Build & Optimize your RAG.

A demonstration of hybrid search with reranking using Qdrant and BGE-M3 model. A showcase of dense and sparse retrieval combined with ColBERT reranking for optimal search results

LLM API Server , OpenAI 同时支持 ChatGLM3 ，Llama, Llama-3, Firefunction, Openfunctions ，BAAI/bge-m3 ,bge-large-zh-v1.5

Adaptive RAG (Web search + Corrective RAG) is an upgraded model of Agentic RAG

Example application for using the BGE-M3 embedding model and Google's Gemma-2-9B-Instruct generation model in a LangChain-based RAG pipeline to answer Lord of the Rings trivia questions

ONNX implementation of the BGE-M3 multilingual embedding model and tokenizer. Generates all three embedding types: dense vectors, sparse weights, and ColBERT vectors

Herramientas para procesar datos de desaparecidos: anonimización de narrativas con IA. Búsqueda semántica de casos similares mediante embeddings de texto (BGE-M3).