Antigravity マルチエージェントシステム実装ガイド

{
  "task": "Create login form component",
  "requirements": {
    "framework": "React",
    "ui_library": "Material-UI",
    "accessibility": "WCAG 2.1 AA"
  },
  "constraints": {
    "bundle_size_limit": "50KB",
    "render_time": "< 100ms"
  }
}

{
  "component_code": "...",
  "accessibility_report": {
    "wcag_level": "AA",
    "issues": []
  },
  "performance_metrics": {
    "bundle_size": "28KB",
    "render_time": "45ms"
  }
}

{
  "task": "Create user authentication API",
  "requirements": {
    "protocol": "REST",
    "database": "PostgreSQL",
    "auth_method": "JWT"
  }
}

{
  "api_endpoints": [...],
  "database_schema": {...},
  "error_handling": {...}
}

{
  "task": "Generate test suite",
  "target_code": "...",
  "coverage_target": 80
}

{
  "unit_tests": "...",
  "integration_tests": "...",
  "coverage_report": {
    "lines": 82,
    "branches": 75
  }
}

# リクエスト
"Create a user authentication system with JWT"
 
# Task Decomposition
tasks:
  - id: "backend_001"
    agent: "BackendAgent"
    description: "Implement JWT authentication API"
    priority: 1  # 最優先（他のタスクの前提）
  
  - id: "frontend_001"
    agent: "FrontendAgent"
    description: "Create login and registration forms"
    depends_on: ["backend_001"]  # backend_001 完了後に実行
    priority: 2
  
  - id: "test_001"
    agent: "TestAgent"
    description: "Write authentication test suite"
    depends_on: ["backend_001"]  # backend_001 完了後に実行
    priority: 2
 
# Execution Order
execution_plan:
  phase_1:
    - backend_001  # 並列不可
  phase_2:
    - frontend_001  # backend_001 と並列実行可能
    - test_001      # backend_001 と並列実行可能
  phase_3:
    - validation    # frontend_001 と test_001 の結果を統合・検証

import { AntigravityManager, Agent } from "@antigravity/sdk";
 
// ステップ1: スペシャリストエージェントを定義
const frontendAgent = new Agent({
  name: "FrontendAgent",
  role: "React component implementation",
  model: "gemma-4-pro",
  system_prompt: `You are an expert React developer...`,
  tools: ["code_generation", "accessibility_check", "performance_analyze"]
});
 
const backendAgent = new Agent({
  name: "BackendAgent",
  role: "RESTful API implementation",
  model: "gemma-4-pro",
  system_prompt: `You are an expert backend architect...`,
  tools: ["api_design", "schema_design", "security_check"]
});
 
const testAgent = new Agent({
  name: "TestAgent",
  role: "Test suite generation",
  model: "gemma-4-pro",
  system_prompt: `You are an expert QA engineer...`,
  tools: ["test_generation", "coverage_analysis"]
});
 
// ステップ2: Manager を設定
const manager = new AntigravityManager({
  agents: [frontendAgent, backendAgent, testAgent],
  strategy: "parallel_with_dependencies",  // 依存関係を考慮した並列処理
  aggregation_mode: "consensus"  // 複数エージェントの判断が異なる場合は投票で決定
});
 
// ステップ3: タスクを送信
const result = await manager.execute({
  request: "Create a full-stack user authentication system",
  constraints: {
    framework: "React + Express",
    security_level: "production",
    test_coverage: 80
  }
});
 
// ステップ4: 結果を取得
console.log(result);
// {
//   "frontend": { code: "...", accessibility_score: 95 },
//   "backend": { code: "...", security_audit: {...} },
//   "tests": { coverage: 82, passing: 145 },
//   "integration_report": { consistency: 0.98, issues: [] }
// }

const taskGraph = {
  phases: [
    {
      name: "Phase 1: Infrastructure",
      tasks: [
        {
          id: "db_schema",
          agent: backendAgent,
          description: "Design database schema",
          depends_on: []  // 前提条件なし
        }
      ]
    },
    {
      name: "Phase 2: Core Logic (Phase 1 に依存)",
      tasks: [
        {
          id: "api_endpoints",
          agent: backendAgent,
          description: "Implement REST API endpoints",
          depends_on: ["db_schema"]  // db_schema 完了を待つ
        },
        {
          id: "frontend_setup",
          agent: frontendAgent,
          description: "Set up React project structure",
          depends_on: []  // db_schema と並列実行可能
        }
      ]
    },
    {
      name: "Phase 3: Integration (Phase 2 に依存)",
      tasks: [
        {
          id: "api_integration",
          agent: frontendAgent,
          description: "Connect frontend to API",
          depends_on: ["api_endpoints"]
        },
        {
          id: "test_suite",
          agent: testAgent,
          description: "Write integration tests",
          depends_on: ["api_endpoints"]  // API が必要
        }
      ]
    }
  ]
};
 
// Manager がこのグラフを解析して最適実行順序を決定
const result = await manager.execute(taskGraph);

