From 3cff280cd211977990138ed9d2fe8d5dbad29131 Mon Sep 17 00:00:00 2001 From: Ibis Prevedello Date: Thu, 2 Mar 2023 19:56:42 -0300 Subject: [PATCH 1/3] feat: add docker to front and backend --- Dockerfile | 54 +- build_and_push | 6 +- docker-compose.yml | 0 langflow/backend/Dockerfile | 14 + langflow/backend/app.py | 9 +- langflow/backend/build.Dockerfile | 54 + langflow/backend/build_and_push | 8 + langflow/backend/dev.py | 10 + langflow/backend/poetry.lock | 749 ++-- langflow/backend/pyproject.toml | 8 +- langflow/frontend/Dockerfile | 5 + langflow/frontend/build.Dockerfile | 5 + langflow/frontend/build_and_push | 5 + langflow/frontend/nginx.conf | 18 + .../src/controllers/NodesServices/index.ts | 8 +- pyproject.toml | 2 +- requirements.txt | 4 - response.json | 3012 ----------------- 18 files changed, 375 insertions(+), 3596 deletions(-) delete mode 100644 docker-compose.yml create mode 100644 langflow/backend/Dockerfile create mode 100644 langflow/backend/build.Dockerfile create mode 100755 langflow/backend/build_and_push create mode 100644 langflow/backend/dev.py create mode 100644 langflow/frontend/Dockerfile create mode 100644 langflow/frontend/build.Dockerfile create mode 100755 langflow/frontend/build_and_push create mode 100644 langflow/frontend/nginx.conf delete mode 100644 requirements.txt delete mode 100644 response.json diff --git a/Dockerfile b/Dockerfile index b27a20173..d56e412d0 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,59 +1,9 @@ -# `python-base` sets up all our shared environment variables FROM python:3.10-slim -# python -ENV PYTHONUNBUFFERED=1 \ - # prevents python creating .pyc files - PYTHONDONTWRITEBYTECODE=1 \ - \ - # pip - PIP_NO_CACHE_DIR=off \ - PIP_DISABLE_PIP_VERSION_CHECK=on \ - PIP_DEFAULT_TIMEOUT=100 \ - \ - # poetry - # https://python-poetry.org/docs/configuration/#using-environment-variables - POETRY_VERSION=1.3.2 \ - # 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" - -RUN apt-get update \ - && apt-get install --no-install-recommends -y \ - # deps for installing poetry - curl \ - # deps for building python deps - build-essential libpq-dev - -# install poetry - respects $POETRY_VERSION & $POETRY_HOME -RUN 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 ./ - -# install runtime deps - uses $POETRY_VIRTUALENVS_IN_PROJECT internally -RUN poetry install --only-root -RUN poetry add "git+https://github.com/ibiscp/langchain.git@ibis" - WORKDIR /app -ENV PATH="/opt/pysetup/.venv/bin:$PATH" - -COPY src/ . +COPY --from=frontend_build /app/build/ / EXPOSE 80 -CMD [ "uvicorn", "--host", "0.0.0.0", "--port", "80", "app:app" ] +# CMD [ "langchain" ] diff --git a/build_and_push b/build_and_push index 87d4ade2b..649441688 100755 --- a/build_and_push +++ b/build_and_push @@ -1,5 +1,7 @@ #! /bin/bash +docker build -t logspace/frontend_build -f build.Dockerfile . poetry remove langchain -docker build -t ibiscp/expert:v0.0.15 . && docker push ibiscp/expert:v0.0.15 -poetry add --editable ../langchain +VERSION=$(toml get --toml-path pyproject.toml tool.poetry.version) +docker build --build-arg VERSION=$VERSION -t ibiscp/langflow:$VERSION . && docker push ibiscp/langflow:$VERSION +poetry add --editable ../../../langchain diff --git a/docker-compose.yml b/docker-compose.yml deleted file mode 100644 index e69de29bb..000000000 diff --git a/langflow/backend/Dockerfile b/langflow/backend/Dockerfile new file mode 100644 index 000000000..0868a365f --- /dev/null +++ b/langflow/backend/Dockerfile @@ -0,0 +1,14 @@ +FROM logspace/backend_build as backend_build + +FROM python:3.10-slim +WORKDIR /app + +RUN apt-get update && apt-get install git -y + +COPY --from=backend_build /app/dist/*.whl /app/ +RUN pip install langflow-0.0.17-py3-none-any.whl +RUN rm *.whl + +EXPOSE 80 + +CMD [ "uvicorn", "--host", "0.0.0.0", "--port", "80", "langflow.backend.app:app" ] diff --git a/langflow/backend/app.py b/langflow/backend/app.py index 169210afa..3eadf93af 100644 --- a/langflow/backend/app.py +++ b/langflow/backend/app.py @@ -10,9 +10,7 @@ def create_app(): app = FastAPI() origins = [ - "http://localhost", - "http://localhost:8080", - "http://localhost:3000", + "*", ] app.add_middleware( @@ -30,8 +28,3 @@ def create_app(): app = create_app() - -if __name__ == "__main__": - import uvicorn - - uvicorn.run(app, host="0.0.0.0", port=5003) diff --git a/langflow/backend/build.Dockerfile b/langflow/backend/build.Dockerfile new file mode 100644 index 000000000..9e291927b --- /dev/null +++ b/langflow/backend/build.Dockerfile @@ -0,0 +1,54 @@ +# `python-base` sets up all our shared environment variables +FROM python:3.10-slim + +# python +ENV PYTHONUNBUFFERED=1 \ + # prevents python creating .pyc files + PYTHONDONTWRITEBYTECODE=1 \ + \ + # pip + PIP_NO_CACHE_DIR=off \ + PIP_DISABLE_PIP_VERSION_CHECK=on \ + PIP_DEFAULT_TIMEOUT=100 \ + \ + # poetry + # https://python-poetry.org/docs/configuration/#using-environment-variables + POETRY_VERSION=1.4.0 \ + # 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" + +RUN apt-get update \ + && apt-get install --no-install-recommends -y \ + # deps for installing poetry + curl \ + # deps for building python deps + build-essential libpq-dev + +# install poetry - respects $POETRY_VERSION & $POETRY_HOME +RUN curl -sSL https://install.python-poetry.org | python3 - + +# copy project requirement files here to ensure they will be cached. +WORKDIR /app +COPY poetry.lock pyproject.toml ./ + +# install runtime deps - uses $POETRY_VIRTUALENVS_IN_PROJECT internally +RUN poetry install --without dev +RUN poetry add "git+https://github.com/ibiscp/langchain.git#ibis" + +COPY *.py langflow/backend/ +RUN rm langflow/backend/dev.py + +RUN poetry build diff --git a/langflow/backend/build_and_push b/langflow/backend/build_and_push new file mode 100755 index 000000000..c3cec99b6 --- /dev/null +++ b/langflow/backend/build_and_push @@ -0,0 +1,8 @@ +#! /bin/bash + +poetry remove langchain +docker build -t logspace/backend_build -f build.Dockerfile . +VERSION=$(toml get --toml-path pyproject.toml tool.poetry.version) +docker build --build-arg VERSION=$VERSION -t logspace/langflow_backend:$VERSION . +# docker push logspace/langflow_backend:$VERSION +# poetry add --editable ../../../langchain diff --git a/langflow/backend/dev.py b/langflow/backend/dev.py new file mode 100644 index 000000000..cec800f6e --- /dev/null +++ b/langflow/backend/dev.py @@ -0,0 +1,10 @@ +import uvicorn +import sys +from pathlib import Path + +path = Path(__file__) +sys.path.append(str(path.parent.parent.parent)) + +from app import app + +uvicorn.run(app, host="0.0.0.0", port=5003) diff --git a/langflow/backend/poetry.lock b/langflow/backend/poetry.lock index 8a6200a2f..c88db5862 100644 --- a/langflow/backend/poetry.lock +++ b/langflow/backend/poetry.lock @@ -1,6 +1,6 @@ [[package]] name = "aiohttp" -version = "3.8.3" +version = "3.8.4" description = "Async http client/server framework (asyncio)" category = "main" optional = false @@ -10,7 +10,7 @@ python-versions = ">=3.6" aiosignal = ">=1.1.2" async-timeout = ">=4.0.0a3,<5.0" attrs = ">=17.3.0" -charset-normalizer = ">=2.0,<3.0" +charset-normalizer = ">=2.0,<4.0" frozenlist = ">=1.1.1" multidict = ">=4.5,<7.0" yarl = ">=1.0,<2.0" @@ -165,14 +165,11 @@ pycparser = "*" [[package]] name = "charset-normalizer" -version = "2.1.1" +version = "3.0.1" description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." category = "main" optional = false -python-versions = ">=3.6.0" - -[package.extras] -unicode-backport = ["unicodedata2"] +python-versions = "*" [[package]] name = "click" @@ -207,22 +204,6 @@ traitlets = ">=5.3" [package.extras] test = ["pytest"] -[[package]] -name = "dataclasses-json" -version = "0.5.7" -description = "Easily serialize dataclasses to and from JSON" -category = "main" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -marshmallow = ">=3.3.0,<4.0.0" -marshmallow-enum = ">=1.5.1,<2.0.0" -typing-inspect = ">=0.4.0" - -[package.extras] -dev = ["flake8", "hypothesis", "ipython", "mypy (>=0.710)", "portray", "pytest (>=6.2.3)", "simplejson", "types-dataclasses"] - [[package]] name = "debugpy" version = "1.6.6" @@ -297,7 +278,7 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0dev)"] [[package]] name = "google-api-python-client" -version = "2.79.0" +version = "2.80.0" description = "Google API Client Library for Python" category = "main" optional = false @@ -369,18 +350,6 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.1 || >4.21.1,<4 [package.extras] grpc = ["grpcio (>=1.44.0,<2.0.0dev)"] -[[package]] -name = "greenlet" -version = "2.0.2" -description = "Lightweight in-process concurrent programming" -category = "main" -optional = false -python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*" - -[package.extras] -docs = ["Sphinx", "docutils (<0.18)"] -test = ["objgraph", "psutil"] - [[package]] name = "h11" version = "0.14.0" @@ -440,7 +409,7 @@ test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio" [[package]] name = "ipython" -version = "8.10.0" +version = "8.11.0" description = "IPython: Productive Interactive Computing" category = "dev" optional = false @@ -455,7 +424,7 @@ jedi = ">=0.16" matplotlib-inline = "*" pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""} pickleshare = "*" -prompt-toolkit = ">=3.0.30,<3.1.0" +prompt-toolkit = ">=3.0.30,<3.0.37 || >3.0.37,<3.1.0" pygments = ">=2.4.0" stack-data = "*" traitlets = ">=5" @@ -491,7 +460,7 @@ testing = ["Django (<3.1)", "attrs", "colorama", "docopt", "pytest (<7.0.0)"] [[package]] name = "jupyter-client" -version = "8.0.2" +version = "8.0.3" description = "Jupyter protocol implementation and client libraries" category = "dev" optional = false @@ -525,61 +494,6 @@ traitlets = ">=5.3" docs = ["myst-parser", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "traitlets"] test = ["ipykernel", "pre-commit", "pytest", "pytest-cov", "pytest-timeout"] -[[package]] -name = "langchain" -version = "0.0.86" -description = "Building applications with LLMs through composability" -category = "main" -optional = false -python-versions = ">=3.8.1,<4.0" -develop = true - -[package.dependencies] -aiohttp = "^3.8.3" -dataclasses-json = "^0.5.7" -numpy = "^1" -pydantic = "^1" -PyYAML = "^6" -requests = "^2" -SQLAlchemy = "^1" -tenacity = "^8.1.0" - -[package.extras] -all = ["anthropic (>=0.2.2,<0.3.0)", "beautifulsoup4 (>=4,<5)", "cohere (>=3,<4)", "elasticsearch (>=8,<9)", "faiss-cpu (>=1,<2)", "google-api-python-client (==2.70.0)", "google-search-results (>=2,<3)", "huggingface_hub (>=0,<1)", "jinja2 (>=3,<4)", "manifest-ml (>=0.0.1,<0.0.2)", "networkx (>=2.6.3,<3.0.0)", "nlpcloud (>=1,<2)", "nltk (>=3,<4)", "openai (>=0,<1)", "pinecone-client (>=2,<3)", "pypdf (>=3.4.0,<4.0.0)", "qdrant-client (>=0.11.7,<0.12.0)", "redis (>=4,<5)", "sentence-transformers (>=2,<3)", "spacy (>=3,<4)", "tensorflow-text (>=2.11.0,<3.0.0)", "tiktoken (>=0,<1)", "torch (>=1,<2)", "transformers (>=4,<5)", "weaviate-client (>=3,<4)", "wikipedia (>=1,<2)", "wolframalpha (==5.0.0)"] -llms = ["anthropic (>=0.2.2,<0.3.0)", "cohere (>=3,<4)", "huggingface_hub (>=0,<1)", "manifest-ml (>=0.0.1,<0.0.2)", "nlpcloud (>=1,<2)", "openai (>=0,<1)", "torch (>=1,<2)", "transformers (>=4,<5)"] - -[package.source] -type = "directory" -url = "../langchain" - -[[package]] -name = "marshmallow" -version = "3.19.0" -description = "A lightweight library for converting complex datatypes to and from native Python datatypes." -category = "main" -optional = false -python-versions = ">=3.7" - -[package.dependencies] -packaging = ">=17.0" - -[package.extras] -dev = ["flake8 (==5.0.4)", "flake8-bugbear (==22.10.25)", "mypy (==0.990)", "pre-commit (>=2.4,<3.0)", "pytest", "pytz", "simplejson", "tox"] -docs = ["alabaster (==0.7.12)", "autodocsumm (==0.2.9)", "sphinx (==5.3.0)", "sphinx-issues (==3.0.1)", "sphinx-version-warning (==1.1.2)"] -lint = ["flake8 (==5.0.4)", "flake8-bugbear (==22.10.25)", "mypy (==0.990)", "pre-commit (>=2.4,<3.0)"] -tests = ["pytest", "pytz", "simplejson"] - -[[package]] -name = "marshmallow-enum" -version = "1.5.1" -description = "Enum field for Marshmallow" -category = "main" -optional = false -python-versions = "*" - -[package.dependencies] -marshmallow = ">=2.0.0" - [[package]] name = "matplotlib-inline" version = "0.1.6" @@ -603,7 +517,7 @@ python-versions = ">=3.7" name = "mypy-extensions" version = "1.0.0" description = "Type system extensions for programs checked with the mypy type checker." -category = "main" +category = "dev" optional = false python-versions = ">=3.5" @@ -615,14 +529,6 @@ category = "dev" optional = false python-versions = ">=3.5" -[[package]] -name = "numpy" -version = "1.24.2" -description = "Fundamental package for array computing in Python" -category = "main" -optional = false -python-versions = ">=3.8" - [[package]] name = "openai" version = "0.26.5" @@ -646,7 +552,7 @@ wandb = ["numpy", "openpyxl (>=3.0.7)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1 name = "packaging" version = "23.0" description = "Core utilities for Python packages" -category = "main" +category = "dev" optional = false python-versions = ">=3.7" @@ -703,11 +609,11 @@ test = ["appdirs (==1.4.4)", "covdefaults (>=2.2.2)", "pytest (>=7.2.1)", "pytes [[package]] name = "prompt-toolkit" -version = "3.0.36" +version = "3.0.38" description = "Library for building powerful interactive command lines in Python" category = "dev" optional = false -python-versions = ">=3.6.2" +python-versions = ">=3.7.0" [package.dependencies] wcwidth = "*" @@ -779,7 +685,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" [[package]] name = "pydantic" -version = "1.10.4" +version = "1.10.5" description = "Data validation and settings management using python type hints" category = "main" optional = false @@ -833,14 +739,6 @@ category = "dev" optional = false python-versions = "*" -[[package]] -name = "pyyaml" -version = "6.0" -description = "YAML parser and emitter for Python" -category = "main" -optional = false -python-versions = ">=3.6" - [[package]] name = "pyzmq" version = "25.0.0" @@ -899,43 +797,11 @@ python-versions = ">=3.7" [[package]] name = "soupsieve" -version = "2.3.2.post1" +version = "2.4" description = "A modern CSS selector implementation for Beautiful Soup." category = "main" optional = false -python-versions = ">=3.6" - -[[package]] -name = "sqlalchemy" -version = "1.4.46" -description = "Database Abstraction Library" -category = "main" -optional = false -python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7" - -[package.dependencies] -greenlet = {version = "!=0.4.17", markers = "python_version >= \"3\" and (platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\")"} - -[package.extras] -aiomysql = ["aiomysql", "greenlet (!=0.4.17)"] -aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing_extensions (!=3.10.0.1)"] -asyncio = ["greenlet (!=0.4.17)"] -asyncmy = ["asyncmy (>=0.2.3,!=0.2.4)", "greenlet (!=0.4.17)"] -mariadb-connector = ["mariadb (>=1.0.1,!=1.1.2)"] -mssql = ["pyodbc"] -mssql-pymssql = ["pymssql"] -mssql-pyodbc = ["pyodbc"] -mypy = ["mypy (>=0.910)", "sqlalchemy2-stubs"] -mysql = ["mysqlclient (>=1.4.0)", "mysqlclient (>=1.4.0,<2)"] -mysql-connector = ["mysql-connector-python"] -oracle = ["cx_oracle (>=7)", "cx_oracle (>=7,<8)"] -postgresql = ["psycopg2 (>=2.7)"] -postgresql-asyncpg = ["asyncpg", "greenlet (!=0.4.17)"] -postgresql-pg8000 = ["pg8000 (>=1.16.6,!=1.29.0)"] -postgresql-psycopg2binary = ["psycopg2-binary"] -postgresql-psycopg2cffi = ["psycopg2cffi"] -pymysql = ["pymysql", "pymysql (<1)"] -sqlcipher = ["sqlcipher3_binary"] +python-versions = ">=3.7" [[package]] name = "stack-data" @@ -967,17 +833,6 @@ anyio = ">=3.4.0,<5" [package.extras] full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart", "pyyaml"] -[[package]] -name = "tenacity" -version = "8.2.1" -description = "Retry code until it succeeds" -category = "main" -optional = false -python-versions = ">=3.6" - -[package.extras] -doc = ["reno", "sphinx", "tornado (>=4.5)"] - [[package]] name = "tomli" version = 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a/langflow/frontend/build.Dockerfile b/langflow/frontend/build.Dockerfile new file mode 100644 index 000000000..af2335b5c --- /dev/null +++ b/langflow/frontend/build.Dockerfile @@ -0,0 +1,5 @@ +FROM node:14-alpine +WORKDIR /app +COPY . /app +RUN npm install +RUN npm run build \ No newline at end of file diff --git a/langflow/frontend/build_and_push b/langflow/frontend/build_and_push new file mode 100755 index 000000000..7722a0e74 --- /dev/null +++ b/langflow/frontend/build_and_push @@ -0,0 +1,5 @@ +#! /bin/bash + +docker build -t logspace/frontend_build -f build.Dockerfile . +docker build --build-arg VERSION=$VERSION -t logspace/langflow_frontend:$VERSION . +docker push logspace/langflow_frontend:$VERSION diff --git a/langflow/frontend/nginx.conf b/langflow/frontend/nginx.conf new file mode 100644 index 000000000..df665f5b6 --- /dev/null +++ b/langflow/frontend/nginx.conf @@ -0,0 +1,18 @@ +server { + gzip on; + gzip_comp_level 2; + gzip_min_length 1000; + gzip_types text/xml text/css; + gzip_http_version 1.1; + gzip_vary on; + gzip_disable "MSIE [4-6] \."; + + listen 80; + + location / { + root /usr/share/nginx/html; + index index.html index.htm; + try_files $uri $uri/ /index.html =404; + } + +} diff --git a/langflow/frontend/src/controllers/NodesServices/index.ts b/langflow/frontend/src/controllers/NodesServices/index.ts index 214e41ee1..3478d9d48 100644 --- a/langflow/frontend/src/controllers/NodesServices/index.ts +++ b/langflow/frontend/src/controllers/NodesServices/index.ts @@ -1,11 +1,13 @@ import { APIObjectType, sendAllProps } from '../../types/api/index'; import axios, { AxiosResponse } from "axios"; +const backendUrl = process.env.BACKEND || "http://localhost:5003"; + export async function getAll():Promise> { - return await axios.get("http://localhost:5003/"); + return await axios.get(`${backendUrl}/all`); } export async function sendAll(data:sendAllProps) { console.log(data); - return await axios.post("http://localhost:5003/predict", data); -} + return await axios.post(`${backendUrl}/predict`, data); +} \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index ba9c20cfc..a057fe4d3 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langflow" -version = "0.1.0" +version = "0.0.1" description = "A Python package with a built-in web application" authors = ["Ibis Prevedello "] packages = [ diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index 9d90c8f98..000000000 --- a/requirements.txt +++ /dev/null @@ -1,4 +0,0 @@ -langchain==0.0.82 -openai==0.26.5 -fastapi==0.91.0 - diff --git a/response.json b/response.json deleted file mode 100644 index ecc3e73e3..000000000 --- a/response.json +++ /dev/null @@ -1,3012 +0,0 @@ -{ - "chains": { - "APIChain": { - "template": { - "memory": { - "type": "Memory", - "required": false, - "default": null, - "list": false, - "show": false - }, - "verbose": { - "type": "bool", - "required": false, - "list": false, - "show": false - }, - "api_request_chain": { - "type": "LLMChain", - "required": true, - "list": false, - "show": true - }, - "api_answer_chain": { - "type": "LLMChain", - "required": true, - "list": false, - "show": true - }, - "requests_wrapper": { - "type": "RequestsWrapper", - "required": true, - "list": false, - "show": true - }, - "api_docs": { - "type": "str", - "required": true, - "list": false, - "show": true - }, - "question_key": { - "type": "str", - "required": false, - "default": "question", - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": "output", - "list": false, - "show": false - } - }, - "_type": "api_chain" - }, - "HypotheticalDocumentEmbedder": { - "template": { - "memory": { - "type": "Memory", - "required": false, - "default": null, - "list": false, - "show": false - }, - "verbose": { - "type": "bool", - "required": false, - "list": false, - "show": false - }, - "base_embeddings": { - "type": "Embeddings", - "required": true, - "list": false, - "show": true - }, - "llm_chain": { - "type": "LLMChain", - "required": true, - "list": false, - "show": true - } - }, - "_type": "hyde_chain" - }, - "LLMChain": { - "template": { - "memory": { - "type": "Memory", - "required": false, - "default": null, - "list": false, - "show": false - }, - "verbose": { - "type": "bool", - "required": false, - "list": false, - "show": false - }, - "prompt": { - "type": "BasePromptTemplate", - "required": true, - "list": false, - "show": true - }, - "llm": { - "type": "BaseLLM", - "required": true, - "list": false, - "show": true - }, - "output_key": { - "type": "str", - "required": false, - "default": "text", - "list": false, - "show": false - } - }, - "_type": "llm_chain" - }, - "LLMBashChain": { - "template": { - "memory": { - "type": "Memory", - "required": false, - "default": null, - "list": false, - "show": false - }, - "verbose": { - "type": "bool", - "required": false, - "list": false, - "show": false - }, - "llm": { - "type": "BaseLLM", - "required": true, - "list": false, - "show": true - }, - "input_key": { - "type": "str", - "required": false, - "default": "question", - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": "answer", - "list": false, - "show": false - }, - "prompt": { - "type": "BasePromptTemplate", - "required": false, - "default": { - "input_variables": [ - "question" - ], - "output_parser": null, - "template": "If someone asks you to perform a task, your job is to come up with a series of bash commands that will perform the task. There is no need to put \"#!/bin/bash\" in your answer. Make sure to reason step by step, using this format:\n\nQuestion: \"copy the files in the directory named 'target' into a new directory at the same level as target called 'myNewDirectory'\"\n\nI need to take the following actions:\n- List all files in the directory\n- Create a new directory\n- Copy the files from the first directory into the second directory\n```bash\nls\nmkdir myNewDirectory\ncp -r target/* myNewDirectory\n```\n\nThat is the format. Begin!