feat(model/qwen-tts): add param language_type

[songguocola]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @songguocola, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request enhances the Qwen Text-to-Speech (TTS) capabilities within the dashscope library by adding a language_type parameter, which provides explicit control over the language of the synthesized audio. It also improves the API's usability by making the voice selection a direct argument and updates the example usage to reflect these changes and incorporate more robust error handling.

Highlights

• New language_type Parameter: Introduced a new language_type parameter for Qwen TTS, allowing users to specify the synthesized language, particularly for the qwen3-tts model.
• Refactored voice Parameter: The voice parameter has been promoted from a **kwargs argument to a direct parameter in the MultiModalConversation.call methods for better clarity and control.
• Updated Sample Code: The test_qwen_tts.py sample has been updated to use the qwen3-tts-flash model, demonstrate the new language_type parameter, and include improved error handling for responses.

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[gemini-code-assist]

Code Review

This pull request introduces a language_type parameter for qwen-tts models, which is a useful addition. The changes are consistently applied across synchronous, asynchronous, and real-time streaming methods. My review includes suggestions to refactor some repetitive code for better maintainability and points out a potential point of confusion in one of the updated sample files.

[gemini-code-assist]

The conditional checks to add text, voice, and language_type to the input dictionary are repetitive. This can be refactored into a loop to improve code readability and make it easier to add more optional parameters in the future.

Suggested change

	if text is not None and text:
	input.update({'text': text})
	if voice is not None and voice:
	input.update({'voice': voice})
	if language_type is not None and language_type:
	input.update({'language_type': language_type})
	for key, value in (('text', text), ('voice', voice), ('language_type', language_type)):
	if value:
	input[key] = value