chroma-core/chroma
Chroma is an open-source search and retrieval database specifically designed for AI applications, supporting document retrieval and vector embeddings.
Awesome AI Agents › RAG and Business Analytics
apecloud/ApeRAG
ApeRAG is a production-ready retrieval-augmented generation platform that combines Graph RAG, vector search, and full-text search with AI agents to build knowledge-base applications. It supports five index types for retrieval: vector, full-text, graph, summary, and vision, giving multi-dimensional document understanding. Built-in AI agents use Model Context Protocol tool support to automatically identify relevant collections, search content intelligently, and add web search for comprehensive question answering. Its Graph RAG is a deeply modified LightRAG implementation with entity normalization that merges entities for cleaner knowledge graphs, and its hybrid retrieval engine blends graph, vector, full-text, summary, and vision-based search. Multimodal processing covers images, charts, and visual content alongside text, and an optional advanced document-parsing service powered by MinerU improves handling of complex documents, tables, and formulas with optional GPU acceleration. ApeRAG exposes an MCP server so AI assistants can browse collections, run hybrid search, and ask natural-language questions directly against a knowledge base, authenticated by API key. The stack is developer-friendly, with a FastAPI backend, a React frontend, and asynchronous task processing via Celery, and it ships enterprise management features including audit logging, LLM model management, graph visualization, and agent workflow management. The easiest way to start it is Docker Compose, exposing a web interface and API docs, while production deployment is supported on Kubernetes through a Helm chart and KubeBlocks integration for databases such as PostgreSQL, Redis, Qdrant, Elasticsearch, and Neo4j. It targets teams building knowledge graphs, context engineering, and intelligent agents that reason across their own documents.
https://github.com/apecloud/ApeRAG
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