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smol-podcaster

Screenshot

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 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.

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 (e.g. https://tmpfiles.org/dl/4338258/audio.mp3), otherwise Dropbox. For example:

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

Or, if you want to use a local file (with absolute or relative paths), use the following:

python smol_podcaster.py audio_sample.mp3 "test" 1

Or, use ~/Downloads/audio_sample.mp3 for file.

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

Optional flags:

  • --transcript_only will generate only the transcript without any of the show notes
  • --generate_extra will also create tweets and title ideas

Audio / Video Sync

If you use smol-podcaster to transcribe both your audio and video files, you can create chapters based on your audio ones, put them in the form, and create a new list that matches the video transcript for YouTube. Usually audio and video have different lengths because less pauses are edited, so re-using the audio timestamps in the video doesn't work.

For example:

Timestamp: [00:10:00] Talking about Latent Space

Audio Transcript: [00:10:00] We love talking about Latent Space

Video Transcript: [00:12:05] We love talking about Latent Space

Will return you new chapters where the timestamp would be [00:12:05] Talking about Latent Space

This is based on string similarity, not hard-matching so don't worry about Whisper's mistakes.

Edit Show Notes

Each run generates a set of show notes from both OAI and Claude. The easiest way to consolidate them is the "Edit Show Notes" feature. Simply click "Edit Episode" to see a list of them, and then make the edits you need.

Screenshot

Screenshot

After you're done editing, press "Save Changes" and it will rewrite the Markdown in your file to show the new cleaned and merged list.

License

MIT License