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CocoIndex is an open-source framework designed for building powerful, local-first semantic search systems. It lets users index and retrieve content based on meaning rather than keywords, making it ideal for modern AI-based search applications. CocoIndex leverages vector embeddings and integrates with various models and frameworks, including OpenAI and Hugging Face, to provide high-quality semantic understanding. It’s built for transparency, ease of use, and local control over your search data, distinguishing itself from closed, black-box systems. The tool is suitable for developers working on personal knowledge bases, AI search interfaces, or private LLM applications.
Features
- Local-first semantic search engine
- Supports OpenAI, Hugging Face, and custom embeddings
- Easily index documents, notes, or files
- Fast nearest neighbor retrieval
- API for embedding and querying indexed data
- CLI and Python SDK for integration into workflows
- Privacy-friendly with no cloud dependency
- Modular architecture for extensibility
Project Samples
License
Apache License V2.0Follow CocoIndex
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