veyra — Build for a Friend

This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend

What I Built

I built veyra, a tool that helps you understand long educational YouTube videos without watching every minute.

The idea came from a problem I noticed while talking with a friend. Long educational videos may or may not contain a lot of useful information, but finding the exact parts you need can take a lot of time.

So I decided to build something around that problem.

With veyra, you paste a YouTube video URL and it breaks the video into 5-minute sections.

Each section gives you:

• A topic
• A short summary
• Important points
• Concepts mentioned
• Useful resources

The goal is not to replace the original video. Instead, veyra gives you a structured way to explore the whole video and quickly understand what each part is about.

I also left the testimonials section open for feedback from the friends I built this for. I haven't received their reviews yet, so I decided not to add fake testimonials and will add their actual thoughts once they have tried veyra.

Demo

Live demo:

https://aiveyra.vercel.app

You can paste a YouTube video URL into the dashboard and let veyra analyze it.

Code

GitHub repository:

https://github.com/Tsaishashanth/veyra

The project is open source, so anyone can check the code or contribute.

How I Built It

The main flow of veyra is:

YouTube URL → Transcript → 5-minute sections → Gemma → Results

I built the application using Next.js, TypeScript and Tailwind CSS.

For the AI part, I used Gemma to analyze each 5-minute section of the video.

The transcript is first divided into smaller sections. Each section is then sent to Gemma, which generates the topic, summary, key points, concepts and useful resources.

I also had to handle videos where the normal YouTube transcript method doesn't work. For those cases, I added a fallback transcript service.

The main reason for splitting the transcript into smaller sections was to keep the AI focused on a specific part of the video instead of sending one large transcript and asking it to understand everything at once.

Why Does Open Innovation Matter?

I wanted to use an open model for veyra because I wanted the AI part of the project to be something I could experiment with and improve.

Using Gemma gives me the freedom to change the prompts, experiment with the way each section is analyzed and explore how open models can be used in a real application.

Since veyra is also open source, developers can look at how the AI is being used and contribute improvements to the project.

For me, open innovation makes it easier to experiment, learn and build on top of the work that already exists.

Prize Categories

Best Use of Gemma

Gemma is used as the main AI model in veyra to analyze each section of a YouTube video and generate the structured results.