llama-index-vector-stores-chroma

What it is and what it does

This package provides a LlamaIndex integration layer for Chroma, a vector database designed for storing and querying embeddings. It acts as a bridge between LlamaIndex's retrieval-augmented generation (RAG) framework and Chroma's vector storage backend, allowing developers to persist embeddings and perform semantic similarity searches within LlamaIndex workflows.

The integration depends on chromadb for the actual vector storage operations and llama-index-core for the framework integration. It is positioned as a specialized connector rather than a standalone tool—you install it when you've already chosen LlamaIndex as your RAG framework and Chroma as your vector store, and you need them to work together seamlessly.

Use it for:

• Build RAG pipelines with LlamaIndex that persist embeddings in Chroma for retrieval across sessions
• Implement semantic search over document collections using LlamaIndex queries backed by Chroma storage
• Integrate Chroma as a vector store option in LlamaIndex applications without writing custom adapter code
• Store and query embeddings from multiple data sources in a unified vector database within LlamaIndex workflows

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Integrates Chroma vector database with LlamaIndex for storing and retrieving embeddings in RAG and semantic search applications.

Yes, if you are already using LlamaIndex and have chosen Chroma as your vector store. The low install friction, permissive MIT license, and lack of known vulnerabilities make it a straightforward choice. The aging maintenance status warrants checking that your versions of chromadb and llama-index-core remain compatible, but the package itself carries no security risk.

Install

llama-index-vector-stores-chroma on PyPI

pip install llama-index-vector-stores-chroma

uv add llama-index-vector-stores-chroma

poetry add llama-index-vector-stores-chroma

Installing llama-index-vector-stores-chroma

Before you install

Low install friction with only two runtime dependencies (chromadb and llama-index-core). Package is aging at 227 days since last release, which may indicate stable maintenance or reduced active development.

License in practice

MIT license permits unrestricted use, modification, and distribution in both open and proprietary projects with minimal obligations.

Quickstart

pip install llama-index-vector-stores-chroma

from llama_index.vector_stores.chroma import ChromaVectorStore
from chromadb import Client

client = Client()
vector_store = ChromaVectorStore(chroma_client=client)

Requires Python 3.10 or later (supports current versions, <4.0)

Verify before relying

• Whether the package receives active maintenance or security updates despite aging status
• Compatibility guarantees with recent versions of chromadb and llama-index-core
• Performance characteristics or limitations when handling large-scale embeddings

Package facts

Evidence: llama_index_vector_stores_chroma-0.5.5-py3-none-any.whl

Tags

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