Turn your meeting recordings into clear, structured minutes using LLMs like Groq Whisper and Google Speech Recognition.
- ✅ Audio Transcription — Automatically convert
.wav
or.mp3
files into text - 🧠 LLM-Powered Summarization — Generate concise and structured meeting minutes
- 🔍 Groq & Google Support — Choose between Groq Whisper models or Google Speech API
- 🪓 Automatic Chunking — Splits large files intelligently for smoother transcription
- ⚙️ Fully Customizable — Pick your preferred transcription and summarization models
- 🧾 CLI & Python API — Use it from the terminal or integrate in your Python workflows
- 📁 Clean Output — Saves transcripts and summaries neatly in your desired folder
pip install transmeet
sudo apt-get update && sudo apt-get install -y ffmpeg gcc && sudo apt-get clean && sudo rm -rf /var/lib/apt/lists/*
Set your GROQ API Key/OPENAI API Key in your environment variables.
export GROQ_API_KEY=your_groq_api_key
To make this permanent:
echo 'export GROQ_API_KEY=your_groq_api_key' >> ~/.bashrc
If using OPENAI, set the
OPENAI_API_KEY
similarly. For Google Speech, no API key is needed; it uses the default model.
from transmeet import generate_meeting_transcript_and_minutes
generate_meeting_transcript_and_minutes(
meeting_audio_file="/path/to/audio.wav",
output_dir="complete_path_to_output_dir/",
transcription_client="groq", # or "openai"
transcription_model="whisper-large-v3-turbo", # change as per your need
llm_client="groq", # or "openai"
llm_model="llama-3.3-70b-versatile", # change as per your need
)
This will save two files in your output directory:
transcription_<timestamp>.txt
meeting_minutes_<timestamp>.md
transmeet -i /path/to/audio.wav -o output/
transmeet \
-i /path/to/audio.wav \
-o output/ \
--transcription-client groq \
--transcription-model whisper-large-v3-turbo \
--llm-client groq \
--llm-model llama-3.3-70b-versatile \
output/
├── transcriptions/
│ └── transcription_20250510_213038.txt
├── meeting_minutes/
│ └── meeting_minutes_20250510_213041.md
.wav
.mp3
Argument | Description |
---|---|
-i , --audio-path |
Path to the input audio file |
-o , --output-dir |
Output directory (default: output/ ) |
--transcription-client |
groq or google (default: groq ) |
--transcription-model |
e.g., whisper-large-v3-turbo |
--llm-client |
groq or openai (default: groq ) |
--llm-model |
e.g., llama-3.3-70b-versatile |
- Groq Whisper:
whisper-large
,whisper-large-v3-turbo
, etc. - Google Speech: Model defaults to their API standard
- LLMs for minutes:
llama-3
,mixtral
,gpt-4
, etc. (Groq/OpenAI)
- Add support for multi-language meetings
- Speaker diarization support
- Upload directly to Notion or Google Docs
- Slack/Discord bots
Deepak Raj 👨💻 GitHub • 🌐 LinkedIN
Pull requests are welcome! Found a bug or need a feature? Open an issue or submit a PR.