# mknotes Improvement Recommendations

This document outlines proposed improvements for the mknotes software, grouped by category.

## Feature Enhancements

- **Support for More Audio Formats** ✅ (Partially implemented - WAV support added)
  - ✅ Added support for WAV files with automatic conversion to MP3 before processing
  - Extend support to include additional formats like FLAC, OGG, etc.
  - ✅ Updated the `find_audio_files` function in `utils.py` to recognize WAV extension

- **Customizable Enhancement Prompts** ✅ (Implemented)
  - ✅ Added CLI argument to select different prompt types (lecture, meeting, interview)
  - ✅ Moved prompts to separate files for easier customization
  - ✅ Created specialized prompts for different use cases (lectures, meeting minutes, interviews)
  - Allow users to provide their own custom prompts via configuration files.

- **Batch Processing Controls**
  - Add the ability to limit the number of files processed in one run.
  - Implement resume functionality for interrupted batch processing.

- **Output Format Options**
  - Support multiple output formats beyond Markdown (e.g., HTML, PDF, DOCX).
  - Add options for customizing Markdown styling.

- **Caching Mechanism**
  - Implement caching for OpenAI API calls to reduce costs and improve performance.
  - Store intermediate results to avoid reprocessing if enhancement fails.

## Technical Improvements

- **Robust Error Handling and Logging**
  - Implement a proper logging system instead of print statements.
  - Add comprehensive error handling with appropriate recovery strategies.
  - Example: Add retry logic for API calls with exponential backoff.

- **Configuration Management**
  - Create a configuration system using YAML/JSON files.
  - Allow users to set default values for all parameters.
  - Support environment-specific configurations.

- **API Key Management**
  - Implement a more secure way to handle API keys.
  - Add support for API key rotation.

- **Performance Optimization**
  - Implement parallel processing for transcription of multiple files.
  - Add an option to use local models for offline processing.

- **Testing Framework**
  - Add unit tests for core functionality.
  - Implement integration tests for the complete workflow.

## Code Structure Improvements

- **Separation of Concerns** ✅ (Partially implemented)
  - ✅ Moved prompts to separate files in a dedicated prompts directory.
  - Create a more abstract API client layer.

- **Progress Tracking and Reporting**
  - Enhance progress reporting beyond simple tqdm bars.
  - Add detailed statistics about processing time, token usage, etc.

- **Plugin Architecture**
  - Implement a plugin system to allow for custom transcription or enhancement modules.
  - Make it easier to switch between different AI models or services.

## User Experience Enhancements

- **Interactive Mode**
  - Add an interactive mode where users can preview and edit enhanced notes before saving.
  - Implement a simple TUI (Text User Interface) for a better CLI experience.

- **Web Interface**
  - Create a simple web interface for users who prefer GUI over CLI.
  - Consider a lightweight Flask/FastAPI app that wraps the core functionality.

- **Notification System**
  - Add notifications for long-running processes (email, desktop notifications).
  - Implement a webhook system for integration with other tools.

## Documentation Improvements

- **Enhanced Documentation**
  - Create comprehensive documentation with examples and use cases.
  - Add a troubleshooting guide for common issues.

- **Sample Configurations**
  - Provide sample configuration files for different use cases.
  - Include examples of custom prompts for different types of content.

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These recommendations are intended to guide future development and prioritization for mknotes. Each suggestion can be implemented independently or as part of a broader roadmap.