chroma

Search infrastructure for AI

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Repository: chroma-core/chroma


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README.md

!Chroma
!Chroma

<p align="center">
<b>Chroma - the open-source data infrastructure for AI</b>. <br />
</p>

<p align="center">
<a href="https://discord.gg/MMeYNTmh3x" target="_blank">
<img src="https://img.shields.io/discord/1073293645303795742?cacheSeconds=3600" alt="Discord">
</a> |
<a href="https://github.com/chroma-core/chroma/blob/master/LICENSE" target="_blank">
<img src="https://img.shields.io/badge/License-Apache_2.0-blue.svg" alt="License">
</a> |
<a href="https://docs.trychroma.com/" target="_blank">
Docs
</a> |
<a href="https://www.trychroma.com/" target="_blank">
Homepage
</a>
</p>

bash
pip install chromadb # python client
for javascript, npm install chromadb!

for client-server mode, chroma run --path /chroma_db_path

Chroma Cloud

Our 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.

Get started with Chroma Cloud

API

The core API is only 4 functions (run our 💡 Google Colab):

python
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

Get involved

Chroma is a rapidly developing project. We welcome PR contributors and ideas for how to improve the project.
- Join the conversation on Discord - #contributing channel
- 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.

License

Apache 2.0