#!/usr/bin/env python3
"""skill-curator 周审计 — 本地 LLM 版（替代云 API agent 模式 cron）
跑 skill-curator.py --report → 本地 7B 分析报告 → 推飞书
用法:
  python3 skill_curator_local.py           # 审计+分析+推送
  python3 skill_curator_local.py --dry     # 仅分析不推送
"""
import json, os, sys, subprocess, urllib.request
from pathlib import Path

for _ in (sys.stdout, sys.stderr):
    try: _.reconfigure(encoding='utf-8', errors='replace')
    except Exception: pass

HOME = Path.home()
SCRIPTS = HOME / ".hermes" / "scripts"
REPORT = HOME / ".hermes" / "skill-curator-report.json"
LLM_URL = "https://apihub.agnes-ai.com/v1/chat/completions"
FEISHU_WEBHOOK = "https://open.feishu.cn/open-apis/bot/v2/hook/446db983-e392-4d2c-bfb8-f9060e5df3ad"


def send_feishu(title: str, content: str):
    card_obj = {
        "header": {"title": {"tag": "plain_text", "content": title}, "template": "orange"},
        "elements": [{"tag": "markdown", "content": content}],
    }
    payload = json.dumps({"msg_type": "interactive", "card": json.dumps(card_obj, ensure_ascii=False)}).encode()
    req = urllib.request.Request(FEISHU_WEBHOOK, data=payload, headers={"Content-Type": "application/json"})
    try:
        with urllib.request.urlopen(req, timeout=10):
            return True
    except Exception as e:
        print(f"[warn] 飞书推送失败: {e}", file=sys.stderr)
        return False


def run_audit():
    """运行 skill-curator 审计，返回报告 JSON 字符串"""
    r = subprocess.run(
        [sys.executable, str(SCRIPTS / "skill-curator.py"), "--report"],
        capture_output=True, text=True, timeout=60,
        cwd=str(SCRIPTS)
    )
    if REPORT.exists():
        try:
            return REPORT.read_text(encoding="utf-8", errors="ignore")[:4000]
        except Exception:
            pass
    return r.stdout.strip()[:4000]


def llm_analyze(report_text):
    """本地 LLM 分析技能审计报告"""
    prompt = f"""你是小唯。分析技能审计报告，给出清理建议。

技能审计报告：
{report_text}

请输出（简洁，按优先级排序）：
🔧 技能清理建议

【优先清理】
- 列出 Tier 3 归档候选，判断是否该清理（保留理由/删除理由）

【需要合并】
- 列出重叠对，判断哪些需要合并

【需要补/归档】
- 缺版本号的技能是否该补或归档

要求：直接给结论和理由，不废话。"""

    payload = json.dumps({
        "model": "agnes-2.5-flash",
        "messages": [{"role": "user", "content": prompt}],
        "temperature": 0.4,
        "max_tokens": 500,
    }).encode("utf-8")
    req = urllib.request.Request(LLM_URL, data=payload, headers={"Content-Type": "application/json", "Authorization": "Bearer sk-7k9e9KGcoZdDuYt2LSA4YXdBTioczleGJm2zzLWCku072ikW"}, method="POST")
    try:
        with urllib.request.urlopen(req, timeout=180) as resp:
            data = json.loads(resp.read().decode("utf-8"))
        return data["choices"][0]["message"]["content"]
    except Exception as e:
        print(f"[error] 本地 LLM 调用失败: {e}", file=sys.stderr)
        return None


def main():
    dry = "--dry" in sys.argv

    print("1. 运行技能审计...")
    report = run_audit()
    print(f"   报告 {len(report)} 字符")

    print("2. 本地 LLM 分析...")
    analysis = llm_analyze(report)
    if not analysis:
        print("[error] 分析失败", file=sys.stderr)
        sys.exit(1)
    print(f"   分析 {len(analysis)} 字符")

    if dry:
        print("\n=== 分析结果 ===\n")
        print(analysis)
    else:
        print("3. 推送飞书...")
        ok = send_feishu("🔧 技能清理建议", analysis)
        print(f"   推送: {'✅' if ok else '❌'}")


if __name__ == "__main__":
    main()