From e70a59dcd431c67ec0522e63b99c2bf0629e2750 Mon Sep 17 00:00:00 2001 From: Charles Packer Date: Wed, 13 Dec 2023 21:36:03 -0800 Subject: [PATCH] added autogen as an extra (#616) * added autogen as an extra * updated docs Co-authored-by: hemanthsavasere --- docs/autogen.md | 2 +- poetry.lock | 92 ++++++++++++++++++++++++++++++++++++++++++++++++- pyproject.toml | 2 ++ 3 files changed, 94 insertions(+), 2 deletions(-) diff --git a/docs/autogen.md b/docs/autogen.md index c4d14d13..f76af4b6 100644 --- a/docs/autogen.md +++ b/docs/autogen.md @@ -8,7 +8,7 @@ The MemGPT+AutoGen integration was last tested using AutoGen version v0.2.0. - If you are having issues, please first try installing the specific version of AutoGen using `pip install pyautogen==0.2.0` + If you are having issues, please first try installing the specific version of AutoGen using `pip install pyautogen==0.2.0` (or `poetry install -E autogen` if you are using Poetry). ## Overview diff --git a/poetry.lock b/poetry.lock index 6bd13a33..f418157d 100644 --- a/poetry.lock +++ b/poetry.lock @@ -688,6 +688,17 @@ files = [ [package.extras] graph = ["objgraph (>=1.7.2)"] +[[package]] +name = "diskcache" +version = "5.6.3" +description = "Disk Cache -- Disk and file backed persistent cache." +optional = false +python-versions = ">=3" +files = [ + {file = "diskcache-5.6.3-py3-none-any.whl", hash = "sha256:5e31b2d5fbad117cc363ebaf6b689474db18a1f6438bc82358b024abd4c2ca19"}, + {file = "diskcache-5.6.3.tar.gz", hash = "sha256:2c3a3fa2743d8535d832ec61c2054a1641f41775aa7c556758a109941e33e4fc"}, +] + [[package]] name = "distlib" version = "0.3.7" @@ -771,6 +782,43 @@ docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1 testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)"] typing = ["typing-extensions (>=4.8)"] +[[package]] +name = "flaml" +version = "2.1.1" +description = "A fast library for automated machine learning and tuning" +optional = false +python-versions = ">=3.6" +files = [ + {file = "FLAML-2.1.1-py3-none-any.whl", hash = "sha256:ba34f1a06f3cbc6bb23a2ea4830a264375f6bba497f402122a73e42647a15535"}, + {file = "FLAML-2.1.1.tar.gz", hash = "sha256:53e94aacc996da80fe779bc6833d3b25c80c77fe11667d0912798e49293282eb"}, +] + +[package.dependencies] +NumPy = ">=1.17.0rc1" + +[package.extras] +autogen = ["diskcache", "openai (==0.27.8)", "termcolor"] +automl = ["lightgbm (>=2.3.1)", "pandas (>=1.1.4)", "scikit-learn (>=0.24)", "scipy (>=1.4.1)", "xgboost (>=0.90)"] +autozero = ["packaging", "pandas", "scikit-learn"] +azureml = ["azureml-mlflow"] +benchmark = ["catboost (>=0.26)", "pandas (==1.1.4)", "psutil (==5.8.0)", "xgboost (==1.3.3)"] +blendsearch = ["optuna (==2.8.0)", "packaging"] +catboost = ["catboost (>=0.26)"] +forecast = ["hcrystalball (==0.1.10)", "holidays (<0.14)", "prophet (>=1.0.1)", "pytorch-forecasting (>=0.9.0)", "pytorch-lightning (==1.9.0)", "statsmodels (>=0.12.2)", "tensorboardX (==2.6)"] +hf = ["datasets", "nltk", "rouge-score", "seqeval", "transformers[torch] (==4.26)"] +mathchat = ["diskcache", "openai (==0.27.8)", "pydantic (==1.10.9)", "sympy", "termcolor", "wolframalpha"] +nlp = ["datasets", "nltk", "rouge-score", "seqeval", "transformers[torch] (==4.26)"] +nni = ["nni"] +notebook = ["jupyter"] +openai = ["diskcache", "openai (==0.27.8)"] +ray = ["ray[tune] (>=1.13,<2.0)"] +retrievechat = ["chromadb", "diskcache", "openai (==0.27.8)", "sentence-transformers", "termcolor", "tiktoken"] +spark = ["joblib (<1.3.0)", "joblibspark (>=0.5.0)", "pyspark (>=3.2.0)"] +synapse = ["joblib (<1.3.0)", "joblibspark (>=0.5.0)", "optuna (==2.8.0)", "pyspark (>=3.2.0)"] +test = ["catboost (>=0.26,<1.2)", "coverage (>=5.3)", "dataclasses", "datasets", "hcrystalball (==0.1.10)", "ipykernel", "joblib (<1.3.0)", "joblibspark (>=0.5.0)", "lightgbm (>=2.3.1)", "mlflow", "nbconvert", "nbformat", "nltk", "openml", "optuna (==2.8.0)", "packaging", "pandas (>=1.1.4)", "pre-commit", "psutil (==5.8.0)", "pydantic (==1.10.9)", "pyspark (>=3.2.0)", "pytest (>=6.1.1)", "pytorch-forecasting (>=0.9.0,<=0.10.1)", "pytorch-lightning (<1.9.1)", "requests (<2.29.0)", "rgf-python", "rouge-score", "scikit-learn (>=0.24)", "scipy (>=1.4.1)", "seqeval", "statsmodels (>=0.12.2)", "sympy", "tensorboardX (==2.6)", "thop", "torch", "torchvision", "transformers[torch] (==4.26)", "wolframalpha", "xgboost (>=0.90)"] +ts-forecast = ["hcrystalball (==0.1.10)", "holidays (<0.14)", "prophet (>=1.0.1)", "statsmodels (>=0.12.2)"] +vw = ["scikit-learn", "vowpalwabbit (>=8.10.0,<9.0.0)"] + [[package]] name = "flatbuffers" version = "23.5.26" @@ -2837,6 +2885,34 @@ files = [ [package.dependencies] pyasn1 = ">=0.4.6,<0.6.0" +[[package]] +name = "pyautogen" +version = "0.2.0" +description = "Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework" +optional = false +python-versions = ">=3.8, <3.12" +files = [ + {file = "pyautogen-0.2.0-py3-none-any.whl", hash = "sha256:d7bf4d239f85152e191026d8173f649e256c431cf31b93ca3629cd2f0c525a46"}, + {file = "pyautogen-0.2.0.tar.gz", hash = "sha256:858f2d15eaa68f043f7b67b975a6d27f738c98ca4d7e0e96b400061c0ac3e692"}, +] + +[package.dependencies] +diskcache = "*" +flaml = "*" +openai = ">=1.2,<2.0" +python-dotenv = "*" +termcolor = "*" +tiktoken = "*" + +[package.extras] +blendsearch = ["flaml[blendsearch]"] +graphs = ["matplotlib (>=3.8.1,<3.9.0)", "networkx (>=3.2.1,<3.3.0)"] +lmm = ["pillow", "replicate"] +mathchat = ["pydantic (==1.10.9)", "sympy", "wolframalpha"] +retrievechat = ["chromadb", "ipython", "pypdf", "sentence-transformers"] +teachable = ["chromadb"] +test = ["coverage (>=5.3)", "ipykernel", "nbconvert", "nbformat", "pre-commit", "pytest (>=6.1.1)", "pytest-asyncio"] + [[package]] name = "pydantic" version = "2.5.2" @@ -3771,6 +3847,20 @@ files = [ [package.extras] doc = ["reno", "sphinx", "tornado (>=4.5)"] +[[package]] +name = "termcolor" +version = "2.4.0" +description = "ANSI color formatting for output in terminal" +optional = false +python-versions = ">=3.8" +files = [ + {file = "termcolor-2.4.0-py3-none-any.whl", hash = "sha256:9297c0df9c99445c2412e832e882a7884038a25617c60cea2ad69488d4040d63"}, + {file = "termcolor-2.4.0.tar.gz", hash = "sha256:aab9e56047c8ac41ed798fa36d892a37aca6b3e9159f3e0c24bc64a9b3ac7b7a"}, +] + +[package.extras] +tests = ["pytest", "pytest-cov"] + [[package]] name = "tiktoken" version = "0.5.2" @@ -4801,4 +4891,4 @@ server = ["fastapi", "uvicorn", "websockets"] [metadata] lock-version = "2.0" python-versions = "<3.12,>=3.9" -content-hash = "4f675213d5a79f001bfb7441c9fba23ae114079ec61a30b0c88833c5427f152e" +content-hash = "7f42967b71364246aa9c4ed604d71d43a31843a6d3113d8d08d9816b5cf39106" diff --git a/pyproject.toml b/pyproject.toml index 00ac4d9c..b7d3c00d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -54,12 +54,14 @@ uvicorn = {version = "^0.24.0.post1", optional = true} chromadb = "^0.4.18" pytest-asyncio = {version = "^0.23.2", optional = true} pydantic = "^2.5.2" +pyautogen = {version = "0.2.0", optional = true} [tool.poetry.extras] local = ["torch", "huggingface-hub", "transformers"] postgres = ["pgvector", "psycopg", "psycopg-binary", "psycopg2-binary", "pg8000"] dev = ["pytest", "pytest-asyncio", "black", "pre-commit", "datasets"] server = ["websockets", "fastapi", "uvicorn"] +autogen = ["pyautogen"] [build-system] requires = ["poetry-core"]