mknotes

A command-line tool to transcribe all MP3 and M4A audio files in a directory using Faster Whisper, then enhance the transcriptions into comprehensive notes using OpenAI's GPT-4.1 model.

Features

Batch transcribes all .mp3 and .m4a files in a specified directory
Saves transcriptions as .txt files
Enhances notes using GPT-4.1 with a custom prompt
Outputs enhanced notes in markdown format
Configurable input and output directories

Installation

# Clone the repository
git clone https://github.com/yourusername/mknotes.git
cd mknotes

# Create a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

Usage

export OPENAI_API_KEY="your-api-key-here"
python main.py --input-dir /path/to/audio/files --output-dir /path/to/output [--turbo]

--input-dir: Directory containing audio files (required)
--output-dir: Directory for output files (default: "output")
--turbo: Enable turbo mode for faster inference (uses int8_float16 compute type)
--force: Force re-processing of files even if output files already exist

Turbo Mode Hardware Requirements

The --turbo flag enables faster inference using the int8_float16 compute type, which can significantly speed up transcription. However, this requires:

CUDA-compatible GPU with Tensor Cores (NVIDIA Ampere, Turing, or newer architecture)
Or CPU with AVX2 support

If your hardware does not support this optimization, the program will automatically fall back to the next most compatible compute type and print a warning.

Compute Type Fallback

The program will attempt to use the most efficient compute type supported by your hardware, in the following order:

int8_float16 (if --turbo is enabled)
float16
int8
float32 (most compatible, works on virtually all hardware)

If a compute type is not supported, the program will try the next one in the list until successful.

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