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
endee-io/endee
Endee is an open-source vector database specifically engineered for AI applications requiring fast and efficient search and retrieval. It targets use cases such as Retrieval-Augmented Generation (RAG) pipelines, semantic search, hybrid search, recommendation systems, and filtered vector retrieval APIs. The project emphasizes production-oriented performance and fine-grained control over retrieval processes. Implemented in C++, Endee is optimized for modern CPU architectures, supporting instruction sets like AVX2, AVX512, NEON, and SVE2 to maximize performance. Key features include support for dense and sparse vectors for hybrid search, payload filtering for metadata-aware retrieval, and operational capabilities like backup workflows and runtime observability. Endee offers flexible deployment options, including local builds, Docker images, and prebuilt registry images. It provides an HTTP API for managing indexes and serving retrieval workloads, making it suitable for integrating into various AI agent memory and contextual retrieval layers using frameworks like LangChain or LlamaIndex.
https://github.com/endee-io/endee
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