// シングルエージェント（順序実行）の場合
const serial_time = 
  await backendAgent.execute(task1) +      // 5分
  await frontendAgent.execute(task2) +     // 4分
  await testAgent.execute(task3);          // 3分
// 合計: 12分
 
// マルチエージェント（並列処理）の場合
const parallel_result = await manager.execute({
  strategy: "parallel",
  tasks: [task1, task2_frontend, task3_test]
  // task2_frontend と task3_test は task1 の 次フェーズ
});
// 実行時間:
// Phase 1: 5分 (backend)
// Phase 2: 4分 (frontend と test 並列)
// 合計: 9分
 
// 短縮率: (12 - 9) / 12 = 25% 短縮

const agents = {
  frontend: new Agent({
    model: "gemma-4-pro",
    system_prompt: `You are a world-class React developer.
    When making decisions, consider:
    1. Component reusability
    2. Performance (bundle size < 50KB per component)
    3. Accessibility (WCAG 2.1 AA)
    4. User experience consistency
    
    When you need to collaborate with other agents:
    - Backend API contract: JSON format only, no streaming
    - Test coverage: Minimum 80%`,
    temperature: 0.3,  // 低い = 一貫性重視
    top_p: 0.9
  }),
 
  backend: new Agent({
    model: "gemma-4-pro",
    system_prompt: `You are an expert backend architect.
    When making decisions, consider:
    1. API design (REST with clear contract)
    2. Security (authentication, authorization, validation)
    3. Scalability (database indexing, caching strategy)
    4. Error handling (standardized error codes)
    
    When you collaborate with frontend:
    - Frontend expects JSON responses with specific schema
    - Provide clear error messages for validation failures`,
    temperature: 0.2,  // より決定的
    top_p: 0.8
  }),
 
  test: new Agent({
    model: "gemma-4-pro",
    system_prompt: `You are a meticulous QA engineer.
    When writing tests, consider:
    1. Unit test coverage: 80% minimum
    2. Edge cases: Off-by-one, null inputs, empty arrays
    3. Integration points: API contracts, database interactions
    4. Performance tests: Response time < threshold
    
    When reviewing other agents' output:
    - Validate type safety
    - Check error handling completeness`,
    temperature: 0.2,  // 一貫性最優先
    top_p: 0.8
  })
};

const manager = new AntigravityManager({
  agents: [frontendAgent, backendAgent, testAgent],
  
  // Gemma 4 の思考プロセスを活用して、エージェント間の矛盾を自動解決
  conflict_resolution: async (conflict) => {
    const reasoningAgent = new Agent({
      model: "gemma-4-pro",
      system_prompt: `You are an arbitrator between specialist agents.
      Analyze their arguments and make a final decision that:
      1. Respects each agent's expertise
      2. Prioritizes system consistency
      3. Explains your reasoning clearly`,
      enable_extended_thinking: true  // 深い思考を有効化
    });
    
    return await reasoningAgent.execute({
      task: "Resolve conflict",
      context: conflict
    });
  }
});

{
  "project": "TodoApp",
  "status": "COMPLETE",
  "metrics": {
    "total_lines_of_code": 4250,
    "backend_files": 12,
    "frontend_components": 8,
    "test_files": 15,
    "coverage": {
      "overall": 87,
      "backend": 88,
      "frontend": 86
    }
  },
  "quality_report": {
    "security_audit": {
      "status": "PASS",
      "vulnerabilities": 0,
      "jwt_implementation": "Secure"
    },
    "performance_audit": {
      "frontend_bundle_size": "45KB",
      "initial_load_time": "1.2s",
      "api_response_time": "< 100ms"
    },
    "accessibility_audit": {
      "wcag_level": "AA",
      "aria_labels": "100%",
      "keyboard_navigation": "PASS"
    }
  },
  "artifacts": {
    "frontend": {
      "path": "src/",
      "components": [
        { "name": "LoginForm", "coverage": 92 },
        { "name": "TodoList", "coverage": 88 },
        { "name": "AddTodoForm", "coverage": 85 }
      ]
    },
    "backend": {
      "path": "server/",
      "endpoints": [
        { "path": "/auth/register", "coverage": 90 },
        { "path": "/auth/login", "coverage": 92 },
        { "path": "/todos", "coverage": 87 }
      ]
    },
    "tests": {
      "unit_tests": 45,
      "integration_tests": 12,
      "e2e_tests": 8
    }
  }
}

enum AgentErrorType {
  // Type A: エージェント内部エラー（独立解決可能）
  INTERNAL_ERROR = "Internal processing error",
  
  // Type B: エージェント間矛盾（Manager が調整）
  CONSISTENCY_VIOLATION = "Output conflicts with other agent",
  
  // Type C: リソース不足（再試行・フォールバック）
  RESOURCE_EXHAUSTED = "GPU memory, API rate limit exceeded",
  
