AINewsCurator

Want to create a high-quality newsletter on any topic effortlessly? The AI NewsCurator Agent does it for you! This smart, multi-agent tool browses the web, gathers the latest information, summarizes key insights, and compiles a polished newsletter—so you don't have to.

How It Works:

📰 Newsletter Agent – Searches the internet for the most relevant articles.
✍️ Summarizer Agent – Extracts key points and creates easy-to-read summaries.
📢 Publisher Agent – Compiles everything into a well-structured newsletter.

Perfect for content creators, researchers, and businesses looking to stay informed without the hassle. Just input a topic, and let AI do the rest! 🎯

✨ Key Features

• 🔍 Smart Search: Utilizes Tavily API to find the most relevant and recent AI/ML news articles
• 🤖 Intelligent Summarization: Leverages OpenAI's advanced language models to create concise, readable summaries
• 📝 Professional Formatting: Automatically formats content into a well-structured newsletter
• 🎨 Modern UI: Clean, intuitive interface built with Streamlit
• 🔄 Multiple LLM Support: Designed to support various language models (OpenAI, Ollama, VLLM, Groq, Claude, Gemini)

🚀 Getting Started

Prerequisites

• Python 3.8 or higher
• Tavily API key (Get it here)
• OpenAI API key (Get it here)

📦 Installation

1. Clone the repository:

git clone https://github.com/akhil-bot/AINewsCurator.git
cd AINewsCurator

2. Install required packages:

pip install -r requirements.txt

🎮 Usage

1. Start the application:

streamlit run main.py

2. Open your web browser and navigate to the provided URL

3. In the application:

   • Enter your API keys of your Tavily and LLM Provider in the sidebar configuration
   • Type your query in the text area (e.g., "Latest AI agents")
   • Click "Generate News Letter" to create your newsletter
   • Copy or save the generated News Letter

💡 Example Queries

• "Latest developments in AI agents"
• "Recent breakthroughs in machine learning"
• "AI startup news this week"
• "New AI tools and applications"

🏗️ Project Structure

ai-newsletter-generator/
├── agents/                 # Agent implementations for different tasks
│   └── Agents.py          # Core agent classes (NewsSearcher, Summarizer, Publisher)
├── graphs/                 # Workflow definitions
│   └── graph.py           # Main workflow graph configuration
├── models/                # LLM model implementations
│   ├── openai_models.py   # OpenAI integration
│   ├── ollama_models.py   # Ollama integration
│   └── ...                # Other model integrations
├── states/                # State management
│   └── state.py          # Workflow state definitions
├── prompts/               # Prompt templates
│   └── prompts.py        # System prompts for agents
├── utils/                 # Helper utilities
├── config/               # Configuration files
├── main.py               # Main Streamlit application
└── requirements.txt      # Project dependencies

🔧 Configuration Options

• LLM Provider: Choose between different language model providers (currently OpenAI active)
• Model: Select specific model (e.g., GPT-4, GPT-3.5-turbo)
• Temperature: Adjust creativity level (0.0 - 1.0)
• API Keys: Securely store your Tavily and LLM provider API keys

🔜 Future Improvements

1. Additional LLM Providers

   • Integration with Ollama
   • Support for VLLM
   • Claude and Gemini implementations

2. Enhanced Features

   • Custom newsletter templates
   • Scheduled report generation
   • Email distribution capability
   • PDF export option

3. UI Enhancements

   • Dark/light mode toggle
   • Mobile-responsive design
   • Custom styling options
   • Report history view

4. Advanced Configuration

   • Custom search parameters
   • Multiple source filtering
   • Language selection
   • Category-based filtering

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

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

📄 License

This project is licensed under the Apache 2.0 License - see the LICENSE file for details.

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Made with ❤️ by passionate AI Engineers