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Deployment

VisoRAG is a GPU-backed Python API. Treat it as a long-running service, not a static site or serverless function.

Recommended Shape

  • GPU VM, workstation, or notebook runtime for real model inference.
  • FastAPI/Uvicorn behind a reverse proxy or platform gateway.
  • TLS terminated at the gateway.
  • Strong VISORAG_API_TOKEN.
  • Restricted CORS origins.
  • Private temporary upload storage.

Not Recommended Without Changes

  • Public internet exposure of the raw Uvicorn server.
  • Serverless hosting that cannot provide persistent GPU runtime or large model downloads.
  • Multi-user production workloads without a real auth layer, quotas, audit logs, and request isolation.
  • Using the fallback demo token or placeholder .env.example values.
  • Processing sensitive documents while request logs include filenames or query snippets.

Local Service Command

export VISORAG_API_TOKEN="change-me"
python -m visorag serve --host 0.0.0.0 --port 8000

Use 127.0.0.1 for local-only testing.

Production Hardening Checklist

  • Replace the example token with a high-entropy secret.
  • Restrict CORS in api/app.py or at the gateway.
  • Disable or restrict sensitive request/response logging. The current runtime may log filenames and query snippets.
  • Keep uploaded files and rendered page images out of source control and CI artifacts.
  • Patch dependencies and model runtime packages regularly.
  • Review upstream model and package licenses before redistribution.
  • Add monitoring for GPU memory, request latency, failed renderings, and failed model loads.