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deploying-to-production.md

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Deploying to Production

This project is designed for local/self-hosted deployments with PostgreSQL and a local-network model endpoint.

Baseline Deployment

  1. Provision PostgreSQL with pgvector enabled.
  2. Build and run the unified app container.
  3. Provide environment values from .env.example.
  4. Expose only port 8000 from the app service.

Minimum Environment

SERVER_HOST=0.0.0.0
SERVER_PORT=8000
DATABASE_URL=postgresql+asyncpg://...
OPENAI_BASE_URL=http://<lm-studio-host>:1234/v1
OPENAI_API_KEY=lm-studio
OPENAI_MODEL=mistralai/ministral-3-14b-reasoning
EMBEDDING_MODEL=text-embedding-qwen3-embedding-4b@q4_k_m
EMBEDDING_DIMENSIONS=1536
# Optional dedicated embedding endpoint/key (falls back to OPENAI_* when empty)
EMBED_OPENAI_BASE_URL=
EMBED_OPENAI_API_KEY=
DEFAULT_MEMORY_NAMESPACE=local
SEARCH_CACHE_TTL_SECONDS=300

Hardening Checklist

  • Keep PostgreSQL non-public when possible.
  • Restrict inbound access to app port 8000.
  • Use strong DB credentials and rotate periodically.
  • Enable backup/restore for PostgreSQL data volume.
  • Keep namespace conventions stable across clients.

Validation

  • GET /health
  • GET /health/cache
  • GET /mcp/info
  • POST /api/v1/memory/search with X-Memory-Namespace