PLAN.md

OpenCode Research Query Website - Project Plan

Project Overview

A research and query website that leverages OpenCode's capabilities as the backend engine, providing intelligent web search and data visualization capabilities. The system combines the power of AI coding agents with web search functionality to deliver research results through an intuitive web interface.

Architecture Design

Core Components

1. Backend Service (OpenCode) - AI agent core for processing queries and performing research
2. Web Interface (OpenCode Web) - Browser-based frontend provided by OpenCode's built-in web server
3. Custom Frontend Layer - Additional UI extensions built for research data visualization
4. Data Processing Layer - Transformation and analysis of research results
5. Storage Layer - Session management, query history, and saved research

Technical Stack

Backend

• OpenCode AI Agent (terminal/web interface)
• Node.js ecosystem
• Local LLM providers (optional)
• API server for custom frontend integration
• Web server with CORS support

Frontend

• React or similar framework
• OpenCode's built-in web interface (customized)
• Visualization libraries (D3.js, Chart.js, or similar)
• Real-time data updates
• Responsive design

Infrastructure

• Local deployment (this machine)
• Node.js runtime
• File system for project data
• Optional: database for persistent storage (SQLite, JSON files)

Project Implementation Plan

Phase 1: Foundation Setup (Week 1)

Tasks:

1. Install and configure OpenCode locally

   curl -fsSL https://opencode.ai/install | bash
   cd opencode-research-project
   opencode
   /init

2. Set up project directory structure

   opencode-research/
   ├── backend/
   │   ├── config/
   │   ├── sessions/
   │   └── scripts/
   ├── frontend/
   │   ├── components/
   │   ├── pages/
   │   └── public/
   └── data/
       ├── queries/
       └── results/
   

3. Configure OpenCode web server

   • Set custom port (e.g., 4096)
   • Configure CORS for custom frontend
   • Set authentication credentials

   opencode web --port 4096 --cors https://localhost:3000

4. Create custom tools and scripts for research workflows

Phase 2: Backend Development (Week 2-3)

Tasks:

1. Custom Research Tools

   • Web search integration scripts
   • Data extraction modules
   • Analysis template scripts
   • Citation and reference handling

2. Session Management

   • Auto-initialization for research queries
   • Query pattern recognition
   • Result storage and organization
   • Session history tracking

3. API Integration

   • REST API endpoints for custom frontend
   • WebSocket support for real-time updates
   • Query parameter processing
   • Result formatting and transformation

4. OpenCode Configuration

   {
     "research-queries": {
       "default": "Analyze and synthesize findings from web search results",
       "citation-format": "APA",
       "max-depth": 3,
       "include-graphics": true
     }
   }

Phase 3: Frontend Development (Week 4-5)

Tasks:

1. Core UI Components

   • Search input interface
   • Query history panel
   • Real-time result display
   • Result filtering and sorting
   • Visual data presentation

2. Visualization Features

   • Trend analysis charts
   • Keyword frequency graphs
   • Source credibility indicators
   • Comparative data tables
   • Network relationships mapping

3. Data Display Components

   • Results cards with rich formatting
   • Progress indicators for ongoing searches
   • Export options (PDF, JSON, CSV)
   • Save and bookmark functionality

4. User Experience

   • Responsive design for all devices
   • Dark/light mode support
   • Keyboard shortcuts
   • Loading states and error handling

Phase 4: Integration Testing (Week 6)

Tasks:

1. End-to-End Testing

   • Query submission → OpenCode processing → Frontend display
   • Multiple session management
   • File system operations
   • API rate limiting

2. Performance Optimization

   • Query response time monitoring
   • Session state management
   • Frontend rendering optimization
   • Server resource utilization

3. Security Testing

   • Authentication verification
   • CORS configuration review
   • Input validation
   • Session expiration

Phase 5: Deployment and Launch (Week 7)

Tasks:

1. Final Configuration

   • Production environment setup
   • Backup and recovery procedures
   • Documentation creation
   • User guide and tutorials

2. Launch Preparation

   • System availability testing
   • Performance benchmarks
   • Error handling verification
   • Backup process testing

3. Live Deployment

   • Start web server
   • Verify frontend connectivity
   • Monitor initial queries
   • Collect user feedback

Key Features

Advanced Research Features

• Smart Query Processing: OpenCode analyzes and decomposes complex research questions
• Multi-Source Aggregation: Collects data from multiple web sources systematically
• Contextual Analysis: Maintains query context across multiple search iterations
• Automated Summarization: Generates comprehensive research summaries
• Source Evaluation: Assesses and ranks information credibility

Visualization Capabilities

• Temporal Data Charts: Timeline visualization of research topics
• Keyword Clusters: Semantic relationships between concepts
• Confidence Heatmaps: Visualization of data reliability and uncertainty
• Comparative Analysis: Side-by-side evaluation of different query approaches

User Interface Features

• Session Management: Multiple concurrent research sessions
• Real-time Feedback: Progress indicators and status updates
• Export Functions: Multiple format options for research results
• History Tracking: Complete query and result history
• Custom Workflows: Adaptable query templates and research patterns

OpenCode Integration Highlights

Leveraged Capabilities

• Session Management: Multiple concurrent research sessions
• Multi-Agent Support: Parallel research threads
• Plan Mode: Feature planning before execution
• Error Recovery: Automatic retry and undo mechanisms
• Custom Tools: Specialized research function implementations
• Code/Analysis Templates: Pre-built research logic patterns

