implementation_templates.json

{
  "orchestrator_example": "\n# Multi-Agent Orchestrator Implementation\nimport asyncio\nfrom typing import Dict, List, Any, Optional\nfrom dataclasses import dataclass\nfrom enum import Enum\nimport json\nimport logging\n\nclass AgentType(Enum):\n    GPT5 = \"gpt5\"\n    CLAUDE_SONNET = \"claude_sonnet\"\n    GEMINI_2_5_PRO = \"gemini_2_5_pro\"\n    GROK_4 = \"grok_4\"\n\n@dataclass\nclass AgentResult:\n    agent_type: AgentType\n    result: Any\n    confidence: float\n    execution_time: float\n    metadata: Dict[str, Any]\n\nclass MultiAgentOrchestrator:\n    def __init__(self, config: Dict[str, Any]):\n        self.config = config\n        self.agents = self._initialize_agents()\n        self.logger = logging.getLogger(__name__)\n\n    def _initialize_agents(self) -> Dict[AgentType, Any]:\n        \"\"\"Initialize all agent instances based on configuration\"\"\"\n        agents = {}\n        for model_key, model_config in self.config[\"models\"].items():\n            agent_type = AgentType(model_key)\n            agents[agent_type] = self._create_agent(agent_type, model_config)\n        return agents\n\n    async def execute_parallel(self, task: Dict[str, Any]) -> List[AgentResult]:\n        \"\"\"Execute task across multiple agents in parallel\"\"\"\n        selected_agents = self._select_agents_for_task(task)\n\n        # Create async tasks for each agent\n        tasks = []\n        for agent_type in selected_agents:\n            agent_task = self._create_agent_task(agent_type, task)\n            tasks.append(agent_task)\n\n        # Execute in parallel with timeout\n        try:\n            results = await asyncio.wait_for(\n                asyncio.gather(*tasks, return_exceptions=True),\n                timeout=task.get(\"timeout\", 300)\n            )\n            return self._process_results(results)\n        except asyncio.TimeoutError:\n            self.logger.error(\"Task execution timed out\")\n            return []\n\n    async def consensus_building(self, results: List[AgentResult]) -> AgentResult:\n        \"\"\"Build consensus from multiple agent results\"\"\"\n        if not results:\n            raise ValueError(\"No results to build consensus from\")\n\n        # Weighted voting based on confidence scores\n        weighted_results = []\n        total_weight = 0\n\n        for result in results:\n            weight = result.confidence\n            weighted_results.append((result, weight))\n            total_weight += weight\n\n        # Select highest confidence result or create synthesis\n        if len(results) == 1:\n            return results[0]\n\n        return self._synthesize_results(weighted_results, total_weight)\n\n    def _select_agents_for_task(self, task: Dict[str, Any]) -> List[AgentType]:\n        \"\"\"Select appropriate agents based on task requirements\"\"\"\n        task_type = task.get(\"type\", \"general\")\n\n        # Default selection logic - customize based on needs\n        agent_mapping = {\n            \"planning\": [AgentType.GPT5],\n            \"analysis\": [AgentType.CLAUDE_SONNET, AgentType.GEMINI_2_5_PRO],\n            \"research\": [AgentType.GEMINI_2_5_PRO, AgentType.GROK_4],\n            \"coding\": [AgentType.CLAUDE_SONNET, AgentType.GPT5],\n            \"general\": list(AgentType)\n        }\n\n        return agent_mapping.get(task_type, [AgentType.GPT5])\n\n# Usage Example\nasync def main():\n    # Load configuration\n    with open(\"multi_agent_labs_strategy.json\", \"r\") as f:\n        config = json.load(f)\n\n    # Initialize orchestrator\n    orchestrator = MultiAgentOrchestrator(config)\n\n    # Example task\n    task = {\n        \"type\": \"coding\",\n        \"description\": \"Create a REST API for user management\",\n        \"requirements\": [\"authentication\", \"CRUD operations\", \"validation\"],\n        \"timeout\": 300\n    }\n\n    # Execute parallel processing\n    results = await orchestrator.execute_parallel(task)\n\n    # Build consensus\n    final_result = await orchestrator.consensus_building(results)\n\n    print(f\"Final result: {final_result}\")\n\nif __name__ == \"__main__\":\n    asyncio.run(main())\n",
