}
        outputContains("creating model for root project 'root'")
        outputContains("creating model for project ':a'")

        when:
        executer.withArguments(ENABLE_CLI)
        def model2 = runBuildAction(new FetchCustomModelForEachProject())

        then:
        model2.size() == 2
        model2[0].message == "It works from project :"
        model2[1].message == "It works from project :a"

        and:

        when:
        executer.withArguments(ENABLE_CLI)
        def model2 = runBuildAction(new FetchCustomModelForEachProject())

        then:
        model2.size() == 4
        model2[0].message == "project :a classpath = 2"
        model2[1].message == "project :b classpath = 1"
        model2[2].message == "project :c classpath = 0"
        model2[3].message == "project :d classpath = 0"

        and:

        }

        when:
        executer.withArguments(ENABLE_CLI)
        def model2 = runBuildAction(new FetchCustomModelForEachProject())

        then:
        model2.size() == 3
        model2[0].message == "project a"
        model2[1].message == "project b"
        model2[2].message == "It works from project :c"

        and:
        fixture.assertStateLoaded()

        when:

        when:
        executer.withArguments(ENABLE_CLI)
        def model2 = fetchModel(GradleBuild)

        then:
        model2.rootProject.name == "root"
        model2.projects.size() == 3
        model2.projects[0].name == "root"
        model2.projects[1].name == "a"
        model2.projects[2].name == "b"

        and:
        fixture.assertStateLoaded()

        server.expectConcurrent("model-a", "model-b")

        executer.withArguments(ENABLE_CLI)
        def model3 = runBuildAction(new FetchCustomModelForEachProjectInParallel())

        then:
        model3.size() == 3
        model3[0].message == "It works from project :"
        model3[1].message == "this is project a"
        model3[2].message == "this is project b"

        and:

        def model2 = models2.right
        model2.size() == 2
        model2[0].message == "It works from project :"
        model2[1].message == "It works from project :a"

        and:
        fixture.assertStateLoaded()
        outputDoesNotContain("creating model")
    }

    def "caches execution of phased BuildAction that queries custom tooling model and that runs tasks"() {
        given:

    model_ = input_model_->GetModel();
  }

  std::unique_ptr<FlatBufferModel> input_model_;
  const Model* model_;

  bool IsModelInputOrOutput(const Model* model, uint32_t tensor_idx) {
    for (size_t subgraph_idx = 0; subgraph_idx < model_->subgraphs()->size();
         ++subgraph_idx) {
      const auto subgraph = model->subgraphs()->Get(subgraph_idx);

Paul <******@****.***> 1713480573 -0400

John Howard <******@****.***> 1716996669 -0700

## See it in the docs

When you see the automatic docs, you can check that the input model and output model will both have their own JSON Schema:

<img src="/img/tutorial/response-model/image01.png">

And both models will be used for the interactive API documentation:

<img src="/img/tutorial/response-model/image02.png">

## Other Return Type Annotations