Configuration Strategy

1. Research-Specific Agents: Custom agents for different research types
2. Model Selection: Optimized LLMs for analytical tasks
3. Tool Integration: Web scraping, data extraction, and analysis tools
4. Rule-Based Processing: Content filtering and quality assessment
5. Skill Systems: Pre-programmed research methodologies

Implementation Details

Custom Tools Development

• web-search-tool.js: Advanced search query generation and execution
• data-extractor.js: Structured data extraction from web pages
• citation-generator.js: Automatic citation formatting
• quality-assessor.js: Source reliability evaluation
• summarizer.js: Research result processing and synthesis

Session Structure

Session {
  id: string,
  query: string,
  timestamp: Date,
  agent: 'researcher-001',
  status: 'active' | 'completed' | 'failed',
  currentPhase: ['analysis' | 'search' | 'extraction' | 'synthesis'],
  results: [Result],
  metadata: {
    sources: number,
    processingTime: number,
    confidenceScore: number
  }
}

API Endpoints

POST /api/query - Submit new research query
GET /api/history/ - Retrieve query history
GET /api/result/{id} - Get specific result details
POST /api/export - Export results in various formats
GET /api/sessions - List active sessions

Monitoring and Maintenance

Performance Metrics

• Query response time tracking
• Server resource utilization
• Frontend rendering performance
• Session success/failure rates
• Data storage utilization

Maintenance Activities

• Regular software updates
• OpenCode version upgrades
• Custom tool debugging
• Frontend UI improvements
• Configuration optimization

Security Considerations

Local Deployment Benefits

• No network exposure for development
• Complete data privacy on local machine
• Customized security configurations
• No third-party data sharing

Security Features

• Optional password authentication
• CORS restrictions
• Input sanitization for user queries
• Regular session cleanup

Future Enhancements

1. Advanced Analysis

   • Natural language query interpretation
   • Machine learning-based result ranking
   • Multi-language research capabilities
   • Domain-specific knowledge bases

2. Collaboration Features

   • Shareable research sessions
   • Team research workflows
   • Collaborative editing of results
   • Annotation and commenting system

3. Integration Extensions

   • Direct integration with academic databases
   • Database-specific research tools
   • Citation manager integration
   • Publishing export capabilities

Success Criteria

Functional Requirements

• Query processing within 30 seconds for complex questions
• Support for 10+ concurrent research sessions
• Visualization for 3+ different data types
• Export functionality for 3+ output formats

Performance Targets

• Frontend response time < 100ms for data updates
• Server uptime > 99%
• Memory usage < 4GB under normal operation
• Storage capacity for 1000+ research projects

User Experience Goals

• Intuitive query interface for non-technical users
• Clear visual feedback throughout research process
• Accessible design for users with disabilities
• Cross-device compatibility

Budget and Resource Requirements

Hardware

• CPU: Modern processor (4+ cores recommended)
• RAM: 8GB minimum, 16GB recommended
• Storage: 20GB free space for projects and data
• Network: Local network access for optional scanning

Software Costs

• OpenCode: Free and open source
• LLM Provider: Free models included, paid optional
• Development Tools: Free and open source (VS Code, etc.)
• Database: Optional free alternatives (SQLite, JSON)

Time Investment

• Phase 1: 1 week
• Phase 2: 2 weeks
• Phase 3: 2 weeks
• Phase 4: 1 week
• Phase 5: 1 week Total: 7 weeks (asynchronous development possible)

Risk Assessment and Mitigation

Technical Risks

• LLM Performance Variability: Mitigated using reliable open source models or paid providers
• Web Scraping Limits: Addressed through rate limiting and ethical scraping practices
• Frontend Integration Complexity: Minimized using established patterns and OpenCode's built-in APIs

Resource Limitations

• Local Server Capacity: Managed through session quotas and result filtering
• Storage Space: Controlled through automated cleanup and result archiving
• Multi-session Performance: Optimized through connection pooling and efficient data handling

Mitigation Strategies

• Regular backup and version control
• Comprehensive error handling and logging
• Graceful degradation for non-critical features
• User training and documentation

Project Timeline

Week 1: Foundation Setup

• OpenCode installation and configuration
• Project structure setup
• Basic tooling configuration

Week 2: Backend Development - Part 1

• Custom research tools implementation
• Session management system
• Basic API structure

Week 3: Backend Development - Part 2

• Advanced research features
• Data processing pipeline
• Quality assessment tools

Week 4: Frontend Development - Part 1

• Core UI components
• Search interface
• Basic visualization

Week 5: Frontend Development - Part 2

• Advanced visualizations
• User experience enhancements
• Export functionality

Week 6: Integration Testing

• Testing all components
• Performance optimization
• Security reviews

Week 7: Launch and Documentation

• Final deployment
• Documentation completion
• User training

Conclusion

This research query website leverages OpenCode's powerful AI capabilities while maintaining full control through local deployment. The integrated approach combines OpenCode's analytical intelligence with custom-built frontend visualization, creating a powerful research tool for students, researchers, and professionals. The modular architecture allows for incremental development and easy feature enhancements as new capabilities become available.