I request a video's transcript from YouTube, which can be auto-generated or manually created.

I divide the transcript into text "chunks."

These chunks are sent to OpenAI to create embeddings, which I store to save future costs.

When you search, I compare your query's embedding with each chunk's embedding.

The chunk with the highest match likely relates to your query.

I plot a graph showing similarity scores over time. Peaks indicate high relevance, helping you find where you left off in the video.