feat(ai): Phase 22 OpenClaw + Nemotron 協作架構 (ADR-044)
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統帥批准實作「仲裁-執行分工」架構: - OpenClaw = 仲裁者 (Why + Risk Level) - Nemotron = 執行者 (How + kubectl Command) 新增功能: - config.py: ENABLE_NEMOTRON_COLLABORATION Feature Flag - openclaw.py: generate_incident_proposal_with_tools() - openclaw.py: _call_nemotron_tools() Nemotron 呼叫 - telegram_gateway.py: TelegramMessage Nemotron 欄位 - telegram_gateway.py: format_with_nemotron() 雙區塊格式 - decision_manager.py: 整合協作方法 - proposal_service.py: 整合協作方法 觸發條件: - LOW 風險 → 僅 OpenClaw - MEDIUM/HIGH/CRITICAL → OpenClaw + Nemotron 雙軌 首席架構師審查: 83/100 條件通過 Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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# ADR-044: OpenClaw + Nemotron 協作架構
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> **狀態**: ✅ **已批准**
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> **決策日期**: 2026-03-31
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> **批准日期**: 2026-03-31 18:30 (台北時區)
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> **決策者**: 首席架構師 + 統帥
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> **提案者**: Claude Code
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> **相關**: ADR-036 Nemotron Tool Calling, Phase 18 自動修復
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## 背景
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AWOOOI 目前有兩個 AI 能力：
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1. **OpenClaw** - 主要大腦，負責 Root Cause Analysis、風險評估、決策推理
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2. **Nemotron** - Tool Calling 專家，83.3% 精準度執行 K8s 操作
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統帥需求：在同一個 Telegram 中同時看到兩者的分析結果。
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## 問題陳述
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如何讓兩個 AI 在 Telegram 中協作，而不會：
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- 訊息混亂（誰說了什麼？）
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- 責任不清（誰做的決策？）
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- 無限迴圈（互相觸發）
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- 增加過多延遲
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## 決策
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### 採用「仲裁-執行分工」架構
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```
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OpenClaw = 仲裁者 (Arbitrator) - 決定「為什麼」和「風險等級」
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Nemotron = 執行者 (Executor) - 決定「怎麼做」和「具體指令」
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```
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### 職責分離
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| 角色 | OpenClaw | Nemotron |
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|------|----------|----------|
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| **任務** | Root Cause Analysis | Tool Calling |
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| **輸出** | 風險等級 + 責任團隊 + 原因推理 | kubectl 指令 + 參數驗證 |
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| **模型** | Ollama/Gemini (RCA 任務) | Nemotron-mini (Tool 任務) |
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| **信心度** | 0-100% (AI 分析品質) | 驗證狀態 (✅/❌) |
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| **備援** | Expert System 規則 | Gemini Tool Calling |
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### 流程設計
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```
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1. Incident 產生
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↓
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2. OpenClaw.generate_incident_proposal()
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→ 輸出: risk_level, reasoning, primary_responsibility
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↓
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3. 判斷是否需要 Nemotron
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├─ LOW 風險 → 跳過 Nemotron
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└─ MEDIUM/HIGH/CRITICAL → 呼叫 Nemotron
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↓
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4. NvidiaProvider.tool_call()
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→ 輸出: tool_name, arguments, validation_status
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↓
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5. 組合結果 → 推送 Telegram 卡片
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↓
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6. 用戶簽核 → 執行
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```
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### 觸發條件
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| 風險等級 | OpenClaw | Nemotron | 原因 |
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|----------|----------|----------|------|
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| LOW | ✅ | ❌ | 低風險操作不需要 Tool 驗證 |
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| MEDIUM | ✅ | ✅ | 需要 Tool 驗證操作可行性 |
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| HIGH | ✅ | ✅ | 高風險必須雙重驗證 |
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| CRITICAL | ✅ | ✅ + HITL | 危險操作必須人工介入 |
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## 實作規格
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### 1. 擴展 TelegramMessage
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```python
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@dataclass
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class TelegramMessage:
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# 現有欄位...
