### 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)

session.query(DagRun)
                    .filter(
                        DagRun.dag_id == self.dag_id,
                        DagRun.execution_date == info.logical_date,
                    )
                    .one()
                )
                ti = TaskInstance(self, run_id=dag_run.run_id)
            except NoResultFound:
                
                dr = DagRun(
                    dag_id=self.dag_id,
                    run_id=DagRun.generate_run_id(DagRunType.MANUAL, info.logical_date),
                    run_type=DagRunType.MANUAL,
                    execution_date=info.logical_date,
                    data_interval=info.data_interval,
                )
                ti = TaskInstance(self, run_id=dr.run_id)
                ti.dag_run = dr
                session.add(dr)
                session.flush()
            ti.run(
                mark_success=mark_success,
                ignore_depends_on_past=ignore_depends_on_past,
                wait_for_past_depends_before_skipping=wait_for_past_depends_before_skipping,
                ignore_ti_state=ignore_ti_state,
                test_mode=test_mode,
                session=session,
            )
    def dry_run(self) -> None: