README.md

---
title: 🤖 ResearchCopilot
emoji: 🔬
colorFrom: indigo
colorTo: purple
sdk: gradio
sdk_version: 5.33.1
app_file: app.py
pinned: true
license: mit
short_description: Multi-agent AI research system
tags:
- agent-demo-track
- multi-agent
- research
- perplexity
- claude
- openai
video_overview: https://youtu.be/SuBUxtBKUvQ
collection: https://huggingface.co/collections/Agents-MCP-Hackathon
---

# 🤖 ResearchCopilot - Multi-Agent Research System

**Track 3: Agentic Demo Showcase - Gradio MCP Hackathon 2025**

A sophisticated multi-agent AI system that demonstrates the power of collaborative AI agents working together to conduct comprehensive research. ResearchCopilot breaks down complex research queries into structured tasks and employs specialized agents to gather, analyze, and synthesize information from multiple sources.

## 🎯 Demo Video
[Link to video demonstration will be added here]

## 🚀 Features

### Multi-Agent Architecture
- **🎯 Planner Agent**: Intelligently breaks down research queries into structured, prioritized tasks
- **🔍 Retriever Agent**: Searches multiple sources (Perplexity API, Google Search, Academic databases)
- **📝 Summarizer Agent**: Analyzes and synthesizes information using Claude/GPT models
- **📚 Citation Agent**: Generates proper academic citations in multiple formats (APA, MLA, Chicago, IEEE, Harvard)

### Key Capabilities
- Real-time collaborative agent orchestration
- Adaptive research planning based on query complexity
- Cross-agent learning and decision making
- Parallel task execution for efficient research
- Professional citation generation
- Comprehensive research documentation

### Technical Highlights
- Built with Gradio for intuitive user experience
- Deployed on Modal for scalable serverless execution
- Asynchronous agent communication
- Real API integrations (Perplexity, Google, Anthropic)
- Comprehensive error handling and fallbacks

## 🏗️ System Architecture

```
┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   User Query    │───▶│   Orchestrator  │───▶│   Results UI    │
└─────────────────┘    └─────────────────┘    └─────────────────┘
                               │
                ┌──────────────┼──────────────┐
                │              │              │
        ┌───────▼───────┐ ┌────▼──────┐ ┌────▼──────┐
        │ Planner Agent │ │ Retriever │ │Summarizer │
        └───────────────┘ │   Agent   │ │   Agent   │
                          └───────────┘ └───────────┘
                                 │             │
                          ┌──────▼──────┐ ┌───▼────────┐
                          │   APIs      │ │ Citation   │
                          │ Perplexity  │ │   Agent    │
                          │   Google    │ └────────────┘
                          │  Academic   │
                          └─────────────┘
```

## 🛠️ Installation & Setup

### Local Development

1. **Clone and Install Dependencies**
```bash
git clone <repository-url>
cd research-copilot
pip install -r requirements.txt
```

2. **Environment Configuration**
```bash
cp .env.example .env
# Edit .env with your API keys
```

3. **Run Locally**
```bash
python research_copilot.py
```

### Modal Deployment

1. **Install Modal**
```bash
pip install modal
modal setup
```

2. **Configure Secrets**
```bash
modal secret create research-copilot-secrets \
  PERPLEXITY_API_KEY=your_key \
  GOOGLE_API_KEY=your_key \
  GOOGLE_SEARCH_ENGINE_ID=your_id \
  ANTHROPIC_API_KEY=your_key
```

3. **Deploy to Modal**
```bash
modal deploy modal_app.py
```

## 🔧 API Keys Required

### Required for Full Functionality
- **Perplexity API**: Real-time search capabilities
- **Google Custom Search API**: Web search functionality  
- **Anthropic Claude API**: Advanced summarization

### Optional
- **OpenAI API**: Alternative summarization
- **Additional APIs**: ArXiv, CrossRef for academic sources

*Note: The system includes comprehensive mock data for demonstration without API keys*

## 💡 Usage Examples

### Basic Research Query
```
"Latest developments in quantum computing for drug discovery"
```

### Comparative Analysis
```
"Compare renewable energy adoption in Europe vs Asia 2024"
```

### Academic Research
```
"Recent peer-reviewed studies on AI bias in healthcare diagnostics"
```

### Technical Analysis
```
"How does blockchain technology improve supply chain transparency"
```

## 🎨 User Interface

The Gradio interface provides:
- **Interactive Research Input**: Natural language query processing with example prompts
- **Real-time Agent Activity**: Live visualization of agent collaboration and decision-making
- **Tabbed Results Display**: 
  - 📊 Summary: Comprehensive research synthesis with key findings
  - 📚 Sources: Detailed source analysis with relevance scoring
  - 📖 Citations: Multi-format academic citations (APA, MLA, Chicago, IEEE, Harvard)
  - 🔍 Process Log: Complete agent activity timeline and reasoning
- **Progress Tracking**: Real-time progress indicators for each research phase
- **Responsive Design**: Works seamlessly across desktop and mobile devices

## 🏆 Hackathon Submission - Track 3

### Innovation Highlights
- **Multi-Agent Orchestration**: Demonstrates sophisticated AI agent collaboration
- **Adaptive Intelligence**: Agents learn from each other and adjust strategies dynamically
- **Real-world Integration**: Production-ready with actual API integrations
- **Scalable Architecture**: Built for real-world deployment and usage

### Demo Scenarios
1. **Academic Research**: "Climate change impact on Arctic biodiversity"
2. **Technology Analysis**: "Comparison of LLM architectures for code generation"
3. **Market Research**: "Sustainable packaging trends in food industry 2025"
4. **Policy Analysis**: "AI regulation frameworks across major economies"

## 📁 Project Structure

```
research-copilot/
├── research_copilot.py      # Main app with full UI and agent system
├── modal_app.py             # Modal deployment configuration  
├── enhanced_agents.py       # Production agents with API integrations
├── requirements.txt         # All dependencies
├── .env.example            # API key template
├── deploy.sh               # One-command deployment
├── README.md               # Comprehensive documentation
└── Project_Structure.md    # This summary
```

## 🧪 Testing

```bash
# Run agent tests
python -m pytest tests/test_agents.py -v

# Run integration tests
python -m pytest tests/test_integration.py -v

# Run UI tests
python -m pytest tests/test_ui.py -v
```

## 🔮 Future Enhancements

### Planned Features
- **Voice Interface**: Natural language voice queries and responses
- **Research Templates**: Pre-configured workflows for different research types
- **Collaborative Research**: Multi-user research sessions with shared workspaces
- **Export Options**: PDF reports, Word documents, presentation slides
- **Advanced Analytics**: Research quality metrics and bias detection
- **Custom Agent Training**: User-specific agent customization and learning

### API Integrations Roadmap
- **ArXiv**: Academic paper search and analysis
- **PubMed**: Medical and life sciences research
- **CrossRef**: DOI resolution and metadata
- **Semantic Scholar**: AI-powered academic search
- **News APIs**: Real-time news aggregation
- **Social Media**: Trend analysis and public sentiment

## 🤝 Contributing

We welcome contributions! Please see our contributing guidelines:

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](LICENSE) file for details.

## 🙏 Acknowledgments

- **Gradio Team**: For the amazing interface framework
- **Modal**: For serverless deployment platform
- **Anthropic**: For Claude API integration
- **Perplexity**: For real-time search capabilities
- **Hackathon Organizers**: For the opportunity to showcase multi-agent AI

## 📞 Contact

- **Team**: ResearchCopilot Development Team
- **Email**: 24f1001493@ds.study.iitm.ac.in
- **Demo**: [Link to live demo]
- **Video**: [Link to demonstration video]

---

**Built for the Gradio Agents & MCP Hackathon 2025 - Track 3: Agentic Demo Showcase**

*Demonstrating the future of AI-powered research through intelligent agent collaboration*