  "fastapi_backend": "\n# FastAPI Backend for Multi-Agent System\nfrom fastapi import FastAPI, WebSocket, HTTPException, BackgroundTasks\nfrom fastapi.middleware.cors import CORSMiddleware\nfrom pydantic import BaseModel\nfrom typing import Dict, List, Any, Optional\nimport asyncio\nimport json\nimport uuid\nfrom datetime import datetime\n\napp = FastAPI(title=\"Multi-Agent Labs API\", version=\"1.0.0\")\n\n# Add CORS middleware\napp.add_middleware(\n    CORSMiddleware,\n    allow_origins=[\"http://localhost:3000\"],  # Next.js dev server\n    allow_credentials=True,\n    allow_methods=[\"*\"],\n    allow_headers=[\"*\"],\n)\n\n# Pydantic models\nclass TaskRequest(BaseModel):\n    type: str\n    description: str\n    requirements: List[str] = []\n    agents: Optional[List[str]] = None\n    parallel: bool = True\n    timeout: int = 300\n\nclass TaskResponse(BaseModel):\n    task_id: str\n    status: str\n    results: List[Dict[str, Any]] = []\n    consensus: Optional[Dict[str, Any]] = None\n    created_at: datetime\n    completed_at: Optional[datetime] = None\n\n# In-memory storage (use Redis/DB in production)\nactive_tasks: Dict[str, TaskResponse] = {}\ntask_results: Dict[str, List[Dict[str, Any]]] = {}\n\n@app.post(\"/api/tasks\", response_model=TaskResponse)\nasync def create_task(task: TaskRequest, background_tasks: BackgroundTasks):\n    \"\"\"Create and execute a new multi-agent task\"\"\"\n    task_id = str(uuid.uuid4())\n\n    # Create task response\n    task_response = TaskResponse(\n        task_id=task_id,\n        status=\"running\",\n        created_at=datetime.now()\n    )\n\n    active_tasks[task_id] = task_response\n\n    # Execute task in background\n    background_tasks.add_task(execute_multi_agent_task, task_id, task)\n\n    return task_response\n\n@app.get(\"/api/tasks/{task_id}\", response_model=TaskResponse)\nasync def get_task_status(task_id: str):\n    \"\"\"Get status of a specific task\"\"\"\n    if task_id not in active_tasks:\n        raise HTTPException(status_code=404, detail=\"Task not found\")\n\n    return active_tasks[task_id]\n\n@app.get(\"/api/tasks\", response_model=List[TaskResponse])\nasync def list_tasks():\n    \"\"\"List all tasks\"\"\"\n    return list(active_tasks.values())\n\n@app.websocket(\"/ws/{task_id}\")\nasync def websocket_endpoint(websocket: WebSocket, task_id: str):\n    \"\"\"WebSocket for real-time task updates\"\"\"\n    await websocket.accept()\n\n    try:\n        while True:\n            if task_id in active_tasks:\n                task_status = active_tasks[task_id]\n                await websocket.send_json({\n                    \"task_id\": task_id,\n                    \"status\": task_status.status,\n                    \"timestamp\": datetime.now().isoformat()\n                })\n\n            await asyncio.sleep(1)  # Send updates every second\n\n    except Exception as e:\n        print(f\"WebSocket error: {e}\")\n    finally:\n        await websocket.close()\n\nasync def execute_multi_agent_task(task_id: str, task: TaskRequest):\n    \"\"\"Execute multi-agent task (placeholder implementation)\"\"\"\n    try:\n        # Simulate agent processing\n        await asyncio.sleep(2)  # Simulate processing time\n\n        # Update task status\n        active_tasks[task_id].status = \"completed\"\n        active_tasks[task_id].completed_at = datetime.now()\n        active_tasks[task_id].results = [\n            {\"agent\": \"gpt5\", \"result\": \"Planning completed\", \"confidence\": 0.9},\n            {\"agent\": \"claude_sonnet\", \"result\": \"Code analysis done\", \"confidence\": 0.85},\n        ]\n        active_tasks[task_id].consensus = {\n            \"final_result\": \"Task completed successfully\",\n            \"confidence\": 0.87\n        }\n\n    except Exception as e:\n        active_tasks[task_id].status = \"failed\"\n        print(f\"Task {task_id} failed: {e}\")\n\nif __name__ == \"__main__\":\n    import uvicorn\n    uvicorn.run(app, host=\"0.0.0.0\", port=8000)\n",
