mknotes/enhancement_proposals.md

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.