OpenAI-powered semantic search for the All-In Podcast

[transitivebs]

https://github.com/transitive-bullshit/yt-semantic-search

[transitivebs]

My favorite podcast is the All-In Pod, but search and discovery is tough for podcasts.

So I built a semantic search index that lets you search across every episode of the pod with Google-level accuracy.

It uses OpenAI's latest ada-2 embedding model and Pinecone to index the embeddings + k-NN search. Wrapped up in a Next.js + Vercel webapp.

The project is designed to work with any YouTube channel / playlist. I'm just using All-In as a demo.

Would love to hear feedback & suggestions.

[gbertb]

Great job! Love this. What other improvements besides using whisper did you have in mind?

[transitivebs → gbertb]

Honestly I haven't thought too much about it. Just having fun building :)

[jamesbriggs]

Very cool, how are you doing the speech-to-text part, with Whisper?

[gbertb → jamesbriggs]

The about page explains it. Used a "hacky" method in retrieving the YT transcripts.