slurpai

Convert voice notes, videos, and audio files into AI-ready text and images.

Consultants, researchers, and anyone who works with AI tools faces the same problem: clients and colleagues send voice notes, screen recordings, and video walkthroughs — but your AI workflow needs text and images. SlurpAI bridges that gap with a single command.

pip install slurpai
export OPENAI_API_KEY=sk-...
slurpai client-feedback.opus

That's it. You get a folder with transcript.txt and you're ready to feed it into whatever AI tool you're using.

pip install slurpai

You also need ffmpeg on your PATH:

| OS | Command | |----|---------| | macOS | brew install ffmpeg | | Ubuntu/Debian | sudo apt install ffmpeg | | Windows | choco install ffmpeg or download from ffmpeg.org |

# Transcribe a voice note
slurpai recording.opus

# Process a video (transcript + frame grabs every 15 seconds)
slurpai feedback.mp4

# Batch process everything in a folder
slurpai *.opus *.mp4

# Grab frames more frequently
slurpai --frame-interval 5 demo.mp4

# Use local Whisper instead of OpenAI API
pip install slurpai[local]
slurpai --backend faster-whisper recording.opus

# Preview what would be processed
slurpai --dry-run *.opus

Each file produces a folder alongside it:

recording/
├── transcript.txt    # Plain text transcription
├── frames/           # Video frame grabs (video only)
│   ├── frame_001.jpg
│   ├── frame_002.jpg
│   └── ...
└── process.log       # Timestamped processing log

Re-running the same command skips already-completed files (idempotent).

By default, slurpai sends your audio to [OpenAI's Whisper API](https://platform.openai.com/docs/guides/speech-to-text) for transcription. Your audio is transmitted to OpenAI's servers. Review [OpenAI's data usage policy](https://openai.com/policies/api-data-usage-