Você receberá uma response assim:

```json
{
  "description": "Some data",
  "content": "hello"
}
```

## Pydantic `bytes` para dados de saída { #pydantic-bytes-for-output-data }

Você também pode usar campos `bytes` com `ser_json_bytes` na configuração do modelo para dados de saída, e o Pydantic irá *serializar* os bytes como base64 ao gerar a response JSON.

 *
 * @author Chris Povirk
 * @since 11.0
 */
@GwtCompatible
public interface AsyncFunction<I extends @Nullable Object, O extends @Nullable Object> {
  /**
   * Returns an output {@code Future} to use in place of the given {@code input}. The output {@code
   * Future} need not be {@linkplain Future#isDone done}, making {@code AsyncFunction} suitable for
   * asynchronous derivations.
   *

    void testReadDataWireFormatExceedsBufferSize() {
        // Create a response with small output buffer
        byte[] smallOutputBuffer = new byte[5];
        TransCallNamedPipeResponse smallResponse = new TransCallNamedPipeResponse(mockConfig, smallOutputBuffer);

        byte[] buffer = new byte[100];

        // Try to read more data than output buffer can hold
        SMBProtocolDecodingException exception =

## Çıkış Verisi için Pydantic `bytes` { #pydantic-bytes-for-output-data }

Çıkış verisi için de model config'inde `ser_json_bytes` ile `bytes` alanları kullanabilirsiniz; Pydantic JSON response üretirken bytes'ı base64 olarak serialize eder.

{* ../../docs_src/json_base64_bytes/tutorial001_py310.py ln[1:2,12:16,29,38:41] hl[16] *}

## Giriş ve Çıkış Verisi için Pydantic `bytes` { #pydantic-bytes-for-input-and-output-data }

		// Should not be set unless there are different handlers for the same HandlerID.
		Subroute string

		// OutCapacity is the output capacity. If <= 0 capacity will be 1.
		OutCapacity int

		// InCapacity is the output capacity.
		// If == 0 no input is expected
		InCapacity int
	}
)

type subHandlerID [32]byte

#include "tensorflow/core/platform/types.h"

namespace tensorflow {

// Represents the results of the execution of an operation.
struct OutputList {
  std::vector<AbstractTensorHandle*> outputs;
  int expected_num_outputs = -1;
};

namespace tracing {

// =============================================================================
// Implementation detail for the unified execution APIs for Eager and tracing

				break
			}
		} else if p.arch.Family == sys.Loong64 {
			if arch.IsLoong64RDTIME(op) {
				// The Loong64 RDTIME family of instructions is a bit special,
				// in that both its register operands are outputs
				prog.To = a[0]
				if a[1].Type != obj.TYPE_REG {
					p.errorf("invalid addressing modes for 2nd operand to %s instruction, must be register", op)
					return
				}
				prog.RegTo2 = a[1].Reg
				break

type testLogger struct {
	current atomic.Pointer[testing.TB]
	action  atomic.Int32
}

// SetLogTB will set the logger to output to tb.
// Call the returned function to disable logging.
func (t *testLogger) SetLogTB(tb testing.TB) func() {
	return t.setTB(tb, logMessage)
}

// SetErrorTB will set the logger to output to tb.Error.
// Call the returned function to disable logging.
func (t *testLogger) SetErrorTB(tb testing.TB) func() {

		{Bucket: "test-getobjectinfo", Name: "Asia/empty-dir/", ContentType: "application/octet-stream", IsDir: true},
	}
	testCases := []struct {
		bucketName string
		objectName string

		// Expected output of GetObjectInfo.
		result ObjectInfo
		err    error
		// Flag indicating whether the test is expected to pass or not.
		shouldPass bool
	}{
		// Test cases with invalid bucket names ( Test number 1-4 ).

Sie erhalten eine Response wie:

```json
{
  "description": "Some data",
  "content": "hello"
}
```

## Pydantic `bytes` für Ausgabedaten { #pydantic-bytes-for-output-data }

Sie können in der Modellkonfiguration für Ausgabedaten auch `bytes`-Felder mit `ser_json_bytes` verwenden; Pydantic wird die Bytes bei der Erzeugung der JSON-Response als base64 *serialisieren*.