Remove default branch assignment for layered image type in _resolve_musubi_target function in app.py. This change simplifies branch handling by eliminating the automatic assignment of a specific branch when no branch is set, enhancing clarity in target resolution logic.

Update _update_dataset_toml function in app.py to handle multiple_target removal

Enhance _copy_uploads function in app.py to support RGBA conversion

Add musubi-tuner-layered to .gitignore

Update app.py to enable GPU support and streamline model download process

Add musubi tuner target resolution and branch handling in app.py

Add layered training functionality and enhance error handling in app.py

Refactor app.py and download_qwen_image_models.py for improved model handling

Refactor app.py to improve regex replacements and UI components

Add dataset configuration synchronization in run_training

Refactor app.py by removing unused active process management code. This cleanup enhances code clarity and reduces complexity by eliminating unnecessary global variables and functions related to process termination, while maintaining the core functionality of the training process.

Enhance run_training function in app.py to include run_out_dir in yield outputs. This update improves the tracking of the output directory throughout the training process and ensures consistent error handling by including run_out_dir in all yield statements, enhancing user feedback and clarity.

Refactor _stop_active_training function in app.py

Add edit model version handling and filename generation

Enhance run_training function in app.py to emit an initial log message upon invocation. This update improves user feedback by confirming the start of the training process and maintains existing error handling for required output names.

Refactor active process management in app.py

Add active process management for training in app.py

Refactor refresh functionality in app.py to retrieve checkpoints and scripts together

Add functionality to refresh scripts and configuration files in app.py

Enhance run_training function in app.py to yield artifacts alongside checkpoints. Update error handling to include artifacts in log outputs, and add functionality to track and expose dataset configuration and script files for download. Modify UI to display scripts and configuration files, improving user experience and accessibility.

Add dataset configuration update functionality in app.py

Update requirements.txt to add Jupyter package for enhanced development capabilities and ensure proper formatting with newlines at the end of the file.

Enhance run_training function in app.py to ensure child Python processes are unbuffered for real-time logging. Update _prepare_script to include unbuffered flag and modify UI launch to support ssr_mode, improving compatibility with different Gradio versions.

Update requirements.txt to change index-url to extra-index-url for PyTorch, ensuring correct package source configuration.

Reorder entries in requirements.txt for clarity and ensure OpenAI package is listed correctly.

Update requirements.txt to add OpenAI package and reorder torchvision entry for clarity.

Add OpenAI package to requirements.txt for enhanced functionality and integration.

Refactor Gradio UI in QIE_prompt_generator.py to encapsulate the layout within a build_ui function, enhancing modularity and readability. The update includes improved organization of input fields and maintains the existing functionality for prompt generation.

Refactor UI in app.py to implement a tabbed layout for the Trainer and Prompt Generator sections, enhancing organization and user experience. The update includes restructured input fields and improved accessibility for image uploads and prompt generation functionalities.

Enhance _list_checkpoints function in app.py to skip files that are zero-length, too new, or unreadable. This improvement ensures more robust file handling by filtering out potentially in-flight files, thereby reducing errors during checkpoint listing.

Add zero-length file check in _list_checkpoints function of app.py to skip empty files during checkpoint listing. This enhancement improves the robustness of file handling by preventing errors related to empty files.

Refactor error handling in run_training function of app.py to remove unnecessary None yields. This change streamlines the output by ensuring consistent return values when errors occur, enhancing clarity in the training process.

Update prefix/suffix naming in _prepare_script of app.py to ensure consistency with target parameters. This change improves clarity in metadata creation by correctly labeling the flags for target prefix and suffix.

Refactor UI layout in app.py by reorganizing the prefix/suffix input fields into accordions for improved accessibility and visual coherence. This update enhances the user experience during image uploads by maintaining a consistent structure across control sections.

Refactor UI layout in app.py to improve organization of target image input fields. Adjust the arrangement of the prefix and suffix textboxes for better accessibility and visual coherence, enhancing the overall user experience during image uploads.

Refactor UI in app.py to enhance layout and styling of sections, improving organization and accessibility. Adjust padding and margins for better visual consistency, and update accordion titles for clarity on prefix/suffix functionality in image uploads.

Refactor UI layout in app.py by consolidating input fields into accordions for better organization and accessibility. This update enhances the user experience for managing target and control images, improving the overall interface for image uploads and training configurations.

Refactor UI layout in app.py to improve organization and accessibility of input fields by grouping related elements and adding custom CSS styling. This enhances the overall user experience for image uploads and training parameter configurations.

Refactor UI layout in app.py to enhance user experience by incorporating an accordion for control_0 image previews. This change improves organization and accessibility of image upload and preview functionalities.

Enhance app.py by implementing a logging mechanism for training progress and model performance metrics. This addition improves monitoring capabilities during training sessions and aids in debugging.

Update .gitignore to include __pycache__ directory for better file management and to prevent unnecessary cache files from being tracked.

Add hyperparameter overriding functionality in _prepare_script of app.py to allow safer and more flexible adjustments of learning rate, network dimension, seed, max training epochs, and save frequency. This enhances configurability for training scripts.

Refactor app.py to update prefix/suffix naming conventions for metadata creation and enhance UI with new training hyperparameter inputs. Modify train_QIE.sh to utilize dynamic hyperparameter values for training execution, improving configurability and user experience.

Add hyperparameter override options in _prepare_script function of app.py to allow dynamic adjustment of learning rate, network dimension, and seed during script preparation. Update UI elements for clarity in target image handling.

Implement target prefix/suffix functionality in app.py and create_image_caption_json.py for improved image processing. Update UI to reflect changes, enhancing user experience with clearer labeling and file handling. Refactor related functions to accommodate new naming conventions.

Add checkpoint listing functionality in app.py to track and display model checkpoints during training. Update run_training to yield checkpoint information and enhance Gradio UI with checkpoint file outputs for improved user experience.

Refactor app.py to set output_dir_base to the unique dataset directory and enhance Gradio UI launch by allowing access to specific runtime directories, improving file serving capabilities.

Update app.py to remove outdated startup instructions from the UI, enhance train_QIE.sh to dynamically set cache_directory, and modify requirements.txt to specify a custom index URL for torchvision installation.

Update torchvision dependency in requirements.txt from 0.20.1 to 0.22.1 for improved functionality and compatibility.

Add Torch version check in train_QIE.sh to log availability and version information, enhancing debugging and environment validation.