🎥 ⚡ 🤖 A powerful YouTube video analysis tool that leverages Google's Gemini AI to provide comprehensive insights, summaries, and interactive Q&A for any YouTube video with available transcripts.
- Comprehensive Video Analysis: Generate detailed summaries, key points, and insights from YouTube videos
- Multiple Analysis Types:
- Summary & Key Points
- Title Suggestions
- Quotes with Timestamps
- Key Terms & Definitions
- Full Analysis (all of the above)
- Interactive Q&A: Ask questions about the video content and get AI-powered responses
- Export Options: Download analysis results in both Word and Text formats
- Full Transcript Access: View and download complete video transcripts
- Large Context Window: Utilizes Gemini's 1M token input capacity for comprehensive analysis
- Clone the repository:
git clone https://github.com/lhiebert01/GeminiYouTubeApp.git
cd GeminiYouTubeApp
- Create and activate a virtual environment:
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
- Install dependencies:
pip install -r requirements.txt
- Create a
.env
file in the project root with your API keys:
GEMINI_API_KEY=your_gemini_api_key
YOUTUBE_API_KEY=your_youtube_api_key
- For Streamlit deployment, configure secrets in your Streamlit dashboard:
- Navigate to your app settings
- Add the above environment variables in the Secrets management section
-
Gemini API Key:
- Visit Google AI Studio
- Create a new API key
- Copy the key to your
.env
file or Streamlit secrets
-
YouTube API Key:
- Go to Google Cloud Console
- Create a new project or select an existing one
- Enable the YouTube Data API v3
- Create credentials (API key)
- Copy the key to your
.env
file or Streamlit secrets
- Run the application locally:
streamlit run app.py
- Enter a YouTube URL in the sidebar
- Select your desired analysis type
- Click "Run Analysis" to generate insights
- Use the Q&A interface to ask specific questions about the video
- Download results in your preferred format
-
Summary & Key Points
- Comprehensive summary (2-3 paragraphs)
- Key points in table format
-
Title Suggestions
- 3-5 alternative titles with explanations
- Based on video content and themes
-
Quotes with Timestamps
- 5-10 significant quotes
- Context and significance explanations
-
Key Terms & Definitions
- Important concepts and jargon
- Clear, organized definitions
-
All Analysis
- Complete analysis including all above features
- Word Document: Complete analysis with formatting
- Text File: Plain text version of analysis
- Transcript: Raw video transcript
- Built with Streamlit and Google's Gemini AI
- Uses YouTube Data API v3 for video information
- Implements smart text truncation for long videos
- Maintains session state for seamless user experience
The application is deployed on Streamlit Cloud. For deployment:
- Push your changes to GitHub
- Connect your repository to Streamlit Cloud
- Configure your environment variables in Streamlit Cloud
- Deploy!
- Never commit
.env
file or secrets to the repository - Use environment variables for all sensitive information
- Implement rate limiting and error handling for API calls
- Fork the repository
- Create a feature branch
- Commit your changes
- Push to the branch
- Create a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
- Architecture Overview - Detailed application structure and flow
- Technical Details - In-depth technical implementation details
For a complete understanding of the application architecture and flow, please see the Architecture Documentation.
Developed by Lindsay Hiebert using Google's Gemini AI and Streamlit.
For questions or collaboration, please reach out through LinkedIn.