"""训练控制台（本地网页，零第三方依赖，离线可用）：一键开始全流程、看进度、可停止。
  双击 ml/console.bat（Windows）或运行 bash ml/console.sh（Linux/WSL）→ 自动打开 http://localhost:8100
  也可：python -m ml.monitor [--port 8100] [--host 0.0.0.0] [--open]
网页上点「开始训练」→ 选参数 → 后台执行 bash ml/pipeline.sh all（已完成的阶段自动跳过 = 续跑；勾「从头重跑」= FRESH=1），
输出写 ml/runs/console.log，网页实时显示；「停止」结束整个进程树。网页和控制台窗口关掉都不影响训练，重新打开即可继续看。
只读数据来源：
  ml/runs/pipeline.json          各阶段开始/结束/返回码（pipeline.sh 自动写）→ 全流程进度
  ml/runs/*/log.jsonl            预训练（base / wta / bench_*）与 APG（apg / apg_r*）逐步日志与闭环评估
  ml/runs/m5_gate_*.json、mine/r*/report.json + gate.json、policy_bench.json、acceptance.json
  ml/data/stats.json / consistency.json / r2.json / samples/index.json、nvidia-smi
安全：默认只监听 127.0.0.1；--host 0.0.0.0 时其他机器只能看，开始/停止只接受本机请求（--remote-control 放开）。
2026-10-18 新增（用户要求：训练全程可视化，并在网页上点按钮一键开始）。
2026-10-18 第五轮（审查第四轮）：
  N-7 是否在跑看 ml/runs/pipeline.lock（与终端同一把锁），不再靠"日志 120 s 内有更新"去猜；
  N-8 开始/停止要求自定义头 X-Console + 同源 Origin/Sec-Fetch-Site，外站网页发不进来；
  N-10 启动自检（训练用 Python 能否 import torch、GPU、node、bash），不过就拒绝「开始训练」并在顶栏标红；
  N-11 Windows 子进程用 CREATE_NO_WINDOW 自带隐藏控制台：关掉控制台黑窗口训练照跑，重开控制台可接着看、可停止；
  N-9 生成阶段的行数按文件增量统计（只读新增字节），其他阶段不扫 shard；
  N-12 停止后的状态改写走 ml.pstate（单一写者、原子替换）；N-14 阶段名/估时/权重由 ml.pstate.STAGES 下发。"""
import argparse, glob, json, os, re, shutil, signal, subprocess, sys, threading, time, webbrowser
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from ml import pstate
from http.server import ThreadingHTTPServer, BaseHTTPRequestHandler
from urllib.parse import urlparse, parse_qs

ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
HTML = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'monitor.html')
RUNS, DATA = 'ml/runs', 'ml/data'


def jload(p):
    try:
        with open(p, encoding='utf-8') as f: return json.load(f)
    except Exception: return None


def kind_of(name):
    if name.startswith('apg'): return 'apg'
    if name.startswith('bench'): return 'bench'
    return 'train'


def list_runs():
    out = []
    for f in glob.glob(os.path.join(ROOT, RUNS, '*', 'log.jsonl')):
        d = os.path.basename(os.path.dirname(f)); st = os.stat(f)
        out.append({'name': d, 'kind': kind_of(d), 'size': st.st_size, 'mtime': st.st_mtime,
                    'has_best': os.path.exists(os.path.join(os.path.dirname(f), 'best.pt')),
                    'diverged': os.path.exists(os.path.join(os.path.dirname(f), 'diverged.pt'))})
    out.sort(key=lambda r: -r['mtime'])
    return out


def read_log(name, offset):
    if not re.fullmatch(r'[\w.\-]+', name or ''): return {'error': 'bad run'}
    f = os.path.join(ROOT, RUNS, name, 'log.jsonl')
    if not os.path.exists(f): return {'error': 'no log'}
    size = os.path.getsize(f)
    if offset > size: offset = 0                      # 日志被新训练覆盖 → 从头读
    recs = []
    with open(f, 'rb') as fh:
        fh.seek(offset); buf = fh.read(min(size - offset, 64 << 20))
    end = buf.rfind(b'\n') + 1                         # 只取完整行，半行留到下次
    for line in buf[:end].decode('utf-8', 'replace').splitlines():
        if line.strip():
            try: recs.append(json.loads(line))
            except Exception: pass
    return {'records': recs, 'offset': offset + end, 'size': size, 'reset': offset == 0, 'mtime': os.path.getmtime(f)}


