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Generally, this PR is CI performance focused + aims to clean up some dependencies at the same time. 1. Unpins upper bounds for `numpy` in all `pyproject.toml` files where `numpy` is specified 2. Requires `numpy >= 2.1.0` for Python 3.13 and `numpy > v1.26.0` for Python 3.12, plus a `numpy` min version bump for `chroma` 3. Speeds up CI by minutes - linting on Python 3.13, installing `numpy < 2.1.0` was taking [~3 minutes](https://github.com/langchain-ai/langchain/actions/runs/14316342925/job/40123305868?pr=30713), now the entire env setup takes a few seconds 4. Deleted the `numpy` test dependency from partners where that was not used, specifically `huggingface`, `voyageai`, `xai`, and `nomic`. It's a bit unfortunate that `langchain-community` depends on `numpy`, we might want to try to fix that in the future... Closes https://github.com/langchain-ai/langchain/issues/26026 Fixes https://github.com/langchain-ai/langchain/issues/30555
langchain-openai
This package contains the LangChain integrations for OpenAI through their openai SDK.
Installation and Setup
- Install the LangChain partner package
pip install langchain-openai
- Get an OpenAI api key and set it as an environment variable (
OPENAI_API_KEY)
Chat model
See a usage example.
from langchain_openai import ChatOpenAI
If you are using a model hosted on Azure, you should use different wrapper for that:
from langchain_openai import AzureChatOpenAI
For a more detailed walkthrough of the Azure wrapper, see here
Text Embedding Model
See a usage example
from langchain_openai import OpenAIEmbeddings
If you are using a model hosted on Azure, you should use different wrapper for that:
from langchain_openai import AzureOpenAIEmbeddings
For a more detailed walkthrough of the Azure wrapper, see here
LLM (Legacy)
LLM refers to the legacy text-completion models that preceded chat models. See a usage example.
from langchain_openai import OpenAI
If you are using a model hosted on Azure, you should use different wrapper for that:
from langchain_openai import AzureOpenAI
For a more detailed walkthrough of the Azure wrapper, see here