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# 新增 Nemotron 結果欄位
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nemotron_enabled: bool = False
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nemotron_tools: list[dict] | None = None # Tool Calling 結果
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nemotron_validation: str = "" # "✅ 驗證通過" / "❌ 驗證失敗"
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nemotron_latency_ms: float = 0.0
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```
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### 2. 擴展 generate_incident_proposal
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```python
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async def generate_incident_proposal_with_tools(
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self,
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incident_id: str,
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severity: str,
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signals: list[dict],
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affected_services: list[str],
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) -> tuple[dict | None, str, bool]:
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"""
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Phase 22: OpenClaw + Nemotron 協作
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Returns:
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(proposal_dict, provider, success)
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proposal_dict 新增:
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- nemotron_tools: Tool Calling 結果
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- nemotron_validation: 驗證狀態
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"""
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# Step 1: OpenClaw 仲裁
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proposal, provider, success = await self.generate_incident_proposal(
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incident_id, severity, signals, affected_services
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)
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if not success:
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return proposal, provider, success
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# Step 2: 判斷是否需要 Nemotron
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risk_level = proposal.get("risk_level", "low").lower()
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if risk_level == "low":
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proposal["nemotron_enabled"] = False
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return proposal, provider, True
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# Step 3: Nemotron Tool Calling
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from src.services.nvidia_provider import get_nvidia_provider
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nvidia = get_nvidia_provider()
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tool_result = await nvidia.tool_call(
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messages=[{
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"role": "user",
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"content": f"""
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根據以下分析，生成對應的 kubectl 操作：
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- Incident: {incident_id}
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- 原因: {proposal.get('reasoning', '')}
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- 目標資源: {proposal.get('target_resource', '')}
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- 建議操作: {proposal.get('action', '')}
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"""
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}],
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tools=K8S_OPERATION_TOOLS,
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)
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# Step 4: 驗證 Tool Calling 結果
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validation = await self._validate_tool_calls(tool_result.tool_calls)
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proposal["nemotron_enabled"] = True
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proposal["nemotron_tools"] = [
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{"tool": tc.tool_name, "args": tc.arguments, "valid": tc.valid}
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for tc in tool_result.tool_calls
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]
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proposal["nemotron_validation"] = validation
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proposal["nemotron_latency_ms"] = tool_result.latency_ms
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return proposal, provider, True
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```
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### 3. Telegram 卡片格式
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```python
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def format_with_nemotron(self) -> str:
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"""格式化含 Nemotron 結果的訊息"""
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# OpenClaw 區塊
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openclaw_block = f"""
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🤖 <b>OpenClaw 仲裁</b>
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├ 📊 信心: {self.confidence_emoji} {self.confidence_pct}%
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├ 👥 責任: {self.primary_responsibility}
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└ 💡 原因: {self.root_cause[:50]}
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"""
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# Nemotron 區塊 (如果啟用)
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nemotron_block = ""
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if self.nemotron_enabled and self.nemotron_tools:
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tools_str = "\n".join([
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f" {'✅' if t['valid'] else '❌'} {t['tool']}: {t['args'][:30]}"
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for t in self.nemotron_tools[:3] # 最多顯示 3 個
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])
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nemotron_block = f"""
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━━━━━━━━━━━━━━━━━━━
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🔧 <b>Nemotron 執行方案</b>
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{tools_str}
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└ 驗證: {self.nemotron_validation}
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"""
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return f"{openclaw_block}{nemotron_block}"
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```
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### 4. 異步執行 (非阻塞)
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```python
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async def _push_decision_to_telegram_async(
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incident: Incident,
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proposal_data: dict,
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) -> None:
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"""
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異步推送，不阻塞主流程
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Phase 22: 如果 Nemotron 延遲過長 (>10s)，先推送 OpenClaw 結果，
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Nemotron 結果後續用 edit_message 更新
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"""
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# 先推送 OpenClaw 結果
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message_id = await gateway.send_approval_card(
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# ... OpenClaw 結果
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)
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# 如果需要 Nemotron，異步執行並更新
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if proposal_data.get("risk_level") in ["medium", "high", "critical"]:
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asyncio.create_task(
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_update_with_nemotron_result(message_id, incident, proposal_data)
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)
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```
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## 後果
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### 正面
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- **清晰分工**: OpenClaw 和 Nemotron 職責明確
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- **可追蹤**: 每個 AI 的貢獻獨立顯示
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- **容錯性**: 備援鏈清晰 (Nemotron → Gemini → Expert)
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- **效能**: 低風險操作不觸發 Nemotron，節省延遲
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### 負面
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- **延遲增加**: 高風險操作需要兩輪 LLM
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- **複雜度**: 訊息格式需要擴展
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### 風險緩解
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| 風險 | 緩解 |
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|------|------|
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| Nemotron 延遲 11-45s | 異步執行，先推送 OpenClaw 結果 |
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| Tool Calling 失敗 | Fallback 到 Gemini，再失敗則只顯示 OpenClaw |