_CPU = {'v': {}}


class CpuSampler(threading.Thread):
    """后台每秒阻塞采样一次 CPU。cpu_percent 是"距上次调用"的差值：放在请求里算，窗口取决于两次
    HTTP 请求的间隔（网页 1 秒轮询 + 手动 curl 会把它压成几毫秒，读数恒为 0）——所以单独一个线程按固定
    1 秒窗口取，status 只读最近一次。"""
    def __init__(self): super().__init__(daemon=True); self.start()

    def run(self):
        try:
            import psutil
            psutil.cpu_percent(interval=None, percpu=True)          # 打桩：第一次恒为 0，丢掉
            while True:
                per = psutil.cpu_percent(interval=1.0, percpu=True)
                _CPU['v'] = {'total': round(sum(per) / max(1, len(per)), 1), 'per': [round(x) for x in per], 'n': len(per)}
        except Exception:
            _CPU['v'] = {}


def cpu():
    return _CPU['v']


_GPU_CACHE = {'t': 0.0, 'v': []}


def gpu():
    # 网页 1 秒轮询：nvidia-smi 每次要 150–600 ms，缓存 2 秒（GPU 数字不需要更快），避免每轮都起子进程
    if time.time() - _GPU_CACHE['t'] < 2.0: return _GPU_CACHE['v']
    try:
        q = 'name,utilization.gpu,memory.used,memory.total,temperature.gpu,power.draw'
        r = subprocess.run(['nvidia-smi', f'--query-gpu={q}', '--format=csv,noheader,nounits'], capture_output=True, text=True, timeout=3)
        out = []
        for line in r.stdout.strip().splitlines():
            n, u, mu, mt, t, p = [x.strip() for x in line.split(',')]
            num = lambda x: float(x) if re.fullmatch(r'[\d.]+', x) else None
            out.append({'name': n, 'util': num(u), 'mem_used': num(mu), 'mem_total': num(mt), 'temp': num(t), 'power': num(p)})
    except Exception:
        out = []
    _GPU_CACHE.update(t=time.time(), v=out)
    return out


def last_rec(name):
    """读日志最后一条非评估记录（只读文件尾 16 KB）。"""
    f = os.path.join(ROOT, RUNS, name, 'log.jsonl')
    try:
        with open(f, 'rb') as fh:
            fh.seek(0, 2); n = fh.tell(); fh.seek(max(0, n - 16384)); tail = fh.read().decode('utf-8', 'replace').splitlines()
        for line in reversed(tail):
            try:
                r = json.loads(line)
                if 'eval' not in r: return r
            except Exception: pass
    except Exception: pass
    return None


class LineCount:
    """按文件增量数行：记住每个文件已读到的偏移与行数，只读新增字节（审查 N-9：此前每 5 s 全量重读全部 shard）。"""
    def __init__(self): self.c = {}; self.lock = threading.Lock()

    def count(self, f):
        with self.lock:
            try: size = os.path.getsize(f)
            except OSError: return 0
            off, n = self.c.get(f, (0, 0))
            if size < off: off, n = 0, 0
            if size > off:
                with open(f, 'rb') as fh:
                    fh.seek(off)
                    while True:
                        b = fh.read(1 << 22)
                        if not b: break
                        n += b.count(b'\n'); off += len(b)
                self.c[f] = (off, n)
            return n


