Files
hive/docs/project-complete.md
anthonyrawlins 6933a6ccb1 Add CCLI (CLI agent integration) complete implementation
- Complete Gemini CLI agent adapter with SSH execution
- CLI agent factory with connection pooling
- SSH executor with AsyncSSH for remote CLI execution
- Backend integration with CLI agent manager
- MCP server updates with CLI agent tools
- Frontend UI updates for mixed agent types
- Database migrations for CLI agent support
- Docker deployment with CLI source integration
- Comprehensive documentation and testing

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-07-10 12:45:43 +10:00

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# 🎉 CCLI Integration Project: COMPLETE
**Project**: Google Gemini CLI Integration with Hive 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 Hive 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**: Hive coordinator extension, database migration, API endpoints, mixed routing
- **Results**: Full backend support for CLI agents alongside Ollama agents
- **Key Files**: `backend/app/core/hive_coordinator.py`, `backend/app/api/cli_agents.py`, `ccli/docs/phase3-completion-summary.md`
### ✅ **Phase 4: MCP Server Updates (COMPLETE)**
- **Scope**: Claude MCP tools, HiveClient enhancement, mixed agent coordination
- **Results**: Claude can fully manage and coordinate CLI agents via MCP protocol
- **Key Files**: `mcp-server/src/hive-tools.ts`, `mcp-server/src/hive-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) │
├─────────────────────────────────────────────────────────────────┤
│ hive_register_cli_agent | hive_get_agents | coordinate_dev │
└─────────────────────────────┬───────────────────────────────────┘
┌─────────────────────────────▼───────────────────────────────────┐
│ WEB INTERFACE │
│ 🎛️ Mixed Agent Dashboard | ⚡ CLI Registration | 📊 Statistics │
└─────────────────────────────┬───────────────────────────────────┘
┌─────────────────────────────▼───────────────────────────────────┐
│ HIVE 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**: `AgentType` enum 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**: Hive task format to CLI execution
## 🎯 **Production Capabilities**
### **For End Users (Claude AI)**
- **Register CLI Agents**: `hive_register_cli_agent` with full configuration
- **Quick Setup**: `hive_register_predefined_cli_agents` for instant deployment
- **Monitor Mixed Agents**: `hive_get_agents` with 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)**
```
hive_register_predefined_cli_agents
```
#### **2. View Mixed Agent Status**
```
hive_get_agents
```
#### **3. Create Mixed Agent Workflow**
```
hive_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**
```bash
cd /home/tony/AI/projects/hive/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 Hive 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 Hive platform is ready to orchestrate it.*