## See it in the docs { #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 { #other-return-type-annotations }

Коли Ви дивитесь автоматичну документацію, Ви можете побачити, що вхідна модель і вихідна модель мають власну JSON-схему:

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

І обидві моделі використовуються для інтерактивної API-документації:

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

## Інші анотації типів повернення

# Extra Models { #extra-models }

Continuing with the previous example, it will be common to have more than one related model.

This is especially the case for user models, because:

* The **input model** needs to be able to have a password.
* The **output model** should not have a password.
* The **database model** would probably need to have a hashed password.

/// danger

# Query Parameter Models { #query-parameter-models }

If you have a group of **query parameters** that are related, you can create a **Pydantic model** to declare them.

This would allow you to **re-use the model** in **multiple places** and also to declare validations and metadata for all the parameters at once. 😎

/// note

This is supported since FastAPI version `0.115.0`. 🤓

///

///

## Cookies with a Pydantic Model { #cookies-with-a-pydantic-model }

Declare the **cookie** parameters that you need in a **Pydantic model**, and then declare the parameter as `Cookie`:

{* ../../docs_src/cookie_param_models/tutorial001_an_py310.py hl[9:12,16] *}

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

# Header Parameter Models { #header-parameter-models }

If you have a group of related **header parameters**, you can create a **Pydantic model** to declare them.

This would allow you to **re-use the model** in **multiple places** and also to declare validations and metadata for all the parameters at once. 😎

/// note

This is supported since FastAPI version `0.115.0`. 🤓

///

### Model for Input { #model-for-input }

If you use this model as an input like here:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:15] hl[14] *}

...then the `description` field will **not be required**. Because it has a default value of `None`.

### Input Model in Docs { #input-model-in-docs }

          <velocityBasedir>${project.basedir}/../../src/mdo</velocityBasedir>
          <models>
            <model>src/main/mdo/maven.mdo</model>
          </models>
          <templates>
            <template>model.vm</template>
          </templates>
          <params>
            <param>packageModelV4=org.apache.maven.api.model</param>
            <param>isMavenModel=true</param>
          </params>
        </configuration>

              <velocityBasedir>${project.basedir}/../../src/mdo</velocityBasedir>
              <version>2.0.0</version>
              <models>
                <model>src/main/mdo/plugin.mdo</model>
              </models>
              <templates>
                <template>model.vm</template>
              </templates>
              <params>
                <param>packageModelV4=org.apache.maven.api.plugin.descriptor</param>

        Map<String, Object> params = new HashMap<>();
        params.put("param", "value");

        // First call with model name
        ComponentUtil.setFessConfig(new FessConfig.SimpleImpl() {
            @Override
            public String getLtrModelName() {
                return "model1";
            }

            @Override
            public int getLtrWindowSize() {
                return 50;