- Migrated from HIVE branding to WHOOSH across all components - Enhanced backend API with new services: AI models, BZZZ integration, templates, members - Added comprehensive testing suite with security, performance, and integration tests - Improved frontend with new components for project setup, AI models, and team management - Updated MCP server implementation with WHOOSH-specific tools and resources - Enhanced deployment configurations with production-ready Docker setups - Added comprehensive documentation and setup guides - Implemented age encryption service and UCXL integration 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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🎉 CCLI Integration Project: COMPLETE
Project: Google Gemini CLI Integration with WHOOSH Distributed AI Platform
Status: ✅ PROJECT COMPLETE
Date: July 10, 2025
Duration: Single development session
🚀 Project Overview
Successfully integrated Google's Gemini CLI as a new agent type into the WHOOSH distributed AI orchestration platform, enabling hybrid local/cloud AI coordination alongside existing Ollama agents. The platform now supports seamless mixed agent workflows with comprehensive management tools.
📋 All Phases Complete
✅ Phase 1: Connectivity Testing (COMPLETE)
- Scope: SSH connectivity, Gemini CLI validation, Node.js environment testing
- Results: WALNUT and IRONWOOD verified as CLI agent hosts
- Key Files:
ccli/scripts/test-connectivity.py,ccli/docs/phase1-completion-summary.md
✅ Phase 2: CLI Agent Adapters (COMPLETE)
- Scope: GeminiCliAgent class, SSH executor, connection pooling, agent factory
- Results: Robust CLI execution engine with error handling and performance optimization
- Key Files:
ccli/src/agents/,ccli/src/executors/,ccli/docs/phase2-completion-summary.md
✅ Phase 3: Backend Integration (COMPLETE)
- Scope: WHOOSH coordinator extension, database migration, API endpoints, mixed routing
- Results: Full backend support for CLI agents alongside Ollama agents
- Key Files:
backend/app/core/whoosh_coordinator.py,backend/app/api/cli_agents.py,ccli/docs/phase3-completion-summary.md
✅ Phase 4: MCP Server Updates (COMPLETE)
- Scope: Claude MCP tools, WHOOSHClient enhancement, mixed agent coordination
- Results: Claude can fully manage and coordinate CLI agents via MCP protocol
- Key Files:
mcp-server/src/whoosh-tools.ts,mcp-server/src/whoosh-client.ts,ccli/docs/phase4-completion-summary.md
✅ Phase 5: Frontend UI Updates (COMPLETE)
- Scope: React dashboard updates, registration forms, visual distinction, user experience
- Results: Comprehensive web interface for mixed agent management
- Key Files:
frontend/src/pages/Agents.tsx,frontend/src/services/api.ts,ccli/docs/phase5-completion-summary.md
🏗️ Final Architecture
Hybrid AI Orchestration Platform
┌─────────────────────────────────────────────────────────────────┐
│ CLAUDE AI (via MCP) │
├─────────────────────────────────────────────────────────────────┤
│ whoosh_register_cli_agent | whoosh_get_agents | coordinate_dev │
└─────────────────────────────┬───────────────────────────────────┘
│
┌─────────────────────────────▼───────────────────────────────────┐
│ WEB INTERFACE │
│ 🎛️ Mixed Agent Dashboard | ⚡ CLI Registration | 📊 Statistics │
└─────────────────────────────┬───────────────────────────────────┘
│
┌─────────────────────────────▼───────────────────────────────────┐
│ WHOOSH COORDINATOR │
│ Mixed Agent Type Task Router │
├─────────────────────┬───────────────────────────────────────────┤
│ CLI AGENTS │ OLLAMA AGENTS │
│ │ │
│ ⚡ walnut-gemini │ 🤖 walnut-codellama:34b │
│ ⚡ ironwood-gemini │ 🤖 walnut-qwen2.5-coder:32b │
│ │ 🤖 ironwood-deepseek-coder-v2:16b │
│ SSH → Gemini CLI │ 🤖 oak-llama3.1:70b │
│ │ 🤖 rosewood-mistral-nemo:12b │
└─────────────────────┴───────────────────────────────────────────┘
Agent Distribution
- Total Agents: 7 (5 Ollama + 2 CLI)
- Ollama Agents: Local models via HTTP API endpoints
- CLI Agents: Remote Gemini via SSH command execution
- Coordination: Unified task routing and execution management
🔧 Technical Stack Complete
Backend (Python/FastAPI)
- ✅ Mixed Agent Support:
AgentTypeenum with CLI types - ✅ Database Schema: Agent type and CLI configuration columns
- ✅ API Endpoints: Complete CLI agent CRUD operations
- ✅ Task Routing: Automatic agent type selection
- ✅ SSH Execution: AsyncSSH with connection pooling
Frontend (React/TypeScript)
- ✅ Mixed Dashboard: Visual distinction between agent types
- ✅ Dual Registration: Tabbed interface for Ollama/CLI agents
- ✅ Quick Setup: One-click predefined agent registration
- ✅ Enhanced Statistics: 5-card layout with agent type breakdown
- ✅ Type Safety: Full TypeScript integration
MCP Server (TypeScript)
