### 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)

sla: timedelta | None = None,
        execution_timeout: timedelta | None = DEFAULT_TASK_EXECUTION_TIMEOUT,
        on_execute_callback: None | TaskStateChangeCallback | list[TaskStateChangeCallback] = None,
        on_failure_callback: None | TaskStateChangeCallback | list[TaskStateChangeCallback] = None,
        on_success_callback: None | TaskStateChangeCallback | list[TaskStateChangeCallback] = None,
        on_retry_callback: None | TaskStateChangeCallback | list[TaskStateChangeCallback] = None,
        pre_execute: TaskPreExecuteHook | None = None,
        post_execute: TaskPostExecuteHook | None = None,
        trigger_rule: str = DEFAULT_TRIGGER_RULE,
        resources: dict[str, Any] | None = None,
        run_as_user: str | None = None,
        task_concurrency: int | None = None,
        max_active_tis_per_dag: int | None = None,
        executor_config: dict | None = None,
        do_xcom_push: bool = True,
        inlets: Any | None = None,
        outlets: Any | None = None,
        task_group: TaskGroup | None = None,
        doc: str | None = None,
        doc_md: str | None = None,
        doc_json: str | None = None,
        doc_yaml: str | None = None,
        doc_rst: str | None = None,
        **kwargs,
    ):
        from airflow.models.dag import DagContext
        from airflow.utils.task_group import TaskGroupContext
        self.__init_kwargs = {}
        super().__init__()
        kwargs.pop("_airflow_mapped_validation_only", None)