llama-index-embeddings-langchain
llama-index embeddings langchain integration
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later and llama-index-core as a runtime dependency.
- Low install friction with a single runtime dependency on llama-index-core.
- Actively maintained with recent releases.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions.
last release 2026-03-12 (155 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 108,611 downloads/mo, #12,550 on PyPI
Alternatives
Verify before relying
pip install llama-index-embeddings-langchain
from llama_index_embeddings_langchain import LangchainEmbedding
embedding = LangchainEmbedding(model_name='your-model')- 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
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 on this page. Verify before relying on it.
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
llama-index-embeddings-langchain on PyPI
Before you install
Low install friction with a single runtime dependency on llama-index-core. Actively maintained with recent releases.
Requires Python 3.10 or later and llama-index-core as a runtime dependency.
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')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 the current Python release <4.0,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagellama-index-core |
| Maintenance | Actively maintained 155 days since the last release |
| First released | |
| Downloads | 108,611 / month, #12,550 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: llama_index_embeddings_langchain-0.5.0-py3-none-any.whl
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See also llama-index-embeddings-openai · llama-index-llms-langchain · llama-index-embeddings-huggingface · llama-index-embeddings-ollama · llama-index-embeddings-azure-openai · llama-index-vector-stores-chroma · llama-index-retrievers-bm25 · llama-index-vector-stores-qdrant · langchain-baseten · llama-index-utils-workflow