---
id: langchain-weaviate
version: "0.0.8"
license: MIT
license_treatment: permissive
maintenance: active
---

# langchain-weaviate — An integration package connecting Weaviate and LangChain

License: permissive · Maintenance: active · Downloads: 325.8K/mo

## What it is and what it does

langchain-weaviate is an integration package that bridges LangChain applications with Weaviate, an open-source AI-native vector database. It allows LangChain users to use Weaviate as their vector store backend for storing and retrieving embeddings, eliminating the need to write custom integration code.

The package depends on langchain-core, numpy, and weaviate-client, and requires Python 3.10 or later. It assumes you already have LangChain installed and a running Weaviate instance deployed—whether via Docker Compose, Weaviate Cloud Services, Kubernetes, or a cloud provider. The package is actively maintained with no known security vulnerabilities.

Use it for:

- Store embeddings generated by LangChain in Weaviate for semantic search and retrieval-augmented generation workflows.
- Build AI applications that need persistent, queryable vector storage with LangChain's language model orchestration.
- Integrate Weaviate as a vector store backend in LangChain agents or chains that require embedding-based retrieval.
- Migrate or connect existing Weaviate deployments to LangChain-based applications without custom adapter code.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Integrates Weaviate vector database with LangChain, enabling LangChain applications to store and retrieve embeddings in Weaviate.

Yes, if you are building a LangChain application and have or plan to deploy Weaviate. The package has low install friction, active maintenance, permissive licensing, and no known vulnerabilities. The main prerequisite is having a running Weaviate instance; without that, the package alone is not useful.

## Install

pip install langchain-weaviate
uv add langchain-weaviate
poetry add langchain-weaviate

## Installing langchain-weaviate

Before you install: Low install friction with three straightforward runtime dependencies. The package is actively maintained with a recent release and no known vulnerabilities.

License in practice: MIT license permits unrestricted use, modification, and distribution with minimal legal friction.

Quickstart:

pip install langchain-weaviate

from langchain_weaviate import WeaviateVectorStore

vector_store = WeaviateVectorStore.from_documents(
    documents, embeddings, client=weaviate_client
)

A running Weaviate instance must be deployed and accessible before using this package.

Verify before relying:

- Whether the package supports all Weaviate deployment methods mentioned in the description (Docker Compose, WCS, Kubernetes, cloud providers) or only a subset.
- Specific LangChain version compatibility constraints beyond what the package declares.

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 325.8K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

weaviate langchain integration, vector store for langchain, embedding storage weaviate, langchain vector database, ai-native vector database integration, langchain weaviate connector, vector-database, langchain-integration, embeddings

[View on SkillFed](https://skillfed.io/packages/langchain-weaviate) · [View on PyPI](https://pypi.org/project/langchain-weaviate/)