ResearchBridge is an innovative research platform developed for the Hypermode Knowledge Graph + AI Challenge. It empowers researchers with real-time collaboration tools, advanced citation management, and AI-powered research assistance.

• Streamline academic research workflow through AI-assisted paper analysis
• Enable real-time collaboration between researchers
• Provide intelligent citation network visualization and management
• Offer contextual research suggestions and gap analysis
• Create a knowledge graph of research papers and their relationships

Youtube Link - https://www.youtube.com/watch?v=FGaYIt-YvlQ

Devpost Link - https://devpost.com/software/researchbridge

Main dashboard showing the project interface

Workflow diagram explaining the system architecture

Real-time collaborative text editor interface

AI-powered research assistant integrated with Modus

User profile and research management page

The project is built using a modern tech stack:

• Frontend: React with TypeScript
• Backend: Go with WebSocket support
• AI Integration: Google's Gemini Pro API via Modus Framework
• Knowledge Graph: Neo4j for citation network analysis
• Real-time Collaboration: WebSocket-based communication

1. Gemini Pro Integration

   • Implemented through Modus Framework for research analysis
   • Provides paper summaries, methodology analysis, and research gaps identification
   • Generates contextual research suggestions and related topics
   • Analyzes research impact and limitations

2. Citation Analysis

   • Uses Google Scholar API integration for citation data
   • Tracks citation metrics and impact factors
   • Generates citation networks and relationship graphs

The project utilizes Neo4j as the primary knowledge graph database to:

• Store and analyze paper relationships
• Track citation networks and academic influence
• Identify research clusters and emerging topics
• Enable graph-based paper recommendations

The Modus Framework is used to:

• Manage AI service connections
• Handle authentication and API key management
• Provide structured endpoints for AI interactions
• Enable seamless integration with Gemini Pro API

• Real-time collaborative text editor with multi-user support
• Advanced citation network visualization
• AI-powered research assistant integration
• WebSocket-based real-time communication
• Modern, intuitive user interface with exceptional UX design
• Seamless document management and version control

Before running the project, ensure you have:

• Node.js (v14 or higher)
• Go (v1.16 or higher)
• npm or yarn package manager
• Neo4j Database
• Google Cloud API credentials for Gemini Pro
• SERP API key for Google Scholar integration

cd frontend
npm install

cd backend
npm install

cd citation-network
go mod tidy

Create a .env file in the citation-network directory with:

MODUS_GEMINI_API_KEY=your_gemini_api_key
SERP_API_KEY=your_serp_api_key
NEO4J_URI=your_neo4j_uri
NEO4J_USER=your_neo4j_user
NEO4J_PASSWORD=your_neo4j_password

1. Start Neo4j database
2. Run the citation network service:

cd citation-network
go run .

3. WebSocket Server

cd backend
node websocket-server.js

WebSocket connections at ws://localhost:8080

4. Start the backend server:

cd backend
npm run start

5. Launch the frontend:

cd frontend
npm run dev

Contributions are welcome! Please read our contributing guidelines and submit pull requests for any enhancements.

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