"openapi": "3.1.0",
            "info": {"title": "FastAPI", "version": "0.1.0"},
            "paths": {
                "/predict": {
                    "get": {
                        "summary": "Predict",
                        "operationId": "predict_predict_get",
                        "parameters": [
                            {
                                "required": True,

    yield
    # Clean up the ML models and release the resources
    ml_models.clear()


app = FastAPI(lifespan=lifespan)


@app.get("/predict")
async def predict(x: float):
    result = ml_models["answer_to_everything"](x)

# NOTE: These are not valid JSON:API resources
# but they are fine for testing requestBody with custom media_type
class Product(BaseModel):
    name: str
    price: float


class Shop(BaseModel):
    name: str


@app.post("/products")
async def create_product(data: Product = Body(media_type=media_type, embed=True)):
    pass  # pragma: no cover


@app.post("/shops")
async def create_shop(

from fastapi import FastAPI
from fastapi.testclient import TestClient
from pydantic import BaseModel

app = FastAPI()


class Product(BaseModel):
    name: str
    description: str = None  # type: ignore
    price: float


@app.get("/product")
async def create_item(product: Product):
    return product


client = TestClient(app)


def test_get_with_body():