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FastAPI

As explained in Domain-Specific Small Language Models

A Python web framework for building APIs with automatic documentation, asynchronous request handling, and data validation support.

FastAPI is a Python web framework for building performant APIs with type hints, asynchronous request handling, validation, and automatically generated interactive documentation. It suits data-driven APIs, microservices, and machine-learning inference endpoints. section 11.2

Core operational elements include:

  • Routes map HTTP methods and URL paths to Python functions. section 11.2
  • Pydantic models validate structured request and response data. section 11.2 section 11.5
  • Async functions allow other work while network operations or inference complete. section 11.2.2
  • Swagger UI and ReDoc expose generated API documentation at /docs and /redoc. section 11.2

How Domain-Specific Small Language Models covers it

How deep it goes
Explains application setup, routes, validation, asynchronous inference, server startup, and generated documentation without descending into framework internals.
Examples
Uses root and POST routes, validated generation requests, GPT-2 inference, interactive documentation, and a Docker deployment.
What it assumes
Assumes Python and type-hint familiarity while introducing FastAPI application creation, route decorators, request models, and server commands.
What you can do after
Build a validated asynchronous inference API and expose it locally or in a container with generated documentation.
How it connects
Connects FastAPI with Starlette, Pydantic, Swagger UI, ReDoc, REST APIs, and ONNX Runtime.
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