7. Here the `response_model` is using a type annotation of a list of `Author` dataclasses.

    Again, you can combine `dataclasses` with standard type annotations.

8. Notice that this *path operation function* uses regular `def` instead of `async def`.

    As always, in FastAPI you can combine `def` and `async def` as needed.

      options.tpu_transfer_result_to_host;
  Status status = tensorflow::CreateTfExecutorToTfrtPipeline(pm, pass_options);
  if (!status.ok()) {
    return diag_handler.Combine(status);
  }

  if (mlir::failed(pm.run(module)))
    return diag_handler.Combine(tensorflow::errors::Internal(
        "failed to lower TF Dialect to CoreRT dialect."));

  if (VLOG_IS_ON(1)) {
    VLOG(1) << "TFRT dialect: ";

{!../../../docs_src/additional_responses/tutorial003.py!}
```

It will all be combined and included in your OpenAPI, and shown in the API docs:

<img src="/img/tutorial/additional-responses/image01.png">

## Combine predefined responses and custom ones

You might want to have some predefined responses that apply to many *path operations*, but you want to combine them with custom responses needed by each *path operation*.

  if (failed(pass_manager.run(module))) {
    return status_handler.Combine(
        absl::InvalidArgumentError("VHLO lowering failed"));
  }

  if (!tflite::MlirToFlatBufferTranslateFunction(
          module, options, &translated_result, serialize_stablehlo_ops)) {
    return status_handler.Combine(
        absl::InternalError("Could not translate MLIR to FlatBuffer."));
  }

      - name: Store coverage files
        uses: actions/upload-artifact@v4
        with:
          name: coverage-${{ matrix.python-version }}-${{ matrix.pydantic-version }}
          path: coverage

  coverage-combine:
    needs: [test]
    runs-on: ubuntu-latest
    steps:
      - name: Dump GitHub context
        env:
          GITHUB_CONTEXT: ${{ toJson(github) }}
        run: echo "$GITHUB_CONTEXT"

	}
	return analyzers
}

// AllCombined returns all analyzers combined as one
func AllCombined() analysis.CombinedAnalyzer {
	return analysis.Combine("all", All()...)
}

// AllMultiClusterCombined returns all multi-cluster analyzers combined as one
func AllMultiClusterCombined() analysis.CombinedAnalyzer {
	return analysis.Combine("all-multi-cluster", AllMultiCluster()...)

}

Status StatusScopedDiagnosticHandler::ConsumeStatus() {
  return BaseScopedDiagnosticHandler::ConsumeStatus();
}

Status StatusScopedDiagnosticHandler::Combine(Status status) {
  absl::Status absl_s = BaseScopedDiagnosticHandler::Combine(status);

  return absl_s;
}

		},
		cli.BoolFlag{
			Usage: "combine inline data",
			Name:  "combine",
		},
		cli.BoolFlag{
			Usage: "combine inline data across versions when size matches",
			Name:  "xver",
		},
	}

	app.Action = func(c *cli.Context) error {
		ndjson := c.Bool("ndjson")
		if c.Bool("data") && c.Bool("combine") {
			return errors.New("cannot combine --data and --combine")
		}
		// file / version / file

   */
  private static final Collector<Object, ?, Optional<Object>> TO_OPTIONAL =
      Collector.of(
          ToOptionalState::new,
          ToOptionalState::add,
          ToOptionalState::combine,
          ToOptionalState::getOptional,
          Collector.Characteristics.UNORDERED);

  /**
   * A collector that converts a stream of zero or one elements to an {@code Optional}.
   *

  TF_RETURN_IF_ERROR(AddForwardLoopCounter(
      while_ctx, scope.NewSubScope("ForwardLoopCounter"), &forward_loop_count));

  // TODO(skyewm): can we combine the backprop loop counter and main gradient
  // loop into a single loop? The original Python code doesn't combine the
  // loops, but I'm not sure why.
  Output backprop_counter_cond;
  TF_RETURN_IF_ERROR(AddBackPropLoopCounter(