original_type = field.type_
    if is_dataclass(original_type) and hasattr(original_type, "__pydantic_model__"):
        original_type = original_type.__pydantic_model__
    use_type = original_type
    if lenient_issubclass(original_type, BaseModel):
        original_type = cast(Type[BaseModel], original_type)
        use_type = cloned_types.get(original_type)
        if use_type is None:

except (ImportError, AttributeError):
  pass

del importlib

# Delete modules that should be hidden from dir().
# Don't fail if these modules are not available.
# For e.g. this file will be originally placed under tensorflow/_api/v1 which
# does not have "python", "core" directories. Then, it will be copied
# to tensorflow/ which does have these two directories.
try:
  del python
except NameError:
  pass

        return {"filename": file.filename}
    ```
    """

    file: Annotated[
        BinaryIO,
        Doc("The standard Python file object (non-async)."),
    ]
    filename: Annotated[Optional[str], Doc("The original file name.")]
    size: Annotated[Optional[int], Doc("The size of the file in bytes.")]
    headers: Annotated[Headers, Doc("The headers of the request.")]
    content_type: Annotated[