v0.12.0

Add Support for Local Whisper Models and Integrate llmR for Summarization

Enhancements

• Support for Local Whisper Models: Added functions use_whisper_local_stt and use_mlx_whisper_local_stt to support local Whisper models via Python with reticulate, with the second being optimized for Mac OS with Apple Silicon (Commit: 69e4f5e).
• Integration with llmR: Refactored the code to rely on the llmR package for LLM interactions, removing redundant LLM-related functions (Commit: 2331b46).
• Enhanced Speech-to-Text Workflow: Updated perform_speech_to_text to use whisper_local as the default model and enhanced speech_to_summary_workflow to display the selected speech-to-text model (Commit: 69e4f5e).

Fixes

• Dependency Management: Replaced custom dependency check function with rlang::check_installed for better package management (Commit: 3227b0d).

Documentation

• Updated README: Revised README to describe the use of llmR for summarization and the addition of new local models for speech-to-text (Commit: 8bff883).

Summary

This pull request introduces significant enhancements to the minutemaker package by adding support for local Whisper models, integrating the llmR package for LLM interactions, and improving the speech-to-text workflow. Additionally, it fixes dependency management issues and updates the documentation to reflect these changes.

What's Changed

• Add Support for Local Whisper Models and Integrate llmR for Summarization by @bakaburg1 in #23

Full Changelog: v0.10.0...v0.12.0