README.md

metadata

title: Deep_Research_Assistant
app_file: app.py
sdk: gradio
sdk_version: 5.29.0

🔍 Deep Research Assistant

A comprehensive AI-powered research assistant that delivers high-quality, well-researched reports with built-in quality assurance and email delivery capabilities.

🚀 Features

🤖 Enhanced AI Research System

• Quality Evaluation: Every report is automatically assessed for completeness, accuracy, and clarity
• Smart Optimization: Reports scoring below 7/10 are automatically improved
• Multi-Strategy Search: Uses multiple search approaches for comprehensive coverage
• Email Delivery: Optional email delivery of research reports

🎯 Research Modes

1. 🚀 Interactive Research with Clarification (Recommended)

   • Generates clarifying questions to focus your research
   • Provides more targeted and relevant results
   • Uses the enhanced quality assurance pipeline

2. 🤖 Enhanced Direct Research

   • Advanced AI system with automatic quality evaluation
   • Iterative improvement when needed
   • Full traceability with OpenAI traces

3. ⚡ Quick Research

   • Fast research for simple queries
   • Legacy compatibility mode
   • Good for straightforward questions

🛠️ Setup

Environment Variables

You'll need to set up the following environment variables:

# Required - OpenAI API for research
OPENAI_API_KEY=your_openai_api_key_here

# Optional - SendGrid for email delivery
SENDGRID_API_KEY=your_sendgrid_api_key_here
[email protected]

For Hugging Face Spaces Deployment

1. Fork this space or create a new one
2. Add your secrets in the Space settings:
   • OPENAI_API_KEY: Your OpenAI API key
   • SENDGRID_API_KEY: Your SendGrid API key (optional)
   • SENDGRID_FROM_EMAIL: Your verified sender email (optional)
3. Deploy - The space will automatically install dependencies and launch

For Local Development

1. Clone the repository:

   git clone <your-repo-url>
   cd deep_research
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Set up environment variables:

   cp .env.example .env
   # Edit .env with your API keys
   

4. Run the application:

   python app.py
   

📊 Quality Assurance System

Our enhanced research system includes automatic quality evaluation:

Evaluation Criteria

• Completeness: How thoroughly the query is addressed
• Accuracy: Factual correctness and source reliability
• Clarity: Writing quality and organization
• Depth: Analysis depth and insight quality
• Relevance: Content alignment with the original query

Scoring Scale

• 9-10: Excellent (no refinement needed)
• 7-8: Good (minor improvements)
• 5-6: Adequate (refinement recommended)
• 1-4: Poor (automatic refinement triggered)

🎮 How to Use

1. Enter Your Research Query: Describe what you want to research

2. Configure Email (Optional): Set up email delivery if desired

3. Choose Research Mode:

   • Click "🚀 Start Research" for interactive clarification mode
   • Use "🤖 Enhanced Research" for direct advanced research
   • Use "⚡ Quick Research" for fast results

4. Get Results:

   • View comprehensive research report
   • Receive email delivery (if configured)
   • Access detailed trace logs for transparency

🔧 Technical Architecture

Built with:

• Frontend: Gradio for interactive web interface
• Backend: OpenAI Agents framework for modular AI system
• Quality Assurance: Automated evaluation and optimization pipeline
• Email: SendGrid integration for report delivery
• Tracing: OpenAI trace integration for full transparency

Agent-Based Architecture

The system uses specialized AI agents:

• Research Manager: Orchestrates the entire research process
• Planner Agent: Creates strategic search plans
• Search Agent: Performs web searches
• Writer Agent: Generates comprehensive reports
• Evaluator Agent: Assesses report quality
• Optimizer Agent: Improves reports when needed
• Email Agent: Handles report delivery

📝 Example Queries

Try these example research queries:

• "Latest developments in renewable energy storage technology"
• "Impact of AI on healthcare industry in 2024"
• "Sustainable urban planning strategies for climate change"
• "Cybersecurity trends and threats in financial services"
• "Electric vehicle market analysis and future projections"

🤝 Contributing

We welcome contributions! Areas for improvement:

• Additional research sources and tools
• Enhanced evaluation criteria
• New output formats
• UI/UX improvements
• Performance optimizations

📄 License

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

🙋‍♀️ Support

• Issues: Report bugs or request features via GitHub Issues
• Documentation: Check out the enhanced README in the repository
• Trace Logs: Use the provided trace IDs to debug research processes

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Built with ❤️ using OpenAI Agents, Gradio, and modern AI research techniques.