tiangolo.fastapi/docs/en/docs/tutorial/header-param-models.md

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. 🤓

///

Header Parameters with a Pydantic Model

Declare the header parameters that you need in a Pydantic model, and then declare the parameter as Header:

{* ../../docs_src/header_param_models/tutorial001_an_py310.py hl[9:14,18] *}

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

Check the Docs

You can see the required headers in the docs UI at /docs:

Forbid Extra Headers

In some special use cases (probably not very common), you might want to restrict the headers that you want to receive.

You can use Pydantic's model configuration to forbid any extra fields:

{* ../../docs_src/header_param_models/tutorial002_an_py310.py hl[10] *}

If a client tries to send some extra headers, they will receive an error response.

For example, if the client tries to send a tool header with a value of plumbus, they will receive an error response telling them that the header parameter tool is not allowed:

{
    "detail": [
        {
            "type": "extra_forbidden",
            "loc": ["header", "tool"],
            "msg": "Extra inputs are not permitted",
            "input": "plumbus",
        }
    ]
}

Summary

You can use Pydantic models to declare headers in FastAPI. 😎