A quick tour of FastAPI

Now that you know why we pick FastAPI, let us look at what the framework actually gives you. Three pillars: path operation decorators for routes, Pydantic BaseModel classes for payloads, and auto-generated OpenAPI docs at /docs that stay in sync with your code.

main.py
python
from dotenv import load_dotenv
load_dotenv()

from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from router import router

app = FastAPI(
    title="Streaming LLM Applications with FastAPI",
    description="Learn to stream LLM responses in real-time with Server-Sent Events",
    version="1.0.0",
)

app.include_router(router)

The app entry point. Notice how small it is: create the FastAPI instance, add middleware, include a router. Routing logic lives elsewhere.

router.py
python
from fastapi import APIRouter
from models import StoryRequest
from service import generate_story_stream

router = APIRouter(prefix="/bedtime-story", tags=["bedtime-story"])

@router.get("/health")
async def health_check():
    return {"status": "healthy", "service": "bedtime-story-generator"}

A router groups related routes under a common prefix and tag. The tag shows up as a section in the auto-generated /docs page.

Yes. FastAPI reads your route signatures and Pydantic models, builds an OpenAPI schema, and serves Swagger UI at /docs plus ReDoc at /redoc. The docs stay in sync because they are generated from the same source as your validation. When you change a field, the docs change with it.

Matching exercise: Match each FastAPI pillar to its job

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