The main interface for entering a YouTube URL and generating a summary.

Building YouTube Transcript Summarizer: Making Video Content More Accessible with AI

As someone who enjoys building practical tools that bridge the gap between technology and everyday needs, I wanted to tackle a common challenge: extracting value from long-form YouTube videos quickly and efficiently. The result was the YouTube Transcript Summarizer—a web application that downloads YouTube video transcripts and generates detailed, structured summaries using AI.

The Problem Space

YouTube is a treasure trove of information, but not everyone has the time to watch lengthy videos or sift through transcripts. I saw an opportunity to leverage AI to make video content more accessible, helping users get to the core insights without the time investment.

Key Features

• Download transcripts from YouTube videos
• Generate comprehensive, structured summaries with AI
• Modern, intuitive web interface
• Option to force new summaries for updated content
• Output includes Summary, Highlights, Key Insights, and Conclusion sections

View all generated summaries in a modern, card-based grid.

Development Process

The project was built with a focus on simplicity and usability:

• Python & Flask: For a lightweight backend and rapid prototyping
• Gemini LLM: For high-quality, AI-powered summarization
• Clean UI: Minimalist frontend for a distraction-free experience
• File-based Storage: Summaries and transcripts are stored locally for easy access and management

Setup & Usage

1. Clone the repository:

   git clone https://github.com/fjchng/youtube-transcript
   cd youtube-transcript
   

2. Create a virtual environment and activate it:

   python -m venv venv
   source venv/bin/activate  # On Windows, use: venv\Scripts\activate
   

3. Install dependencies:

   pip install -r requirements.txt
   

4. Add your Gemini API key to a .env file:

   GEMINI_API_KEY=your_api_key_here
   

5. Start the Flask app and open http://localhost:5000 in your browser.

User Experience

The app is designed to be as straightforward as possible:

• Paste a YouTube URL and click “Generate Summary”
• Wait a few moments for the transcript and summary to be generated
• Browse all your generated summaries in a visually organized grid

Example of a detailed summary generated for a YouTube video, including sections for Summary, Highlights, Key Insights, and Conclusion.

Learnings & Takeaways

1. Simplicity Wins: Focusing on a clear, single-purpose workflow made the app more approachable and useful.
2. AI as a Force Multiplier: Integrating LLMs can turn raw data (like transcripts) into actionable insights for users.
3. User Feedback Matters: Early testers appreciated the structured output, which validated the design choices.
4. Open Source Value: Sharing the project on GitHub has already sparked interest and contributions from others.

Conclusion

Building the YouTube Transcript Summarizer was a fun and fulfilling project that combined my interests in AI, automation, and user-centric design. It’s a reminder that even small tools can have a big impact when they solve real problems.

The project is open source—check it out or contribute at github.com/fjchng/youtube-transcript.

Projects like these keep me excited about the possibilities of AI and the power of building for real-world needs.