### 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)

"Please use `none_failed_min_one_success`.",
                RemovedInAirflow3Warning,
                stacklevel=2,
            )
            trigger_rule = TriggerRule.NONE_FAILED_MIN_ONE_SUCCESS
        if not TriggerRule.is_valid(trigger_rule):
            raise AirflowException(
                f"The trigger_rule must be one of {TriggerRule.all_triggers()},"
                f"'{dag.dag_id if dag else ''}.{task_id}'; received '{trigger_rule}'."
            )
        self.trigger_rule: TriggerRule = TriggerRule(trigger_rule)
        self.depends_on_past: bool = depends_on_past
        self.ignore_first_depends_on_past: bool = ignore_first_depends_on_past
        self.wait_for_past_depends_before_skipping: bool = wait_for_past_depends_before_skipping
        self.wait_for_downstream: bool = wait_for_downstream
        if wait_for_downstream:
            self.depends_on_past = True
        self.retry_delay = coerce_timedelta(retry_delay, key="retry_delay")
        self.retry_exponential_backoff = retry_exponential_backoff
        self.max_retry_delay = (
            max_retry_delay
            if max_retry_delay is None
            else coerce_timedelta(max_retry_delay, key="max_retry_delay")
        )
        
        self.params: ParamsDict | dict = ParamsDict(params)
        if priority_weight is not None and not isinstance(priority_weight, int):
            raise AirflowException(
                f"`priority_weight` for task '{self.task_id}' only accepts integers, "
                f"received '{type(priority_weight)}'."