### 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)

DagContext.push_context_managed_dag(self)
        return self
    def __exit__(self, _type, _value, _tb):
        DagContext.pop_context_managed_dag()
    
    @staticmethod
    def _upgrade_outdated_dag_access_control(access_control=None):
        """
        Looks for outdated dag level actions (can_dag_read and can_dag_edit) in DAG
        access_controls (for example, {'role1': {'can_dag_read'}, 'role2': {'can_dag_read', 'can_dag_edit'}})
        and replaces them with updated actions (can_read and can_edit).
        """
        if not access_control:
            return None
        new_perm_mapping = {
            permissions.DEPRECATED_ACTION_CAN_DAG_READ: permissions.ACTION_CAN_READ,
            permissions.DEPRECATED_ACTION_CAN_DAG_EDIT: permissions.ACTION_CAN_EDIT,
        }
        updated_access_control = {}
        for role, perms in access_control.items():
            updated_access_control[role] = {new_perm_mapping.get(perm, perm) for perm in perms}
        if access_control != updated_access_control:
            warnings.warn(
                "The 'can_dag_read' and 'can_dag_edit' permissions are deprecated. "
                "Please use 'can_read' and 'can_edit', respectively.",
                RemovedInAirflow3Warning,
                stacklevel=3,
            )
        return updated_access_control
    def date_range(