838 lines
39 KiB
Python
838 lines
39 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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services/code_review_pipeline_service.py
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Post-Deploy AI Agent Code Review Pipeline
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觸發時機：CD 健康檢查通過後，由 Gitea Action webhook 呼叫
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Pipeline：
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Step 1 system 讀取變更檔案內容
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Step 2 Hermes 程式碼掃描（bugs / security / performance）
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Step 3 OpenClaw 架構品質評估（Ollama-first，Gemini 僅備援）
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Step 4 ElephantAlpha 決策協調（severity 判定 + auto-fix 裁量）
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Step 5 NemoTron 行動派遣（action_plans 寫入 + AiderHeal 觸發）
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結果輸出：
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- ai_insights（type='code_review_result'）
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- action_plans（type='code_review_fix'）
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- Telegram 告警（啟動 / 完成 / 錯誤）
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- 前端 /code-review/ 即時 polling 狀態
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"""
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import json
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import logging
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import os
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import re
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import threading
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from datetime import datetime
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from typing import Any, Dict, List, Optional
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from database.manager import get_session
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from sqlalchemy import text
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# ADR-027：Code Review 走 OllamaService 取得三主機級聯 retry。
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from services.hermes_analyst_service import HERMES_MODEL as _HERMES_MODEL
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from services.ai_call_logger import log_ai_call # Operation Ollama-First v5.0 P1
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logger = logging.getLogger(__name__)
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# ── Pipeline 全域狀態（供前端 polling）─────────────────────────────────────
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_current_pipeline: Dict[str, Any] = {}
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_pipeline_lock = threading.Lock()
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GEMINI_API_KEY = os.getenv("GEMINI_API_KEY", "")
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# Gemini 僅作 Code Review Ollama/Claude 主路徑都失敗後的最後雲端備援。
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REVIEW_MODEL = os.getenv("OPENCLAW_MODEL", "gemini-2.5-flash")
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CODE_REVIEW_OLLAMA_MODEL = os.getenv(
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"CODE_REVIEW_OLLAMA_MODEL",
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os.getenv("OPENCLAW_OLLAMA_MODEL", "qwen3:14b"),
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)
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CODE_REVIEW_OLLAMA_TIMEOUT = int(os.getenv("CODE_REVIEW_OLLAMA_TIMEOUT", "120"))
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INTERNAL_TOKEN = os.getenv("INTERNAL_WEBHOOK_TOKEN", "")
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AUTO_FIX_ENABLED = os.getenv("CODE_REVIEW_AUTO_FIX_ENABLED", "true").lower() == "true"
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ALLOW_INSECURE_WEBHOOK = os.getenv("MOMO_ALLOW_INSECURE_INTERNAL_WEBHOOK_FOR_DEV", "").lower() == "true"
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# Phase 7 Frontier 升級 feature flag — 預設 OFF；啟用後只作 Ollama 失敗後的雲端備援。
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CODE_REVIEW_USE_CLAUDE = os.getenv("CODE_REVIEW_USE_CLAUDE", "false").lower() == "true"
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CLAUDE_REVIEW_MODEL = os.getenv("CLAUDE_MODEL", "claude-opus-4-7")
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# ═══════════════════════════════════════════════════════════════════════════════
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# Pipeline Class
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# ═══════════════════════════════════════════════════════════════════════════════
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class CodeReviewPipeline:
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"""
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5-Step post-deploy code review pipeline.
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Call pipeline.run() inside a daemon thread.
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"""
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def __init__(self, commit_sha: str, changed_files: List[str],
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branch: str = "main", deploy_type: str = "sync"):
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self.commit_sha = commit_sha
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self.branch = branch
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self.deploy_type = deploy_type
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self.started_at = datetime.now()
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self.pipeline_id = f"cr_{commit_sha[:8]}_{self.started_at.strftime('%Y%m%d_%H%M%S')}"
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# 只 review Python + YAML 檔（跳過靜態資源）
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self.changed_files = [
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f for f in changed_files
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if f.endswith(('.py', '.yaml', '.yml', '.json'))
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and not f.startswith(('node_modules/', '.git/'))
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]
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self.state: Dict[str, Any] = {
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"pipeline_id": self.pipeline_id,
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"commit_sha": commit_sha,
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"branch": branch,
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"changed_files": self.changed_files,
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"status": "running",
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"current_step": 0,
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"total_steps": 5,
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"steps": [],
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"findings": [],
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"severity_summary": {"critical": 0, "high": 0, "medium": 0, "low": 0},
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"openclaw_report": "",
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"ea_decision": {},
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"auto_fix_triggered": False,
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"started_at": self.started_at.isoformat(),
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"completed_at": None,
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"message": "",
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}
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self._sync_global()
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# ── State helpers ─────────────────────────────────────────────────────────
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def _sync_global(self):
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global _current_pipeline
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with _pipeline_lock:
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_current_pipeline = dict(self.state)
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def _step_start(self, num: int, name: str, agent: str):
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self.state["current_step"] = num
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self.state["steps"].append({
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"step": num,
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"name": name,
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"agent": agent,
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"status": "running",
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"started_at": datetime.now().isoformat(),
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"completed_at": None,
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"summary": "",
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})
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self._sync_global()
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logger.info("[CodeReview] ▶ Step %d/5 %s (%s)", num, name, agent)
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def _step_done(self, num: int, summary: str, ok: bool = True):
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for s in self.state["steps"]:
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if s["step"] == num:
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s["status"] = "ok" if ok else "error"
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s["completed_at"] = datetime.now().isoformat()
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s["summary"] = summary[:300]
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self._sync_global()
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logger.info("[CodeReview] %s Step %d — %s", "✓" if ok else "✗", num, summary[:100])
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def _finish(self, status: str, message: str):
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self.state["status"] = status
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self.state["completed_at"] = datetime.now().isoformat()
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self.state["message"] = message
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self._sync_global()
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# ── Main pipeline ─────────────────────────────────────────────────────────
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def run(self):
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"""Execute full pipeline. Designed to run in daemon thread."""
