assertThat(result).contains(address("2a03:2880:f029:11:face:b00c:0:2"))
    val request1 = server.takeRequest()
    assertThat(request1.method).isEqualTo("GET")
    val request2 = server.takeRequest()
    assertThat(request2.method).isEqualTo("GET")
    assertThat(listOf(request1.path, request2.path))
      .containsExactlyInAnyOrder(
        "/lookup?ct&dns=AAABAAABAAAAAAAABmdvb2dsZQNjb20AAAEAAQ",

        VersionRequest requestB = new VersionRequest();
        requestB.addRepository(newTestRepository());
        Artifact artifactB =
                new DefaultArtifact("org.apache.maven.its", "dep-mng5324", "classifierB", "jar", "07.20.3-SNAPSHOT");
        requestB.setArtifact(artifactB);

        VersionResult resultB = versionResolver.resolveVersion(session, requestB);

Sebastián Ramírez <******@****.***> 1728247014 +0200

Sebastián Ramírez <******@****.***> 1728247014 +0200

Sebastián Ramírez <******@****.***> 1728247014 +0200

Sebastián Ramírez <******@****.***> 1728247014 +0200

Sebastián Ramírez <******@****.***> 1728247014 +0200

```

////

**FastAPI** will **extract** the data for **each field** from the **form data** in the request and give you the Pydantic model you defined.

## Check the Docs

You can verify it in the docs UI at `/docs`:

<div class="screenshot">
<img src="/img/tutorial/request-form-models/image01.png">
</div>

## Forbid Extra Form Fields

  public void run() throws Exception {
    for (int i = 0; i < 5; i++) {
      System.out.println("    Request: " + i);

      Request request = new Request.Builder()
          .url("https://api.github.com/search/repositories?q=http")
          .build();

      OkHttpClient clientForCall;
      if (i == 2) {
        // Force this request's response to be written to the cache. This way, subsequent responses
        // can be read from the cache.

    now served with tensorflow/serving, it will accept requests using 'inputs'
    and 'outputs'. Starting at 1.2, such a model will accept the keys specified
    during export. Therefore, inference requests using 'inputs' and 'outputs'
    may start to fail. To fix this, either update any inference clients to send
    requests with the actual input and output keys used by the trainer code, or