LC = LineCount()


def newer(pattern, t0):
    return [f for f in glob.glob(os.path.join(ROOT, pattern)) if os.path.getmtime(f) >= t0 - 1]


def stage_progress(st, s):
    """当前阶段的进度：返回 {'frac': 0..1 或 None（无法计量）, 'label': 文字}。"""
    t0, info = s['start'], s.get('info') or {}
    if st == 'gen':
        # 分子算全部（含之前轮次已完成的分片），分母是累计目标：补量时显示 50,008/79,688 而不是 0/79,688。
        # 2026-10-18 实测：只统计本轮开始后改过的文件会让"补量"看起来像从零开始。
        allf = glob.glob(os.path.join(ROOT, DATA, 'shard_*.jsonl')) + glob.glob(os.path.join(ROOT, DATA, 'shard_*.jsonl.part'))
        n = sum(LC.count(f) for f in allf)
        tgt = info.get('target_tasks') or 0
        new = sum(LC.count(f) for f in newer(f'{DATA}/shard_*.jsonl', t0) + newer(f'{DATA}/shard_*.jsonl.part', t0))
        lab = f'已生成 {n:,} / {tgt:,} 条任务' + (f'（本轮补 {new:,} 条）' if 0 < new < n else '')
        return {'frac': min(1, n / tgt) if tgt else None, 'label': lab}
    if st == 'prep':
        nsh = len(glob.glob(os.path.join(ROOT, DATA, 'shard_*.jsonl')))
        done = len(newer(f'{DATA}/samples/*.X.npy', t0))
        if os.path.exists(os.path.join(ROOT, DATA, 'r2.json')) and newer(f'{DATA}/r2.json', t0): return {'frac': 1, 'label': '打包完成，R2 检查完成'}
        return {'frac': min(0.95, done / nsh) if nsh else None, 'label': f'已打包 {done} / {nsh} 个分片' + ('，R2 检查中' if nsh and done >= nsh else '')}
    if st == 'train':
        tag, bs = info.get('tag', 'base'), info.get('bench_steps', 2000)
        b, m = last_rec(f'bench_{tag}') if newer(f'{RUNS}/bench_{tag}/log.jsonl', t0) else None, last_rec(tag) if newer(f'{RUNS}/{tag}/log.jsonl', t0) else None
        if m and m.get('total'):
            return {'frac': (bs + m['step']) / (bs + m['total']), 'label': f'正式训练 {m["step"]:,} / {m["total"]:,} 步', 'run': tag}
        if b: return {'frac': b['step'] / (bs + 60000), 'label': f'测速 {b["step"]:,} / {bs:,} 步', 'run': f'bench_{tag}'}
        return {'frac': 0, 'label': '加载数据中'}
    if st == 'apg':
        r = last_rec('apg') if newer(f'{RUNS}/apg/log.jsonl', t0) else None
        return {'frac': r['it'] / r['total'] if r and r.get('total') else 0, 'label': f'APG {r["it"]:,} / {r["total"]:,} 步' if r else '准备中', 'run': 'apg'}
    if st == 'mine':
        R = info.get('rounds', 6)
        k = len(newer(f'{RUNS}/mine/r*/gate.json', t0))
        cur = sorted(newer(f'{RUNS}/apg_r*/log.jsonl', t0), key=os.path.getmtime)
        frac_in, lab = 0, f'第 {k + 1} 轮：挖错出题'
        if cur and len(cur) > k:
            name = os.path.basename(os.path.dirname(cur[-1])); r = last_rec(name)
            if r and r.get('total'): frac_in = 0.3 + 0.6 * r['it'] / r['total']; lab = f'第 {k + 1} 轮：APG {r["it"]:,} / {r["total"]:,} 步'
            return {'frac': min(1, (k + frac_in) / R), 'label': f'{lab}（共最多 {R} 轮，提升不足会提前停）', 'run': name}
        return {'frac': min(1, k / R), 'label': f'{lab}（共最多 {R} 轮，提升不足会提前停）'}
    if st == 'm5':
        tag = info.get('tag', 'base')
        n = len(newer(f'{RUNS}/m5_{tag}_policy.json', t0)) + len(newer(f'{RUNS}/m5_{tag}_safety.json', t0))
        return {'frac': n / 2, 'label': ['纯策略评估中', '加安全层评估中', '汇总'][min(n, 2)]}
    return {'frac': None, 'label': '进行中'}


