Backend engineering
Designing FastAPI services for AI products
A Python API around a model needs clear boundaries, validation, and predictable failure behavior before it needs more endpoints.
Aryan (@istmX)3 min read
Start with a clear boundary
Keep request validation, application logic, and provider calls separate. This makes the service easier to change and keeps framework details from leaking into product logic.
Handle failure deliberately
Model requests can time out, be rate limited, or return malformed output. Set timeouts, validate responses, and map provider failures to stable API errors.
Make the result understandable
For long work, return a task identifier and expose status separately. Typed response contracts, request IDs, and structured logs make the service easier to operate.