Chroma - the open-source data infrastructure for AI.
pip install chromadb # python client # for javascript, npm install chromadb! # for client-server mode, chroma run --path /chroma_db_pathOur hosted service, Chroma Cloud, powers serverless vector, hybrid, and full-text search. It's extremely fast, cost-effective, scalable and painless. Create a DB and try it out in under 30 seconds with $5 of free credits.
The core API is only 4 functions (run our 💡 Google Colab):
import chromadb # setup Chroma in-memory, for easy prototyping. Can add persistence easily! client = chromadb.Client() # Create collection. get_collection, get_or_create_collection, delete_collection also available! collection = client.create_collection("all-my-documents") # Add docs to the collection. Can also update and delete. Row-based API coming soon! collection.add( documents=["This is document1", "This is document2"], # we handle tokenization, embedding, and indexing automatically. You can skip that and add your own embeddings as well metadatas=[{"source": "notion"}, {"source": "google-docs"}], # filter on these! ids=["doc1", "doc2"], # unique for each doc ) # Query/search 2 most similar results. You can also .get by id results = collection.query( query_texts=["This is a query document"], n_results=2, # where={"metadata_field": "is_equal_to_this"}, # optional filter # where_document={"$contains":"search_string"} # optional filter )Learn about all features on our Docs
Chroma is a rapidly developing project. We welcome PR contributors and ideas for how to improve the project.
- Join the conversation on Discord -
#contributingchannel - Review the 🛣️ Roadmap and contribute your ideas
- Grab an issue and open a PR -
Good first issue tag - Read our contributing guide
Release Cadence We currently release new tagged versions of the pypi and npm packages on Mondays. Hotfixes go out at any time during the week.