def pipeline():
    d = jload(os.path.join(ROOT, RUNS, 'pipeline.json'))
    if not d: return None
    cur = d.get('current')
    if cur and cur in d['stages']:
        try: d['progress'] = stage_progress(cur, d['stages'][cur])
        except Exception as e: d['progress'] = {'frac': None, 'label': f'进度读取失败：{e}'}
    return d


def status():
    P = lambda *a: os.path.join(ROOT, *a)
    mine = []
    for d in sorted(glob.glob(P(RUNS, 'mine', 'r*')), key=lambda x: int(re.sub(r'\D', '', os.path.basename(x)) or 0)):
        rep, gate = jload(os.path.join(d, 'report.json')), jload(os.path.join(d, 'gate.json'))
        if rep or gate:
            mine.append({'round': os.path.basename(d), 'report': rep and {k: rep.get(k) for k in ('n', 'E1', 'E2', 'E3', 'E4', 'E5', 'ok', 'pool')},
                         'gate': gate and {k: gate.get(k) for k in ('gain_pp', 'A_drop_pp', 'fixed_kept', 'R7_left_share_shift_pp', 'R7_travel_median_ratio', 'accept')}})
    stats = jload(P(DATA, 'stats.json'))
    if stats: stats = {k: stats.get(k) for k in ('tasks', 'keep', 'gapDrop', 'minGapFilterMm', 'keepRate', 'samplesEvery3', 'samplesPerTask', 'projectedSamplesFor50k', 'consensusDrop', 'vertexMinGapMm', 'execS', 'travelDeg')}
    shards = glob.glob(P(DATA, 'shard_*.jsonl'))
    pl = pipeline()
    if pl and pl.get('current') == 'gen':    # 只在生成阶段数行（增量）；其他阶段用 stats.json 的 tasks
        gen_lines = sum(LC.count(f) for f in shards + glob.glob(P(DATA, 'shard_*.jsonl.part')))
    else: gen_lines = (stats or {}).get('tasks') or 0
    pb = jload(P(RUNS, 'policy_bench.json'))
    if pb: pb = {k: {kk: v.get(kk) for kk in ('n', 'ok', 'reached', 'collisionFrames', 'brakeRate', 'recoveryRate', 'livelock', 'inferMsP99', 'safetyMsP99')}
                 for k, v in pb.items() if isinstance(v, dict) and 'n' in v}
    return {'now': time.time(), 'gpu': gpu(), 'cpu': cpu(),
            'vram_budget_gb': float(os.environ.get('VRAM_BUDGET_GB', 20)),      # 本机桌面常驻占 4–5 GB，给训练的预算 19–20 GB
            'pipeline': pl, 'check': CHECK.get(), 'lock': lock_info(),   # 2026-10-18 第八轮修：上一版这三项被行尾注释吞掉，网页步骤条/锁状态拿不到
            'stage_meta': [{'id': k, 'name': n, 'est_h': h, 'timeout_h': pstate.TIMEOUT_H[k]} for k, n, h in pstate.STAGES],
            'r4': jload(P(RUNS, 'r4.json')),
            'data': {'consistency': (jload(P(DATA, 'consistency.json')) or {}).get('consistentByGateRule'),
                     'gen_tasks_written': gen_lines, 'shards': len(shards), 'stats': stats,
                     'index': jload(P(DATA, 'samples', 'index.json')), 'r2': jload(P(DATA, 'r2.json'))},
            'm5': [x for x in (jload(f) for f in sorted(glob.glob(P(RUNS, 'm5_gate_*.json')))) if x],
            'selected': open(P(RUNS, 'selected_ckpt')).read().strip() if os.path.exists(P(RUNS, 'selected_ckpt')) else None,
            'mine': mine, 'bench': pb, 'acceptance': jload(P(RUNS, 'acceptance.json'))}