\n\nQuestion: {question}", - "template_format": "f-string", - "validate_template": true, - "_type": "prompt" - }, - "list": false, - "show": false - } - }, - "_type": "llm_bash_chain" - }, - "LLMCheckerChain": { - "template": { - "memory": { - "type": "Memory", - "required": false, - "default": null, - "list": false, - "show": false - }, - "verbose": { - "type": "bool", - "required": false, - "list": false, - "show": false - }, - "llm": { - "type": "BaseLLM", - "required": true, - "list": false, - "show": true - }, - "create_draft_answer_prompt": { - "type": "PromptTemplate", - "required": false, - "default": { - "input_variables": [ - "question" - ], - "output_parser": null, - "template": "{question}\n\n", - "template_format": "f-string", - "validate_template": true, - "_type": "prompt" - }, - "list": false, - "show": false - }, - "list_assertions_prompt": { - "type": "PromptTemplate", - "required": false, - "default": { - "input_variables": [ - "statement" - ], - "output_parser": null, - "template": "Here is a statement:\n{statement}\nMake a bullet point list of the assumptions you made when producing the above statement.\n\n", - "template_format": "f-string", - "validate_template": true, - "_type": "prompt" - }, - "list": false, - "show": false - }, - "check_assertions_prompt": { - "type": "PromptTemplate", - "required": false, - "default": { - "input_variables": [ - "assertions" - ], - "output_parser": null, - "template": "Here is a bullet point list of assertions:\n{assertions}\nFor each assertion, determine whether it is true or false. If it is false, explain why.\n\n", - "template_format": "f-string", - "validate_template": true, - "_type": "prompt" - }, - "list": false, - "show": false - }, - "revised_answer_prompt": { - "type": "PromptTemplate", - "required": false, - "default": { - "input_variables": [ - "checked_assertions", - "question" - ], - "output_parser": null, - "template": "{checked_assertions}\n\nQuestion: In light of the above assertions and checks, how would you answer the question '{question}'?\n\nAnswer:", - "template_format": "f-string", - "validate_template": true, - "_type": "prompt" - }, - "list": false, - "show": false - }, - "input_key": { - "type": "str", - "required": false, - "default": "query", - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": "result", - "list": false, - "show": false - } - }, - "_type": "llm_checker_chain" - }, - "LLMMathChain": { - "template": { - "memory": { - "type": "Memory", - "required": false, - "default": null, - "list": false, - "show": false - }, - "verbose": { - "type": "bool", - "required": false, - "list": false, - "show": false - }, - "llm": { - "type": "BaseLLM", - "required": true, - "list": false, - "show": true - }, - "prompt": { - "type": "BasePromptTemplate", - "required": false, - "default": { - "input_variables": [ - "question" - ], - "output_parser": null, - "template": "You are GPT-3, and you can't do math.\n\nYou can do basic math, and your memorization abilities are impressive, but you can't do any complex calculations that a human could not do in their head. You also have an annoying tendency to just make up highly specific, but wrong, answers.\n\nSo we hooked you up to a Python 3 kernel, and now you can execute code. If anyone gives you a hard math problem, just use this format and we’ll take care of the rest:\n\nQuestion: ${{Question with hard calculation.}}\n```python\n${{Code that prints what you need to know}}\n```\n```output\n${{Output of your code}}\n```\nAnswer: ${{Answer}}\n\nOtherwise, use this simpler format:\n\nQuestion: ${{Question without hard calculation}}\nAnswer: ${{Answer}}\n\nBegin.\n\nQuestion: What is 37593 * 67?\n\n```python\nprint(37593 * 67)\n```\n```output\n2518731\n```\nAnswer: 2518731\n\nQuestion: {question}\n", - "template_format": "f-string", - "validate_template": true, - "_type": "prompt" - }, - "list": false, - "show": false - }, - "input_key": { - "type": "str", - "required": false, - "default": "question", - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": "answer", - "list": false, - "show": false - } - }, - "_type": "llm_math_chain" - }, - "LLMRequestsChain": { - "template": { - "memory": { - "type": "Memory", - "required": false, - "default": null, - "list": false, - "show": false - }, - "verbose": { - "type": "bool", - "required": false, - "list": false, - "show": false - }, - "llm_chain": { - "type": "LLMChain", - "required": true, - "list": false, - "show": true - }, - "requests_wrapper": { - "type": "RequestsWrapper", - "required": false, - "list": false, - "show": false - }, - "text_length": { - "type": "int", - "required": false, - "default": 8000, - "list": false, - "show": false - }, - "requests_key": { - "type": "str", - "required": false, - "default": "requests_result", - "list": false, - "show": false - }, - "input_key": { - "type": "str", - "required": false, - "default": "url", - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": "output", - "list": false, - "show": false - } - }, - "_type": "llm_requests_chain" - }, - "ConversationChain": { - "template": { - "memory": { - "type": "Memory", - "required": false, - "list": false, - "show": false - }, - "verbose": { - "type": "bool", - "required": false, - "list": false, - "show": false - }, - "prompt": { - "type": "BasePromptTemplate", - "required": false, - "default": { - "input_variables": [ - "history", - "input" - ], - "output_parser": null, - "template": "The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.\n\nCurrent conversation:\n{history}\nHuman: {input}\nAI:", - "template_format": "f-string", - "validate_template": true, - "_type": "prompt" - }, - "list": false, - "show": false - }, - "llm": { - "type": "BaseLLM", - "required": true, - "list": false, - "show": true - }, - "output_key": { - "type": "str", - "required": false, - "default": "response", - "list": false, - "show": false - }, - "input_key": { - "type": "str", - "required": false, - "default": "input", - "list": false, - "show": false - } - }, - "_type": "llm_conversation_chain" - }, - "PALChain": { - "template": { - "memory": { - "type": "Memory", - "required": false, - "default": null, - "list": false, - "show": false - }, - "verbose": { - "type": "bool", - "required": false, - "list": false, - "show": false - }, - "llm": { - "type": "BaseLLM", - "required": true, - "list": false, - "show": true - }, - "prompt": { - "type": "BasePromptTemplate", - "required": true, - "list": false, - "show": true - }, - "stop": { - "type": "str", - "required": false, - "default": "\n\n", - "list": false, - "show": false - }, - "get_answer_expr": { - "type": "str", - "required": false, - "default": "print(solution())", - "list": false, - "show": false - }, - "python_globals": { - "type": "dict[str, Any]", - "required": false, - "default": null, - "list": false, - "show": false - }, - "python_locals": { - "type": "dict[str, Any]", - "required": false, - "default": null, - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": "result", - "list": false, - "show": false - }, - "return_intermediate_steps": { - "type": "bool", - "required": false, - "default": false, - "list": false, - "show": false - } - }, - "_type": "pal_chain" - }, - "QAWithSourcesChain": { - "template": { - "memory": { - "type": "Memory", - "required": false, - "default": null, - "list": false, - "show": false - }, - "verbose": { - "type": "bool", - "required": false, - "list": false, - "show": false - }, - "combine_documents_chain": { - "type": "BaseCombineDocumentsChain", - "required": true, - "list": false, - "show": true - }, - "question_key": { - "type": "str", - "required": false, - "default": "question", - "list": false, - "show": false - }, - "input_docs_key": { - "type": "str", - "required": false, - "default": "docs", - "list": false, - "show": false - }, - "answer_key": { - "type": "str", - "required": false, - "default": "answer", - "list": false, - "show": false - }, - "sources_answer_key": { - "type": "str", - "required": false, - "default": "sources", - "list": false, - "show": false - } - }, - "_type": "qa_with_sources_chain" - }, - "StuffDocumentsChain": { - "template": { - "memory": { - "type": "Memory", - "required": false, - "default": null, - "list": false, - "show": false - }, - "verbose": { - "type": "bool", - "required": false, - "list": false, - "show": false - }, - "input_key": { - "type": "str", - "required": false, - "default": "input_documents", - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": "output_text", - "list": false, - "show": false - }, - "llm_chain": { - "type": "LLMChain", - "required": true, - "list": false, - "show": true - }, - "document_prompt": { - "type": "BasePromptTemplate", - "required": false, - "list": false, - "show": false - }, - "document_variable_name": { - "type": "str", - "required": true, - "list": false, - "show": true - } - }, - "_type": "stuff_documents_chain" - }, - "MapReduceDocumentsChain": { - "template": { - "memory": { - "type": "Memory", - "required": false, - "default": null, - "list": false, - "show": false - }, - "verbose": { - "type": "bool", - "required": false, - "list": false, - "show": false - }, - "input_key": { - "type": "str", - "required": false, - "default": "input_documents", - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": "output_text", - "list": false, - "show": false - }, - "llm_chain": { - "type": "LLMChain", - "required": true, - "list": false, - "show": true - }, - "combine_document_chain": { - "type": "BaseCombineDocumentsChain", - "required": true, - "list": false, - "show": true - }, - "collapse_document_chain": { - "type": "BaseCombineDocumentsChain", - "required": false, - "default": null, - "list": false, - "show": false - }, - "document_variable_name": { - "type": "str", - "required": true, - "list": false, - "show": true - }, - "return_intermediate_steps": { - "type": "bool", - "required": false, - "default": false, - "list": false, - "show": false - } - }, - "_type": "map_reduce_documents_chain" - }, - "MapRerankDocumentsChain": { - "template": { - "memory": { - "type": "Memory", - "required": false, - "default": null, - "list": false, - "show": false - }, - "verbose": { - "type": "bool", - "required": false, - "list": false, - "show": false - }, - "input_key": { - "type": "str", - "required": false, - "default": "input_documents", - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": "output_text", - "list": false, - "show": false - }, - "llm_chain": { - "type": "LLMChain", - "required": true, - "list": false, - "show": true - }, - "document_variable_name": { - "type": "str", - "required": true, - "list": false, - "show": true - }, - "rank_key": { - "type": "str", - "required": true, - "list": false, - "show": true - }, - "answer_key": { - "type": "str", - "required": true, - "list": false, - "show": true - }, - "metadata_keys": { - "type": "str", - "required": false, - "default": null, - "list": true, - "show": false - }, - "return_intermediate_steps": { - "type": "bool", - "required": false, - "default": false, - "list": false, - "show": false - } - }, - "_type": "map_rerank_documents_chain" - }, - "RefineDocumentsChain": { - "template": { - "memory": { - "type": "Memory", - "required": false, - "default": null, - "list": false, - "show": false - }, - "verbose": { - "type": "bool", - "required": false, - "list": false, - "show": false - }, - "input_key": { - "type": "str", - "required": false, - "default": "input_documents", - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": "output_text", - "list": false, - "show": false - }, - "initial_llm_chain": { - "type": "LLMChain", - "required": true, - "list": false, - "show": true - }, - "refine_llm_chain": { - "type": "LLMChain", - "required": true, - "list": false, - "show": true - }, - "document_variable_name": { - "type": "str", - "required": true, - "list": false, - "show": true - }, - "initial_response_name": { - "type": "str", - "required": true, - "list": false, - "show": true - }, - "document_prompt": { - "type": "BasePromptTemplate", - "required": false, - "list": false, - "show": false - }, - "return_intermediate_steps": { - "type": "bool", - "required": false, - "default": false, - "list": false, - "show": false - } - }, - "_type": "refine_documents_chain" - }, - "SQLDatabaseChain": { - "template": { - "memory": { - "type": "Memory", - "required": false, - "default": null, - "list": false, - "show": false - }, - "verbose": { - "type": "bool", - "required": false, - "list": false, - "show": false - }, - "llm": { - "type": "BaseLLM", - "required": true, - "list": false, - "show": true - }, - "database": { - "type": "SQLDatabase", - "required": true, - "list": false, - "show": true - }, - "prompt": { - "type": "BasePromptTemplate", - "required": false, - "default": { - "input_variables": [ - "input", - "table_info", - "dialect", - "top_k" - ], - "output_parser": null, - "template": "Given an input question, first create a syntactically correct {dialect} query to run, then look at the results of the query and return the answer. Unless the user specifies in his question a specific number of examples he wishes to obtain, always limit your query to at most {top_k} results using the LIMIT clause. You can order the results by a relevant column to return the most interesting examples in the database.