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| 訊息超長 | 縮寫 Tool 參數，完整內容放 SignOz Link |
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## 併發控制 (與 ADR-038 整合)
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> **首席架構師 P1 必修項** (2026-03-31)
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### 雙 Semaphore 策略
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```python
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# apps/api/src/core/circuit_breaker.py 擴展
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class OpenClawGuard:
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def __init__(self):
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self.openclaw_semaphore = asyncio.Semaphore(3) # 原有
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self.nemotron_semaphore = asyncio.Semaphore(2) # 新增 (NVIDIA API 較慢)
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```
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**設計原因**:
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- Nemotron 併發限制為 2 (低於 OpenClaw 的 3)
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- NVIDIA NIM 免費 tier 有 RPM 限制
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- Nemotron 延遲較高 (11-45s)，過多並發無益
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### 並行執行優化
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```python
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# Step 3 優化: OpenClaw + Nemotron 並行而非串行
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import asyncio
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async def generate_incident_proposal_with_tools(...):
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# 並行啟動 OpenClaw 和 Nemotron (減少延遲)
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openclaw_task = asyncio.create_task(
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self.generate_incident_proposal(incident_id, severity, signals, affected_services)
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)
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# 先等待 OpenClaw 完成，判斷是否需要 Nemotron
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proposal, provider, success = await openclaw_task
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if not success or proposal.get("risk_level", "low").lower() == "low":
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return proposal, provider, success
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# 需要 Nemotron - 此時 OpenClaw 已完成，立即啟動 Nemotron
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nemotron_result = await self._call_nemotron_tools(proposal)
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# 組合結果
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return self._combine_results(proposal, nemotron_result), provider, True
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```
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**延遲對比**:
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| 場景 | 串行 | 並行 | 改善 |
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|------|------|------|------|
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| MEDIUM 風險 | 3s + 15s = 18s | max(3s, 15s) = 15s | -3s |
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| HIGH 風險 | 5s + 30s = 35s | max(5s, 30s) = 30s | -5s |
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---
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## Circuit Breaker 整合
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### 雙層 Circuit Breaker 協調
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```
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┌─────────────────────────────────────────┐
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│ OpenClawGuard (ADR-038) │
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│ - 管理請求佇列 │
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│ - 長期熔斷 (5 分鐘) │
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└─────────────────────────────────────────┘
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│
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▼
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┌─────────────────────────────────────────┐
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│ NvidiaProvider.CircuitBreaker │
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│ - NVIDIA API 短期熔斷 (60s) │
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│ - 失敗 3 次後 OPEN │
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└─────────────────────────────────────────┘
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```
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### 熔斷策略
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| 層級 | 觸發條件 | 恢復時間 | 影響 |
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|------|---------|---------|------|
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| OpenClawGuard | 佇列滿 (>10) | 5 分鐘 | 停止新請求 |
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| NvidiaProvider | 連續 3 失敗 | 60 秒 | Fallback 到 Gemini |
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---
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## Feature Flag 支援
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> **首席架構師 P1 必修項**
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### 環境變數
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```bash
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# 啟用/停用 Nemotron 協作 (預設 true)
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ENABLE_NEMOTRON_COLLABORATION=true
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# Nemotron 呼叫超時 (預設 45s)
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NEMOTRON_TIMEOUT_SECONDS=45
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# 強制使用異步更新 (先推 OpenClaw，後更新 Nemotron)
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NEMOTRON_ASYNC_UPDATE=true
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```
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### 回滾計畫
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```python
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async def generate_incident_proposal_with_tools(...):
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# Feature Flag 檢查
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if not settings.ENABLE_NEMOTRON_COLLABORATION:
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return await self.generate_incident_proposal(...) # 原流程
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# ... 協作邏輯
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```
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**回滾步驟**:
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1. 設置 `ENABLE_NEMOTRON_COLLABORATION=false`
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2. Rollout restart awoooi-api
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3. 無需代碼回滾
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---
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## DI 模式重構
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> **首席架構師 P1 必修項** - 避免函數內 import
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### 修改前 (❌ 違反 DI)
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```python
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# Step 3: Nemotron Tool Calling
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from src.services.nvidia_provider import get_nvidia_provider # ❌ 函數內 import
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nvidia = get_nvidia_provider()
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```
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### 修改後 (✅ DI 模式)
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```python
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# apps/api/src/services/openclaw.py
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from src.services.nvidia_provider import INvidiaProvider
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class OpenClawService:
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def __init__(
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self,
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nvidia_provider: INvidiaProvider | None = None, # DI 注入
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):
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self._nvidia = nvidia_provider or get_nvidia_provider()
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async def generate_incident_proposal_with_tools(
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self,
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incident_id: str,
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severity: str,
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signals: list[dict],
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affected_services: list[str],
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) -> tuple[dict | None, str, bool]:
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# ... 使用 self._nvidia 而非 import
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```
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---
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## 測試策略
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### E2E 測試案例
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```python
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# tests/test_openclaw_nemotron_collaboration.py
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@pytest.mark.asyncio
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async def test_low_risk_skips_nemotron():
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"""LOW 風險不觸發 Nemotron"""
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result = await openclaw.generate_incident_proposal_with_tools(...)
