#!/usr/bin/env python3
"""
小唯主动学习体系 — 长期学习计划
================================
四个维度:
  1. 现有工作优化 (optimizer / skill-manager)
  2. 新工具/新技能探索 (skill-scan)
  3. 业务领域知识积累 (operation/product/growth research)
  4. 系统智能化 (self-evolve / learner — 已有)

用法:
  python3 proactive_learning.py report      → 产出自检报告
  python3 proactive_learning.py learn        → 执行全部学习维度的检查
  python3 proactive_learning.py status       → 查看四个维度的当前状态
"""

import json, os, sys, subprocess
from datetime import datetime, timezone

HOME = os.path.expanduser("~")
HERMES = HOME + "/.hermes"
D = HERMES + "/daemon"
LEARN_DIR = HERMES + "/proactive_learning"
STATE_FILE = LEARN_DIR + "/state.json"
os.makedirs(LEARN_DIR, exist_ok=True)


def log(msg):
    ts = datetime.now().strftime("%H:%M:%S")
    print(f"[PROLEARN] {ts} {msg}", flush=True)


def load_state():
    if os.path.exists(STATE_FILE):
        with open(STATE_FILE) as f:
            return json.load(f)
    return {
        "dimensions": {
            "existing_work":  {"last_run": None, "status": "pending", "findings": []},
            "new_tools":     {"last_run": None, "status": "pending", "findings": []},
            "domain_knowledge": {"last_run": None, "status": "pending", "topics": []},
            "system_smart":  {"last_run": None, "status": "ok"},
        },
        "cycles": 0,
        "created_at": datetime.now(timezone.utc).isoformat(),
    }


def save_state(state):
    with open(STATE_FILE, "w") as f:
        json.dump(state, f, ensure_ascii=False, indent=2)


def shell(cmd, timeout=15):
    try:
        r = subprocess.run(cmd, shell=True, capture_output=True, text=True, timeout=timeout)
        return r.returncode, r.stdout.strip()[:500], r.stderr.strip()[:200]
    except subprocess.TimeoutExpired:
        return -1, "", "timeout"


# ===================== 维度1: 现有工作优化 =====================

def check_existing_work(state):
    """检查 skill 健康分 / optimizer 报告 / daemon 错误日志"""
    dim = state["dimensions"]["existing_work"]
    dim["status"] = "running"

    findings = []

    # 1. Skill 健康分
    rc, out, err = shell("python3 ~/.hermes/scripts/skill-manager.py scan --quiet", timeout=30)
    if rc == 0:
        findings.append("✅ skill-manager 扫描正常")
    else:
        findings.append(f"⚠️ skill-manager 异常: {err or out}")

    # 2. Optimizer 报告
    opt_report = HERMES + "/optimization-report.json"
    if os.path.exists(opt_report):
        mtime = datetime.fromtimestamp(os.path.getmtime(opt_report), tz=timezone.utc)
        age_h = (datetime.now(timezone.utc) - mtime).total_seconds() / 3600
        findings.append(f"📊 optimizer 报告 {age_h:.1f}h 前更新")
    else:
        findings.append("ℹ️ optimizer 报告尚无历史数据")

    # 3. Daemon journal 近期错误
    journal = D + "/journal.jsonl"
    recent_errors = []
    if os.path.exists(journal):
        lines = open(journal).readlines()
        for line in lines[-100:]:
            try:
                entry = json.loads(line)
                if entry.get("type") == "error" or "error" in entry.get("message", "").lower():
                    recent_errors.append(entry.get("message", "")[:80])
            except:
                pass
    if recent_errors:
        findings.append(f"⚠️ daemon journal 近100条中 {len(recent_errors)} 条错误")
    else:
        findings.append("✅ daemon journal 无错误")

    dim["findings"] = findings
    dim["last_run"] = datetime.now(timezone.utc).isoformat()
    dim["status"] = "ok"
    return findings


# ===================== 维度2: 新工具/新技能探索 =====================

def check_new_tools(state):
    """扫描 skills 目录，识别低分/缺失领域，提出新技能建议"""
    dim = state["dimensions"]["new_tools"]
    dim["status"] = "running"

    findings = []