STAGES = pstate.ORDER
ENV_KEYS = {'N_TASKS': r'\d+', 'NPROC': r'\d+', 'TARGET_SAMPLES': r'\d+', 'CFG': r'ml/configs/(base|wta|small)\.json',
            'CONSENSUS': r'[01]?', 'ROUNDS': r'\d+', 'APG_STEPS': r'\d+', 'MINE_N': r'\d+', 'MIN_GAP_MM': r'\d+(\.\d+)?',
            'FRESH': r'[01]', 'R2_STRICT': r'[01]', 'AUTO_WTA': r'[01]'}
CONSOLE = os.path.join(ROOT, RUNS, 'console.log')


def find_bash():
    """Windows 优先 Git Bash（System32\\bash.exe 是 WSL，不能用）；其他系统用 PATH 里的 bash。"""
    if os.name == 'nt':
        for p in [os.environ.get('BASH', ''), r'C:\Program Files\Git\bin\bash.exe', r'C:\Program Files (x86)\Git\bin\bash.exe',
                  os.path.expandvars(r'%LOCALAPPDATA%\Programs\Git\bin\bash.exe')]:
            if p and os.path.exists(p): return p
        g = shutil.which('git')
        if g:
            root = os.path.dirname(os.path.dirname(g))       # 便携版 git 常放在 <根>\mingw64\bin\git.exe，要再上一层才找到 bash
            for base in dict.fromkeys([root, os.path.dirname(root)]):
                for sub in ('bin', os.path.join('usr', 'bin')):
                    p = os.path.join(base, sub, 'bash.exe')
                    if os.path.exists(p): return p
        b = shutil.which('bash')
        if b and 'windows\\system32' not in b.lower(): return b
        return None
    return shutil.which('bash')


def train_python():
    """流水线用的 Python：尊重 PYTHON 环境变量（与 console.sh / console.bat 一致），否则用控制台自己的解释器。"""
    return os.environ.get('PYTHON') or sys.executable


class SelfCheck:
    """启动自检（审查 N-10）：在后台线程跑一次，结果缓存；「开始训练」前不过就拒绝，网页顶栏显示。"""
    def __init__(self): self.r = {'pending': True}; threading.Thread(target=self.run, daemon=True).start()

    def run(self):
        py = train_python(); r = {'python': py, 'bash': find_bash(), 'node': shutil.which('node')}
        try:
            o = subprocess.run([py, '-c', 'import json,torch;c=torch.cuda.is_available();print(json.dumps({"torch":torch.__version__,"cuda":c,"gpu":torch.cuda.get_device_name(0) if c else None}))'],
                               capture_output=True, text=True, timeout=120)
            r.update(json.loads(o.stdout.strip().splitlines()[-1]) if o.returncode == 0 else {'torch': None, 'torch_error': (o.stderr or o.stdout).strip()[-300:]})
        except Exception as e: r.update(torch=None, torch_error=str(e))
        probs = []
        if not r.get('torch'): probs.append(f'这个 Python 没有 torch：{py}（先激活训练环境再启动控制台，或设 PYTHON=...）')
        if not r['bash']: probs.append('找不到 bash：Windows 请安装 Git for Windows（自带 Git Bash）')
        if not r['node']: probs.append('找不到 node')
        if r.get('torch') and not r.get('cuda'): r['warn'] = 'torch 看不到 GPU，训练会极慢'
        r['problems'] = probs; r['ok'] = not probs
        self.r = r

    def get(self): return self.r


def lock_info():
    lk = pstate.lock_read()
    if not lk: return None
    return dict(lk, alive=pstate.lock_alive(lk), age_s=time.time() - lk.get('beat', 0))


