}
```

Aber wenn der Client `http://example.com/items/bar` anfordert (ein nicht-existierendes `item_id` `"bar"`), erhält er einen HTTP-Statuscode 404 (der „Not Found“-Error) und eine JSON-Response wie:

```JSON
{
  "detail": "Item not found"
}
```

/// tip | Tipp

Wenn Sie eine `HTTPException` auslösen, können Sie dem Parameter `detail` jeden Wert übergeben, der in JSON konvertiert werden kann, nicht nur `str`.

    response = client.get(
        "/items/bar?token=jessica", headers={"X-Token": "fake-super-secret-token"}
    )
    assert response.status_code == 404
    assert response.json() == {"detail": "Item not found"}


def test_items_plumbus_with_no_token(client: TestClient):
    response = client.get(
        "/items/plumbus", headers={"X-Token": "fake-super-secret-token"}
    )
    assert response.status_code == 422

   * Returns a predicate that evaluates to {@code true} if each of its components evaluates to
   * {@code true}. The components are evaluated in order, and evaluation will be "short-circuited"
   * as soon as a false predicate is found. It defensively copies the iterable passed in, so future
   * changes to it won't alter the behavior of this predicate. If {@code components} is empty, the
   * returned predicate will always evaluate to {@code true}.
   *

        raise InternalError(
            f"The portal gun is too dangerous to be owned by {username}"
        )
    if item_id != "plumbus":
        raise HTTPException(
            status_code=404, detail="Item not found, there's only a plumbus here"
        )

nvidia-cublas-cu12>=12.5.3.2,<13.0
nvidia-cuda-cupti-cu12>=12.5.82,<13.0
nvidia-cuda-nvcc-cu12>=12.5.82,<13.0
nvidia-cuda-nvrtc-cu12>=12.5.82,<13.0
nvidia-cuda-runtime-cu12>=12.5.82,<13.0
# The upper bound is set for the CUDNN API compatibility.
# See
# https://docs.nvidia.com/deeplearning/cudnn/backend/latest/developer/forward-compatibility.html#cudnn-api-compatibility
nvidia-cudnn-cu12>=9.3.0.75,<10.0
nvidia-cufft-cu12>=11.2.3.61,<12.0

     *
     * @param userMessage the user's message
     * @param history the conversation history
     * @param callback the streaming callback
     */
    void generateNoResultsResponse(String userMessage, List<LlmMessage> history, LlmStreamCallback callback);

    /**
     * Generates a response when the specified document URL is not found.
     *

        )
      return when {
        boundaryIndex != -1L -> boundaryIndex

        // We found the boundary.
        source.buffer.size >= toIndex -> minOf(toIndex, maxByteCount)

        // No boundary before toIndex.
        else -> throw EOFException() // We ran out of data before we found the required boundary.
      }
    }

    @Throws(IOException::class)
    override fun close() {

from collections.abc import Callable
from enum import Enum
from typing import Any, TypeVar, Union

from pydantic import BaseModel
from pydantic.main import IncEx as IncEx

DecoratedCallable = TypeVar("DecoratedCallable", bound=Callable[..., Any])
UnionType = getattr(types, "UnionType", Union)
ModelNameMap = dict[type[BaseModel] | type[Enum], str]

# WSGI inkludieren – Flask, Django und andere { #including-wsgi-flask-django-others }

Sie können WSGI-Anwendungen mounten, wie Sie es in [Unteranwendungen – Mounts](sub-applications.md), [Hinter einem Proxy](behind-a-proxy.md) gesehen haben.

Dazu können Sie die `WSGIMiddleware` verwenden und damit Ihre WSGI-Anwendung wrappen, zum Beispiel Flask, Django usw.

## `WSGIMiddleware` verwenden { #using-wsgimiddleware }

/// info | Info

EMSG0000=test