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

• 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.

MIT License