mirror of
https://github.com/hwchase17/langchain
synced 2024-11-18 09:25:54 +00:00
6ffd5b15bc
<!-- Thank you for contributing to LangChain! Please title your PR "<package>: <description>", where <package> is whichever of langchain, community, core, experimental, etc. is being modified. Replace this entire comment with: - **Description:** a description of the change, - **Issue:** the issue # it fixes if applicable, - **Dependencies:** any dependencies required for this change, - **Twitter handle:** we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` from the root of the package you've modified to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://python.langchain.com/docs/contributing/ If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/docs/integrations` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. -->
546 B
546 B
langchain-pinecone
This package contains the LangChain integration with Pinecone.
Installation
pip install -U langchain-pinecone
And you should configure credentials by setting the following environment variables:
PINECONE_API_KEY
PINECONE_INDEX_NAME
PINECONE_ENVIRONMENT
Usage
The Pinecone
class exposes the connection to the Pinecone vector store.
from langchain_pinecone import Pinecone
embeddings = ... # use a LangChain Embeddings class
vectorstore = Pinecone(embeddings=embeddings)