Chroma

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Chroma is an open-source vector database for semantic document search and management, enabling efficient retrieval and storage of documents with metadata filtering.

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Chroma is the open-source AI application database. Batteries included. Embeddings, vector search, document storage, full-text search, metadata filtering, and multi-modal. All in one place. Retrieval that just works. As it should be.

Chroma is a vector database platform designed to support semantic document search, metadata filtering, and efficient document management with persistent storage. It enables users to find documents based on meaning using advanced embedding techniques, allowing for more accurate and context-aware retrieval compared to traditional keyword-based search. The system supports filtering search results by metadata fields and document content, enhancing the precision and relevance of queries.

Chroma offers persistent storage, ensuring that data remains intact between server restarts, which is useful for managing large collections of documents such as academic papers and research materials. The platform includes comprehensive error handling and automatic retry logic to maintain stable operation, making it suitable for applications requiring reliable document handling and retrieval.

Developed to run on Python 3.8 and above, Chroma is accessible via a Model Context Protocol (MCP) server interface, allowing interaction through MCP tools for creating, reading, updating, deleting, and semantically searching documents. This setup supports the implementation of semantic search engines and metadata-driven document filtering in various domains, facilitating more intuitive and effective information discovery.

This description was generated by AI (artificial intelligence). AI can make mistakes. Check important info.

Website: trychroma.com

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Chroma

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