feat(api): Phase 6.4h replace mock DI with real ProposalService
- Remove MockEngine and embedded Proposal/Guardrails classes - Import real ProposalService with OpenClaw LLM integration - Use get_real_proposal_service() for dependency injection - ProposalService integrates: - OpenClaw LLM (Ollama → Gemini → Claude fallback) - Redis Working Memory - PostgreSQL Episodic Memory - TrustEngine risk assessment - Add llm_provider, llm_confidence, kubectl_command to response - Map ApprovalRiskLevel to Tier (LOW=1, MEDIUM=2, CRITICAL=3) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
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@@ -1,24 +1,33 @@
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"""
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Proposals Router - Phase 6.4g 突觸對接
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======================================
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Proposals Router - Phase 6.4h 真實大腦植入
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==========================================
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POST /api/v1/incidents/{incident_id}/propose
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整合 lewooogo-brain 積木模組實現決策提案生成。
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整合真實 ProposalService + OpenClaw LLM 實現決策提案生成。
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"""
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from fastapi import APIRouter, Depends, HTTPException, status
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from pydantic import BaseModel, Field
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from typing import List
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import structlog
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from src.services.proposal_service import get_proposal_service, ProposalService
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from src.models.approval import RiskLevel as ApprovalRiskLevel
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logger = structlog.get_logger(__name__)
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router = APIRouter(prefix="/api/v1/incidents", tags=["Proposals"])
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class ProposalCreateRequest(BaseModel):
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require_dry_run: bool = Field(
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default=True,
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description="強制要求演練模式，此參數將直接餵給 Guardrails 進行驗證"
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)
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class ProposalResponse(BaseModel):
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proposal_id: str = Field(..., description="決策書唯一識別碼")
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incident_id: str = Field(..., description="關聯的事件 ID")
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@@ -26,94 +35,127 @@ class ProposalResponse(BaseModel):
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tier: int = Field(..., description="判定之授權級別 (1: 自主, 2: 授權, 3: 親核)")
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guardrails_passed: bool = Field(..., description="是否完全通過防爆圈檢測")
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rejection_reason: str | None = Field(default=None, description="若未通過防爆圈，顯示阻擋原因")
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# Phase 6.4h: 額外回傳 LLM 決策資訊
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llm_provider: str | None = Field(default=None, description="LLM 提供者 (ollama/gemini/claude)")
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llm_confidence: float | None = Field(default=None, description="LLM 信心度 (0.0-1.0)")
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kubectl_command: str | None = Field(default=None, description="生成的 kubectl 指令")
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def get_proposal_engine():
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def get_real_proposal_service() -> ProposalService:
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"""
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Phase 6.4g 暫時性 Mock DI，驗證路由暢通
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NOTE: 完全內嵌，不依賴外部 lewooogo-brain 套件 (Docker 相容)
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Phase 6.4h 真實依賴注入: 返回 ProposalService 單例
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ProposalService 整合:
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- OpenClaw LLM (Ollama → Gemini → Claude fallback)
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- Redis Working Memory
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- PostgreSQL Episodic Memory
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- TrustEngine 風險評估
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"""
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from uuid import uuid4
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from pydantic import BaseModel
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# 內嵌 Guardrails 定義 (Docker 相容)
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class Guardrails(BaseModel):
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require_dry_run: bool = True
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allowed_namespace: list[str] = ["awoooi-prod"]
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forbidden_commands: list[str] = ["rm -rf", "drop table", "kubectl delete ns"]
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max_retries: int = 1
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timeout_sec: int = 60
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# 內嵌 Proposal 定義 (Docker 相容)
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class Proposal(BaseModel):
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proposal_id: str
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incident_id: str
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action: str
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description: str
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risk_level: str
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guardrails: dict
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metadata: dict = {}
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class MockEngine:
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async def generate(self, incident_id: str) -> tuple[Proposal | None, str]:
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return Proposal(
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proposal_id=f"prop-{str(uuid4())[:8]}",
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incident_id=incident_id,
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action="kubectl get pods -n awoooi-prod",
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description="Mock proposal for testing",
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risk_level="low",
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guardrails=self.get_default_guardrails().model_dump(),
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metadata={"generated_by": "mock"},
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), "Proposal generated (mock)"
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async def generate_with_skill(self, incident_id: str, skill_id: str):
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return await self.generate(incident_id)
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def get_default_guardrails(self) -> Guardrails:
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return Guardrails(require_dry_run=True)
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return MockEngine()
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return get_proposal_service()
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@router.post(
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"/{incident_id}/propose",
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response_model=ProposalResponse,
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status_code=status.HTTP_201_CREATED,
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summary="生成決策提案 (Phase 6.4g)",
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description="使用 lewooogo-brain 積木生成決策提案",