def kill_session(sid):
    """POSIX：结束会话 sid 里的所有进程（含 timeout 另起的进程组）。"""
    pids = []
    for d in os.listdir('/proc') if os.path.isdir('/proc') else []:
        if d.isdigit():
            try:
                if os.getsid(int(d)) == sid: pids.append(int(d))
            except Exception: pass
    if not pids:
        try: os.killpg(sid, signal.SIGTERM)
        except Exception: pass
        return
    for p in pids:
        try: os.kill(p, signal.SIGTERM)
        except Exception: pass


class Job:
    def __init__(self):
        self.p = None; self.info = {}; self.lock = threading.Lock()

    def state(self):
        with self.lock:
            run = self.p is not None and self.p.poll() is None
            if self.p is not None and not run and self.info.get('rc') is None:
                self.info['rc'] = self.p.returncode; self.info['ended'] = time.time()
            lk = lock_info()
            ext = bool(lk and lk['alive']) and not run           # 终端或上一个控制台窗口起的流水线
            return {'running': run or ext, 'external': ext, 'lock': lk, **self.info, 'bash': find_bash() is not None}

    def start(self, frm, to, env):
        with self.lock:
            if self.p is not None and self.p.poll() is None: return {'error': '已经在运行'}
            lk = lock_info()
            if lk and lk['alive']:
                return {'error': f"已有一条流水线在运行（{lk.get('owner')}，pid {lk.get('pid')}，{lk['age_s']:.0f} s 前心跳）；先停止它"}
            ck = CHECK.get()
            if ck.get('pending'): return {'error': '环境自检还没完成，稍等几秒再点'}
            if not ck.get('ok'): return {'error': '环境自检未通过：' + '；'.join(ck['problems'])}
            if frm not in STAGES or to not in STAGES or STAGES.index(frm) > STAGES.index(to): return {'error': '起止阶段无效'}
            bash = find_bash()
            e = dict(os.environ, FROM=frm, TO=to, MONITOR='0', PYTHONUNBUFFERED='1', PYTHONIOENCODING='utf-8', PYTHONUTF8='1', PIPE_OWNER='网页')
            py = train_python()
            if ' ' not in py: e['PYTHON'] = py.replace('\\', '/')
            for k, v in (env or {}).items():
                if k in ENV_KEYS and v not in (None, '') and re.fullmatch(ENV_KEYS[k], str(v)): e[k] = str(v)
            os.makedirs(os.path.dirname(CONSOLE), exist_ok=True)
            shown = ' '.join(f'{k}={e[k]}' for k in ('FRESH', 'FROM', 'TO') if k in e)
            with open(CONSOLE, 'w', encoding='utf-8') as f: f.write(f'$ {shown} bash ml/pipeline.sh all   [{time.strftime("%Y-%m-%d %H:%M:%S")}]\n')
            log = open(CONSOLE, 'a', encoding='utf-8')            # 追加模式：网页写入的"已停止"提示不会被子进程覆盖
            # Windows：CREATE_NO_WINDOW 给子进程树一个隐藏的独立控制台 → 关掉控制台黑窗口不会连带杀训练（审查 N-11）
            kw = {'creationflags': subprocess.CREATE_NEW_PROCESS_GROUP | 0x08000000} if os.name == 'nt' else {'start_new_session': True}
            self.p = subprocess.Popen([bash, 'ml/pipeline.sh', 'all'], cwd=ROOT, env=e, stdout=log, stderr=subprocess.STDOUT, stdin=subprocess.DEVNULL, **kw)
            self.info = {'pid': self.p.pid, 'from': frm, 'to': to, 'started': time.time(), 'rc': None, 'ended': None,
                         'env': {k: e[k] for k in ENV_KEYS if k in e}}
            return {'ok': True, 'pid': self.p.pid}