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assert result[0]["nemotron_enabled"] is False
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@pytest.mark.asyncio
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async def test_medium_risk_enables_nemotron():
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"""MEDIUM 風險啟用 Nemotron"""
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result = await openclaw.generate_incident_proposal_with_tools(...)
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assert result[0]["nemotron_enabled"] is True
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assert result[0]["nemotron_tools"] is not None
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_nemotron_failure_fallback():
|
||||
"""Nemotron 失敗時 fallback 到 Gemini"""
|
||||
# Mock NVIDIA 失敗
|
||||
with patch("nvidia_provider.tool_call", side_effect=Exception):
|
||||
result = await openclaw.generate_incident_proposal_with_tools(...)
|
||||
# 應該有結果 (來自 Gemini fallback)
|
||||
assert result[2] is True
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_feature_flag_disabled():
|
||||
"""Feature Flag 停用時走原流程"""
|
||||
with patch.dict(os.environ, {"ENABLE_NEMOTRON_COLLABORATION": "false"}):
|
||||
result = await openclaw.generate_incident_proposal_with_tools(...)
|
||||
assert "nemotron_enabled" not in result[0]
|
||||
```
|
||||
|
||||
### 整合測試
|
||||
|
||||
```python
|
||||
@pytest.mark.integration
|
||||
async def test_telegram_message_with_nemotron():
|
||||
"""Telegram 訊息包含 Nemotron 區塊"""
|
||||
msg = TelegramMessage(
|
||||
nemotron_enabled=True,
|
||||
nemotron_tools=[{"tool": "restart_deployment", "args": {...}, "valid": True}],
|
||||
)
|
||||
formatted = msg.format_with_nemotron()
|
||||
assert "Nemotron 執行方案" in formatted
|
||||
assert "✅ restart_deployment" in formatted
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 實作排程 (詳細)
|
||||
|
||||
| 階段 | 內容 | 時間 | 檔案 | 依賴 |
|
||||
|------|------|------|------|------|
|
||||
| **22.1** | TelegramMessage 擴展 | 2h | `telegram_gateway.py` | 無 |
|
||||
| **22.2a** | OpenClawGuard 雙 Semaphore | 1h | `circuit_breaker.py` | 無 |
|
||||
| **22.2b** | DI 模式重構 | 1h | `openclaw.py` | 22.2a |
|
||||
| **22.2c** | `generate_incident_proposal_with_tools` | 2h | `openclaw.py` | 22.2a, 22.2b |
|
||||
| **22.3a** | Feature Flag 支援 | 1h | `config.py` | 無 |
|
||||
| **22.3b** | 異步推送邏輯 | 2h | `decision_manager.py` | 22.1, 22.2c |
|
||||
| **22.4a** | 單元測試 | 2h | `test_openclaw_nemotron*.py` | 22.2c |
|
||||
| **22.4b** | E2E 測試 | 2h | `test_e2e_collaboration.py` | 22.3b |
|
||||
| **總計** | | **13h (~1.5 天)** | | |
|
||||
|
||||
---
|
||||
|
||||
## 首席架構師審查結論
|
||||
|
||||
> **審查日期**: 2026-03-31 (台北時區)
|
||||
> **分數**: 83/100 → **條件通過**
|
||||
|
||||
### P1 必修項 (已補充)
|
||||
|
||||
| 編號 | 項目 | 狀態 |
|
||||
|------|------|------|
|
||||
| P1-1 | 併發控制整合 | ✅ 已補充 |
|
||||
| P1-2 | DI 模式 | ✅ 已補充 |
|
||||
| P1-3 | Feature Flag | ✅ 已補充 |
|
||||
|
||||
### P2 建議項 (後續迭代)
|
||||
|
||||
| 編號 | 項目 | 說明 |
|
||||
|------|------|------|
|
||||
| P2-1 | 並行優化 | 已納入設計 |
|
||||
| P2-2 | Pydantic Model | Phase 22.5 |
|
||||
| P2-3 | NemotronBlock | Phase 22.5 |
|
||||
|
||||
---
|
||||
|
||||
## 相關文件
|
||||
|
||||
- ADR-036: Nemotron Tool Calling 整合
|
||||
- ADR-038: OpenClaw 併發治理
|
||||
- Phase 18: 失敗自動修復閉環
|
||||
- `feedback_ai_rate_limiter.md`: AI 用量控制
|
||||
|
||||
---
|
||||
|
||||
**Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>**
|
||||
Reference in New Issue
Block a user