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summary="生成決策提案 (Phase 6.4h)",
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description="使用真實 OpenClaw LLM + TrustEngine 生成決策提案",
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)
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async def generate_decision_proposal(
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incident_id: str,
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request: ProposalCreateRequest,
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engine=Depends(get_proposal_engine)
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service: ProposalService = Depends(get_real_proposal_service),
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):
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"""
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Phase 6.4h: 真實 LLM 決策提案生成
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流程:
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1. Guardrails 前置檢查 (require_dry_run 必須為 True)
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2. 從 Redis/PostgreSQL 載入 Incident
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3. 呼叫 OpenClaw LLM 生成提案 (Ollama → Gemini → Claude fallback)
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4. TrustEngine 風險評估與 Tier 判定
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5. 建立 ApprovalRequest (向下相容前端)
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6. 返回結構化 ProposalResponse
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"""
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try:
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# Guardrails 檢查: require_dry_run 必須為 True
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# 1. Guardrails 檢查: require_dry_run 必須為 True
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if not request.require_dry_run:
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logger.warning(
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"guardrails_rejected",
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incident_id=incident_id,
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reason="require_dry_run must be True",
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)
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raise HTTPException(
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status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
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detail="Guardrail triggered: require_dry_run must be True"
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)
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proposal, message = await engine.generate(incident_id=incident_id)
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logger.info(
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"proposal_generation_start",
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incident_id=incident_id,
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)
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if proposal is None:
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# 2. 呼叫真實 ProposalService 生成提案
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approval, message = await service.generate_proposal(incident_id)
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if approval is None:
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logger.warning(
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"proposal_generation_failed",
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incident_id=incident_id,
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message=message,
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)
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail=message
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)
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# 計算 tier 基於 risk_level
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tier_map = {"low": 1, "medium": 2, "high": 3}
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tier = tier_map.get(proposal.risk_level, 2)
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# 3. 計算 tier 基於 risk_level
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tier_map = {
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ApprovalRiskLevel.LOW: 1, # 自主 (AI 可直接執行)
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ApprovalRiskLevel.MEDIUM: 2, # 授權 (需 1 人簽核)
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ApprovalRiskLevel.CRITICAL: 3, # 親核 (需 2 人簽核)
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}
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tier = tier_map.get(approval.risk_level, 2)
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# 4. 提取 LLM 資訊 (Phase 6.4h 新增)
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metadata = approval.metadata or {}
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kubectl_command = metadata.get("kubectl_command", "")
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llm_provider = metadata.get("llm_provider")
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llm_confidence = metadata.get("llm_confidence")
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# 5. 組裝 actions 清單
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actions = [approval.action]
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if kubectl_command and kubectl_command != approval.action:
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actions.append(kubectl_command)
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logger.info(
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"proposal_generation_complete",
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incident_id=incident_id,
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proposal_id=str(approval.id),
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tier=tier,
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llm_provider=llm_provider,
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)
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return ProposalResponse(
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proposal_id=proposal.proposal_id,
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incident_id=proposal.incident_id,
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actions=[proposal.action],
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proposal_id=str(approval.id),
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incident_id=incident_id,
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actions=actions,
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tier=tier,
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guardrails_passed=proposal.guardrails.get("require_dry_run", False),
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rejection_reason=None
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guardrails_passed=True, # 通過 TrustEngine 評估
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rejection_reason=None,
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llm_provider=llm_provider,
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llm_confidence=llm_confidence,
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kubectl_command=kubectl_command if kubectl_command else None,
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)
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except HTTPException:
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raise
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except Exception as e:
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raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=f"Internal Error: {str(e)}")
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logger.exception(
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"proposal_generation_error",
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incident_id=incident_id,
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error=str(e),
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)
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raise HTTPException(
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status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
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detail=f"Internal Error: {str(e)}"
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)
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