RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs

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.