CommentScope: Powered by Gemini AI

CommentScope is a cutting-edge Streamlit app that leverages Google's Gemini AI to provide in-depth analysis of YouTube comments. It offers powerful insights and visualizations to help content creators, marketers, and researchers understand their audience better.

Test The Live Demo Here

Features

• Gemini-Powered Comment Summarization: Generate concise and insightful summaries of all comments and replies.
• Sentiment Analysis: Analyze the emotional tone of comments using advanced AI techniques.
• In-Depth Analysis: Identify key themes, topics, and patterns in comment threads using Gemini Pro Exp.
• Comparative Analysis: Compare comments across multiple videos to reveal differences in audience sentiment and discussion points.
• Video Summary Generation: Create comprehensive summaries combining video transcripts and comments.
• Interactive Data Table: Explore, sort, filter, and download comment data.
• User Engagement Score: Measure audience engagement based on likes, replies, and sentiment.
• Trending Videos Analysis: Analyze comments on currently trending YouTube videos.
• Visualizations: Gain insights through sentiment analysis charts, word clouds, and comment length distributions.
• Chat with Comments: Ask questions about the comments and receive AI-generated answers.

Key Requirements

• Python 3.7+: The foundation for the application.
• Streamlit: For building the interactive web app.
• google-generativeai: To interact with Google's Gemini AI.
• youtube-transcript-api: For fetching YouTube video transcripts.
• google-api-python-client: For accessing the YouTube Data API.

Note: A complete list of requirements is available in the requirements.txt file.

Installation

1. Clone the repository:

   git clone https://github.com/djpapzin/Comment-Scope.git  
   cd Comment-Scope  

2. Install the required packages:

   pip install -r requirements.txt
   

3. Set up your API keys:

   • Create a .streamlit/secrets.toml file
   • Add your API keys:

     [general]
     GEMINI_API_KEY = "YOUR_GEMINI_API_KEY"
     YOUTUBE_API_KEY = "YOUR_YOUTUBE_API_KEY"

Usage

1. Run the Streamlit app:

   streamlit run app.py
   

2. Open your web browser and navigate to the provided local URL (usually http://localhost:8501).

3. Enter a YouTube video URL or select a trending video to analyze.

4. Explore the various analysis features and visualizations provided by CommentScope.

Contributing

We welcome contributions! Please see our CONTRIBUTING.md for details on how to submit pull requests, report issues, or request features.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

Acknowledgements

• Google Gemini AI
• YouTube Data API
• Streamlit
• All other open-source libraries used in this project

Disclaimer

This app is for educational and research purposes only. It is not intended for commercial use or to violate any terms of service. Please use responsibly and ethically.