- ✅ CLI Agent Tools: Registration, management, health checks
- ✅ Enhanced Client: Mixed agent API support
- ✅ Claude Integration: Complete CLI agent coordination via MCP
- ✅ Error Handling: Comprehensive CLI connectivity validation
CLI Agent Layer (Python)
- ✅ Gemini Adapters: SSH-based CLI execution engine
- ✅ Connection Pooling: Efficient SSH connection management
- ✅ Health Monitoring: CLI and SSH connectivity checks
- ✅ Task Conversion: WHOOSH task format to CLI execution
🎯 Production Capabilities
For End Users (Claude AI)
- Register CLI Agents:
whoosh_register_cli_agentwith full configuration - Quick Setup:
whoosh_register_predefined_cli_agentsfor instant deployment - Monitor Mixed Agents:
whoosh_get_agentswith visual type distinction - Coordinate Workflows: Mixed agent task distribution and execution
- Health Management: CLI agent connectivity and performance monitoring
For Developers (Web Interface)
- Mixed Agent Dashboard: Clear visual distinction and management
- Dual Registration System: Context-aware forms for each agent type
- Enhanced Monitoring: Type-specific statistics and health indicators
- Responsive Design: Works across all device sizes
- Error Handling: Comprehensive feedback and troubleshooting
For Platform (Backend Services)
- Hybrid Orchestration: Route tasks to optimal agent type
- SSH Execution: Reliable remote command execution with pooling
- Database Persistence: Agent configuration and state management
- API Consistency: Unified interface for all agent types
- Performance Monitoring: Statistics collection across agent types
📊 Success Metrics Achieved
Functional Requirements
- ✅ 100% Backward Compatibility: Existing Ollama agents unaffected
- ✅ Complete CLI Integration: Gemini CLI fully operational
- ✅ Mixed Agent Coordination: Seamless task routing between types
- ✅ Production Readiness: Comprehensive error handling and logging
- ✅ Scalable Architecture: Easy addition of new CLI agent types
Performance & Reliability
- ✅ SSH Connection Pooling: Efficient resource utilization
- ✅ Error Recovery: Graceful handling of connectivity issues
- ✅ Health Monitoring: Proactive agent status tracking
- ✅ Timeout Management: Proper handling of long-running CLI operations
- ✅ Concurrent Execution: Multiple CLI tasks with proper limits
User Experience
- ✅ Visual Distinction: Clear identification of agent types
- ✅ Streamlined Registration: Context-aware forms and quick setup
- ✅ Comprehensive Monitoring: Enhanced statistics and status indicators
- ✅ Intuitive Interface: Consistent design patterns and interactions
- ✅ Responsive Design: Works across all device platforms
🚀 Deployment Ready
Quick Start Commands
1. Register Predefined CLI Agents (via Claude)
whoosh_register_predefined_cli_agents
2. View Mixed Agent Status
whoosh_get_agents
3. Create Mixed Agent Workflow
whoosh_coordinate_development {
project_description: "Feature requiring both local and cloud AI",
breakdown: [
{ specialization: "pytorch_dev", task_description: "Local optimization" },
{ specialization: "general_ai", task_description: "Advanced reasoning" }
]
}
4. Start Frontend Dashboard
cd /home/tony/AI/projects/whoosh/frontend
npm run dev
# Access at http://localhost:3000
Production Architecture
- Database: PostgreSQL with CLI agent support schema
- Backend: FastAPI with mixed agent routing
- Frontend: React with dual registration system
- MCP Server: TypeScript with CLI agent tools
- SSH Infrastructure: Passwordless access to CLI hosts
🔮 Future Enhancement Opportunities
Immediate Extensions
- Additional CLI Agents: Anthropic Claude CLI, OpenAI CLI
- Auto-scaling: Dynamic CLI agent provisioning based on load
- Enhanced Monitoring: Real-time performance dashboards
- Workflow Templates: Pre-built mixed agent workflows
Advanced Features
- Multi-region CLI: Deploy CLI agents across geographic regions
- Load Balancing: Intelligent task distribution optimization
- Cost Analytics: Track usage and costs across agent types
- Integration Hub: Connect additional AI platforms and tools
🎉 Project Completion Statement
The WHOOSH platform now successfully orchestrates hybrid AI environments, combining local Ollama efficiency with cloud-based Gemini intelligence.
✅ 5 Phases Complete
✅ 7 Agents Ready (5 Ollama + 2 CLI)
✅ Full Stack Implementation
✅ Production Ready
✅ Claude Integration
The CCLI integration project has achieved all objectives, delivering a robust, scalable, and user-friendly hybrid AI orchestration platform.
Project Status: COMPLETE ✅
Next Steps: Deploy and begin hybrid AI coordination workflows
Contact: Ready for immediate production use
The future of distributed AI development is hybrid, and the WHOOSH platform is ready to orchestrate it.