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try:
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self._notify_start()
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# Step 1 ─ read files
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self._step_start(1, "讀取變更檔案", "system")
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file_contents = self._read_changed_files()
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if not file_contents:
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self._step_done(1, "無有效 Python/YAML 變更，跳過 Review")
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self._finish("skipped", "無有效變更檔案")
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return
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self._step_done(1, f"讀取 {len(file_contents)} 個檔案")
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# Step 2 ─ Hermes scan
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self._step_start(2, "Hermes 程式碼掃描", "Hermes")
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findings = self._hermes_scan(file_contents)
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cnt = self.state["severity_summary"]
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self._step_done(2, f"CRITICAL={cnt['critical']} HIGH={cnt['high']} MEDIUM={cnt['medium']} LOW={cnt['low']}")
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# Step 3 ─ OpenClaw assessment
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self._step_start(3, "OpenClaw 架構品質評估", "OpenClaw")
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openclaw_report = self._openclaw_assess(file_contents, findings)
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self.state["openclaw_report"] = openclaw_report
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self._step_done(3, openclaw_report[:120] if openclaw_report else "（OpenClaw 未回應）")
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# Step 4 ─ ElephantAlpha orchestration
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self._step_start(4, "ElephantAlpha 決策協調", "ElephantAlpha")
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ea = self._ea_orchestrate(findings, openclaw_report)
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self.state["ea_decision"] = ea
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self._step_done(4, f"優先度={ea.get('priority','?')} auto_fix={ea.get('auto_fix',False)}")
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# Step 5 ─ NemoTron dispatch
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self._step_start(5, "NemoTron 行動派遣", "NemoTron")
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dispatch = self._nemotron_dispatch(ea, findings)
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self._step_done(5, f"寫入 {dispatch['actions']} 筆 action_plans，自動修復={'是' if dispatch['auto_fix'] else '否'}")
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# Persist + notify
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self._save_to_db(findings, openclaw_report, ea)
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self._notify_complete(findings, openclaw_report, ea)
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self._finish("completed", "Pipeline 執行完成")
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except Exception as e:
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logger.error("[CodeReview] Pipeline 例外: %s", e, exc_info=True)
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self._finish("error", str(e)[:200])
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self._notify_error(str(e))
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# ── Step 1：讀取檔案 ───────────────────────────────────────────────────────
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def _read_changed_files(self) -> Dict[str, str]:
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project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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contents: Dict[str, str] = {}
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for rel_path in self.changed_files[:8]: # 最多 8 個檔案
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abs_path = os.path.join(project_root, rel_path)
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try:
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with open(abs_path, encoding="utf-8", errors="ignore") as fh:
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raw = fh.read()
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contents[rel_path] = raw[:6000] + ("\n... (截斷)" if len(raw) > 6000 else "")
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except OSError:
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logger.debug("[CodeReview] 無法讀取 %s（部署路徑不同？）", rel_path)
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return contents
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# ── Step 2：Hermes 掃描 ───────────────────────────────────────────────────
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def _hermes_scan(self, files: Dict[str, str]) -> List[Dict]:
