Preparedness for pre-deployment
- Ensure Docker version 20.10+
- Reserve at least 2GB of RAM
- Prepare persistent storage directory (50GB+ recommended)
Key deployment steps
- mirror construction::
docker build -t unigraph-devserver . - Container Running::
docker run -d -p 4002:4002 -v /path/to/data:/opt/unigraph -p 4001:4001 -p 3000:3000 -P unigraph-devserver - Port Description:: 3000 (Web Front End)/4001 (GraphQL)/4002 (GRPC)
Configuration Optimization Recommendations
- Data catalogs should be stored using SSDs
- For ARM architectures add
--platform linux/amd64parameters - Nginx reverse proxy is recommended for production environments.
Validation Methods
interviewshttp://localhost:3000The initialization boot screen should be seen, and the first load may take 3-5 minutes to build the initial index.
This answer comes from the articleUnigraph: building locally running knowledge graphs and personal search enginesThe
May not be reproduced without permission:AI productivity tools " How to Rapidly Deploy Unigraph Services via Docker?
