field_info=FieldInfo(annotation=model),
            name=model.__name__,
            mode="validation",
        )
        for model in flat_validation_models
    ]
    flat_serialization_model_fields = [
        ModelField(
            field_info=FieldInfo(annotation=model),
            name=model.__name__,
            mode="serialization",
        )
        for model in flat_serialization_models
    ]

Sebastián Ramírez <******@****.***> 1766840096 -0800

    alias: Optional[str] = None,
    mode: Literal["validation", "serialization"] = "validation",
    version: Literal["1", "auto"] = "auto",
) -> ModelField:
    if annotation_is_pydantic_v1(type_):
        raise PydanticV1NotSupportedError(
            "pydantic.v1 models are no longer supported by FastAPI."
            f" Please update the response model {type_!r}."
        )
    class_validators = class_validators or {}

class ItemGroup(BaseModel):
    items: list[tuple[str, str]]


class Coordinate(BaseModel):
    x: float
    y: float


@app.post("/model-with-tuple/")
def post_model_with_tuple(item_group: ItemGroup):
    return item_group


@app.post("/tuple-of-models/")
def post_tuple_of_models(square: tuple[Coordinate, Coordinate]):
    return square


@app.post("/tuple-form/")

        Doc(
            """
            Pydantic's `include` parameter, passed to Pydantic models to set the
            fields to include.
            """
        ),
    ] = None,
    exclude: Annotated[
        Optional[IncEx],
        Doc(
            """
            Pydantic's `exclude` parameter, passed to Pydantic models to set the
            fields to exclude.
            """
        ),
    ] = None,

## 0.30.0

* Add support for Pydantic's ORM mode:
    * Updated documentation about SQL with SQLAlchemy, using Pydantic models with ORM mode, SQLAlchemy models with relations, separation of files, simplification of code and other changes. New docs: [SQL (Relational) Databases](https://fastapi.tiangolo.com/tutorial/sql-databases/).

client = TestClient(app)


def test_get_enums_alexnet():
    response = client.get("/models/alexnet")
    assert response.status_code == 200
    assert response.json() == {"model_name": "alexnet", "message": "Deep Learning FTW!"}


def test_get_enums_lenet():
    response = client.get("/models/lenet")
    assert response.status_code == 200

* data validation
* data serialization
* data documentation, etc.

This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.

/// info

Keep in mind that dataclasses can't do everything Pydantic models can do.

So, you might still need to use Pydantic models.

                if annotation_is_pydantic_v1(model):
                    raise PydanticV1NotSupportedError(
                        "pydantic.v1 models are no longer supported by FastAPI."
                        f" In responses={{}}, please update {model}."
                    )
                response_field = create_model_field(
                    name=response_name, type_=model, mode="serialization"
                )

    Undefined,
    get_compat_model_name_map,
    get_definitions,
    get_schema_from_model_field,
    lenient_issubclass,
)
from fastapi.datastructures import DefaultPlaceholder
from fastapi.dependencies.models import Dependant
from fastapi.dependencies.utils import (
    _get_flat_fields_from_params,
    get_flat_dependant,
    get_flat_params,
    get_validation_alias,
)
from fastapi.encoders import jsonable_encoder