\n\nNever query for all the columns from a specific table, only ask for a the few relevant columns given the question.\n\nPay attention to use only the column names that you can see in the schema description. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which table.\n\nUse the following format:\n\nQuestion: \"Question here\"\nSQLQuery: \"SQL Query to run\"\nSQLResult: \"Result of the SQLQuery\"\nAnswer: \"Final answer here\"\n\nOnly use the tables listed below.\n\n{table_info}\n\nQuestion: {input}", - "template_format": "f-string", - "validate_template": true, - "_type": "prompt" - }, - "list": false, - "show": false - }, - "top_k": { - "type": "int", - "required": false, - "default": 5, - "list": false, - "show": false - }, - "input_key": { - "type": "str", - "required": false, - "default": "query", - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": "result", - "list": false, - "show": false - }, - "return_intermediate_steps": { - "type": "bool", - "required": false, - "default": false, - "list": false, - "show": false - }, - "return_direct": { - "type": "bool", - "required": false, - "default": false, - "list": false, - "show": false - } - }, - "_type": "sql_database_chain" - }, - "VectorDBQAWithSourcesChain": { - "template": { - "memory": { - "type": "Memory", - "required": false, - "default": null, - "list": false, - "show": false - }, - "verbose": { - "type": "bool", - "required": false, - "list": false, - "show": false - }, - "combine_documents_chain": { - "type": "BaseCombineDocumentsChain", - "required": true, - "list": false, - "show": true - }, - "question_key": { - "type": "str", - "required": false, - "default": "question", - "list": false, - "show": false - }, - "input_docs_key": { - "type": "str", - "required": false, - "default": "docs", - "list": false, - "show": false - }, - "answer_key": { - "type": "str", - "required": false, - "default": "answer", - "list": false, - "show": false - }, - "sources_answer_key": { - "type": "str", - "required": false, - "default": "sources", - "list": false, - "show": false - }, - "vectorstore": { - "type": "VectorStore", - "required": true, - "list": false, - "show": true - }, - "k": { - "type": "int", - "required": false, - "default": 4, - "list": false, - "show": false - }, - "reduce_k_below_max_tokens": { - "type": "bool", - "required": false, - "default": false, - "list": false, - "show": false - }, - "max_tokens_limit": { - "type": "int", - "required": false, - "default": 3375, - "list": false, - "show": false - }, - "search_kwargs": { - "type": "dict[str, Any]", - "required": false, - "list": false, - "show": false - } - }, - "_type": "vector_db_qa_with_sources_chain" - }, - "VectorDBQA": { - "template": { - "memory": { - "type": "Memory", - "required": false, - "default": null, - "list": false, - "show": false - }, - "verbose": { - "type": "bool", - "required": false, - "list": false, - "show": false - }, - "vectorstore": { - "type": "VectorStore", - "required": true, - "list": false, - "show": true - }, - "k": { - "type": "int", - "required": false, - "default": 4, - "list": false, - "show": false - }, - "combine_documents_chain": { - "type": "BaseCombineDocumentsChain", - "required": true, - "list": false, - "show": true - }, - "input_key": { - "type": "str", - "required": false, - "default": "query", - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": "result", - "list": false, - "show": false - }, - "return_source_documents": { - "type": "bool", - "required": false, - "default": false, - "list": false, - "show": false - }, - "search_kwargs": { - "type": "dict[str, Any]", - "required": false, - "list": false, - "show": false - }, - "search_type": { - "type": "str", - "required": false, - "default": "similarity", - "list": false, - "show": false - } - }, - "_type": "vector_db_qa" - } - }, - "agents": { - "ZeroShotAgent": { - "template": { - "llm_chain": { - "type": "LLMChain", - "required": true, - "list": false, - "show": true - }, - "allowed_tools": { - "type": "str", - "required": false, - "default": null, - "list": true, - "show": true - }, - "return_values": { - "type": "str", - "required": false, - 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"show": false - }, - "client": { - "type": "Any", - "required": false, - "default": null, - "list": false, - "show": false - }, - "model_name": { - "type": "str", - "required": false, - "default": "text-davinci-003", - "list": false, - "show": false - }, - "temperature": { - "type": "float", - "required": false, - "default": 0.7, - "list": false, - "show": false - }, - "max_tokens": { - "type": "int", - "required": false, - "default": 256, - "list": false, - "show": false - }, - "top_p": { - "type": "float", - "required": false, - "default": 1, - "list": false, - "show": false - }, - "frequency_penalty": { - "type": "float", - "required": false, - "default": 0, - "list": false, - "show": false - }, - "presence_penalty": { - "type": "float", - "required": false, - "default": 0, - "list": false, - "show": false - }, - "n": { - "type": "int", - "required": false, - "default": 1, - "list": false, - "show": false - }, - "best_of": { - "type": "int", - "required": false, - "default": 1, - "list": false, - "show": false - }, - "model_kwargs": { - "type": "dict[str, Any]", - "required": false, - "list": false, - "show": false - }, - "openai_api_key": { - "type": "str", - "required": false, - "default": null, - "list": false, - "show": false - }, - "batch_size": { - "type": "int", - "required": false, - "default": 20, - "list": false, - "show": false - }, - "request_timeout": { - "type": "Union[float, Tuple[float, float], NoneType]", - "required": false, - "default": null, - "list": false, - "show": false - }, - "logit_bias": { - "type": "dict[str, float]", - "required": false, - "list": false, - "show": false - }, - "max_retries": { - "type": "int", - "required": false, - "default": 6, - "list": false, - "show": false - }, - "deployment_name": { - "type": "str", - "required": false, - "default": "", - "list": false, - "show": false - } - }, - "_type": "azure" - } - }, - "memories": { - "CombinedMemory": { - "template": { - "memories": { - "type": "Memory", - "required": true, - "list": true, - "show": true - } - }, - "_type": "combined" - }, - "ConversationBufferMemory": { - "template": { - "human_prefix": { - "type": "str", - "required": false, - "default": "Human", - "list": false, - "show": false - }, - "ai_prefix": { - "type": "str", - "required": false, - "default": "AI", - "list": false, - "show": false - }, - "buffer": { - "type": "str", - "required": false, - "default": "", - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": null, - "list": false, - "show": false - }, - "input_key": { - "type": "str", - "required": false, - "default": null, - "list": false, - "show": false - }, - "memory_key": { - "type": "str", - "required": false, - "default": "history", - "list": false, - "show": false - } - }, - "_type": "conversation_buffer" - }, - "ConversationBufferWindowMemory": { - "template": { - "human_prefix": { - "type": "str", - "required": false, - "default": "Human", - "list": false, - "show": false - }, - "ai_prefix": { - "type": "str", - "required": false, - "default": "AI", - "list": false, - "show": false - }, - "buffer": { - "type": "str", - "required": false, - "list": true, - "show": false - }, - "memory_key": { - "type": "str", - "required": false, - "default": "history", - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": null, - "list": false, - "show": false - }, - "input_key": { - "type": "str", - "required": false, - "default": null, - "list": false, - "show": false - }, - "k": { - "type": "int", - "required": false, - "default": 5, - "list": false, - "show": false - } - }, - "_type": "conversation_buffer_window" - }, - "ConversationSummaryMemory": { - "template": { - "buffer": { - "type": "str", - "required": false, - "default": "", - "list": false, - "show": false - }, - "human_prefix": { - "type": "str", - "required": false, - "default": "Human", - "list": false, - "show": false - }, - "ai_prefix": { - "type": "str", - "required": false, - "default": "AI", - "list": false, - "show": false - }, - "llm": { - "type": "BaseLLM", - "required": true, - "list": false, - "show": true - }, - "prompt": { - "type": "BasePromptTemplate", - "required": false, - "default": { - "input_variables": [ - "summary", - "new_lines" - ], - "output_parser": null, - "template": "Progressively summarize the lines of conversation provided, adding onto the previous summary returning a new summary.\n\nEXAMPLE\nCurrent summary:\nThe human asks what the AI thinks of artificial intelligence. The AI thinks artificial intelligence is a force for good.\n\nNew lines of conversation:\nHuman: Why do you think artificial intelligence is a force for good?\nAI: Because artificial intelligence will help humans reach their full potential.\n\nNew summary:\nThe human asks what the AI thinks of artificial intelligence. The AI thinks artificial intelligence is a force for good because it will help humans reach their full potential.