Cosmetic changes

[ks6088ts]

Cosmetic changes

[Copilot]

Pull Request Overview

This PR refactors the Streamlit chat application with audio support by extracting text-to-speech (TTS) and speech-to-text (STT) functionality into separate modules and restructuring the main application code for better maintainability.

• Extracts TTS functionality into a dedicated TtsWrapper class in template_langgraph/speeches/tts.py
• Extracts STT functionality into a dedicated SttWrapper class in template_langgraph/speeches/stt.py
• Refactors the main Streamlit application to use these new wrapper classes and improve code organization with dataclasses and helper functions

Reviewed Changes

Copilot reviewed 3 out of 4 changed files in this pull request and generated 5 comments.

File	Description
template_langgraph/speeches/tts.py	New TTS wrapper class with audio synthesis and processing capabilities
template_langgraph/speeches/stt.py	New STT wrapper class for Whisper-based transcription
template_langgraph/services/streamlits/pages/chat_with_tools_agent.py	Refactored to use new wrapper classes and improved code structure with dataclasses

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[Copilot]

The __init__ and load_model methods are empty with only pass statements. Consider removing these methods if they're not needed, or add docstrings explaining their intended future purpose.

Suggested change

	def __init__(self):
	pass
	def load_model(self):
	pass

[Copilot]

The language parameter should have a default value or be made optional with str | None type annotation to handle the "auto" detection case consistently with how it's used in the calling code.

Suggested change

	language: str,
	) -> str:
	logger.info(f"Transcribing audio: {audio_path} with language: {language}")
	result = self.model.transcribe(
	audio=audio_path,
	language=language,
	)
	language: str | None = None,
	) -> str:
	logger.info(f"Transcribing audio: {audio_path} with language: {language}")
	if language is not None:
	result = self.model.transcribe(
	audio=audio_path,
	language=language,
	)
	else:
	result = self.model.transcribe(
	audio=audio_path,
	)

[Copilot]

Using a broad except Exception clause can mask important errors. Consider catching more specific exceptions like whisper.WhisperError or IOError to handle known failure modes appropriately.

[Copilot]

Using a broad except Exception clause can mask important errors. Consider catching more specific exceptions related to image processing or file handling instead.

Suggested change

	except Exception as exc: # noqa: BLE001
	except (AttributeError, TypeError, ValueError) as exc:

[Copilot]

Using a broad except Exception clause can mask important errors. Consider catching more specific exceptions related to TTS processing or audio generation instead.