pathwaycom/llm-app
Ready-to-run cloud templates for building real-time RAG, AI pipelines, and enterprise search applications that synchronize with various live data sources.
Awesome Infra for AI › Vector Databases & Retrieval Infrastructure
NGT-labs/NGT
NGT (Neighborhood Graph and Tree) is an open-source library and command-line tool designed for high-speed approximate nearest neighbor (ANN) searches in high-dimensional vector data spaces. It supports various distance functions, including L1, L2, Cosine similarity, Angular, Hamming, Jaccard, Poincare, Lorentz, and Inner product. NGT implements several methods like the core NGT (graph and tree-based), QG (quantized graph-based), and QBG (quantized blob graph-based) to enhance search performance and scalability, particularly for large datasets and billions of objects. It offers features such as dynamic object registration and removal, and the ability to handle data larger than memory using shared memory mapped files. The library supports multiple data types (FP32, FP16, and UINT8) and provides bindings for various programming languages including Python, Ruby, PHP, Rust, Go, C, and C++. NGT is primarily used as an underlying indexing mechanism for vector search and retrieval, making it suitable for applications requiring efficient similarity search on vector embeddings. It's often deployed with its own servers like `ngtd` or `vald` for production use.
https://github.com/NGT-labs/NGT
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