📄️ Configure a knowledge base
Knowledge base, hallucination-free chat, and file management are the three pillars of RAGFlow. RAGFlow's AI chats are based on knowledge bases. Each of RAGFlow's knowledge bases serves as a knowledge source, parsing files uploaded from your local machine and file references generated in File Management into the real 'knowledge' for future AI chats. This guide demonstrates some basic usages of the knowledge base feature, covering the following topics:
📄️ Start an AI-powered chat
Knowledge base, hallucination-free chat, and file management are the three pillars of RAGFlow. Chats in RAGFlow are based on a particular knowledge base or multiple knowledge bases. Once you have created your knowledge base and finished file parsing, you can go ahead and start an AI conversation.
🗃️ Agents
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📄️ Manage team members
Invite or remove team members, join or leave a team.
📄️ Manage files
Knowledge base, hallucination-free chat, and file management are the three pillars of RAGFlow. RAGFlow's file management allows you to upload files individually or in bulk. You can then link an uploaded file to multiple target knowledge bases. This guide showcases some basic usages of the file management feature.
📄️ Configure model API key
An API key is required for RAGFlow to interact with an online AI model. This guide provides information about setting your model API key in RAGFlow.
📄️ Deploy a local LLM
Run models locally using Ollama, Xinference, or other frameworks.
📄️ Run health check on RAGFlow's dependencies
Double-check the health status of RAGFlow's dependencies.
🗃️ Develop
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📄️ Upgrade RAGFlow
Upgrade RAGFlow to nightly-slim/nightly or the latest, published release.