RAGFlow
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine with deep document understanding. It provides a streamlined RAG workflow for businesses of any scale, combining LLM capabilities to provide truthful question-answering with well-founded citations from various complex formatted data.
Install
bash -c "$(curl -fsSL https://raw.githubusercontent.com/Heretek-AI/ProxmoxVE/main/ct/ragflow.sh)"Run as root in the Proxmox VE shell. Pick Default for the sizing below, or Advanced to choose storage, network and resources yourself.
Notes
- Warning: Configure your LLM API key in Settings after first login
- Warning: Requires vm.max_map_count >= 262144 (configured automatically)
- Warning: Minimum 16GB RAM recommended for production workloads
- Warning: MCP Server requires RAGFlow API key - generate in Settings > API Keys
- Access the Web UI at http://<IP>:80
- API endpoint: http://<IP>:9380
- MinIO Console: http://<IP>:9001
- Credentials saved to ~/ragflow.creds after installation
- Elasticsearch may take 1-2 minutes to fully initialize on first start
- Default installation uses CPU for document processing
- For GPU acceleration, additional configuration is required
- Services: MySQL, Elasticsearch, Redis/Valkey, MinIO, RAGFlow Backend
- Optional MCP Server (disabled by default): Enable with 'systemctl enable --now ragflow-mcp.service'
- MCP endpoint: http://<IP>:9382 - for AI assistant integration (Claude Desktop, etc.)
- MCP Documentation: https://ragflow.io/docs/launch_mcp_server
- API Key Guide: https://ragflow.io/docs/acquire_ragflow_api_key
What's new upstream
Fetching releases from GitHub…
Script details
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