RAGFlow
infiniflow/ragflow
An open-source AI knowledge base engine that lets you upload documents and chat with them, getting accurate answers without hallucinations.
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
AI Summary
What This Project Does
Simply put, it's a tool that lets LLMs understand your private files. Upload PDFs, Words, or contracts, then chat with them. It answers based on the content, avoiding made-up facts.
What Problems It Solves
Solves the issue of LLMs "not knowing your data" and "hallucinating". Traditional searching is slow; this finds answers in seconds, great for handling large document volumes.
Who It's For
1. Teams wanting to build private enterprise knowledge bases.
2. Workers who frequently consult contracts or manuals.
3. Developers interested in AI and deploying LLM apps.
Typical Use Cases
- •Quickly search for key clauses in legal contracts.
- •Let customer service bots automatically learn from product manuals.
- •Assist in writing weekly reports based on historical documents.
Key Strengths & Highlights
1. Strong Parsing: Understands complex tables, images, and scans.
2. Free & Open Source: Apache 2.0 license, data stays secure with you.
3. Model Compatible: Supports Tongyi, DeepSeek, OpenAI, and more.
Getting Started Requirements
Requires some technical skill, mainly deployed via Docker. No coding needed for the UI, but you need your own server and model API keys.
Purpose
Suitable for private AI knowledge base deployment and data privacy protection. Not for those just wanting simple API calls without server setup.
Category
Tech Stack
Project Info
- Primary Language
- Python
- Default Branch
- main
- License
- Apache-2.0
- Homepage
- https://ragflow.io
- Created
- Dec 12, 2023
- Last Commit
- 1 months ago
- Last Push
- 1 months ago
- Indexed
- Apr 19, 2026