Deploy and Host LangServe RAG API + pgvector on Railway

Run a production-shaped LangServe/FastAPI starter with Postgres, pgvector, health checks, ingest/search routes, and API-key protection.

About Hosting LangServe RAG API + pgvector on Railway

• langserve: public FastAPI/LangServe service
• postgres: private Postgres database with pgvector
• /health, /ingest, /search, and /rag/invoke endpoints
• Generated API key for protected write/invoke routes
• No bundled model provider key

Why Deploy LangServe RAG API + pgvector on Railway

The published template deploy test created langserve and postgres; both reached SUCCESS; /health, /ingest, and /rag/invoke returned HTTP 200; and vector search still found the ingested document after restarting langserve.

This is a useful RAG API starter, not a novelty prompt demo.

Common Use Cases

• RAG API prototypes
• Private document search starters
• LangServe evaluation environments
• pgvector integration tests
• AI backend starter services

Dependencies for LangServe RAG API + pgvector Hosting

The app requires Postgres with pgvector for document storage and vector search. Model provider keys are intentionally not bundled, and should be supplied by the deployer when generated answers are needed.

Deployment Dependencies

• DATABASE_URL: private Postgres connection string
• APP_API_KEY: generated bearer token for protected endpoints
• OPENAI_API_KEY: optional deployer-provided provider key
• OPENAI_MODEL: chat model to use when a provider key is supplied

After Deploy

1. Set the model provider key your app needs.
2. Call /health.
3. Ingest a small test document.
4. Call /search or /rag/invoke with the generated API key.

Support Checklist

If a deploy fails, include langserve and postgres deployment IDs, the /health response, and logs mentioning pgvector, database setup, or API key validation.