---
id: llama-index-embeddings-langchain
version: "0.5.0"
license: MIT
license_treatment: permissive
maintenance: active
---

# llama-index-embeddings-langchain — llama-index embeddings langchain integration

License: permissive · Maintenance: active · Downloads: 108.6K/mo

## What it is and what it does

This package bridges Langchain's embedding ecosystem into LlamaIndex, letting you leverage Langchain's embedding models and providers when building LlamaIndex applications. It acts as an adapter layer that wraps Langchain embedding implementations so they work as drop-in replacements within LlamaIndex's indexing, retrieval, and vector store operations.

The integration depends only on llama-index-core, keeping the dependency footprint minimal. It's designed for developers who already use or prefer Langchain's embedding infrastructure and want to use those same models within LlamaIndex workflows without reimplementing or duplicating embedding logic.

Use it for:

- Index documents in LlamaIndex with embedding models provided by Langchain
- Switch between different Langchain embedding providers in an existing LlamaIndex application
- Migrate from a pure Langchain setup to LlamaIndex while keeping your embedding provider choice
- Combine Langchain's embedding options with LlamaIndex's retrieval and query capabilities

## Worth the install?

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

Integrates Langchain embedding models with LlamaIndex, allowing you to use Langchain's embedding providers within LlamaIndex's retrieval and indexing workflows.

Yes, if you are already using LlamaIndex and want to use Langchain embedding models. The package has low install friction, active maintenance, no known vulnerabilities, and a permissive MIT license. It is a straightforward integration layer with a single core dependency.

## Install

pip install llama-index-embeddings-langchain
uv add llama-index-embeddings-langchain
poetry add llama-index-embeddings-langchain

## Installing llama-index-embeddings-langchain

Before you install: Low install friction with a single runtime dependency on llama-index-core. Actively maintained with recent releases.

License in practice: MIT license permits commercial and private use with minimal restrictions.

Quickstart:

pip install llama-index-embeddings-langchain

from llama_index_embeddings_langchain import LangchainEmbedding

embedding = LangchainEmbedding(model_name='your-model')

Requires Python 3.10 or later and llama-index-core as a runtime dependency.

Verify before relying:

- Which specific Langchain embedding providers are supported by this integration
- Whether additional Langchain dependencies must be installed separately
- Performance characteristics or overhead of using Langchain embeddings through this adapter

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 108.6K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

langchain embeddings llama index, embedding integration llama index, langchain embedding adapter, llama index embedding provider, vector embedding integration, embedding-integration, llm-tooling

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