\nEND OF EXAMPLE\n\nCurrent summary:\n{summary}\n\nNew lines of conversation:\n{new_lines}\n\nNew summary:", - "template_format": "f-string", - "validate_template": true, - "_type": "prompt" - }, - "list": false, - "show": false - }, - "memory_key": { - "type": "str", - "required": false, - "default": "history", - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": null, - "list": false, - "show": false - }, - "input_key": { - "type": "str", - "required": false, - "default": null, - "list": false, - "show": false - } - }, - "_type": "conversation_summary" - }, - "ConversationEntityMemory": { - "template": { - "buffer": { - "type": "str", - "required": false, - "default": [], - "list": true, - "show": false - }, - "human_prefix": { - "type": "str", - "required": false, - "default": "Human", - "list": false, - "show": false - }, - "ai_prefix": { - "type": "str", - "required": false, - "default": "AI", - "list": false, - "show": false - }, - "llm": { - "type": "BaseLLM", - "required": true, - "list": false, - "show": true - }, - "entity_extraction_prompt": { - "type": "BasePromptTemplate", - "required": false, - "default": { - "input_variables": [ - "history", - "input" - ], - "output_parser": null, - "template": "You are an AI assistant reading the transcript of a conversation between an AI and a human. Extract all of the proper nouns from the last line of conversation. As a guideline, a proper noun is generally capitalized. You should definitely extract all names and places.\n\nThe conversation history is provided just in case of a coreference (e.g. \"What do you know about him\" where \"him\" is defined in a previous line) -- ignore items mentioned there that are not in the last line.\n\nReturn the output as a single comma-separated list, or NONE if there is nothing of note to return (e.g. the user is just issuing a greeting or having a simple conversation).\n\nEXAMPLE\nConversation history:\nPerson #1: how's it going today?\nAI: \"It's going great! How about you?\"\nPerson #1: good! busy working on Langchain. lots to do.\nAI: \"That sounds like a lot of work! What kind of things are you doing to make Langchain better?\"\nLast line:\nPerson #1: i'm trying to improve Langchain's interfaces, the UX, its integrations with various products the user might want ... a lot of stuff.\nOutput: Langchain\nEND OF EXAMPLE\n\nEXAMPLE\nConversation history:\nPerson #1: how's it going today?\nAI: \"It's going great! How about you?\"\nPerson #1: good! busy working on Langchain. lots to do.\nAI: \"That sounds like a lot of work! What kind of things are you doing to make Langchain better?\"\nLast line:\nPerson #1: i'm trying to improve Langchain's interfaces, the UX, its integrations with various products the user might want ... a lot of stuff. I'm working with Person #2.\nOutput: Langchain, Person #2\nEND OF EXAMPLE\n\nConversation history (for reference only):\n{history}\nLast line of conversation (for extraction):\nHuman: {input}\n\nOutput:", - "template_format": "f-string", - "validate_template": true, - "_type": "prompt" - }, - "list": false, - "show": false - }, - "entity_summarization_prompt": { - "type": "BasePromptTemplate", - "required": false, - "default": { - "input_variables": [ - "entity", - "summary", - "history", - "input" - ], - "output_parser": null, - "template": "You are an AI assistant helping a human keep track of facts about relevant people, places, and concepts in their life. Update the summary of the provided entity in the \"Entity\" section based on the last line of your conversation with the human. If you are writing the summary for the first time, return a single sentence.\nThe update should only include facts that are relayed in the last line of conversation about the provided entity, and should only contain facts about the provided entity.\n\nIf there is no new information about the provided entity or the information is not worth noting (not an important or relevant fact to remember long-term), return the existing summary unchanged.\n\nFull conversation history (for context):\n{history}\n\nEntity to summarize:\n{entity}\n\nExisting summary of {entity}:\n{summary}\n\nLast line of conversation:\nHuman: {input}\nUpdated summary:", - "template_format": "f-string", - "validate_template": true, - "_type": "prompt" - }, - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": null, - "list": false, - "show": false - }, - "input_key": { - "type": "str", - "required": false, - "default": null, - "list": false, - "show": false - }, - "store": { - "type": "dict[str, Union[str, NoneType]]", - "required": false, - "default": {}, - "list": false, - "show": false - }, - "entity_cache": { - "type": "str", - "required": false, - "default": [], - "list": true, - "show": false - }, - "k": { - "type": "int", - "required": false, - "default": 3, - "list": false, - "show": false - }, - "chat_history_key": { - "type": "str", - "required": false, - "default": "history", - "list": false, - "show": false - } - }, - "_type": "conversation_entity" - }, - "ConversationSummaryBufferMemory": { - "template": { - "buffer": { - "type": "str", - "required": false, - "list": true, - "show": false - }, - "max_token_limit": { - "type": "int", - "required": false, - "default": 2000, - "list": false, - "show": false - }, - "moving_summary_buffer": { - "type": "str", - "required": false, - "default": "", - "list": false, - "show": false - }, - "llm": { - "type": "BaseLLM", - "required": true, - "list": false, - "show": true - }, - "prompt": { - "type": "BasePromptTemplate", - "required": false, - "default": { - "input_variables": [ - "summary", - "new_lines" - ], - "output_parser": null, - "template": "Progressively summarize the lines of conversation provided, adding onto the previous summary returning a new summary.\n\nEXAMPLE\nCurrent summary:\nThe human asks what the AI thinks of artificial intelligence. The AI thinks artificial intelligence is a force for good.\n\nNew lines of conversation:\nHuman: Why do you think artificial intelligence is a force for good?\nAI: Because artificial intelligence will help humans reach their full potential.\n\nNew summary:\nThe human asks what the AI thinks of artificial intelligence. The AI thinks artificial intelligence is a force for good because it will help humans reach their full potential.\nEND OF EXAMPLE\n\nCurrent summary:\n{summary}\n\nNew lines of conversation:\n{new_lines}\n\nNew summary:", - "template_format": "f-string", - "validate_template": true, - "_type": "prompt" - }, - "list": false, - "show": false - }, - "memory_key": { - "type": "str", - "required": false, - "default": "history", - "list": false, - "show": false - }, - "human_prefix": { - "type": "str", - "required": false, - "default": "Human", - "list": false, - "show": false - }, - "ai_prefix": { - "type": "str", - "required": false, - "default": "AI", - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": null, - "list": false, - "show": false - }, - "input_key": { - "type": "str", - "required": false, - "default": null, - "list": false, - "show": false - } - }, - "_type": "conversation_summary_buffer" - }, - "ConversationKGMemory": { - "template": { - "k": { - "type": "int", - "required": false, - "default": 2, - "list": false, - "show": false - }, - "buffer": { - "type": "str", - "required": false, - "list": true, - "show": false - }, - "kg": { - "type": "NetworkxEntityGraph", - "required": false, - "list": false, - "show": false - }, - "knowledge_extraction_prompt": { - "type": "BasePromptTemplate", - "required": false, - "default": { - "input_variables": [ - "history", - "input" - ], - "output_parser": null, - "template": "You are a networked intelligence helping a human track knowledge triples about all relevant people, things, concepts, etc. and integrating them with your knowledge stored within your weights as well as that stored in a knowledge graph. Extract all of the knowledge triples from the last line of conversation. A knowledge triple is a clause that contains a subject, a predicate, and an object. The subject is the entity being described, the predicate is the property of the subject that is being described, and the object is the value of the property.\n\nEXAMPLE\nConversation history:\nPerson #1: Did you hear aliens landed in Area 51?\nAI: No, I didn't hear that. What do you know about Area 51?\nPerson #1: It's a secret military base in Nevada.\nAI: What do you know about Nevada?\nLast line of conversation:\nPerson #1: It's a state in the US. It's also the number 1 producer of gold in the US.\n\nOutput: (Nevada, is a, state)<|>(Nevada, is in, US)<|>(Nevada, is the number 1 producer of, gold)\nEND OF EXAMPLE\n\nEXAMPLE\nConversation history:\nPerson #1: Hello.\nAI: Hi! How are you?\nPerson #1: I'm good. How are you?\nAI: I'm good too.\nLast line of conversation:\nPerson #1: I'm going to the store.\n\nOutput: NONE\nEND OF EXAMPLE\n\nEXAMPLE\nConversation history:\nPerson #1: What do you know about Descartes?\nAI: Descartes was a French philosopher, mathematician, and scientist who lived in the 17th century.\nPerson #1: The Descartes I'm referring to is a standup comedian and interior designer from Montreal.\nAI: Oh yes, He is a comedian and an interior designer. He has been in the industry for 30 years. His favorite food is baked bean pie.\nPerson #1: Oh huh. I know Descartes likes to drive antique scooters and play the mandolin.\nLast line of conversation:\nOutput: (Descartes, likes to drive, antique scooters)<|>(Descartes, plays, mandolin)\nEND OF EXAMPLE\n\nConversation history (for reference only):\n{history}\nLast line of conversation (for extraction):\nHuman: {input}\n\nOutput:", - "template_format": "f-string", - "validate_template": true, - "_type": "prompt" - }, - "list": false, - "show": false - }, - "entity_extraction_prompt": { - "type": "BasePromptTemplate", - "required": false, - "default": { - "input_variables": [ - "history", - "input" - ], - "output_parser": null, - "template": "You are an AI assistant reading the transcript of a conversation between an AI and a human. Extract all of the proper nouns from the last line of conversation. As a guideline, a proper noun is generally capitalized. You should definitely extract all names and places.\n\nThe conversation history is provided just in case of a coreference (e.g. \"What do you know about him\" where \"him\" is defined in a previous line) -- ignore items mentioned there that are not in the last line.\n\nReturn the output as a single comma-separated list, or NONE if there is nothing of note to return (e.g. the user is just issuing a greeting or having a simple conversation).\n\nEXAMPLE\nConversation history:\nPerson #1: how's it going today?\nAI: \"It's going great! How about you?\"\nPerson #1: good! busy working on Langchain. lots to do.\nAI: \"That sounds like a lot of work! What kind of things are you doing to make Langchain better?\"\nLast line:\nPerson #1: i'm trying to improve Langchain's interfaces, the UX, its integrations with various products the user might want ... a lot of stuff.\nOutput: Langchain\nEND OF EXAMPLE\n\nEXAMPLE\nConversation history:\nPerson #1: how's it going today?\nAI: \"It's going great! How about you?\"\nPerson #1: good! busy working on Langchain. lots to do.\nAI: \"That sounds like a lot of work! What kind of things are you doing to make Langchain better?\"\nLast line:\nPerson #1: i'm trying to improve Langchain's interfaces, the UX, its integrations with various products the user might want ... a lot of stuff. I'm working with Person #2.