### Apache Airflow version

2.5.1

### What happened

Context: I am attempting to use [TypedDict](https://docs.python.org/3/library/typing.html#typing.TypedDict) objects to maintain the keys used in DAG params in a single place, and check for key names across multiple DAGs that use the params.
This raises an error with `mypy` as `params` expects an `Optional[Dict]`. Due to the invariance of `Dict`, this does not accept `TypedDict` objects.

What happened: I passed a `TypedDict` to the `params` arg of `DAG` and got a TypeError.

### What you think should happen instead

`TypedDict` objects should be accepted by `DAG`, which should accept `Optional[Mapping[str, Any]]`. 

Unless I'm mistaken, `params` are converted to a `ParamsDict` class and therefore the appropriate type hint is a generic `Mapping` type.

### How to reproduce

Steps to reproduce

```Python
from typing import TypedDict

from airflow import DAG
from airflow.models import Param

class ParamsTypedDict(TypedDict):
    str_param: Param

params: ParamsTypedDict = {
    "str_param": Param("", type="str")
}

with DAG(
    dag_id="mypy-error-dag",
    # The line below raises a mypy error
    # Argument "params" to "DAG" has incompatible type "ParamsTypedDict"; expected "Optional[Dict[Any, Any]]"  [arg-type]
    params=params,  
) as dag:
    pass
```

### Operating System

Amazon Linux

### Versions of Apache Airflow Providers

_No response_

### Deployment

Docker-Compose

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit PR?

- [X] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

"""Exposes a CLI specific to this DAG"""
        check_cycle(self)
        from airflow.cli import cli_parser
        parser = cli_parser.get_parser(dag_parser=True)
        args = parser.parse_args()
        args.func(args, self)
    @provide_session
    def test(
        self,
        execution_date: datetime | None = None,
        run_conf: dict[str, Any] | None = None,
        conn_file_path: str | None = None,
        variable_file_path: str | None = None,
        session: Session = NEW_SESSION,
    ) -> None:
        """
        Execute one single DagRun for a given DAG and execution date.
        :param execution_date: execution date for the DAG run
        :param run_conf: configuration to pass to newly created dagrun
        :param conn_file_path: file path to a connection file in either yaml or json
        :param variable_file_path: file path to a variable file in either yaml or json
        :param session: database connection (optional)
        """
        def add_logger_if_needed(ti: TaskInstance):