith-0.1.48-py3-none-any.whl", hash = "sha256:2f8967e2aaaed8881efe6f346590681243b315af8ba8a037d969c299d42071d3"}, + {file = "langsmith-0.1.48.tar.gz", hash = "sha256:9cd21cd0928123b2bd2363f03515cb1f6a833d9a9f00420240d5132861d15fcc"}, ] [package.dependencies] @@ -2568,6 +2584,20 @@ rich = ">=10.11.0" shellingham = ">=1.3.0" typing-extensions = ">=3.7.4.3" +[[package]] +name = "types-requests" +version = "2.31.0.20240406" +description = "Typing stubs for requests" +optional = false +python-versions = ">=3.8" +files = [ + {file = "types-requests-2.31.0.20240406.tar.gz", hash = "sha256:4428df33c5503945c74b3f42e82b181e86ec7b724620419a2966e2de604ce1a1"}, + {file = "types_requests-2.31.0.20240406-py3-none-any.whl", hash = "sha256:6216cdac377c6b9a040ac1c0404f7284bd13199c0e1bb235f4324627e8898cf5"}, +] + +[package.dependencies] +urllib3 = ">=2" + [[package]] name = "typing-extensions" version = "4.11.0" @@ -2861,4 +2891,4 @@ local = [] [metadata] lock-version = "2.0" python-versions = ">=3.10,<3.12" -content-hash = "4f3f355cb54985a10ab577f0f2b495c7e6d9e7a8e21838b1742c43de927aba88" +content-hash = "cd3479e6f463fcdce1bef948ca71952b0650d1d7f4891ba1bc873368cd4b095d" diff --git a/src/backend/base/pyproject.toml b/src/backend/base/pyproject.toml index 1f80db272..4a910b53a 100644 --- a/src/backend/base/pyproject.toml +++ b/src/backend/base/pyproject.toml @@ -1,16 +1,16 @@ [tool.poetry] name = "langflow-base" -version = "0.0.30" +version = "0.0.36" description = "A Python package with a built-in web application" -authors = ["Logspace "] +authors = ["Langflow "] maintainers = [ - "Carlos Coelho ", + "Carlos Coelho ", "Cristhian Zanforlin ", - "Gabriel Almeida ", + "Gabriel Almeida ", "Igor Carvalho ", "Lucas Eduoli ", "Otávio Anovazzi ", - "Rodrigo Nader ", + "Rodrigo Nader ", ] repository = "https://github.com/langflow-ai/langflow" license = "MIT" @@ -29,8 +29,9 @@ python = ">=3.10,<3.12" fastapi = "^0.110.1" httpx = "*" uvicorn = "^0.29.0" -gunicorn = "^21.2.0" -langchain = "~0.1.14" +gunicorn = "^22.0.0" +langchain = "~0.1.16" +langchainhub = "~0.1.15" sqlmodel = "^0.0.16" loguru = "^0.7.1" rich = "^13.7.0" diff --git a/src/frontend/cdk.Dockerfile b/src/frontend/cdk.Dockerfile index 0b33e09b8..fb6562976 100644 --- a/src/frontend/cdk.Dockerfile +++ b/src/frontend/cdk.Dockerfile @@ -1,5 +1,5 @@ #baseline -FROM --platform=linux/amd64 node:19-bullseye-slim AS base +FROM --platform=linux/amd64 node:21-bookworm-slim AS base RUN mkdir -p /home/node/app RUN chown -R node:node /home/node && chmod -R 770 /home/node RUN apt-get update && apt-get install -y jq curl diff --git a/src/frontend/dev.Dockerfile b/src/frontend/dev.Dockerfile index 8678b02dd..533726ef0 100644 --- a/src/frontend/dev.Dockerfile +++ b/src/frontend/dev.Dockerfile @@ -1,5 +1,5 @@ #baseline -FROM node:19-bullseye-slim AS base +FROM node:21-bookworm-slim AS base RUN mkdir -p /home/node/app RUN chown -R node:node /home/node && chmod -R 770 /home/node RUN apt-get update && apt-get install -y jq diff --git a/src/frontend/package-lock.json b/src/frontend/package-lock.json index 53250af5d..74e5994a7 100644 --- a/src/frontend/package-lock.json +++ b/src/frontend/package-lock.json @@ -38,6 +38,7 @@ "clsx": "^1.2.1", "cmdk": "^1.0.0", "dompurify": "^3.0.5", + "dotenv": "^16.4.5", "esbuild": "^0.17.19", "framer-motion": "^11.0.6", "lodash": "^4.17.21", @@ -5680,6 +5681,17 @@ "tslib": "^2.0.3" } }, + "node_modules/dotenv": { + "version": "16.4.5", + "resolved": "https://registry.npmjs.org/dotenv/-/dotenv-16.4.5.tgz", + "integrity": "sha512-ZmdL2rui+eB2YwhsWzjInR8LldtZHGDoQ1ugH85ppHKwpUHL7j7rN0Ti9NCnGiQbhaZ11FpR+7ao1dNsmduNUg==", + "engines": { + "node": ">=12" + }, + "funding": { + "url": "https://dotenvx.com" + } + }, "node_modules/eastasianwidth": { "version": "0.2.0", "resolved": "https://registry.npmjs.org/eastasianwidth/-/eastasianwidth-0.2.0.tgz", diff --git a/src/frontend/package.json b/src/frontend/package.json index fd27d8bd6..6e3fbd344 100644 --- a/src/frontend/package.json +++ b/src/frontend/package.json @@ -33,6 +33,7 @@ "clsx": "^1.2.1", "cmdk": "^1.0.0", "dompurify": "^3.0.5", + "dotenv": "^16.4.5", "esbuild": "^0.17.19", "framer-motion": "^11.0.6", "lodash": "^4.17.21", diff --git a/src/frontend/playwright.config.ts b/src/frontend/playwright.config.ts index 649c42390..9535e0a15 100644 --- a/src/frontend/playwright.config.ts +++ b/src/frontend/playwright.config.ts @@ -1,14 +1,17 @@ import { defineConfig, devices } from "@playwright/test"; +import * as dotenv from "dotenv"; +import path from "path"; +dotenv.config(); +dotenv.config({ path: path.resolve(__dirname, "../../.env") }); /** * Read environment variables from file. * https://github.com/motdotla/dotenv */ -// require('dotenv').config(); - /** * See https://playwright.dev/docs/test-configuration. */ + export default defineConfig({ testDir: "./tests", /* Run tests in files in parallel */ @@ -18,7 +21,7 @@ export default defineConfig({ /* Retry on CI only */ retries: process.env.CI ? 2 : 0, /* Opt out of parallel tests on CI. */ - workers: 3, + workers: 1, /* Reporter to use. See https://playwright.dev/docs/test-reporters */ timeout: 120 * 1000, // reporter: [ @@ -40,24 +43,32 @@ export default defineConfig({ projects: [ { name: "chromium", - use: { ...devices["Desktop Chrome"] }, + use: { + ...devices["Desktop Chrome"], + contextOptions: { + // chromium-specific permissions + permissions: ["clipboard-read", "clipboard-write"], + }, + }, }, { name: "firefox", - use: { ...devices["Desktop Firefox"] }, + use: { + ...devices["Desktop Firefox"], + launchOptions: { + firefoxUserPrefs: { + "dom.events.asyncClipboard.readText": true, + "dom.events.testing.asyncClipboard": true, + }, + }, + }, }, - - // { - // name: "webkit", - // use: { ...devices["Desktop Safari"] }, - // }, ], - /* Run your local dev server before starting the tests */ webServer: [ { command: - "poetry run uvicorn --factory langflow.main:create_app --host 127.0.0.1 --port 7860", + "poetry run uvicorn --factory langflow.main:create_app --host 127.0.0.1 --port 7860 --loop asyncio", port: 7860, env: { LANGFLOW_DATABASE_URL: "sqlite:///./temp", @@ -65,7 +76,7 @@ export default defineConfig({ }, stdout: "ignore", - reuseExistingServer: !process.env.CI, + reuseExistingServer: true, timeout: 120 * 1000, }, { diff --git a/src/frontend/src/components/headerComponent/components/menuBar/index.tsx b/src/frontend/src/components/headerComponent/components/menuBar/index.tsx index 756143217..d61f64620 100644 --- a/src/frontend/src/components/headerComponent/components/menuBar/index.tsx +++ b/src/frontend/src/components/headerComponent/components/menuBar/index.tsx @@ -83,7 +83,9 @@ export const MenuBar = ({ diff --git a/src/frontend/src/controllers/API/api.tsx b/src/frontend/src/controllers/API/api.tsx index 033a0e648..8084dfeb9 100644 --- a/src/frontend/src/controllers/API/api.tsx +++ b/src/frontend/src/controllers/API/api.tsx @@ -24,6 +24,9 @@ function ApiInterceptor() { async (error: AxiosError) => { if (error.response?.status === 403 || error.response?.status === 401) { if (!autoLogin) { + if (error?.config?.url?.includes("github")) { + return Promise.reject(error); + } const stillRefresh = checkErrorCount(); if (!stillRefresh) { return Promise.reject(error); diff --git a/src/frontend/src/modals/IOModal/components/chatView/chatMessage/index.tsx b/src/frontend/src/modals/IOModal/components/chatView/chatMessage/index.tsx index b15b61df3..93a0db3c3 100644 --- a/src/frontend/src/modals/IOModal/components/chatView/chatMessage/index.tsx +++ b/src/frontend/src/modals/IOModal/components/chatView/chatMessage/index.tsx @@ -135,7 +135,12 @@ export default function ChatMessage({ alt={!chat.isSend ? "robot_image" : "male_technology"} /> - + {chat.sender_name} diff --git a/src/frontend/src/modals/shareModal/index.tsx b/src/frontend/src/modals/shareModal/index.tsx index 8272bddbe..f37c166f3 100644 --- a/src/frontend/src/modals/shareModal/index.tsx +++ b/src/frontend/src/modals/shareModal/index.tsx @@ -237,6 +237,7 @@ export default function ShareModal({ onCheckedChange={(event: boolean) => { setSharePublic(event); }} + data-testid="public-checkbox" />