natolambert / smol-podcaster

smol-podcaster is your autonomous podcast production intern 🐣

smol-podcaster

We use smol-podcaster to take care of most of Latent Space transcription work. What it will do for you:

• Generate a clean, diarized transcript of the podcast with speaker labels and timestamps
• Generate a list of chapters with timestamps for the episode
• Give you title ideas based on previous ones (modify the prompt to give examples of your own, it comes with Latent Space ones)
• Give you ideas for tweets to announce the podcast

Environment Setup

Activate virtualenv with

source venv/bin/activate

Install dependencies with

pip install -r requirements.txt

Make a copy of the .env.sample and replace it with your keys:

mv .env.sample .env

Run from CLI

To run:

python smol_podcaster.py AUDIO_FILE_URL GUEST_NAME NUMBER_OF_SPEAKERS

The URL needs to be a direct download link, it can't be a GDrive. For files <100MB you can use tmpfiles.org, otherwise Dropbox. For example:

python smol_podcaster.py "https://dl.dropboxusercontent.com/XXXX" "Tianqi" 3

The script will automatically switch https://www.dropbox.com to https://dl.dropboxusercontent.com in the link.

Run with web UI + background runs

If you want to run a bunch in parallel (or remotely) you can use the web UI + celery. Before running, you'll need a broker for celery (I use RabbitMQ).

If you have honcho installed, simply run honcho start, otherwise run each command manually:

celery -A tasks worker --loglevel=INFO
flask --app web.py --debug run

Then simply go to localhost:5000 and fill out the form. The files will be saved locally as /podcast-results just like the cli version.

License

MIT License