ragflow

ragflow

https://github.com/infiniflow/ragflow

RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data.

 

Demo

Try our demo at https://demo.ragflow.io.

 

Key Features

"Quality in, quality out"

• Deep document understanding-based knowledge extraction from unstructured data with complicated formats.
• Finds "needle in a data haystack" of literally unlimited tokens.

🍱 Template-based chunking

• Intelligent and explainable.
• Plenty of template options to choose from.

🌱 Grounded citations with reduced hallucinations

• Visualization of text chunking to allow human intervention.
• Quick view of the key references and traceable citations to support grounded answers.

🍔 Compatibility with heterogeneous data sources

• Supports Word, slides, excel, txt, images, scanned copies, structured data, web pages, and more.

🛀 Automated and effortless RAG workflow

• Streamlined RAG orchestration catered to both personal and large businesses.
• Configurable LLMs as well as embedding models.
• Multiple recall paired with fused re-ranking.
• Intuitive APIs for seamless integration with business.

 

System Architecture

 

 

 

 

 

Configure a knowledge base

https://ragflow.io/docs/dev/configure_knowledge_base

 

Deploy a local LLM

https://ragflow.io/docs/dev/deploy_local_llm

 

Introduction to Agentic RAG

https://ragflow.io/docs/dev/agentic_rag_introduction

 

RAGFlow offers RESTful APIs for you to integrate its capabilities into third-party applications.

https://ragflow.io/docs/dev/api

https://github.com/infiniflow/ragflow/blob/main/docs/references/api.md

 

 

 

Ollama Docker 镜像指南（支持GPU）

https://ollama.qianniu.city/doc/Ollama%20Docker%20%E9%95%9C%E5%83%8F%E6%8C%87%E5%8D%97.html