### Apache Airflow Provider(s)

amazon

### Versions of Apache Airflow Providers

apache-airflow-providers-amazon==7.1.0

### Apache Airflow version

2.5.1

### Operating System

Ubuntu 18.04

### Deployment

Official Apache Airflow Helm Chart

### Deployment details

_No response_

### What happened

When looking at logs in the UI for a running task when using remote s3 logging, the logs for the task are only uploaded to s3 after the task has completed. The the `S3TaskHandler` falls back to the local logs stored on the worker in that case (by falling back to the `FileTaskHandler` behavior) and prepends the line `*** Falling back to local log` to those logs.

This is mostly fine, but for the new log streaming behavior, this means that `*** Falling back to local log` is returned from `/get_logs_with_metadata` on each call, even if there are no new logs.

### What you think should happen instead

I'd expect the falling back message only to be included in calls with no `log_pos` in the metadata or with a `log_pos` of `0`.

### How to reproduce

Start a task with `logging.remote_logging` set to `True` and `logging.remote_base_log_folder` set to `s3://something` and watch the logs while the task is running. You'll see `*** Falling back to local log` printed every few seconds.

### 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)

"""
        Read logs of given task instance and try_number from S3 remote storage.
        If failed, read the log from task instance host machine.
        todo: when min airflow version >= 2.6 then remove this method (``_read``)
        :param ti: task instance object
        :param try_number: task instance try_number to read logs from
        :param metadata: log metadata,
                         can be used for steaming log reading and auto-tailing.
        """
        
        if hasattr(super(), "_read_remote_logs"):
            return super()._read(ti, try_number, metadata)
        
        messages, logs = self._read_remote_logs(ti, try_number, metadata)
        if logs:
            return "".join(f"*** {x}\n" for x in messages) + "\n".join(logs), {"end_of_log": True}
        else:
            local_log, metadata = super()._read(ti, try_number, metadata)
            return "*** Falling back to local log\n" + local_log, metadata
    def s3_log_exists(self, remote_log_location: str) -> bool: