ποΈ Configure a knowledge base
Knowledge base, hallucination-free chat, and file management are 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:
ποΈ Start an AI chat
Knowledge base, hallucination-free chat, and file management are 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.
ποΈ Manage files
Knowledge base, hallucination-free chat, and file management are 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.
ποΈ Set your LLM API key
You have two ways to input your LLM API key.
ποΈ Deploy a local LLM
RAGFlow supports deploying LLMs locally using Ollama or Xinference.
ποΈ Update vm.max_map_count
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