    # 读取 skill-manager 评分
    rc, out, err = shell("python3 ~/.hermes/scripts/skill-manager.py scan", timeout=30)
    skill_json = HERMES + "/skill-health.json"

    low_score_skills = []
    if os.path.exists(skill_json):
        data = json.load(open(skill_json))
        for cat in data.get("categories", {}).values():
            for skill in cat.get("skills", []):
                if skill.get("score", 10) < 6:
                    low_score_skills.append(f"{skill['name']}({skill['score']})")

    if low_score_skills:
        findings.append(f"📉 低分技能({len(low_score_skills)}): {', '.join(low_score_skills[:5])}")
    else:
        findings.append("✅ 技能评分无明显短板")

    # 扫描 skills 目录，列出最近添加
    skills_dir = HERMES + "/skills"
    all_skills = []
    if os.path.exists(skills_dir):
        for root, dirs, files in os.walk(skills_dir):
            for f in files:
                if f == "SKILL.md":
                    skill_name = os.path.basename(root)
                    mtime = os.path.getmtime(os.path.join(root, f))
                    all_skills.append((skill_name, mtime))

    all_skills.sort(key=lambda x: x[1], reverse=True)
    recent = all_skills[:5]
    findings.append(f"📦 共 {len(all_skills)} 个 skill，最近: {', '.join([s[0] for s in recent])}")

    dim["findings"] = findings
    dim["last_run"] = datetime.now(timezone.utc).isoformat()
    dim["status"] = "ok"
    return findings


# ===================== 维度3: 业务领域知识积累 =====================

def check_domain_knowledge(state):
    """检查领域知识积累状态"""
    dim = state["dimensions"]["domain_knowledge"]
    dim["status"] = "running"

    findings = []
    topics_file = LEARN_DIR + "/topics.json"

    topics = []
    if os.path.exists(topics_file):
        topics = json.load(open(topics_file)).get("topics", [])

    if not topics:
        findings.append("ℹ️ 尚未定义学习主题（请告诉我想深入的方向）")
    else:
        for t in topics:
            status = t.get("status", "pending")
            last = t.get("last_research", "从未")
            findings.append(f"📚 {t['name']}: {status}（上次: {last}）")

    dim["topics"] = topics
    dim["last_run"] = datetime.now(timezone.utc).isoformat()
    dim["status"] = "ok"
    return findings


# ===================== 维度4: 系统智能化 =====================

def check_system_smart(state):
    """检查 self-evolve / learner 运行状态"""
    dim = state["dimensions"]["system_smart"]
    dim["status"] = "running"

    findings = []

    # self-evolve 最近运行
    rc, out, _ = shell("ls -t ~/.hermes/*.log 2>/dev/null | head -1", timeout=5)
    if rc == 0 and out:
        findings.append(f"📝 最近日志: {os.path.basename(out)}")
    else:
        findings.append("ℹ️ 暂无运行日志")

    dim["findings"] = findings
    dim["last_run"] = datetime.now(timezone.utc).isoformat()
    dim["status"] = "ok"
    return findings


# ===================== 统一执行 =====================

def run_all_checks():
    state = load_state()
    state["cycles"] += 1

    results = {}
    results["existing_work"] = check_existing_work(state)
    results["new_tools"] = check_new_tools(state)
    results["domain_knowledge"] = check_domain_knowledge(state)
    results["system_smart"] = check_system_smart(state)

    save_state(state)

    # 输出报告
    report = f"**小唯主动学习报告** #{state['cycles']}\n"
    report += f"时间: {datetime.now().strftime('%Y-%m-%d %H:%M')}\n\n"

    labels = {
        "existing_work": "🔧 现有工作优化",
        "new_tools": "🛠️ 新工具/新技能",
        "domain_knowledge": "📖 业务领域知识",
        "system_smart": "🧠 系统智能化",
    }

    for key, label in labels.items():
        report += f"**{label}**\n"
        for f in results[key]:
            report += f"  {f}\n"
        report += "\n"

    return report


if __name__ == "__main__":
    cmd = sys.argv[1] if len(sys.argv) > 1 else "report"

    if cmd == "report":
        print(run_all_checks())
    elif cmd == "status":
        state = load_state()
        print(json.dumps(state["dimensions"], ensure_ascii=False, indent=2))
    elif cmd == "learn":
        print(run_all_checks())
    else:
        print(f"用法: proactive_learning.py [report|status|learn]")