Chroma: векторная БД с 4 функциями API
Chroma — open-source векторная БД с 4 функциями API, автоматическими эмбеддингами и фильтрами. Быстрый старт для прототипов и продакшена.
Chroma — open-source векторная БД с 4 функциями API, автоматическими эмбеддингами и фильтрами. Быстрый старт для прототипов и продакшена.
Можно использовать Chroma как векторное хранилище для RAG-пайплайнов: хранить чанки документов, метаданные и эмбеддинги, затем быстро искать релевантные фрагменты для подачи в LLM. Это упрощает оркестрацию агентов и автоматизацию контента.
расшифровка ролика ↓
 
<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 $5 of free credits.
[Get started with Chroma Cloud](https://trychroma.com/signup)
## API
The core API is only 4 functions (run our [💡 Google Colab](https://colab.research.google.com/drive/1QEzFyqnoFxq7LUGyP1vzR4iLt9PpCDXv?usp=sharing)):
```python import chromadb # setup Chroma in-memory, for easy prototyping. Can add persistence easily! client = chromadb.Client()
# Create collection. get_collection, get_or_create_collection, delete_collection also available! collection = client.create_collection("all-my-documents")
# Add docs to the collection. Can also update and delete. Row-based API coming soon! collection.add( documents=["This is document1", "This is document2"], # we handle tokenization, embedding, and indexing automatically. You can skip that and add your own embeddings as well metadatas=[{"source": "notion"}, {"source": "google-docs"}], # filter on these! ids=["doc1", "doc2"], # unique for each doc )
# Query/search 2 most similar results. You can also .get by id results = collection.query( query_texts=["This is a query document"], n_results=2, # where={"metadata_field": "is_equal_to_this"}, # optional filter # where_document={"$contains":"search_string"} # optional filter ) ```
Learn about all features on our [Docs](https://docs.trychroma.com)
## 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](https://discord.com/invite/chromadb) - `#contributing` channel - [Review the 🛣️ Roadmap and contribute your ideas](https://docs.trychroma.com/docs/overview/oss#roadmap) - [Grab an issue and open a PR](https://github.com/chroma-core/chroma/issues) - [`Good first issue tag`](https://github.com/chroma-core/chroma/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) - [Read our contributing guide](https://docs.trychroma.com/docs/overview/oss#contributing)
**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](./LICENSE)