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"""走 OllamaService 三主機級聯：GCP-A → GCP-B → 111。"""
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try:
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files_text = "\n\n".join(
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f"### {name}\n```python\n{content}\n```"
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for name, content in list(files.items())[:4]
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)
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prompt = f"""你是資深程式碼審查工程師，請掃描以下程式碼並列出所有問題。
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{files_text}
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輸出格式：純 JSON 陣列，每項包含以下欄位：
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- severity: "CRITICAL" | "HIGH" | "MEDIUM" | "LOW"
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- type: "bug" | "security" | "performance" | "maintainability"
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- file: 檔案名稱
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- line_hint: 約略行號或函式名稱
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- description: 問題說明（繁體中文，精簡一句）
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- suggestion: 修復建議（繁體中文，精簡一句）
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只輸出 JSON 陣列，不含其他文字。無問題時輸出 []"""
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from services.ollama_service import OllamaService, get_host_label, get_provider_tag
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with log_ai_call(
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caller='code_review_hermes',
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provider='gcp_ollama',
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model=_HERMES_MODEL,
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request_id=f"cr-{self.commit_sha[:8]}",
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meta={'commit': self.commit_sha[:8], 'branch': self.branch,
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'files': len(files), 'route': 'ollama_first'},
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) as _ctx:
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ollama = OllamaService(model=_HERMES_MODEL)
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resp = ollama.generate(
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prompt=prompt,
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model=_HERMES_MODEL,
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temperature=0.1,
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timeout=CODE_REVIEW_OLLAMA_TIMEOUT,
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)
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actual_provider = get_provider_tag(resp.host or '')
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_ctx.set_provider(actual_provider)
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_ctx.set_tokens(
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input=resp.input_tokens,
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output=resp.output_tokens,
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)
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_ctx.add_meta('host', resp.host)
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_ctx.add_meta('host_label', get_host_label(resp.host or ''))
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if not resp.success:
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_ctx.set_error(resp.error or 'ollama generate failed')
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logger.warning("[CodeReview] Hermes Ollama 掃描失敗: %s", resp.error)
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return []
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raw = (resp.content or "").strip()
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match = re.search(r"\[.*\]", raw, re.DOTALL)
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if not match:
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logger.warning("[CodeReview] Hermes 回應無 JSON: %s", raw[:200])
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return []
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findings = json.loads(match.group())
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for f in findings:
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sev = f.get("severity", "LOW").lower()
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if sev in self.state["severity_summary"]:
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self.state["severity_summary"][sev] += 1
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self.state["findings"] = findings
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self._sync_global()
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return findings
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except Exception as e:
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logger.warning("[CodeReview] Hermes 掃描失敗: %s", e)
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return []
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# ── Step 3：OpenClaw 評估 ──────────────────────────────────────────────────
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def _openclaw_assess(self, files: Dict[str, str], findings: List[Dict]) -> str:
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"""
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路由優先序：
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L1 (預設) → Ollama GCP-A → GCP-B → 111
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L2 (flag CODE_REVIEW_USE_CLAUDE=true) → Claude Opus 4.7 雲端備援
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L3 (GEMINI_API_KEY 存在) → Gemini 雲端備援
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L4 (降級) → ElephantAlpha via NIM/OpenRouter
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"""
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sev = self.state["severity_summary"]
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findings_json = json.dumps(findings[:8], ensure_ascii=False, indent=2)
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files_list = "\n".join(f"- {k} ({len(v)} 字元)" for k, v in list(files.items())[:5])
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system = (
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"你是 OpenClaw 程式碼品質戰略分析師，以技術主管視角評估部署後程式碼。"
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"語言：繁體中文。風格：精準、數據導向、可執行建議。"
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)
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user_prompt = f"""【部署】Commit {self.commit_sha[:8]} @ {self.branch}
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【變更檔案】
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{files_list}
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【Hermes 掃描摘要】CRITICAL={sev['critical']} HIGH={sev['high']} MEDIUM={sev['medium']} LOW={sev['low']}
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【問題明細】
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{findings_json}
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請產出程式碼品質評估（使用 HTML <b> 標題，150字以內）：
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<b>🔍 整體風險等級</b>（一句理由）
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<b>⚠️ 最需關注問題</b>（TOP 2）
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<b>💡 架構優化方向</b>（1條長期建議）
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<b>✅ 本次部署亮點</b>"""
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# ── L1：Ollama-first — GCP-A → GCP-B → 111 ──────────────────────────
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from services.ollama_service import OllamaService, get_host_label, get_provider_tag
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with log_ai_call(
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caller='code_review_openclaw',
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provider='gcp_ollama',
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model=CODE_REVIEW_OLLAMA_MODEL,
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request_id=f"cr-{self.commit_sha[:8]}",
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meta={
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'commit': self.commit_sha[:8],
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'branch': self.branch,
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'route': 'ollama_first',
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},
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) as _ctx:
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ollama = OllamaService(model=CODE_REVIEW_OLLAMA_MODEL)
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resp = ollama.generate(
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prompt=user_prompt,
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system_prompt=system,
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model=CODE_REVIEW_OLLAMA_MODEL,
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temperature=0.2,
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timeout=CODE_REVIEW_OLLAMA_TIMEOUT,
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)
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actual_provider = get_provider_tag(resp.host or '')
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_ctx.set_provider(actual_provider)
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_ctx.set_tokens(input=resp.input_tokens, output=resp.output_tokens)
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_ctx.add_meta('host', resp.host)
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_ctx.add_meta('host_label', get_host_label(resp.host or ''))
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if resp.success and (resp.content or '').strip():
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return resp.content or ""
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_ctx.set_error(resp.error or 'ollama generate failed')
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_ctx.fallback_to_caller('code_review_openclaw')
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logger.warning(
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"[CodeReview] OpenClaw Ollama 三主機皆失敗，才啟用雲端備援: %s",
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resp.error,
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)
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# ── L1：Phase 7 Frontier — Claude Opus 4.7（程式碼能力 #1）────────────
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# feature flag 預設 OFF；ON 時只作 Ollama 失敗後的雲端備援。
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if CODE_REVIEW_USE_CLAUDE:
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try:
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from services.anthropic_service import anthropic_service
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except Exception as e:
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logger.warning("[CodeReview] Claude service import 失敗，改走 Gemini 備援: %s", e)
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anthropic_service = None # type: ignore
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if anthropic_service is not None and anthropic_service.is_available():
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with log_ai_call(
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caller='code_review_openclaw',
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provider='claude',
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model=CLAUDE_REVIEW_MODEL,
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request_id=f"cr-{self.commit_sha[:8]}",
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meta={
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'commit': self.commit_sha[:8],
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'branch': self.branch,
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'flag': 'CODE_REVIEW_USE_CLAUDE',
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},
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) as _ctx:
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resp = anthropic_service.generate(
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prompt=user_prompt,
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system_prompt=system, # ephemeral cache（5 分鐘 TTL，省 ~90% 成本）
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model=CLAUDE_REVIEW_MODEL,
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max_tokens=2048,
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temperature=0.2, # code review 要精確
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cache_system=True,
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timeout=120,
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)
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if resp.success:
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_ctx.set_tokens(input=resp.input_tokens, output=resp.output_tokens)
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_ctx.set_cache_hit(resp.cache_hit)
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_ctx.add_meta('cache_creation_tokens', resp.cache_creation_tokens)
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_ctx.add_meta('cache_read_tokens', resp.cache_read_tokens)
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return resp.content or ""
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# Claude 失敗 → fallback 到 Gemini 備援（L3）
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_ctx.set_error(resp.error or 'claude generate failed')
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_ctx.fallback_to_caller('code_review_openclaw_gemini')
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logger.warning(
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"[CodeReview] Claude 失敗，改走 Gemini 備援: %s", resp.error,
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)
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else:
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logger.info(
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"[CodeReview] CODE_REVIEW_USE_CLAUDE=true 但 Claude 不可用（缺 API key 或 SDK），改走 Gemini 備援",
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)
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# ── L3：Gemini — 僅作 Ollama/Claude 都失敗後的備援 ───────────────────
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if GEMINI_API_KEY:
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with log_ai_call(
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caller='code_review_openclaw_gemini',
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provider='gemini',
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model=REVIEW_MODEL,
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request_id=f"cr-{self.commit_sha[:8]}",
|
||
meta={
|
||
'commit': self.commit_sha[:8],
|
||
'branch': self.branch,
|
||
'fallback_from': 'code_review_openclaw_ollama',
|
||
},
|
||
) as _ctx:
|
||
try:
|
||
import google.generativeai as genai
|
||
genai.configure(api_key=GEMINI_API_KEY)
|
||
model = genai.GenerativeModel(
|
||
model_name=REVIEW_MODEL,
|
||
generation_config=genai.types.GenerationConfig(
|
||
temperature=0.3, max_output_tokens=1500,
|
||
),
|
||
system_instruction=system,
|
||
)
|
||
resp = model.generate_content(user_prompt, request_options={"timeout": 90})
|
||
try:
|
||
usage = getattr(resp, 'usage_metadata', None)
|
||
if usage is not None:
|
||
_ctx.set_tokens(
|
||
input=getattr(usage, 'prompt_token_count', 0) or 0,
|
||
output=getattr(usage, 'candidates_token_count', 0) or 0,
|
||
)
|
||
except Exception:
|
||
logger.debug("[CodeReview] Gemini usage metadata parse failed", exc_info=True)
|
||
return resp.text or ""
|
||
except Exception as e:
|
||
logger.warning("[CodeReview] OpenClaw Gemini 失敗，降級 ElephantAlpha: %s", e)
|
||
_ctx.set_error(f"{type(e).__name__}: {e}")
|
||
_ctx.fallback_to_caller('code_review_elephant')
|
||
|
||
# 降級：ElephantAlpha via OpenRouter（OPENROUTER_API_KEY 容器內一定有）
|
||
# Phase 1 v5.0 logger 追蹤
|
||
with log_ai_call(
|
||
caller='code_review_elephant',
|
||
provider='nim_via_elephant',
|
||
model='nvidia/llama-3.3-nemotron-super-49b-v1.5',
|
||
request_id=f"cr-{self.commit_sha[:8]}",
|
||
meta={'commit': self.commit_sha[:8], 'branch': self.branch},
|
||
) as _ctx:
|
||
try:
|
||
from services.elephant_service import elephant_service
|
||
resp = elephant_service.generate(
|
||
prompt=user_prompt,
|
||
system_prompt=system,
|
||
temperature=0.3,
|
||
timeout=90,
|
||
)
|
||
if resp.success:
|
||
# ElephantResponse 已含 input_tokens/output_tokens
|
||
_ctx.set_tokens(
|
||
input=getattr(resp, 'input_tokens', 0) or 0,
|
||
output=getattr(resp, 'output_tokens', 0) or 0,
|
||
)
|
||
return resp.content or ""
|
||
else:
|
||
_ctx.set_error(getattr(resp, 'error', 'elephant generate failed'))
|
||
except Exception as e:
|
||
logger.warning("[CodeReview] OpenClaw ElephantAlpha 降級也失敗: %s", e)
|
||
_ctx.set_error(f"{type(e).__name__}: {e}")
|
||
|
||
return ""
|
||
|
||
# ── Step 4：ElephantAlpha 決策 ─────────────────────────────────────────────
|
||
|
||
def _ea_orchestrate(self, findings: List[Dict], openclaw_report: str) -> Dict:
|
||
sev = self.state["severity_summary"]
|
||
critical_n = sev["critical"]
|
||
high_n = sev["high"]
|
||
|
||
# 嘗試呼叫 ElephantAlpha 做精細判斷
|
||
try:
|
||
from services.elephant_service import elephant_service
|
||
|
||
top3 = json.dumps(
|
||
[f for f in findings if f.get("severity") in ("CRITICAL", "HIGH")][:3],
|
||
ensure_ascii=False,
|
||
)
|
||
prompt = f"""你是 Elephant Alpha，負責協調 Code Review 後的修復決策。
|
||
|
||
【部署】commit={self.commit_sha[:8]} branch={self.branch}
|
||
【問題統計】CRITICAL={critical_n} HIGH={high_n} MEDIUM={sev['medium']} LOW={sev['low']}
|
||
【Top 問題】{top3}
|
||
【OpenClaw評估摘要】{openclaw_report[:300]}
|
||
|
||
請以 JSON 回答（不含其他文字）：
|
||
{{
|
||
"priority": "critical|high|medium|low",
|
||
"auto_fix": true|false,
|
||
"reasoning": "決策理由（繁體中文，一句話，需含具體數字）",
|
||
"fix_files": ["需自動修復的檔案（最多5個，所有有問題的檔案）"],
|
||
"human_review_needed": false
|
||
}}
|
||
|
||
規則（依 ADR-020 全自動修復政策，覆寫 ADR-012 L3 HITL 對 code review 的限制）：
|
||
- 任何 finding（不論 CRITICAL/HIGH/MEDIUM/LOW）→ auto_fix=true，human_review_needed=false
|
||
- 安全網是 Git revert + Gitea CI/CD 回滾，不依賴人工審查門檻
|
||
- priority 按最嚴重 severity 決定：CRITICAL>HIGH>MEDIUM>LOW
|
||
- fix_files 填入所有有問題的檔案（最多 5 個，AiderHeal 端會再限流）"""
|
||
|
||
resp = elephant_service.generate(
|
||
prompt=prompt,
|
||
json_mode=True,
|
||
temperature=0.1,
|
||
timeout=60,
|
||
)
|
||
if resp.success:
|
||
return self._guard_ea_decision(json.loads(resp.content), findings)
|
||
except Exception as e:
|
||
logger.warning("[CodeReview] ElephantAlpha 決策失敗，回退規則: %s", e)
|
||
|
||
# 規則 fallback：ADR-020 全自動修復政策。任何 finding 一律 auto_fix=true。
|
||
has_findings = len(findings) > 0
|
||
priority = (
|
||
"critical" if critical_n > 0 else
|
||
"high" if high_n > 0 else
|
||
"medium" if sev["medium"] > 0 else
|
||
"low" if sev["low"] > 0 else "low"
|
||
)
|
||
auto_fix = bool(has_findings and AUTO_FIX_ENABLED)
|
||
fix_files = list({
|
||
f.get("file", "") for f in findings if f.get("file")
|
||
})[:5]
|
||
|
||
return {
|
||
"priority": priority,
|
||
"auto_fix": auto_fix,
|
||
"reasoning": f"ADR-020 全自動修復：CRITICAL={critical_n} HIGH={high_n} MEDIUM={sev['medium']} LOW={sev['low']}，"
|
||
+ ("觸發 AiderHeal 自動修復（Git+CI/CD 為回滾安全網）" if auto_fix else "無 finding，無需修復"),
|
||
"fix_files": fix_files,
|
||
"human_review_needed": False,
|
||
}
|
||
|
||
def _guard_ea_decision(self, decision: Dict, findings: List[Dict]) -> Dict:
|
||
"""ADR-020 全自動修復政策：有 finding 一律 auto_fix=true，僅受 AUTO_FIX_ENABLED 主開關控制。"""
|
||
sev = self.state["severity_summary"]
|
||
priority = (decision.get("priority") or "").lower() or (
|
||
"critical" if sev["critical"] > 0 else
|
||
"high" if sev["high"] > 0 else
|
||
"medium" if sev["medium"] > 0 else
|
||
"low"
|
||
)
|
||
has_findings = bool(findings)
|
||
allowed_auto_fix = bool(has_findings and AUTO_FIX_ENABLED)
|
||
if has_findings and not AUTO_FIX_ENABLED:
|
||
logger.warning(
|
||
"[CodeReview] auto_fix 被 CODE_REVIEW_AUTO_FIX_ENABLED=false 主開關擋下 priority=%s",
|
||
priority,
|
||
)
|
||
|
||
decision["priority"] = priority
|
||
decision["auto_fix"] = allowed_auto_fix
|
||
decision["human_review_needed"] = False
|
||
decision["reasoning"] = (
|
||
f"{decision.get('reasoning', '')} "
|
||
f"[ADR-020 全自動修復: auto_fix={'enabled' if allowed_auto_fix else 'flag_disabled'}, priority={priority}]"
|
||
).strip()
|
||
return decision
|
||
|
||
# ── Step 5：NemoTron 派遣 ──────────────────────────────────────────────────
|
||
|
||
def _nemotron_dispatch(self, ea: Dict, findings: List[Dict]) -> Dict:
|
||
auto_fix = ea.get("auto_fix", False)
|
||
fix_files = ea.get("fix_files", [])
|
||
priority_map = {"critical": 1, "high": 2, "medium": 3, "low": 4}
|
||
priority_num = priority_map.get(ea.get("priority", "low"), 4)
|
||
|
||
actions_created = 0
|
||
session = get_session()
|
||
try:
|
||
# 每個需修復的檔案建立一筆 action_plan
|
||
for fpath in fix_files[:3]:
|
||
related = [f for f in findings if f.get("file") == fpath][:3]
|
||
desc = f"Code Review 修復：{fpath}｜{', '.join(f.get('description','')[:40] for f in related)}"
|
||
session.execute(text("""
|
||
INSERT INTO action_plans
|
||
(action_type, description, status, priority, metadata_json, created_at)
|
||
VALUES
|
||
('code_review_fix', :desc, :status, :priority, :meta, NOW())
|
||
"""), {
|
||
"desc": desc[:500],
|
||
"status": "auto_pending" if auto_fix else "auto_disabled",
|
||
"priority": priority_num,
|
||
"meta": json.dumps({
|
||
"pipeline_id": self.pipeline_id,
|
||
"commit_sha": self.commit_sha,
|
||
"file": fpath,
|
||
"auto_fix": auto_fix,
|
||
"ea_priority": ea.get("priority"),
|
||
"findings": related,
|
||
}, ensure_ascii=False),
|
||
})
|
||
actions_created += 1
|
||
session.commit()
|
||
except Exception as e:
|
||
logger.warning("[CodeReview] action_plans 寫入失敗: %s", e)
|
||
session.rollback()
|
||
finally:
|
||
session.close()
|
||
|
||
# 觸發 AiderHeal（非阻塞）
|
||
if auto_fix and fix_files:
|
||
self.state["auto_fix_triggered"] = True
|
||
self._sync_global()
|
||
self._trigger_aider_heal(findings, fix_files)
|
||
|
||
return {"actions": actions_created, "auto_fix": auto_fix}
|
||
|
||
def _trigger_aider_heal(self, findings: List[Dict], fix_files: List[str]):
|
||
"""非阻塞觸發 AiderHeal 自動修復"""
|
||
def _heal_worker():
|
||
try:
|
||
from services.aider_heal_executor import execute_code_fix
|
||
for fpath in fix_files[:2]: # 最多同時修 2 個檔案
|
||
related = [f for f in findings if f.get("file") == fpath]
|
||
if not related:
|
||
continue
|
||
worst = sorted(related, key=lambda x: {"CRITICAL":0,"HIGH":1,"MEDIUM":2,"LOW":3}.get(x.get("severity","LOW"),3))[0]
|
||
result = execute_code_fix(
|
||
error_type=f"code_review_{worst.get('type','bug')}",
|
||
error_message=worst.get("description", "Code Review 發現問題"),
|
||
target_file=fpath,
|
||
context={"suggestion": worst.get("suggestion", ""), "pipeline_id": self.pipeline_id},
|
||
)
|
||
logger.info("[CodeReview] AiderHeal %s → %s", fpath, result.get("message", ""))
|
||
except Exception as e:
|
||
logger.error("[CodeReview] AiderHeal 觸發失敗: %s", e)
|
||
|
||
t = threading.Thread(target=_heal_worker, daemon=True, name=f"aider-heal-{self.commit_sha[:8]}")
|
||
t.start()
|
||
|
||
# ── DB 持久化 ──────────────────────────────────────────────────────────────
|
||
|
||
def _save_to_db(self, findings: List[Dict], openclaw_report: str, ea: Dict):
|
||
session = get_session()
|
||
try:
|
||
row = session.execute(text("""
|
||
INSERT INTO ai_insights
|
||
(insight_type, content, confidence, created_by,
|
||
status, metadata_json, period, created_at)
|
||
VALUES
|
||
('code_review_result', :content, :conf, 'code_review_pipeline',
|
||
'active', :meta, :period, NOW())
|
||
RETURNING id
|
||
"""), {
|
||
"content": json.dumps({
|
||
"findings": findings,
|
||
"openclaw_report": openclaw_report,
|
||
"ea_decision": ea,
|
||
"severity_summary": self.state["severity_summary"],
|
||
}, ensure_ascii=False)[:8000],
|
||
"conf": 0.90,
|
||
"meta": json.dumps({
|
||
"pipeline_id": self.pipeline_id,
|
||
"commit_sha": self.commit_sha,
|
||
"branch": self.branch,
|
||
"changed_files": self.changed_files,
|
||
"auto_fix_triggered": self.state["auto_fix_triggered"],
|
||
}, ensure_ascii=False),
|
||
"period": datetime.now().strftime("%Y-%m-%d"),
|
||
}).fetchone()
|
||
session.commit()
|
||
if row:
|
||
try:
|
||
from services.openclaw_learning_service import enqueue_insight_embedding
|
||
enqueue_insight_embedding(row[0], "code_review_result", json.dumps({
|
||
"findings": findings,
|
||
"openclaw_report": openclaw_report,
|
||
"ea_decision": ea,
|
||
}, ensure_ascii=False), datetime.now().strftime("%Y-%m-%d"))
|
||
except Exception as embed_err:
|
||
logger.warning("[CodeReview] embedding queue enqueue failed: %s", embed_err)
|
||
logger.info("[CodeReview] ai_insights 寫入成功 pipeline=%s", self.pipeline_id)
|
||
except Exception as e:
|
||
logger.error("[CodeReview] DB 寫入失敗: %s", e)
|
||
session.rollback()
|
||
finally:
|
||
session.close()
|
||
|
||
# ── Telegram 通知 ─────────────────────────────────────────────────────────
|
||
|
||
def _notify_start(self):
|
||
try:
|
||
from services.telegram_templates import _send_telegram_raw
|
||
files_list = "\n".join(f" • {f}" for f in self.changed_files[:5])
|
||
if len(self.changed_files) > 5:
|
||
files_list += f"\n （+{len(self.changed_files)-5} 個）"
|
||
_send_telegram_raw(
|
||
f"🔍 <b>Code Review 啟動</b>\n"
|
||
f"══════════════════════════\n"
|
||
f"📦 Commit <code>{self.commit_sha[:8]}</code> 🌿 {self.branch}\n"
|
||
f"📝 變更檔案：\n{files_list}\n"
|
||
f"══════════════════════════\n"
|
||
f"🤖 <i>Hermes → OpenClaw → Elephant Alpha → NemoTron</i>\n"
|
||
f"📊 即時進度：https://mo.wooo.work/code-review/"
