README.md

metadata

title: Gpt Oss News Agent
emoji: 🌍
colorFrom: green
colorTo: blue
sdk: gradio
sdk_version: 5.42.0
app_file: app.py
pinned: false
short_description: AI-powered news research assistant with real-time search

📰 AI News Research Assistant

An intelligent AI-powered news research assistant built with Gradio that provides real-time news search, article fetching, and comprehensive summaries using GPT-OSS models.

✨ Features

• Real-time News Search: Access current headlines from Google News RSS feeds
• Topic-specific Research: Search for news on specific subjects, companies, or events
• Site-restricted Search: Limit searches to specific news domains
• Article Content Extraction: Download and analyze full article content when needed
• AI-powered Summaries: Get intelligent news summaries with proper citations
• Multiple Model Support: Choose between GPT-OSS 120B and 20B models
• Modern Web Interface: Clean, responsive Gradio-based chat interface
• Langfuse Integration: Built-in observability and tracing for interactions

🚀 Quick Start

Prerequisites

• Python 3.8+
• API keys for:
  • Hugging Face (HF_TOKEN)
  • Serper API (SERPER_API_KEY)
  • Langfuse (optional, for observability)

Installation

1. Clone the repository

   git clone <your-repo-url>
   cd agent_gradio_app
   

2. Install dependencies

   pip install -r requirements.txt
   

3. Set up environment variables

   # Create .env file
   echo "HF_TOKEN=your_huggingface_token" > .env
   echo "SERPER_API_KEY=your_serper_api_key" >> .env
   echo "LANGFUSE_PUBLIC_KEY=your_langfuse_public_key" >> .env
   echo "LANGFUSE_SECRET_KEY=your_langfuse_secret_key" >> .env
   

4. Run the application

   python agent_gradio_chat.py
   

5. Open your browser Navigate to http://localhost:7860

🔧 Configuration

Available Models

• GPT-OSS 120B: Larger, more capable model for complex reasoning tasks
• GPT-OSS 20B: Faster, more efficient model for quick responses

Environment Variables

Variable	Description	Required
HF_TOKEN	Hugging Face API token	Yes
SERPER_API_KEY	Serper API key for web search	Yes
LANGFUSE_PUBLIC_KEY	Langfuse public key for observability	No
LANGFUSE_SECRET_KEY	Langfuse secret key for observability	No

💡 Usage Examples

General News Requests

• "What are the top news stories today?"
• "What's happening in the world right now?"
• "Show me the latest headlines"

Topic-specific Research

• "What's the latest on artificial intelligence?"
• "Tell me about recent developments in climate change"
• "What's happening with Tesla stock?"

Site-specific Searches

• "What's the latest climate change news on the BBC?"
• "Show me recent AI articles from MIT Technology Review"
• "What's new on Ars Technica about cybersecurity?"

🛠️ How It Works

The application uses a sophisticated agent loop that:

1. Analyzes User Queries: Understands the type of news request
2. Selects Appropriate Tools: Chooses from available search and fetch tools
3. Executes Searches: Performs targeted news searches using various APIs
4. Extracts Content: Downloads and processes article content when needed
5. Synthesizes Information: Provides comprehensive summaries with citations
6. Tracks Interactions: Logs all interactions for observability

Available Tools

• fetch_google_news_rss: Get top headlines from Google News
• serper_news_search: Search for specific topics in Google News
• serper_site_search: Restrict searches to specific domains
• fetch_article: Download and extract article content

📁 Project Structure

agent_gradio_app/
├── agent_gradio_chat.py    # Main application file
├── requirements.txt         # Python dependencies
├── config.json             # Configuration file
├── .env                    # Environment variables (create this)
├── README.md               # This file
└── run_app.sh             # Convenience script to run the app

🔍 API Dependencies

• Hugging Face: Model inference and hosting
• Serper API: Web search capabilities
• Trafilatura: Article content extraction
• Langfuse: Observability and tracing

🚀 Deployment

Local Development

python agent_gradio_chat.py

Production Deployment

# Using the convenience script
chmod +x run_app.sh
./run_app.sh

# Or directly with custom settings
python agent_gradio_chat.py --server-name 0.0.0.0 --server-port 7860

Docker (Optional)

FROM python:3.9-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
EXPOSE 7860
CMD ["python", "agent_gradio_chat.py"]

🧪 Testing

Test the application with various news queries:

# Test basic functionality
python -c "
from agent_gradio_chat import run_agent
response = run_agent('What are the top news stories today?')
print(response)
"

🤝 Contributing

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

📝 License

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

🙏 Acknowledgments

• Gradio for the web interface framework
• Hugging Face for model hosting and inference
• OpenAI for the GPT-OSS models
• Serper for web search capabilities

📞 Support

For issues, questions, or contributions:

• Open an issue on GitHub
• Check the documentation
• Review the code comments for implementation details

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Happy news researching! 🚀📰