  "nextjs_frontend": "\n// Next.js Frontend Component for Multi-Agent Dashboard\n// pages/dashboard.tsx\nimport React, { useState, useEffect } from 'react';\nimport { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';\nimport { Button } from '@/components/ui/button';\nimport { Input } from '@/components/ui/input';\nimport { Badge } from '@/components/ui/badge';\nimport { Loader2, Play, Eye, CheckCircle, XCircle } from 'lucide-react';\n\ninterface Task {\n  task_id: string;\n  status: string;\n  type: string;\n  description: string;\n  created_at: string;\n  completed_at?: string;\n  results: Array<{\n    agent: string;\n    result: string;\n    confidence: number;\n  }>;\n  consensus?: {\n    final_result: string;\n    confidence: number;\n  };\n}\n\ninterface AgentStatus {\n  name: string;\n  status: 'active' | 'idle' | 'error';\n  current_task?: string;\n  performance: number;\n}\n\nexport default function MultiAgentDashboard() {\n  const [tasks, setTasks] = useState<Task[]>([]);\n  const [agents, setAgents] = useState<AgentStatus[]>([\n    { name: 'GPT-5', status: 'idle', performance: 0.92 },\n    { name: 'Claude Sonnet', status: 'idle', performance: 0.88 },\n    { name: 'Gemini 2.5 Pro', status: 'idle', performance: 0.85 },\n    { name: 'Grok 4', status: 'idle', performance: 0.81 }\n  ]);\n\n  const [newTask, setNewTask] = useState({\n    type: 'general',\n    description: '',\n    requirements: ''\n  });\n\n  const [isLoading, setIsLoading] = useState(false);\n\n  // Fetch tasks from API\n  useEffect(() => {\n    fetchTasks();\n    const interval = setInterval(fetchTasks, 5000); // Poll every 5 seconds\n    return () => clearInterval(interval);\n  }, []);\n\n  const fetchTasks = async () => {\n    try {\n      const response = await fetch('/api/tasks');\n      const data = await response.json();\n      setTasks(data);\n    } catch (error) {\n      console.error('Failed to fetch tasks:', error);\n    }\n  };\n\n  const createTask = async () => {\n    if (!newTask.description.trim()) return;\n\n    setIsLoading(true);\n    try {\n      const response = await fetch('/api/tasks', {\n        method: 'POST',\n        headers: { 'Content-Type': 'application/json' },\n        body: JSON.stringify({\n          ...newTask,\n          requirements: newTask.requirements.split(',').map(r => r.trim()).filter(Boolean)\n        })\n      });\n\n      if (response.ok) {\n        setNewTask({ type: 'general', description: '', requirements: '' });\n        fetchTasks();\n      }\n    } catch (error) {\n      console.error('Failed to create task:', error);\n    } finally {\n      setIsLoading(false);\n    }\n  };\n\n  const getStatusColor = (status: string) => {\n    switch (status) {\n      case 'completed': return 'bg-green-500';\n      case 'running': return 'bg-blue-500';\n      case 'failed': return 'bg-red-500';\n      default: return 'bg-gray-500';\n    }\n  };\n\n  const getStatusIcon = (status: string) => {\n    switch (status) {\n      case 'completed': return <CheckCircle className=\"h-4 w-4\" />;\n      case 'running': return <Loader2 className=\"h-4 w-4 animate-spin\" />;\n      case 'failed': return <XCircle className=\"h-4 w-4\" />;\n      default: return <Eye className=\"h-4 w-4\" />;\n    }\n  };\n\n  return (\n    <div className=\"min-h-screen bg-gray-50 p-6\">\n      <div className=\"max-w-7xl mx-auto space-y-6\">\n\n        {/* Header */}\n        <div className=\"text-center\">\n          <h1 className=\"text-3xl font-bold text-gray-900\">Multi-Agent Labs Dashboard</h1>\n          <p className=\"text-gray-600 mt-2\">Orchestrate AI agents across multiple models</p>\n        </div>\n\n        {/* Agent Status Grid */}\n        <div className=\"grid grid-cols-1 md:grid-cols-4 gap-4\">\n          {agents.map((agent) => (\n            <Card key={agent.name}>\n              <CardContent className=\"p-4\">\n                <div className=\"flex items-center justify-between\">\n                  <div>\n                    <h3 className=\"font-semibold\">{agent.name}</h3>\n                    <Badge variant={agent.status === 'active' ? 