The resulting app, YouTubeTranscriptOptimizer.com, makes it really quick and easy to paste in a YouTube video URL and have it automatically generate not just a really accurate direct transcription, but also a super polished and beautifully formatted written document that can be used independently of the video.

The document basically sticks to the same material as discussed in the video, but it sounds much more like a real piece of writing and not just a transcript. It also lets you optionally generate quizzes based on the contents of the document, which can be either multiple choice or short-answer quizzes, and the multiple choice quizzes get turned into interactive HTML files where you can actually take the quiz and it will grade your answers and score the quiz for you. And to make things simpler for less tech-savvy content creators, I made it easy to host the resulting quizzes and documents directly so you can easily share them with your potentially even less tech-savvy audience.

This was the first bigger project that I made using a Nextjs/FastAPI stack, and I was very pleased with the framework. It really lets you manage complexity in a nice way. Things did start to get a bit complicated with state management, and I found using Zustand helped to centralize some of that. Anyway, I'm still trying to figure out the exact target market for this tool. Right now it's more targeted to content creators on YouTube who have a Patreon or similar and want to reward their supporters, but I'm realizing that the market of YouTube viewers is much bigger and those people might want to use the tool themselves to turn videos into documents and quizzes for self study purposes.

I'm also working on another version that is document-centric, but it's a bit of a different problem. In the case of YouTube video transcripts, we are dealing with raw speech utterances, so there could be run-on sentences, filler words and other speech errors, etc. Thus we need to really transform the underlying content to first get the optimized document, which can differ quite significantly from the raw transcript. Then we use that optimized document to generate the quizzes.

In the case of a document only workflow, we generally want to stick to what's in the document very closely, and just extract the text accurately using OCR if needed (or extract it directly in case we don't need OCR) and then reformat it into nice looking markdown-- but without changing the actual content itself, just its appearance. When we've turned the original document into nice looking markdown, we can then use this to generate the quizzes and perhaps other related outputs (e.g, Anki cards, Powerpoint-type presentation slides, etc).

Anyway, I'd love to get some initial feedback. I've done a lot of testing, so it should all basically be working now, but I've never dealt with a heavy load, so it's possible that it will melt down my servers if there is too much traffic.