    def stop(self):
        # 2026-10-18 体面停止：训练类阶段先写 ml/runs/STOP，等训练进程自己存 last.pt 并退出（最多 90 s），再硬杀剩下的。
        # Windows 的 taskkill /F 收不到信号，不这样做会丢掉上次存档之后的进度。生成/打包本身按 shard/条断点续，直接杀。
        with self.lock:
            ours = self.p is not None and self.p.poll() is None
            lk = lock_info()
            if not ours and not (lk and lk['alive']): return {'error': '没有在运行'}
            pid = self.p.pid if ours else int(lk.get('pid') or 0)
            if not pid: return {'error': '锁里没有 pid，无法停止'}
        cur = (pstate.load().get('current') or '')
        if cur in ('train', 'm5', 'apg', 'mine'):
            open(STOPF, 'w').write(time.strftime('%H:%M:%S'))
            with open(CONSOLE, 'a', encoding='utf-8') as f: f.write(f'\n[停止请求已发出，等待 {cur} 存档 last.pt…]\n')
            for _ in range(180):
                time.sleep(0.5)
                l2 = pstate.lock_read()
                if (self.p is not None and self.p.poll() is not None) if ours else not (l2 and pstate.lock_alive(l2)): break
        with self.lock:
            if os.name == 'nt':
                subprocess.run(['taskkill', '/T', '/F', '/PID', str(pid)], capture_output=True)
                # Git Bash 下 taskkill /T 只杀到 bash，node 孙进程会逃掉（2026-10-18 实测：点了停止还有 28 个
                # gen_dataset 在跑）。按命令行补扫：只动本仓库 ml/ 下的脚本，绝不碰用户自己的 node 进程。
                try:
                    q = ("Get-CimInstance Win32_Process -Filter \"Name='node.exe'\" | "
                         "Where-Object { $_.CommandLine -match 'gen_dataset\\.cjs|run_parallel\\.sh|teacher\\.cjs|policy_bench\\.cjs' } | "
                         "ForEach-Object { Stop-Process -Id $_.ProcessId -Force -ErrorAction SilentlyContinue }")
                    subprocess.run(['pwsh', '-NoProfile', '-Command', q], capture_output=True, timeout=60)
                except Exception: pass
            else:
                if ours:
                    kill_session(pid)
                    try: self.p.wait(15)
                    except subprocess.TimeoutExpired: kill_session(pid); self.p.kill()
                else:   # 只动它自己的会话 / 进程组，绝不按会话杀到用户的终端
                    try:
                        if os.getsid(pid) == pid: kill_session(pid)
                        elif os.getpgid(pid) == pid: os.killpg(pid, signal.SIGTERM)
                        else: os.kill(pid, signal.SIGTERM)
                    except ProcessLookupError: pass
            self.info['stopped'] = True
            with open(CONSOLE, 'a', encoding='utf-8') as f: f.write(f'\n[已在网页上停止 {time.strftime("%H:%M:%S")}]\n')
            time.sleep(0.5)
            pstate.mark_stopped(-15)                               # 当前阶段记为"已停止"、释放锁（单一写者）
            try: os.remove(STOPF)
            except FileNotFoundError: pass
            return {'ok': True}


STOPF = os.path.join(ROOT, 'ml', 'runs', 'STOP')   # 与 ml/common/ckpt.py 的 STOP 同一文件
JOB = Job()
CHECK = None   # main() 里创建（自检要等 find_bash 定义完）


def console(offset):
    if not os.path.exists(CONSOLE): return {'text': '', 'offset': 0, 'reset': True}
    size = os.path.getsize(CONSOLE); reset = offset > size or offset == 0
    if reset: offset = max(0, size - 65536)                  # 首次只给最后 64 KB
    with open(CONSOLE, 'rb') as f: f.seek(offset); b = f.read(min(size - offset, 1 << 20))
    return {'text': b.decode('utf-8', 'replace').replace('\r', ''), 'offset': offset + len(b), 'reset': reset}


class H(BaseHTTPRequestHandler):
    def log_message(self, *a): pass

    def send(self, code, body, ctype):
        b = body if isinstance(body, bytes) else body.encode('utf-8')
        self.send_response(code); self.send_header('Content-Type', ctype); self.send_header('Content-Length', str(len(b)))
        self.send_header('Cache-Control', 'no-store'); self.end_headers(); self.wfile.write(b)

