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Co-authored-by: Yang Yong(雍洋) <yongyang1030@163.com>

…nt task after broadcasting. Handle exceptions when clearing task event.

## Contributing Guidelines

We have prepared a `pre-commit` hook to enforce consistent code
formatting across the project. If your code complies with the standards,
you should not see any errors, you can clean up your code following the
steps below:

1. Install the required dependencies:

```shell
    pip install ruff pre-commit
```

2. Then, run the following command before commit:

```shell
    pre-commit run --all-files
```

3. Finally, please double-check your code to ensure it complies with the
following additional specifications as much as possible:
- Avoid hard-coding local paths: Make sure your submissions do not
include hard-coded local paths, as these paths are specific to
individual development environments and can cause compatibility issues.
Use relative paths or configuration files instead.
- Clear error handling: Implement clear error-handling mechanisms in
your code so that error messages can accurately indicate the location of
the problem, possible causes, and suggested solutions, facilitating
quick debugging.
- Detailed comments and documentation: Add comments to complex code
sections and provide comprehensive documentation to explain the
functionality of the code, input-output requirements, and potential
error scenarios.

Thank you for your contributions!

- Updated `ServerConfig` to raise a RuntimeError when no free port is found, providing clearer guidance for configuration adjustments.
- Introduced chunked broadcasting and receiving methods in `DistributedManager` to handle large byte data more efficiently.
- Refactored `broadcast_task_data` and `receive_task_data` methods to utilize the new chunking methods for improved readability and performance.
- Enhanced error logging in `image_utils.py` by replacing print statements with logger warnings.
- Cleaned up the `main.py` file by removing unused signal handling code.

- Introduced `image_utils.py` with functions to check, extract, and save base64-encoded images.
- Updated `TaskRequest` schema to accept base64 images or URLs in `image_path`.
- Modified `VideoGenerationService` to handle base64 images, saving them appropriately.
- Updated scripts to convert local image paths to base64 before sending requests.

Refactor distributed inference worker to remove unused asyncio event loop and streamline task data processing in VideoGenerationService.

* Enhance BaseRunner with model protocols and type hints and fix lora load

* Add support for multiple LoRAs configuration and enhance lora_strength argument handling

* doc: style fix

* feat: add synchronous file writing method and enhance async file saving in API server

* refactor: clean up image file handling in API server and improve error message in service

* fix: correct frequency computation in WanTransformerInfer

* refactor: restructure API server and distributed inference services

- Removed the old api_server_dist.py file and integrated its functionality into a new modular structure.
- Created a new ApiServer class to handle API routes and services.
- Introduced DistributedInferenceService and FileService for better separation of concerns.
- Updated the main entry point to initialize and run the new API server with distributed inference capabilities.
- Added schema definitions for task requests and responses to improve data handling.
- Enhanced error handling and logging throughout the services.

* refactor: enhance API structure and file handling in server

- Introduced APIRouter for modular route management in the ApiServer class.
- Updated task creation and file download endpoints to improve clarity and functionality.
- Implemented a new method for streaming file responses with proper MIME type handling.
- Refactored task request schema to auto-generate task IDs and handle optional video save paths.
- Improved error handling and logging for better debugging and user feedback.

* feat: add configurable parameters for video generation

- Introduced new parameters: infer_steps, target_video_length, and seed to the API and task request schema.
- Updated DefaultRunner and VideoGenerationService to handle the new parameters for enhanced video generation control.
- Improved default values for parameters to ensure consistent behavior.

* refactor: enhance profiling context for async support

* refactor: improve signal handling in API server

* feat: enhance video generation capabilities with audio support

* refactor: improve subprocess call for audio-video merging in wan_audio_runner.py

* refactor: enhance API server argument parsing and improve code readability

* refactor: enhance logging and improve code comments for clarity

* refactor: update response model for task listing endpoint to return a dictionary

* docs: update API endpoints and improve documentation clarity

* refactor: update API endpoints in scripts for task management and remove unused code

* fix: pre-commit