'default' : 'secondary'}>\n                      {agent.status}\n                    </Badge>\n                  </div>\n                  <div className=\"text-right\">\n                    <div className=\"text-sm text-gray-500\">Performance</div>\n                    <div className=\"font-bold\">{(agent.performance * 100).toFixed(1)}%</div>\n                  </div>\n                </div>\n              </CardContent>\n            </Card>\n          ))}\n        </div>\n\n        {/* Create New Task */}\n        <Card>\n          <CardHeader>\n            <CardTitle>Create New Task</CardTitle>\n          </CardHeader>\n          <CardContent>\n            <div className=\"space-y-4\">\n              <div className=\"grid grid-cols-1 md:grid-cols-2 gap-4\">\n                <div>\n                  <label className=\"block text-sm font-medium mb-2\">Task Type</label>\n                  <select \n                    className=\"w-full p-2 border rounded-md\"\n                    value={newTask.type}\n                    onChange={(e) => setNewTask({...newTask, type: e.target.value})}\n                  >\n                    <option value=\"general\">General</option>\n                    <option value=\"planning\">Planning</option>\n                    <option value=\"analysis\">Analysis</option>\n                    <option value=\"coding\">Coding</option>\n                    <option value=\"research\">Research</option>\n                  </select>\n                </div>\n                <div>\n                  <label className=\"block text-sm font-medium mb-2\">Requirements (comma-separated)</label>\n                  <Input\n                    placeholder=\"authentication, validation, testing\"\n                    value={newTask.requirements}\n                    onChange={(e) => setNewTask({...newTask, requirements: e.target.value})}\n                  />\n                </div>\n              </div>\n\n              <div>\n                <label className=\"block text-sm font-medium mb-2\">Task Description</label>\n                <Input\n                  placeholder=\"Describe what you want the agents to accomplish...\"\n                  value={newTask.description}\n                  onChange={(e) => setNewTask({...newTask, description: e.target.value})}\n                />\n              </div>\n\n              <Button \n                onClick={createTask} \n                disabled={isLoading || !newTask.description.trim()}\n                className=\"w-full md:w-auto\"\n              >\n                {isLoading ? <Loader2 className=\"mr-2 h-4 w-4 animate-spin\" /> : <Play className=\"mr-2 h-4 w-4\" />}\n                Execute Task\n              </Button>\n            </div>\n          </CardContent>\n        </Card>\n\n        {/* Tasks List */}\n        <Card>\n          <CardHeader>\n            <CardTitle>Recent Tasks</CardTitle>\n          </CardHeader>\n          <CardContent>\n            <div className=\"space-y-4\">\n              {tasks.length === 0 ? (\n                <div className=\"text-center text-gray-500 py-8\">\n                  No tasks yet. Create your first task above.\n                </div>\n              ) : (\n                tasks.map((task) => (\n                  <div key={task.task_id} className=\"border rounded-lg p-4 hover:bg-gray-50 transition-colors\">\n                    <div className=\"flex items-start justify-between\">\n                      <div className=\"flex-1\">\n                        <div className=\"flex items-center gap-2 mb-2\">\n                          {getStatusIcon(task.status)}\n                          <Badge className={getStatusColor(task.status)}>{task.status}</Badge>\n                          <Badge variant=\"outline\">{task.type}</Badge>\n                        </div>\n\n                        <h4 className=\"font-medium mb-1\">{task.description}</h4>\n                        <p className=\"text-sm