### 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)

if not dag:
        return {}, ParamsDict()
    dag_args = copy.copy(dag.default_args)
    dag_params = copy.deepcopy(dag.params)
    if task_group:
        if task_group.default_args and not isinstance(task_group.default_args, collections.abc.Mapping):
            raise TypeError("default_args must be a mapping")
        dag_args.update(task_group.default_args)
    return dag_args, dag_params
def get_merged_defaults(
    dag: DAG | None,
    task_group: TaskGroup | None,
    task_params: dict | None,
    task_default_args: dict | None,
) -> tuple[dict, ParamsDict]:
    args, params = _get_parent_defaults(dag, task_group)
    if task_params:
        if not isinstance(task_params, collections.abc.Mapping):
            raise TypeError("params must be a mapping")
        params.update(task_params)
    if task_default_args:
        if not isinstance(task_default_args, collections.abc.Mapping):
            raise TypeError("default_args must be a mapping")
        args.update(task_default_args)
        with contextlib.suppress(KeyError):
            params.update(task_default_args["params"] or {})
    return args, params
class _PartialDescriptor: