A Streamlit application that creates AI-powered audio podcasts from web content and custom URLs. The application scrapes content, generates summaries, and converts them into audio format for easy consumption.

• Browse and play audio podcasts organized by date
• Audio player with standard playback controls
• Clear organization of content with dates and timestamps

• Create Today's Podcast: Automatically generates a podcast from today's AI news and updates
• Custom URL Management:
  • Add URLs of your choice to include in podcasts
  • View list of saved URLs with addition dates
  • Delete URLs that are no longer needed
• Create from Saved URLs: Generate podcasts specifically from your saved URLs

• View all generated podcasts with creation dates and times
• Delete unwanted podcasts and their associated report files
• Organized display with easy-to-use controls

1. Clone the repository:

git clone https://github.com/bnarasimha/daily-dose-of-ai.git

2. Navigate to the project directory:

cd daily-dose-of-ai

3. Install required packages:

pip install -r requirements.txt

4. Set up environment variables:
   Copy .env.example file and create a .env file in the root directory and update API keys.
   Here you can find details about creating Agent in GenAI Platform.

1. Start the Streamlit application:

streamlit run main.py

2. Access the application in your web browser at http://localhost:8501 (Or click the Url in terminal)

├── main.py                    # Main Streamlit application
├── database.py               # SQLite database operations
├── src               # Source files
   ├── get_daily_updates.py      # Run the flow
   ├── daily_updates_urls_finder.py  # URL finding and listing
   ├── daily_updates_scraper.py  # URL scraper and highlights generator
   ├── daily_updates_podcaster.py  # Audio file creator
   ├── database.py  # Handle database operations
├── audio_files/             # Directory for generated audio files
└── custom_urls.db          # SQLite database for custom URLs

• Python 3.10+
• Streamlit
• SQLite3
• gTTS (Google Text-to-Speech)
• Other dependencies listed in requirements.txt

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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

• GenAI Platform for LLama Models
• OpenAI for GPT models
• Streamlit for the web framework
• Google Text-to-Speech for audio generation