  // Type D: 入力不正（ユーザー確認必要）
  INPUT_INVALID = "Request violates constraints"
}
 
const errorHandler = {
  INTERNAL_ERROR: async (agent, error) => {
    // 同じエージェントで再試行（異なるプロンプト）
    return await agent.retry({
      alternative_approach: true,
      max_retries: 3
    });
  },
  
  CONSISTENCY_VIOLATION: async (manager, agents, conflict) => {
    // Manager が仲裁して矛盾を解決
    return await manager.resolveConflict(agents, conflict);
  },
  
  RESOURCE_EXHAUSTED: async (agent) => {
    // より軽量なモデルにフォールバック
    return await agent.execute({
      model: "gemma-4-standard",  // 通常版に切り替え
      mode: "streaming"  // ストリーミングで メモリ削減
    });
  },
  
  INPUT_INVALID: async (manager, request) => {
    // ユーザーに確認して修正
    const clarification = await askUser(
      "Request is ambiguous. Did you mean: A or B?"
    );
    return await manager.execute({
      ...request,
      clarified_constraint: clarification
    });
  }
};

class SelfHealingAgent extends Agent {
  async execute(task) {
    const initialOutput = await super.execute(task);
    
    // ステップ1: 自己検証
    const validationResult = await this.validate(initialOutput);
    
    if (validationResult.is_valid) {
      return initialOutput;
    }
    
    // ステップ2: 問題分析
    const issues = validationResult.issues;
    console.log(`Found ${issues.length} issues. Attempting self-repair...`);
    
    // ステップ3: 自動修復
    const repairs = issues.map(issue => ({
      type: issue.type,
      location: issue.location,
      suggestion: `Fix ${issue.type} at line ${issue.location.line}`
    }));
    
    // ステップ4: 修復実行
    const repairedOutput = await this.applyRepairs(
      initialOutput,
      repairs
    );
    
    // ステップ5: 検証の再実行
    const finalValidation = await this.validate(repairedOutput);
    
    if (finalValidation.is_valid) {
      return repairedOutput;
    } else {
      // 修復失敗 → Manager にエスカレート
      throw new ConsistencyViolationError(
        `Self-repair failed: ${finalValidation.issues.map(i => i.message).join(', ')}`
      );
    }
  }
}

const optimizationStrategies = {
  // 1. エージェント選択の最適化
  agent_selection: {
    strategy: "capability_matching",
    rules: [
      "Use Gemma 4 Standard for simple tasks (< 500 tokens output)",
      "Use Gemma 4 Pro for complex reasoning tasks",
      "Use Gemma 4 Max only when absolutely necessary"
    ]
  },
  
  // 2. 並列度の動的調整
  parallelization: {
    strategy: "adaptive_parallelism",
    policy: (available_resources) => {
      if (available_resources.gpu_memory > 20) return 4;  // 4並列
      if (available_resources.gpu_memory > 15) return 2;  // 2並列
      return 1;  // シーケンシャル
    }
  },
  
  // 3. キャッシュとメモ化
  caching: {
    enable_prompt_caching: true,
    cache_duration: 3600,  // 1時間
    cache_keys: [
      "system_prompt",
      "repeated_instructions",
      "style_guides"
    ]
  },
  
  // 4. トークン効率化
  token_optimization: {
    summarize_long_outputs: true,
    max_summary_length: 200,
    compression_ratio_target: 0.3
  }
};
 
// コスト計算
const costCalculator = {
  estimate_total_cost: (project) => {
    let total_cost = 0;
    
    for (const agent of project.agents) {
      const input_tokens = agent.estimated_input_tokens;
      const output_tokens = agent.estimated_output_tokens;
      
      const model_pricing = {
        "gemma-4-standard": { input: 0.075, output: 0.3 },   // per 1M tokens
        "gemma-4-pro": { input: 0.15, output: 0.6 },
        "gemma-4-max": { input: 0.30, output: 1.2 }
      };
      
      const pricing = model_pricing[agent.model];
      total_cost += 
        (input_tokens / 1_000_000) * pricing.input +
        (output_tokens / 1_000_000) * pricing.output;
    }
    
    return total_cost;
  }
};

// 実装予定: v1.5.0
const self_organizing_manager = new AutoManager({
  agents: [agent1, agent2, agent3],
  negotiation_enabled: true,
  allow_role_swapping: true
  // エージェント自身が「自分は本当にこの役割に向いているか」を判断
});

// 実装予定: v1.6.0
const shared_memory = new CollaborativeMemory({
  type: "vector_database",  // エンベディング ベース
  agents: [all_agents],
  retention_policy: "learned_patterns_only"
  // 過去の成功・失敗パターンを全エージェントで共有
});

// 実装予定: v1.7.0
const skill_transfer = new DynamicSkillTransfer({
  source_agent: frontend_agent,
  skill: "accessibility_optimization",
  target_agents: [test_agent, backend_agent],
  transfer_method: "prompt_injection"
  // テストエージェントがバックエンドのテストでもアクセシビリティをチェック
});