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added autogen as an extra (#616)

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* added autogen as an extra

* updated docs

Co-authored-by: hemanthsavasere <hemanth.savasere@gmail.com>
This commit is contained in:
Charles Packer
2023-12-13 21:36:03 -08:00
committed by GitHub
parent 8cc1ed0f59
commit e70a59dcd4
3 changed files with 94 additions and 2 deletions
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2
docs/autogen.md
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@@ -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

92
poetry.lock generated
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@@ -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"

2
pyproject.toml
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@@ -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"]