\nOutput: Langchain, Person #2\nEND OF EXAMPLE\n\nConversation history (for reference only):\n{history}\nLast line of conversation (for extraction):\nHuman: {input}\n\nOutput:", - "template_format": "f-string", - "validate_template": true, - "_type": "prompt" - }, - "list": false, - "show": false - }, - "llm": { - "type": "BaseLLM", - "required": true, - "list": false, - "show": true - }, - "human_prefix": { - "type": "str", - "required": false, - "default": "Human", - "list": false, - "show": false - }, - "ai_prefix": { - "type": "str", - "required": false, - "default": "AI", - "list": false, - "show": false - }, - "output_key": { - "type": "str", - "required": false, - "default": null, - "list": false, - "show": false - }, - "input_key": { - "type": "str", - "required": false, - "default": null, - "list": false, - "show": false - }, - "memory_key": { - "type": "str", - "required": false, - "default": "history", - "list": false, - "show": false - } - }, - "_type": "conversation_kg" - } - }, - "tools": { - "python_repl": { - "template": {}, - "name": "Python REPL", - "description": "A Python shell. Use this to execute python commands. Input should be a valid python command. If you expect output it should be printed out." - }, - "requests": { - "template": {}, - "name": "Requests", - "description": "A portal to the internet. Use this when you need to get specific content from a site. Input should be a specific url, and the output will be all the text on that page." - }, - "terminal": { - "template": {}, - "name": "Terminal", - "description": "Executes commands in a terminal. Input should be valid commands, and the output will be any output from running that command." - }, - "pal-math": { - "template": { - "llm": { - "type": "BaseLLM", - "required": true, - "list": false, - "show": true - } - }, - "name": "PAL-MATH", - "description": "A language model that is really good at solving complex word math problems. Input should be a fully worded hard word math problem." - }, - "pal-colored-objects": { - "template": { - "llm": { - "type": "BaseLLM", - "required": true, - "list": false, - "show": true - } - }, - "name": "PAL-COLOR-OBJ", - "description": "A language model that is really good at reasoning about position and the color attributes of objects. Input should be a fully worded hard reasoning problem. Make sure to include all information about the objects AND the final question you want to answer." - }, - "llm-math": { - "template": { - "llm": { - "type": "BaseLLM", - "required": true, - "list": false, - "show": true - } - }, - "name": "Calculator", - "description": "Useful for when you need to answer questions about math." - }, - "open-meteo-api": { - "template": { - "llm": { - "type": "BaseLLM", - "required": true, - "list": false, - "show": true - } - }, - "name": "Open Meteo API", - "description": "Useful for when you want to get weather information from the OpenMeteo API. The input should be a question in natural language that this API can answer." - }, - "news-api": { - "template": { - "llm": { - "type": "BaseLLM", - "required": true, - "list": false, - "show": true - }, - "news_api_key": { - "type": "str", - "required": true, - "list": false, - "show": true - } - }, - "name": "News API", - "description": "Use this when you want to get information about the top headlines of current news stories. The input should be a question in natural language that this API can answer." - }, - "tmdb-api": { - "template": { - "llm": { - "type": "BaseLLM", - "required": true, - "list": false, - "show": true - }, - "tmdb_bearer_token": { - "type": "str", - "required": true, - "list": false, - "show": true - } - }, - "name": "TMDB API", - "description": "Useful for when you want to get information from The Movie Database. The input should be a question in natural language that this API can answer." - }, - "wolfram-alpha": { - "template": { - "wolfram_alpha_appid": { - "type": "str", - "required": true, - "list": false, - "show": true - } - }, - "name": "Wolfram Alpha", - "description": "A wrapper around Wolfram Alpha. Useful for when you need to answer questions about Math, Science, Technology, Culture, Society and Everyday Life. Input should be a search query." - }, - "google-search": { - "template": { - "google_api_key": { - "type": "str", - "required": true, - "list": false, - "show": true - }, - "google_cse_id": { - "type": "str", - "required": true, - "list": false, - "show": true - } - }, - "name": "Google Search", - "description": "A wrapper around Google Search. Useful for when you need to answer questions about current events. Input should be a search query." - }, - "serpapi": { - "template": { - "serpapi_api_key": { - "type": "str", - "required": true, - "list": false, - "show": true - }, - "aiosession": { - "type": "str", - "required": true, - "list": false, - "show": true - } - }, - "name": "Search", - "description": "A search engine. Useful for when you need to answer questions about current events. Input should be a search query." - } - } - } \ No newline at end of file From 2decce7f6b302fcafa9f0e3e8879009f8c476c09 Mon Sep 17 00:00:00 2001 From: Ibis Prevedello Date: Thu, 2 Mar 2023 23:25:24 -0300 Subject: [PATCH 2/3] refac: new version for Dockerfile --- Dockerfile | 66 +- build_and_push | 11 +- langflow/backend/poetry.lock | 360 +++++++- langflow/backend/pyproject.toml | 8 +- langflow/cli.py | 5 +- poetry.lock | 1411 +------------------------------ pyproject.toml | 16 +- 7 files changed, 445 insertions(+), 1432 deletions(-) diff --git a/Dockerfile b/Dockerfile index d56e412d0..cbef555ba 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,9 +1,69 @@ -FROM python:3.10-slim +FROM logspace/backend_build as backend_build +FROM logspace/frontend_build as frontend_build +# `python-base` sets up all our shared environment variables +FROM python:3.10-slim as langflow_build + +# python +ENV PYTHONUNBUFFERED=1 \ + # prevents python creating .pyc files + PYTHONDONTWRITEBYTECODE=1 \ + \ + # pip + PIP_NO_CACHE_DIR=off \ + PIP_DISABLE_PIP_VERSION_CHECK=on \ + PIP_DEFAULT_TIMEOUT=100 \ + \ + # poetry + # https://python-poetry.org/docs/configuration/#using-environment-variables + POETRY_VERSION=1.4.0 \ + # 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" + +RUN apt-get update \ + && apt-get install --no-install-recommends -y \ + # deps for installing poetry + curl \ + # deps for building python deps + build-essential libpq-dev git + +# install poetry - respects $POETRY_VERSION & $POETRY_HOME +RUN curl -sSL https://install.python-poetry.org | python3 - + +# copy project requirement files here to ensure they will be cached. WORKDIR /app +COPY pyproject.toml ./ +#poetry.lock -COPY --from=frontend_build /app/build/ / +# Copy files from frontend +COPY --from=frontend_build /app/build /app/langflow/frontend/build/ -EXPOSE 80 +# Copy files from backend and install +COPY --from=backend_build /app/dist/*.whl /app/dist/ + +# Copy cli.py +COPY langflow/cli.py /app/langflow/ + +# RUN pip install langflow-0.0.17-py3-none-any.whl +RUN poetry install +# RUN poetry add dist/langflow-0.0.17-py3-none-any.whl +# RUN rm *.whl + +# RUN poetry build + +# EXPOSE 80 # CMD [ "langchain" ] diff --git a/build_and_push b/build_and_push index 649441688..ad74d6368 100755 --- a/build_and_push +++ b/build_and_push @@ -1,7 +1,12 @@ #! /bin/bash +cd langflow/frontend docker build -t logspace/frontend_build -f build.Dockerfile . -poetry remove langchain +cd ../backend +docker build -t logspace/backend_build -f build.Dockerfile . + +cd ../../ VERSION=$(toml get --toml-path pyproject.toml tool.poetry.version) -docker build --build-arg VERSION=$VERSION -t ibiscp/langflow:$VERSION . && docker push ibiscp/langflow:$VERSION -poetry add --editable ../../../langchain +docker build --build-arg VERSION=$VERSION -t ibiscp/langflow:$VERSION . +# docker push ibiscp/langflow:$VERSION +# poetry add --editable ../../../langchain diff --git a/langflow/backend/poetry.lock b/langflow/backend/poetry.lock index c88db5862..2be4e0a9e 100644 --- a/langflow/backend/poetry.lock +++ b/langflow/backend/poetry.lock @@ -204,6 +204,22 @@ traitlets = ">=5.3" [package.extras] test = ["pytest"] +[[package]] +name = "dataclasses-json" +version = "0.5.7" +description = "Easily serialize dataclasses to and from JSON" +category = "main" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +marshmallow = ">=3.3.0,<4.0.0" +marshmallow-enum = ">=1.5.1,<2.0.0" +typing-inspect = ">=0.4.0" + +[package.extras] +dev = ["flake8", "hypothesis", "ipython", "mypy (>=0.710)", "portray", "pytest (>=6.2.3)", "simplejson", "types-dataclasses"] + [[package]] name = "debugpy" version = "1.6.6" @@ -350,6 +366,18 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.1 || >4.21.1,<4 [package.extras] grpc = ["grpcio (>=1.44.0,<2.0.0dev)"] +[[package]] +name = "greenlet" +version = "2.0.2" +description = "Lightweight in-process concurrent programming" +category = "main" +optional = false +python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*" + +[package.extras] +docs = ["Sphinx", "docutils (<0.18)"] +test = ["objgraph", "psutil"] + [[package]] name = "h11" version = "0.14.0" @@ -494,6 +522,63 @@ traitlets = ">=5.3" docs = ["myst-parser", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "traitlets"] test = ["ipykernel", "pre-commit", "pytest", "pytest-cov", "pytest-timeout"] +[[package]] +name = "langchain" +version = "0.0.86" +description = "Building applications with LLMs through composability" +category = "main" +optional = false +python-versions = ">=3.8.1,<4.0" +develop = false + +[package.dependencies] +aiohttp = "^3.8.3" +dataclasses-json = "^0.5.7" +numpy = "^1" +pydantic = "^1" +PyYAML = "^6" +requests = "^2" +SQLAlchemy = "^1" +tenacity = "^8.1.0" + +[package.extras] +all = ["anthropic (>=0.2.2,<0.3.0)", "beautifulsoup4 (>=4,<5)", "cohere (>=3,<4)", "elasticsearch (>=8,<9)", "faiss-cpu (>=1,<2)", "google-api-python-client (==2.70.0)", "google-search-results (>=2,<3)", "huggingface_hub (>=0,<1)", "jinja2 (>=3,<4)", "manifest-ml (>=0.0.1,<0.0.2)", "networkx (>=2.6.3,<3.0.0)", "nlpcloud (>=1,<2)", "nltk (>=3,<4)", "openai (>=0,<1)", "pinecone-client (>=2,<3)", "pypdf (>=3.4.0,<4.0.0)", "qdrant-client (>=0.11.7,<0.12.0)", "redis (>=4,<5)", "sentence-transformers (>=2,<3)", "spacy (>=3,<4)", "tensorflow-text (>=2.11.0,<3.0.0)", "tiktoken (>=0,<1)", "torch (>=1,<2)", "transformers (>=4,<5)", "weaviate-client (>=3,<4)", "wikipedia (>=1,<2)", "wolframalpha (==5.0.0)"] +llms = ["anthropic (>=0.2.2,<0.3.0)", "cohere (>=3,<4)", "huggingface_hub (>=0,<1)", 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"sha256:8b1ff0c400943b6145df8119c41c244ca8207f1f10c9c057aeed1560e4806e3d"}, +] uritemplate = [ {file = "uritemplate-4.1.1-py2.py3-none-any.whl", hash = "sha256:830c08b8d99bdd312ea4ead05994a38e8936266f84b9a7878232db50b044e02e"}, {file = "uritemplate-4.1.1.tar.gz", hash = "sha256:4346edfc5c3b79f694bccd6d6099a322bbeb628dbf2cd86eea55a456ce5124f0"}, diff --git a/langflow/backend/pyproject.toml b/langflow/backend/pyproject.toml index 2de3c0fc4..fca09f975 100644 --- a/langflow/backend/pyproject.toml +++ b/langflow/backend/pyproject.toml @@ -1,9 +1,12 @@ [tool.poetry] name = "langflow" version = "0.0.17" -description = "" +description = "Backend for Langflow" authors = ["Ibis Prevedello "] -# readme = "README.md" +# packages = [ +# { include = "*.py" } +# ] +# exclude = ['dev.py'] [tool.poetry.dependencies] python = "^3.10" @@ -13,6 +16,7 @@ uvicorn = "^0.20.0" beautifulsoup4 = "^4.11.2" google-search-results = "^2.4.1" google-api-python-client = "^2.79.0" +langchain = {git = "https://github.com/ibiscp/langchain.git", rev = "ibis"} [tool.poetry.group.dev.dependencies] black = "^23.1.0" diff --git a/langflow/cli.py b/langflow/cli.py index 1398f8a43..4cdc9445e 100644 --- a/langflow/cli.py +++ b/langflow/cli.py @@ -15,11 +15,12 @@ app.mount( name="static", ) + def main(): import uvicorn - uvicorn.run(app, host="localhost", port=8000) + uvicorn.run(app, host="localhost", port=80) if __name__ == "__main__": - main() \ No newline at end of file + main() diff --git a/poetry.lock b/poetry.lock index 25ac1abe0..23181f7ac 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,113 +1,3 @@ -[[package]] -name = "aiohttp" -version = "3.8.4" -description = "Async http client/server framework (asyncio)" -category = "main" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -aiosignal = ">=1.1.2" -async-timeout = ">=4.0.0a3,<5.0" -attrs = ">=17.3.0" -charset-normalizer = ">=2.0,<4.0" -frozenlist = ">=1.1.1" -multidict = ">=4.5,<7.0" -yarl = ">=1.0,<2.0" - -[package.extras] -speedups = ["Brotli", "aiodns", "cchardet"] - -[[package]] -name = "aiosignal" -version = "1.3.1" -description = "aiosignal: a list of registered asynchronous callbacks" -category = "main" -optional = false -python-versions = ">=3.7" - -[package.dependencies] -frozenlist = ">=1.1.0" - -[[package]] -name = "anyio" -version = "3.6.2" -description = "High level compatibility layer for multiple asynchronous event loop implementations" -category = "main" -optional = false -python-versions = ">=3.6.2" - -[package.dependencies] -idna = ">=2.8" -sniffio = ">=1.1" - -[package.extras] -doc = ["packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"] -test = ["contextlib2", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (<0.15)", "uvloop (>=0.15)"] -trio = ["trio (>=0.16,<0.22)"] - -[[package]] -name = "async-timeout" -version = "4.0.2" -description = "Timeout context manager for asyncio programs" -category = "main" -optional = false -python-versions = ">=3.6" - -[[package]] -name = "attrs" -version = "22.2.0" -description = "Classes Without Boilerplate" -category = "main" -optional = false -python-versions = ">=3.6" - -[package.extras] -cov = ["attrs[tests]", "coverage-enable-subprocess", "coverage[toml] (>=5.3)"] -dev = ["attrs[docs,tests]"] -docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope.interface"] -tests = ["attrs[tests-no-zope]", "zope.interface"] -tests-no-zope = ["cloudpickle", "cloudpickle", "hypothesis", "hypothesis", "mypy (>=0.971,<0.990)", "mypy (>=0.971,<0.990)", "pympler", "pympler", "pytest (>=4.3.0)", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-mypy-plugins", "pytest-xdist[psutil]", "pytest-xdist[psutil]"] - -[[package]] -name = "beautifulsoup4" -version = "4.11.2" -description = "Screen-scraping library" -category = "main" -optional = false -python-versions = ">=3.6.0" - -[package.dependencies] -soupsieve = ">1.2" - -[package.extras] -html5lib = ["html5lib"] -lxml = ["lxml"] - -[[package]] -name = "cachetools" -version = "5.3.0" -description = "Extensible memoizing collections and decorators" -category = "main" -optional = false -python-versions = "~=3.7" - -[[package]] -name = "certifi" -version = "2022.12.7" -description = "Python package for providing Mozilla's CA Bundle." -category = "main" -optional = false -python-versions = ">=3.6" - -[[package]] -name = "charset-normalizer" -version = "3.0.1" -description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." -category = "main" -optional = false -python-versions = "*" - [[package]] name = "click" version = "8.1.3" @@ -127,153 +17,6 @@ category = "main" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7" -[[package]] -name = "dataclasses-json" -version = "0.5.7" -description = "Easily serialize dataclasses to and from JSON" -category = "main" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -marshmallow = ">=3.3.0,<4.0.0" -marshmallow-enum = ">=1.5.1,<2.0.0" -typing-inspect = ">=0.4.0" - -[package.extras] -dev = ["flake8", "hypothesis", "ipython", "mypy (>=0.710)", "portray", "pytest (>=6.2.3)", "simplejson", "types-dataclasses"] - -[[package]] -name = "fastapi" -version = "0.91.0" -description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production" -category = "main" -optional = false -python-versions = ">=3.7" - -[package.dependencies] -pydantic = ">=1.6.2,<1.7 || >1.7,<1.7.1 || >1.7.1,<1.7.2 || >1.7.2,<1.7.3 || >1.7.3,<1.8 || >1.8,<1.8.1 || >1.8.1,<2.0.0" -starlette = ">=0.24.0,<0.25.0" - -[package.extras] -all = ["email-validator (>=1.1.1)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=2.11.2)", "orjson (>=3.2.1)", "python-multipart (>=0.0.5)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"] -dev = ["pre-commit (>=2.17.0,<3.0.0)", "ruff (==0.0.138)", "uvicorn[standard] (>=0.12.0,<0.21.0)"] -doc = ["mdx-include (>=1.4.1,<2.0.0)", "mkdocs (>=1.1.2,<2.0.0)", "mkdocs-markdownextradata-plugin (>=0.1.7,<0.3.0)", "mkdocs-material (>=8.1.4,<9.0.0)", "pyyaml (>=5.3.1,<7.0.0)", "typer[all] (>=0.6.1,<0.8.0)"] -test = ["anyio[trio] (>=3.2.1,<4.0.0)", "black (==22.10.0)", "coverage[toml] (>=6.5.0,<8.0)", "databases[sqlite] (>=0.3.2,<0.7.0)", "email-validator (>=1.1.1,<2.0.0)", "flask (>=1.1.2,<3.0.0)", "httpx (>=0.23.0,<0.24.0)", "isort (>=5.0.6,<6.0.0)", "mypy (==0.982)", "orjson (>=3.2.1,<4.0.0)", "passlib[bcrypt] (>=1.7.2,<2.0.0)", "peewee (>=3.13.3,<4.0.0)", "pytest (>=7.1.3,<8.0.0)", "python-jose[cryptography] (>=3.3.0,<4.0.0)", "python-multipart (>=0.0.5,<0.0.6)", "pyyaml (>=5.3.1,<7.0.0)", "ruff (==0.0.138)", "sqlalchemy (>=1.3.18,<1.4.43)", "types-orjson (==3.6.2)", "types-ujson (==5.6.0.0)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0,<6.0.0)"] - 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-[package.extras] -docs = ["Sphinx", "docutils (<0.18)"] -test = ["objgraph", "psutil"] - [[package]] name = "h11" version = "0.14.0" @@ -282,362 +25,6 @@ category = "main" optional = false python-versions = ">=3.7" -[[package]] -name = "httplib2" -version = "0.21.0" -description = "A comprehensive HTTP client library." -category = "main" -optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" - -[package.dependencies] -pyparsing = {version = ">=2.4.2,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.0.2 || >3.0.2,<3.0.3 || >3.0.3,<4", markers = "python_version > \"3.0\""} - -[[package]] -name = "idna" -version = "3.4" -description = "Internationalized Domain Names in Applications (IDNA)" -category = "main" -optional = false -python-versions = ">=3.5" - -[[package]] -name = "langchain" -version = "0.0.86" -description = "Building applications with LLMs through composability" -category = "main" -optional = false -python-versions = ">=3.8.1,<4.0" -develop = false - -[package.dependencies] -aiohttp = "^3.8.3" -dataclasses-json = "^0.5.7" -numpy = "^1" -pydantic = "^1" -PyYAML = "^6" -requests = "^2" -SQLAlchemy = "^1" -tenacity = "^8.1.0" - 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{ include = "langflow/backend/*.py" } + # { include = "langflow/backend/*.py" } ] include = [{path= "langflow/frontend/build/*", format=["sdist", "wheel"]}, {path= "langflow/frontend/build/static/js/*", format=["sdist", "wheel"]}, @@ -20,12 +20,10 @@ build-backend = "poetry.core.masonry.api" [tool.poetry.dependencies] python = "^3.10" -openai = "^0.26.5" -fastapi = "^0.91.0" +# openai = "^0.26.5" +# fastapi = "^0.91.0" uvicorn = "^0.20.0" -beautifulsoup4 = "^4.11.2" -google-search-results = "^2.4.1" -google-api-python-client = "^2.79.0" -langchain = {git = "https://github.com/ibiscp/langchain.git", rev = "ibis"} - -[tool.poetry.dev-dependencies] \ No newline at end of file +# beautifulsoup4 = "^4.11.2" +# google-search-results = "^2.4.1" +# google-api-python-client = "^2.79.0" +# langchain = {git = "https://github.com/ibiscp/langchain.git", rev = "ibis"} \ No newline at end of file From 3ec4257a635d4dfe3b32ff936cb4079e41e2b103 Mon Sep 17 00:00:00 2001 From: Ibis Prevedello Date: Sat, 4 Mar 2023 11:22:19 -0300 Subject: [PATCH 3/3] feat: fix integration with newest langchain version --- langflow/backend/list_endpoints.py | 16 +++- langflow/backend/poetry.lock | 14 ++- langflow/backend/pyproject.toml | 2 +- langflow/backend/signature.py | 112 +++-------------------- langflow/backend/util.py | 138 +++++++++++++++++++++++++---- 5 files changed, 156 insertions(+), 126 deletions(-) diff --git a/langflow/backend/list_endpoints.py b/langflow/backend/list_endpoints.py index bf5741666..5448b3613 100644 --- a/langflow/backend/list_endpoints.py +++ b/langflow/backend/list_endpoints.py @@ -98,7 +98,15 @@ def list_memories(): def list_tools(): """List all load tools""" - return [ - util.get_tool_params(util.get_tools_dict(tool))["name"] - for tool in get_all_tool_names() - ] + tools = [] + + for tool in get_all_tool_names(): + if tool_params := util.get_tool_params(util.get_tools_dict(tool)): + tools.append(tool_params["name"]) + + return tools + + # return [ + # util.get_tool_params(util.get_tools_dict(tool))["name"] + # for tool in get_all_tool_names() + # ] diff --git a/langflow/backend/poetry.lock b/langflow/backend/poetry.lock index 2be4e0a9e..a6a343680 100644 --- a/langflow/backend/poetry.lock +++ b/langflow/backend/poetry.lock @@ -524,12 +524,12 @@ test = ["ipykernel", "pre-commit", "pytest", "pytest-cov", "pytest-timeout"] [[package]] name = "langchain" -version = "0.0.86" +version = "0.0.100" description = "Building applications with LLMs through composability" category = "main" optional = false python-versions = ">=3.8.1,<4.0" -develop = false +develop = true [package.dependencies] aiohttp = "^3.8.3" @@ -542,14 +542,12 @@ SQLAlchemy = "^1" tenacity = "^8.1.0" [package.extras] -all = ["anthropic (>=0.2.2,<0.3.0)", "beautifulsoup4 (>=4,<5)", "cohere (>=3,<4)", "elasticsearch (>=8,<9)", "faiss-cpu (>=1,<2)", "google-api-python-client (==2.70.0)", "google-search-results (>=2,<3)", "huggingface_hub (>=0,<1)", "jinja2 (>=3,<4)", "manifest-ml (>=0.0.1,<0.0.2)", "networkx (>=2.6.3,<3.0.0)", "nlpcloud (>=1,<2)", "nltk (>=3,<4)", "openai (>=0,<1)", "pinecone-client (>=2,<3)", "pypdf (>=3.4.0,<4.0.0)", "qdrant-client (>=0.11.7,<0.12.0)", "redis (>=4,<5)", "sentence-transformers (>=2,<3)", "spacy (>=3,<4)", "tensorflow-text (>=2.11.0,<3.0.0)", "tiktoken (>=0,<1)", "torch (>=1,<2)", "transformers (>=4,<5)", "weaviate-client (>=3,<4)", "wikipedia (>=1,<2)", "wolframalpha (==5.0.0)"] +all = ["anthropic (>=0.2.2,<0.3.0)", "beautifulsoup4 (>=4,<5)", "cohere (>=3,<4)", "elasticsearch (>=8,<9)", "faiss-cpu (>=1,<2)", "google-api-python-client (==2.70.0)", "google-search-results (>=2,<3)", "huggingface_hub (>=0,<1)", "jinja2 (>=3,<4)", "manifest-ml (>=0.0.1,<0.0.2)", "networkx (>=2.6.3,<3.0.0)", "nlpcloud (>=1,<2)", "nltk (>=3,<4)", "nomic (>=1.0.43,<2.0.0)", "openai (>=0,<1)", "opensearch-py (>=2.0.0,<3.0.0)", "pinecone-client (>=2,<3)", "pypdf (>=3.4.0,<4.0.0)", "qdrant-client (>=1.0.4,<2.0.0)", "redis (>=4,<5)", "sentence-transformers (>=2,<3)", "spacy (>=3,<4)", "tensorflow-text (>=2.11.0,<3.0.0)", "tiktoken (>=0,<1)", "torch (>=1,<2)", "transformers (>=4,<5)", "weaviate-client (>=3,<4)", "wikipedia (>=1,<2)", "wolframalpha (==5.0.0)"] llms = ["anthropic (>=0.2.2,<0.3.0)", "cohere (>=3,<4)", "huggingface_hub (>=0,<1)", "manifest-ml (>=0.0.1,<0.0.2)", "nlpcloud (>=1,<2)", "openai (>=0,<1)", "torch (>=1,<2)", "transformers (>=4,<5)"] [package.source] -type = "git" -url = "https://github.com/ibiscp/langchain.git" -reference = "ibis" -resolved_reference = "059e90090639e3c8c23928f1799e715b5635f681" +type = "directory" +url = "../../../langchain" [[package]] name = "marshmallow" @@ -1101,7 +1099,7 @@ multidict = ">=4.0" [metadata] lock-version = "1.1" python-versions = "^3.10" -content-hash = "fb4b97be211d190c4feff42124fce6062b8717373d32b4894ae53f760742faaa" +content-hash = "37ef2fda1358fdb0b52d9584f0fc903a9581310cc271c5bbfb79b6085176bf2e" [metadata.files] aiohttp = [ diff --git a/langflow/backend/pyproject.toml b/langflow/backend/pyproject.toml index fca09f975..d83a0488c 100644 --- a/langflow/backend/pyproject.toml +++ b/langflow/backend/pyproject.toml @@ -16,7 +16,7 @@ uvicorn = "^0.20.0" beautifulsoup4 = "^4.11.2" google-search-results = "^2.4.1" google-api-python-client = "^2.79.0" -langchain = {git = "https://github.com/ibiscp/langchain.git", rev = "ibis"} +langchain = {path = "../../../langchain", develop = true} [tool.poetry.group.dev.dependencies] black = "^23.1.0" diff --git a/langflow/backend/signature.py b/langflow/backend/signature.py index 4ba2e009d..bfa2c94f6 100644 --- a/langflow/backend/signature.py +++ b/langflow/backend/signature.py @@ -18,93 +18,13 @@ router = APIRouter( ) -def build_template_from_function(name: str, type_to_loader_dict: dict): - classes = [ - item.