Feature/qwen3 integration

[Limbicnation]

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[gemini-code-assist]

Summary of Changes

Hello @Limbicnation, 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 significantly enhances the application's image analysis capabilities by integrating the Qwen3-VL-4B-Instruct model. It provides a robust framework for loading and utilizing this new model, complete with dependency management, a dummy fallback for resilience, and updates to the user interface and prompt templating system to ensure seamless operation and user experience.

Highlights

• Qwen3 Model Integration: Introduced the Qwen3-VL-4B-Instruct vision-language model, allowing for new image analysis capabilities within the application.
• New Model Implementation: Added a dedicated Qwen3Model class to handle the loading, setup, and image analysis logic for the Qwen3 model, including dependency checks and optimized model loading parameters.
• Dummy Fallback Model: Implemented a dummy_qwen3_model.py to provide a graceful fallback mechanism when the full Qwen3 model dependencies are not met, preventing application crashes.
• User Interface and Template Updates: Updated the main application interface to include 'qwen3' as a selectable model option and extended the template manager to support specific prompt templates for the Qwen3 model.

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[claude]

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[gemini-code-assist]

Code Review

This pull request introduces support for the Qwen3 model, including its implementation, a dummy fallback, and integration into the main application UI and template system. The changes are well-structured and follow the existing patterns for adding new models.

My review includes a few suggestions for improvement:

• In main.py, I recommend using more specific exceptions for model loading to improve error handling clarity.
• In models/qwen3_model.py, I've identified an opportunity to remove redundant code (an unused tokenizer and a duplicate environment variable setting) and a high-severity performance issue in the batch processing implementation which should be addressed.
• In templates/template_manager.py, there's a minor code duplication in the fallback templates that could be refactored for better maintainability.

Overall, this is a solid addition. Addressing the performance issue in analyze_images_batch is the most important point.

[claude]

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