text-gray-500\">\n                          Created: {new Date(task.created_at).toLocaleString()}\n                        </p>\n\n                        {task.results && task.results.length > 0 && (\n                          <div className=\"mt-3\">\n                            <div className=\"text-sm font-medium mb-2\">Agent Results:</div>\n                            <div className=\"space-y-1\">\n                              {task.results.map((result, index) => (\n                                <div key={index} className=\"text-sm bg-gray-100 rounded p-2\">\n                                  <span className=\"font-medium\">{result.agent}:</span> {result.result}\n                                  <span className=\"float-right text-gray-500\">\n                                    {(result.confidence * 100).toFixed(1)}% confidence\n                                  </span>\n                                </div>\n                              ))}\n                            </div>\n                          </div>\n                        )}\n\n                        {task.consensus && (\n                          <div className=\"mt-3 p-3 bg-blue-50 rounded-lg\">\n                            <div className=\"text-sm font-medium text-blue-800 mb-1\">Consensus Result:</div>\n                            <div className=\"text-sm text-blue-700\">{task.consensus.final_result}</div>\n                            <div className=\"text-xs text-blue-600 mt-1\">\n                              Confidence: {(task.consensus.confidence * 100).toFixed(1)}%\n                            </div>\n                          </div>\n                        )}\n                      </div>\n                    </div>\n                  </div>\n                ))\n              )}\n            </div>\n          </CardContent>\n        </Card>\n      </div>\n    </div>\n  );\n}\n",
  "docker_compose": "\n# docker-compose.yml for Multi-Agent System\nversion: '3.8'\n\nservices:\n  # FastAPI Backend\n  backend:\n    build: \n      context: ./backend\n      dockerfile: Dockerfile\n    ports:\n      - \"8000:8000\"\n    environment:\n      - OPENAI_API_KEY=${OPENAI_API_KEY}\n      - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}\n      - GOOGLE_API_KEY=${GOOGLE_API_KEY}\n      - GROK_API_KEY=${GROK_API_KEY}\n      - REDIS_URL=redis://redis:6379\n      - DATABASE_URL=postgresql://user:password@postgres:5432/multiagent\n    depends_on:\n      - redis\n      - postgres\n    volumes:\n      - ./backend:/app\n      - /var/run/docker.sock:/var/run/docker.sock\n    restart: unless-stopped\n\n  # Next.js Frontend\n  frontend:\n    build:\n      context: ./frontend\n      dockerfile: Dockerfile\n    ports:\n      - \"3000:3000\"\n    environment:\n      - NEXT_PUBLIC_API_URL=http://localhost:8000\n    depends_on:\n      - backend\n    volumes:\n      - ./frontend:/app\n      - /app/node_modules\n    restart: unless-stopped\n\n  # Redis for caching and state management\n  redis:\n    image: redis:7-alpine\n    ports:\n      - \"6379:6379\"\n    volumes:\n      - redis_data:/data\n    restart: unless-stopped\n\n  # PostgreSQL for persistent storage\n  postgres:\n    image: postgres:15-alpine\n    ports:\n      - \"5432:5432\"\n    environment:\n      - POSTGRES_USER=user\n      - POSTGRES_PASSWORD=password\n      - POSTGRES_DB=multiagent\n    volumes:\n      - postgres_data:/var/lib/postgresql/data\n    restart: unless-stopped\n\n  # Vector Database (Chroma)\n  chroma:\n    image: chromadb/chroma:latest\n    ports:\n      - \"8001:8000\"\n    volumes:\n      - chroma_data:/chroma/chroma\n    environment:\n      - CHROMA_SERVER_HOST=0.0.0.0\n      - CHROMA_SERVER_HTTP_PORT=8000\n    restart: unless-stopped\n\n  # Monitoring (optional)\n  prometheus:\n    image: prom/prometheus:latest\n    ports:\n      - \"9090:9090\"\n    volumes:\n      - ./monitoring/prometheus.yml:/etc/prometheus/prometheus.yml\n      - prometheus_data:/prometheus\n    restart: unless-stopped\n\nvolumes:\n  redis_data:\n  postgres_data:\n  chroma_data:\n  prometheus_data:\n"
}