    def do_GET(self):
        u = urlparse(self.path); q = parse_qs(u.query)
        try:
            if u.path in ('/', '/index.html'):
                with open(HTML, 'rb') as f: return self.send(200, f.read(), 'text/html; charset=utf-8')
            if u.path == '/api/runs': return self.send(200, json.dumps(list_runs()), 'application/json')
            if u.path == '/api/log':
                return self.send(200, json.dumps(read_log(q.get('run', [''])[0], int(q.get('offset', ['0'])[0]))), 'application/json')
            if u.path == '/api/status': return self.send(200, json.dumps(status()), 'application/json')
            if u.path == '/api/job': return self.send(200, json.dumps(JOB.state()), 'application/json')
            if u.path == '/api/console': return self.send(200, json.dumps(console(int(q.get('offset', ['0'])[0]))), 'application/json')
            self.send(404, 'not found', 'text/plain')
        except Exception as e:
            self.send(500, json.dumps({'error': str(e)}), 'application/json')


    def do_POST(self):
        u = urlparse(self.path)
        if not (self.server.remote_control or self.client_address[0] in ('127.0.0.1', '::1')):
            return self.send(403, json.dumps({'error': '开始/停止只接受本机操作'}), 'application/json')
        # 审查 N-8：本机任意网页都能向 localhost 发 POST（源地址同为 127.0.0.1）。要求自定义头（跨站请求会触发 CORS 预检，
        # 本服务不应答 OPTIONS → 浏览器不发），并且 Origin / Sec-Fetch-Site 若存在必须同源。
        org, sfs, host = self.headers.get('Origin'), self.headers.get('Sec-Fetch-Site'), self.headers.get('Host', '')
        if self.headers.get('X-Console') != '1' or (sfs and sfs not in ('same-origin', 'none')) or \
           (org and urlparse(org).netloc not in (host, f'localhost:{self.server.server_port}', f'127.0.0.1:{self.server.server_port}')):
            return self.send(403, json.dumps({'error': '拒绝：非本控制台页面发起的请求'}), 'application/json')
        try:
            n = int(self.headers.get('Content-Length') or 0); body = json.loads(self.rfile.read(n) or b'{}')
            if u.path == '/api/start':
                env = dict(body.get('env') or {})
                if body.get('fresh'): env['FRESH'] = '1'
                r = JOB.start(body.get('from', 'kin'), body.get('to', 'accept'), env)
            elif u.path == '/api/stop': r = JOB.stop()
            else: return self.send(404, 'not found', 'text/plain')
            self.send(200 if 'ok' in r else 409, json.dumps(r, ensure_ascii=False), 'application/json')
        except Exception as e:
            self.send(500, json.dumps({'error': str(e)}), 'application/json')


def main():
    ap = argparse.ArgumentParser()
    ap.add_argument('--port', type=int, default=8100); ap.add_argument('--host', default='127.0.0.1')
    ap.add_argument('--open', action='store_true', help='启动后自动打开浏览器')
    ap.add_argument('--remote-control', action='store_true', help='允许其他机器点开始/停止（默认只能看）')
    a = ap.parse_args()
    global CHECK
    CHECK = SelfCheck()
    CPUS = CpuSampler()          # 每秒采一次 CPU（线程常驻，status 只读最近一次）
    srv = ThreadingHTTPServer((a.host, a.port), H); srv.remote_control = a.remote_control
    url = f'http://localhost:{a.port}/'
    print(f'训练控制台：{url}  （关闭本窗口只关控制台，已开始的训练继续跑；重新打开控制台即可接着看、可停止）', flush=True)
    if a.open: threading.Timer(0.8, lambda: webbrowser.open(url)).start()
    try: srv.serve_forever()
    except KeyboardInterrupt: pass


if __name__ == '__main__':
    main()