Pre-deployment preparation
Need to make sure that the host meets:
- NVIDIA graphics card driver version ≥ 535
- Docker Engine 24.0+
- At least 16GB of video memory and 64GB of RAM
Standardized deployment process
- Get the official docker-compose.yml configuration file
- fulfillment
docker-compose up --build -dStart container cluster (with WebUI, vector database, modeling services) - Visit http://localhost:8843进入控制台
Deployment validation points
- pass (a bill or inspection etc)
docker logs ultrarag-webView real-time logs - Verify component status in the System Health panel of the WebUI
- Run the pre-built smoke test case (with 5 standard queries)
Production-level tuning recommendations
For enterprise level deployment recommendations:
1) Modify the default port 8843 to enhance security
2) Mount persistence volume to save model data (requires about 50GB of space)
3) Configure Nginx Reverse Proxy for HTTPS Encryption
This answer comes from the articleUltraRAG: A One-Stop RAG System Solution to Simplify Data Construction and Model Fine-TuningThe
May not be reproduced without permission:AI productivity tools " How to Rapidly Deploy UltraRAG Systems via Docker?
