FastAPI

FastAPI combines an ASGI web layer with Pydantic-based data validation and OpenAPI descriptions. Function parameters and request models describe accepted inputs; response models describe what the application exposes. Dependencies provide reusable request-scoped behavior such as authentication or database access. Async endpoints can cooperate while waiting for compatible network operations, but declaring a function async does not make CPU-intensive inference nonblocking. Model loading, connection pools and cleanup belong to application lifecycle management. The framework serves the interface; model scheduling, task queues and deployment capacity remain architectural decisions.

A practitioner defines request and response models, separates transport concerns from inference logic and uses dependencies to enforce caller identity and resource access. They decide whether an operation should run in the request, a worker or an external inference service. They arrange startup and shutdown for expensive resources, expose useful failures and prevent sensitive internal fields from entering responses. Tests inspect validation failures, unauthorized access, cancellation and concurrent requests, yielding an API that remains predictable when inputs or infrastructure fail.

Automatic documentation cannot prove that a contract is complete or secure. Blocking calls inside an async endpoint can stall the event loop, and loading a large model per process can multiply memory requirements. Pydantic coercion may accept values differently from a strict business rule. Inspect worker memory, dependency cleanup, exception responses and real concurrency; a development server and a single successful request are insufficient deployment evidence.