1
Start RAGFlow Server
Launch a local RAGFlow server using Docker or by building from source.
2
Create Dataset
Upload files for parsing and configure intervention options as needed.
3
Configure Model Providers
Add LLM API keys and set system model settings via the UI under Model Providers.
4
Set Up AI Chat
Select datasets and chat models in the Chat tab to start interacting.
5
Use APIs or Python Client
Integrate or interact with RAGFlow functionalities using the RESTful API or Python client.