**FastAPI** fornece as mesmas `starlette.responses` como `fastapi.responses` apenas como uma conveniência para você, desenvolvedor. Mas a maioria das respostas disponíveis vem diretamente do Starlette.

E como a `Response` pode ser usada frequentemente para definir cabeçalhos e cookies, **FastAPI** também a fornece em `fastapi.Response`.

///

## Cabeçalhos personalizados

from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None


class User(BaseModel):
    username: str
    full_name: Union[str, None] = None


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item, user: User):

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None


class User(BaseModel):
    username: str
    full_name: str | None = None


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item, user: User, importance: int = Body()):

from typing import Union

from fastapi import FastAPI, File, UploadFile

app = FastAPI()


@app.post("/files/")
async def create_file(file: Union[bytes, None] = File(default=None)):
    if not file:
        return {"message": "No file sent"}
    else:
        return {"file_size": len(file)}


@app.post("/uploadfile/")
async def create_upload_file(file: Union[UploadFile, None] = None):
    if not file:

from typing import Annotated

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None


@app.put("/items/{item_id}")
async def update_item(
    item_id: int,
    item: Annotated[
        Item,
        Body(
            examples=[
                {

from enum import Enum

from fastapi import FastAPI


class ModelName(str, Enum):
    alexnet = "alexnet"
    resnet = "resnet"
    lenet = "lenet"


app = FastAPI()


@app.get("/models/{model_name}")
async def get_model(model_name: ModelName):
    if model_name is ModelName.alexnet:
        return {"model_name": model_name, "message": "Deep Learning FTW!"}

    if model_name.value == "lenet":

from typing import List

from fastapi import FastAPI, Query
from pydantic import BaseModel, Field
from typing_extensions import Literal

app = FastAPI()


class FilterParams(BaseModel):
    class Config:
        extra = "forbid"

    limit: int = Field(100, gt=0, le=100)
    offset: int = Field(0, ge=0)
    order_by: Literal["created_at", "updated_at"] = "created_at"
    tags: List[str] = []


@app.get("/items/")

import warnings
from typing import List

from fastapi import APIRouter, FastAPI
from fastapi.routing import APIRoute
from fastapi.testclient import TestClient
from pydantic import BaseModel


def custom_generate_unique_id(route: APIRoute):
    return f"foo_{route.name}"


def custom_generate_unique_id2(route: APIRoute):
    return f"bar_{route.name}"


def custom_generate_unique_id3(route: APIRoute):

{!../../docs_src/websockets/tutorial001.py!}
```

## Create a `websocket`

In your **FastAPI** application, create a `websocket`:

```Python hl_lines="1  46-47"
{!../../docs_src/websockets/tutorial001.py!}
```

/// note | "Technical Details"

You could also use `from starlette.websockets import WebSocket`.

You can import it directly from `fastapi`:

```python
from fastapi import BackgroundTasks
```