langchain/pyproject.toml

[tool.poetry]
name = "langchain-monorepo"
version = "0.0.1"
description = "LangChain mono-repo"
authors = []
license = "MIT"
readme = "README.md"
repository = "https://www.github.com/hwchase17/langchain"


[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"

[tool.poetry.group.docs.dependencies]
langchain = { path = "libs/langchain/", develop = true }
autodoc_pydantic = "^1.8.0"
myst_parser = "^0.18.1"
nbsphinx = "^0.8.9"
sphinx = "^4.5.0"
sphinx-autobuild = "^2021.3.14"
sphinx_book_theme = "^0.3.3"
sphinx_rtd_theme = "^1.0.0"
sphinx-typlog-theme = "^0.8.0"
sphinx-panels = "^0.6.0"
toml = "^0.10.2"
myst-nb = "^0.17.1"
linkchecker = "^10.2.1"
sphinx-copybutton = "^0.5.1"
nbdoc = "^0.0.82"


[tool.poetry.group.codespell.dependencies]
codespell = "^2.2.0"


[tool.codespell]
skip = '.git,*.pdf,*.svg,*.pdf,*.yaml,*.ipynb,poetry.lock,*.min.js,*.css,package-lock.json,example_data,_dist,examples'
# Ignore latin etc
ignore-regex = '.*(Stati Uniti|Tense=Pres).*'
# whats is a typo but used frequently in queries so kept as is
# aapply - async apply
# unsecure - typo but part of API, decided to not bother for now
ignore-words-list = 'momento,collison,ned,foor,reworkd,parth,whats,aapply,mysogyny,unsecure,damon'
fix api ref (#8083) 10 months ago			`[tool.poetry]`
			`name = "langchain-monorepo"`
			`version = "0.0.1"`
			`description = "LangChain mono-repo"`
			`authors = []`
			`license = "MIT"`
			`readme = "README.md"`
			`repository = "https://www.github.com/hwchase17/langchain"`


			`[tool.poetry.dependencies]`
			`python = ">=3.8.1,<4.0"`

			`[tool.poetry.group.docs.dependencies]`
			`langchain = { path = "libs/langchain/", develop = true }`
			`autodoc_pydantic = "^1.8.0"`
			`myst_parser = "^0.18.1"`
			`nbsphinx = "^0.8.9"`
			`sphinx = "^4.5.0"`
			`sphinx-autobuild = "^2021.3.14"`
			`sphinx_book_theme = "^0.3.3"`
			`sphinx_rtd_theme = "^1.0.0"`
			`sphinx-typlog-theme = "^0.8.0"`
			`sphinx-panels = "^0.6.0"`
			`toml = "^0.10.2"`
			`myst-nb = "^0.17.1"`
			`linkchecker = "^10.2.1"`
			`sphinx-copybutton = "^0.5.1"`
			`nbdoc = "^0.0.82"`


codespell: workflow, config + some (quite a few) typos fixed (#6785) Probably the most boring PR to review ;) Individual commits might be easier to digest --------- Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> 11 months ago			`[tool.poetry.group.codespell.dependencies]`
			`codespell = "^2.2.0"`


			`[tool.codespell]`
			`skip = '.git,.pdf,.svg,.pdf,.yaml,.ipynb,poetry.lock,.min.js,*.css,package-lock.json,example_data,_dist,examples'`
			`# Ignore latin etc`
			`ignore-regex = '.(Stati Uniti\|Tense=Pres).'`
			`# whats is a typo but used frequently in queries so kept as is`
			`# aapply - async apply`
			`# unsecure - typo but part of API, decided to not bother for now`
FEAT: Integrate Xinference LLMs and Embeddings (#8171) - [Xorbits Inference(Xinference)](https://github.com/xorbitsai/inference) is a powerful and versatile library designed to serve language, speech recognition, and multimodal models. Xinference supports a variety of GGML-compatible models including chatglm, whisper, and vicuna, and utilizes heterogeneous hardware and a distributed architecture for seamless cross-device and cross-server model deployment. - This PR integrates Xinference models and Xinference embeddings into LangChain. - Dependencies: To install the depenedencies for this integration, run `pip install "xinference[all]"` - Example Usage: To start a local instance of Xinference, run `xinference`. To deploy Xinference in a distributed cluster, first start an Xinference supervisor using `xinference-supervisor`: `xinference-supervisor -H "${supervisor_host}"` Then, start the Xinference workers using `xinference-worker` on each server you want to run them on. `xinference-worker -e "http://${supervisor_host}:9997"` To use Xinference with LangChain, you also need to launch a model. You can use command line interface (CLI) to do so. Fo example: `xinference launch -n vicuna-v1.3 -f ggmlv3 -q q4_0`. This launches a model named vicuna-v1.3 with `model_format="ggmlv3"` and `quantization="q4_0"`. A model UID is returned for you to use. Now you can use Xinference with LangChain: ```python from langchain.llms import Xinference llm = Xinference( server_url="http://0.0.0.0:9997", # suppose the supervisor_host is "0.0.0.0" model_uid = {model_uid} # model UID returned from launching a model ) llm( prompt="Q: where can we visit in the capital of France? A:", generate_config={"max_tokens": 1024}, ) ``` You can also use RESTful client to launch a model: ```python from xinference.client import RESTfulClient client = RESTfulClient("http://0.0.0.0:9997") model_uid = client.launch_model(model_name="vicuna-v1.3", model_size_in_billions=7, quantization="q4_0") ``` The following code block demonstrates how to use Xinference embeddings with LangChain: ```python from langchain.embeddings import XinferenceEmbeddings xinference = XinferenceEmbeddings( server_url="http://0.0.0.0:9997", model_uid = model_uid ) ``` ```python query_result = xinference.embed_query("This is a test query") ``` ```python doc_result = xinference.embed_documents(["text A", "text B"]) ``` Xinference is still under rapid development. Feel free to [join our Slack community](https://xorbitsio.slack.com/join/shared_invite/zt-1z3zsm9ep-87yI9YZ_B79HLB2ccTq4WA) to get the latest updates! - Request for review: @hwchase17, @baskaryan - Twitter handle: https://twitter.com/Xorbitsio --------- Co-authored-by: Bagatur <baskaryan@gmail.com> 10 months ago			`ignore-words-list = 'momento,collison,ned,foor,reworkd,parth,whats,aapply,mysogyny,unsecure,damon'`