|
||
)
|
||
except Exception as e:
|
||
logger.warning("[CodeReview] 啟動通知失敗: %s", e)
|
||
|
||
def _notify_complete(self, findings: List[Dict], openclaw_report: str, ea: Dict):
|
||
try:
|
||
from services.telegram_templates import _send_telegram_raw
|
||
sev = self.state["severity_summary"]
|
||
priority = ea.get("priority", "medium")
|
||
auto_fix = ea.get("auto_fix", False)
|
||
|
||
icon = {"critical": "🔴", "high": "🟠", "medium": "🟡", "low": "🟢"}.get(priority, "🟡")
|
||
top_issues = [f for f in findings if f.get("severity") in ("CRITICAL", "HIGH")][:3]
|
||
issues_lines = "\n".join(
|
||
f" {'🔴' if f['severity']=='CRITICAL' else '🟠'} [{f['severity']}] {f.get('description','')} — <i>{f.get('file','')}</i>"
|
||
for f in top_issues
|
||
) or " ✅ 無高風險問題"
|
||
|
||
msg = (
|
||
f"{icon} <b>Code Review 完成</b> · <code>{self.commit_sha[:8]}</code>\n"
|
||
f"══════════════════════════\n"
|
||
f"🔴 CRITICAL <b>{sev['critical']}</b> "
|
||
f"🟠 HIGH <b>{sev['high']}</b> "
|
||
f"🟡 MEDIUM <b>{sev['medium']}</b> "
|
||
f"🟢 LOW <b>{sev['low']}</b>\n"
|
||
f"══════════════════════════\n"
|
||
f"<b>⚠️ 主要問題</b>\n{issues_lines}\n"
|
||
)
|
||
if openclaw_report:
|
||
msg += f"\n{openclaw_report[:400]}\n"
|
||
|
||
if auto_fix:
|
||
fix_status = "🔧 已觸發自動修復（AiderHeal）"
|
||
elif sev['critical'] + sev['high'] + sev['medium'] + sev['low'] == 0:
|
||
fix_status = "✅ 無需修復動作"
|
||
else:
|
||
fix_status = "🛑 自動修復主開關關閉（CODE_REVIEW_AUTO_FIX_ENABLED=false）"
|
||
msg += (
|
||
f"══════════════════════════\n"
|
||
f"🤖 Elephant Alpha：<b>{priority.upper()}</b> {fix_status}\n"
|
||
f"📊 完整報告：https://mo.wooo.work/code-review/"
|
||
)
|
||
_send_telegram_raw(msg)
|
||
except Exception as e:
|
||
logger.warning("[CodeReview] 完成通知失敗: %s", e)
|
||
|
||
def _notify_error(self, error: str):
|
||
try:
|
||
from services.telegram_templates import _send_telegram_raw
|
||
_send_telegram_raw(
|
||
f"🚨 <b>Code Review Pipeline 失敗</b>\n"
|
||
f"Commit：<code>{self.commit_sha[:8]}</code> @ {self.branch}\n"
|
||
f"錯誤：{error[:200]}\n"
|
||
f"📊 查看：https://mo.wooo.work/code-review/"
|
||
)
|
||
except Exception as exc:
|
||
logger.warning("[CodeReview] 失敗通知發送失敗: %s", exc, exc_info=True)
|
||
|
||
|
||
# ═══════════════════════════════════════════════════════════════════════════════
|
||
# 公開 API
|
||
# ═══════════════════════════════════════════════════════════════════════════════
|
||
|
||
def trigger_post_deploy_review(
|
||
commit_sha: str,
|
||
changed_files: List[str],
|
||
branch: str = "main",
|
||
deploy_type: str = "sync",
|
||
) -> str:
|
||
"""
|
||
啟動 Pipeline（後台 daemon thread）。
|
||
回傳 pipeline_id。由 routes/code_review_routes.py 的 webhook 端點呼叫。
|
||
"""
|
||
pipeline = CodeReviewPipeline(commit_sha, changed_files, branch, deploy_type)
|
||
t = threading.Thread(
|
||
target=pipeline.run,
|
||
daemon=True,
|
||
name=f"code-review-{commit_sha[:8]}",
|
||
)
|
||
t.start()
|
||
logger.info("[CodeReview] 已派發 pipeline=%s files=%d", pipeline.pipeline_id, len(pipeline.changed_files))
|
||
return pipeline.pipeline_id
|
||
|
||
|
||
def get_current_state() -> Dict[str, Any]:
|
||
"""前端 polling 用：取得目前 pipeline 即時狀態"""
|
||
with _pipeline_lock:
|
||
return dict(_current_pipeline)
|
||
|
||
|
||
def get_history(limit: int = 20) -> List[Dict]:
|
||
"""取得 ai_insights 中歷史 code_review_result 記錄"""
|
||
session = get_session()
|
||
try:
|
||
rows = session.execute(text("""
|
||
SELECT id, content, confidence, metadata_json, created_at, status
|
||
FROM ai_insights
|
||
WHERE insight_type = 'code_review_result'
|
||
ORDER BY created_at DESC
|
||
LIMIT :lim
|
||
"""), {"lim": limit}).fetchall()
|
||
|
||
results = []
|
||
for r in rows:
|
||
meta, content = {}, {}
|
||
try:
|
||
meta = json.loads(r[3]) if r[3] else {}
|
||
content = json.loads(r[1]) if r[1] else {}
|
||
except Exception:
|
||
logger.debug("[CodeReview] history row JSON decode failed id=%s", r[0], exc_info=True)
|
||
sev = content.get("severity_summary", {})
|
||
results.append({
|
||
"id": r[0],
|
||
"pipeline_id": meta.get("pipeline_id", ""),
|
||
"commit_sha": meta.get("commit_sha", "")[:8],
|
||
"branch": meta.get("branch", ""),
|
||
"changed_files": meta.get("changed_files", []),
|
||
"severity_summary": sev,
|
||
"total_issues": sum(sev.values()),
|
||
"auto_fix": meta.get("auto_fix_triggered", False),
|
||
"findings": content.get("findings", []),
|
||
"openclaw_report": content.get("openclaw_report", ""),
|
||
"ea_decision": content.get("ea_decision", {}),
|
||
"created_at": r[4].isoformat() if r[4] else "",
|
||
"status": r[5] or "active",
|
||
})
|
||
return results
|
||
except Exception as e:
|
||
logger.warning("[CodeReview] 歷史讀取失敗: %s", e)
|
||
return []
|
||
finally:
|
||
session.close()
|
||
|
||
|
||
def verify_internal_token(request_token: str) -> bool:
|
||
"""驗證 CD webhook 來源 token。Production 預設必填，避免外部觸發 auto-review/fix 鏈。"""
|
||
if not INTERNAL_TOKEN:
|
||
if ALLOW_INSECURE_WEBHOOK:
|
||
logger.warning("[CodeReview] INTERNAL_WEBHOOK_TOKEN 未設定，僅因 dev override 放行")
|
||
return True
|
||
logger.error("[CodeReview] INTERNAL_WEBHOOK_TOKEN 未設定，拒絕 webhook")
|
||
return False
|
||
return request_token == INTERNAL_TOKEN
|