__annotations__["return"].__name__ for item in type_to_loader_dict.values() - ] - - # Raise error if name is not in chains - if name not in classes: - raise ValueError(f"{name} not found") - - for _type, v in type_to_loader_dict.items(): - if v.__annotations__["return"].__name__ == name: - _class = v.__annotations__["return"] - - docs = util.get_class_doc(_class) - - variables = {"_type": _type} - for name, value in _class.__fields__.items(): - if name in ["callback_manager", "requests_wrapper"]: - continue - variables[name] = {} - for name_, value_ in value.__repr_args__(): - if name_ == "default_factory": - try: - variables[name]["default"] = util.get_default_factory( - module=_class.__base__.__module__, function=value_ - ) - except Exception: - variables[name]["default"] = None - elif name_ not in ["name"]: - variables[name][name_] = value_ - - variables[name]["placeholder"] = ( - docs["Attributes"][name] if name in docs["Attributes"] else "" - ) - - return { - "template": util.format_dict(variables), - "description": docs["Description"], - "base_classes": util.get_base_classes(_class), - } - - -def build_template_from_class(name: str, type_to_cls_dict: dict): - classes = [item.__name__ for item in type_to_cls_dict.values()] - - # Raise error if name is not in chains - if name not in classes: - raise ValueError(f"{name} not found.") - - for _type, v in type_to_cls_dict.items(): - if v.__name__ == name: - _class = v - - docs = util.get_class_doc(_class) - - variables = {"_type": _type} - for name, value in _class.__fields__.items(): - if name in ["callback_manager"]: - continue - variables[name] = {} - for name_, value_ in value.__repr_args__(): - if name_ == "default_factory": - try: - variables[name]["default"] = util.get_default_factory( - module=_class.__base__.__module__, function=value_ - ) - except Exception: - variables[name]["default"] = None - elif name_ not in ["name"]: - variables[name][name_] = value_ - - variables[name]["placeholder"] = ( - docs["Attributes"][name] if name in docs["Attributes"] else "" - ) - - return { - "template": util.format_dict(variables), - "description": docs["Description"], - "base_classes": util.get_base_classes(_class), - } - - @router.get("/chain") def get_chain(name: str): """Get the signature of a chain.""" try: - return build_template_from_function(name, chains.loading.type_to_loader_dict) + return util.build_template_from_function( + name, chains.loading.type_to_loader_dict + ) except ValueError as exc: raise HTTPException(status_code=404, detail="Chain not found") from exc @@ -113,7 +33,7 @@ def get_chain(name: str): def get_agent(name: str): """Get the signature of an agent.""" try: - return build_template_from_class(name, agents.loading.AGENT_TO_CLASS) + return util.build_template_from_class(name, agents.loading.AGENT_TO_CLASS) except ValueError as exc: raise HTTPException(status_code=404, detail="Agent not found") from exc @@ -122,7 +42,9 @@ def get_agent(name: str): def get_prompt(name: str): """Get the signature of a prompt.""" try: - return build_template_from_function(name, prompts.loading.type_to_loader_dict) + return util.build_template_from_function( + name, prompts.loading.type_to_loader_dict + ) except ValueError as exc: raise HTTPException(status_code=404, detail="Prompt not found") from exc @@ -131,7 +53,7 @@ def get_prompt(name: str): def get_llm(name: str): """Get the signature of an llm.""" try: - return build_template_from_class(name, llms.type_to_cls_dict) + return util.build_template_from_class(name, llms.type_to_cls_dict) except ValueError as exc: raise HTTPException(status_code=404, detail="LLM not found") from exc @@ -152,7 +74,7 @@ def get_llm(name: str): def get_memory(name: str): """Get the signature of a memory.""" try: - return build_template_from_class(name, memories.type_to_cls_dict) + return util.build_template_from_class(name, memories.type_to_cls_dict) except ValueError as exc: raise HTTPException(status_code=404, detail="Memory not found") from exc @@ -173,10 +95,10 @@ def get_memory(name: str): def get_tool(name: str): """Get the signature of a tool.""" - all_tools = { - util.get_tool_params(util.get_tools_dict(tool))["name"]: tool - for tool in get_all_tool_names() - } + all_tools = {} + for tool in get_all_tool_names(): + if tool_params := util.get_tool_params(util.get_tools_dict(tool)): + all_tools[tool_params["name"]] = tool # Raise error if name is not in tools if name not in all_tools.keys(): @@ -185,7 +107,7 @@ def get_tool(name: str): type_dict = { "str": { "type": "str", - "required": True, + "required": False, "list": False, "show": True, "placeholder": "", @@ -218,9 +140,3 @@ def get_tool(name: str): **util.get_tool_params(util.get_tools_dict(tool_type)), "base_classes": ["Tool"], } - - -# {"template": signature.tool(tool), **values} -# for tool, values in tools.items() -# } -# return {k: util.get_tool_params(v) for k, v in merged_dict.items()} diff --git a/langflow/backend/util.py b/langflow/backend/util.py index 615ba32ce..1596adb4a 100644 --- a/langflow/backend/util.py +++ b/langflow/backend/util.py @@ -2,6 +2,8 @@ import ast import inspect import re import importlib + +from langchain.agents.load_tools import * from langchain.agents.load_tools import ( _BASE_TOOLS, _LLM_TOOLS, @@ -11,6 +13,88 @@ from langchain.agents.load_tools import ( from typing import Optional +def build_template_from_function(name: str, type_to_loader_dict: dict): + classes = [ + item.__annotations__["return"].__name__ for item in type_to_loader_dict.values() + ] + + # Raise error if name is not in chains + if name not in classes: + raise ValueError(f"{name} not found") + + for _type, v in type_to_loader_dict.items(): + if v.__annotations__["return"].__name__ == name: + _class = v.__annotations__["return"] + + docs = get_class_doc(_class) + + variables = {"_type": _type} + for name, value in _class.__fields__.items(): + if name in ["callback_manager", "requests_wrapper"]: + continue + variables[name] = {} + for name_, value_ in value.__repr_args__(): + if name_ == "default_factory": + try: + variables[name]["default"] = get_default_factory( + module=_class.__base__.__module__, function=value_ + ) + except Exception: + variables[name]["default"] = None + elif name_ not in ["name"]: + variables[name][name_] = value_ + + variables[name]["placeholder"] = ( + docs["Attributes"][name] if name in docs["Attributes"] else "" + ) + + return { + "template": format_dict(variables), + "description": docs["Description"], + "base_classes": get_base_classes(_class), + } + + +def build_template_from_class(name: str, type_to_cls_dict: dict): + classes = [item.__name__ for item in type_to_cls_dict.values()] + + # Raise error if name is not in chains + if name not in classes: + raise ValueError(f"{name} not found.") + + for _type, v in type_to_cls_dict.items(): + if v.__name__ == name: + _class = v + + docs = get_class_doc(_class) + + variables = {"_type": _type} + for name, value in _class.__fields__.items(): + if name in ["callback_manager"]: + continue + variables[name] = {} + for name_, value_ in value.__repr_args__(): + if name_ == "default_factory": + try: + variables[name]["default"] = get_default_factory( + module=_class.__base__.__module__, function=value_ + ) + except Exception: + variables[name]["default"] = None + elif name_ not in ["name"]: + variables[name][name_] = value_ + + variables[name]["placeholder"] = ( + docs["Attributes"][name] if name in docs["Attributes"] else "" + ) + + return { + "template": format_dict(variables), + "description": docs["Description"], + "base_classes": get_base_classes(_class), + } + + def get_base_classes(cls): bases = cls.__bases__ if not bases: @@ -45,7 +129,7 @@ def get_tools_dict(name: Optional[str] = None): return tools[name] if name else tools -def get_tool_params(func): +def get_tool_params(func, **kwargs): # Parse the function code into an abstract syntax tree tree = ast.parse(inspect.getsource(func)) @@ -54,19 +138,35 @@ def get_tool_params(func): # Find the first return statement if isinstance(node, ast.Return): tool = node.value - if isinstance(tool, ast.Call) and tool.func.id == "Tool": - if tool.keywords: - tool_params = {} - for keyword in tool.keywords: - if keyword.arg == "name": - tool_params["name"] = ast.literal_eval(keyword.value) - elif keyword.arg == "description": - tool_params["description"] = ast.literal_eval(keyword.value) - return tool_params - return { - "name": ast.literal_eval(tool.args[0]), - "description": ast.literal_eval(tool.args[2]), - } + if isinstance(tool, ast.Call): + if tool.func.id == "Tool": + if tool.keywords: + tool_params = {} + for keyword in tool.keywords: + if keyword.arg == "name": + tool_params["name"] = ast.literal_eval(keyword.value) + elif keyword.arg == "description": + tool_params["description"] = ast.literal_eval( + keyword.value + ) + return tool_params + return { + "name": ast.literal_eval(tool.args[0]), + "description": ast.literal_eval(tool.args[2]), + } + else: + # get the class object from the return statement + try: + class_obj = eval( + compile(ast.Expression(tool), "", "eval") + ) + except Exception: + return None + + return { + "name": getattr(class_obj, "name"), + "description": getattr(class_obj, "description"), + } # Return None if no return statement was found return None @@ -162,7 +262,15 @@ def format_dict(d): value["show"] = bool( (value["required"] and key not in ["input_variables"]) or key - in ["allowed_tools", "verbose", "Memory", "memory", "prefix", "examples"] + in [ + "allowed_tools", + "verbose", + "Memory", + "memory", + "prefix", + "examples", + "temperature", + ] or "api_key" in key )