RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.

The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text

Dockerfile for the creation of a GitHub Actions runner image to be deployed dynamically

Repo for CI Testing

A library for efficient similarity search and clustering of dense vectors.