feat: open architecture filter, expand search keywords, let platform decide compatibility

Dockerfile

@@ -4,6 +4,8 @@ ENV PYTHONUNBUFFERED=1
 
 WORKDIR /app
 
+RUN mkdir -p /app/data
+
 COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt
 

main.py

@@ -1,18 +1,26 @@
 """
-ModelHub Cancel-All 智能体
-启动后自动取消当前账号所有 waiting/running 状态的验证任务
-用法：推送此版本到平台，选择对应 tag 运行即可
+ModelHub 全云端提交智能体
+部署在平台容器中，直接从内网提交验证任务
+
+功能：
+- POST /run    → 触发一次完整流程（搜索→筛选→提交）
+- GET /status  → 查看当前状态
+- GET /health  → 健康检查
 """
 
 import json
 import os
 import signal
-import time
+import sqlite3
 import threading
+import time
+import traceback
 from datetime import datetime
 from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
+from urllib.parse import urlparse, parse_qs
 
 import requests
+import yaml
 
 # ============================================================
 # 配置
@@ -20,19 +28,37 @@ import requests
 
 HOST = "0.0.0.0"
 PORT = 8080
+STRATEGY_ID = os.getenv("STRATEGY_ID", "")
 
-# 目标GPU和Token（跟提交版本保持一致）
-TARGET_GPU = "Iluvatar_bi-150"
+# 目标GPU
+TARGET_GPU = "Iluvatar_bi-100"
+
+# 账号Token
 TARGET_TOKEN = "f45f1aae2c094426be237c88b1085015"
 
+# 架构白名单
+SUPPORTED_ARCH_KEYWORDS = ['Qwen', 'Qwen2', 'Qwen3']
+SUPPORTED_MODEL_TYPES = [
+    'qwen', 'qwen2', 'qwen2_vl', 'qwen2_5_vl', 'qwen2_audio',
+    'qwen3', 'qwen3_vl', 'qwen3_5', 'qwen3_5_moe',
+]
+SUPPORTED_SPECIAL_ARCHS = ['Eagle3Speculator', 'LlamaForCausalLMEagle3']
+
 MODELHUB_API = "https://modelhub.org.cn/api"
-BATCH_SIZE = 50  # 每批取消数量（API上限）
+
+# 搜索关键词
+SEARCH_KEYWORDS = ['qwen', 'Qwen2', 'Qwen3', 'Qwen3.5', 'Llama-3', 'Llama-3.1', 'Mistral', 'DeepSeek']
 
 # ============================================================
 # 全局状态
 # ============================================================
 
-state = {'running': False, 'last_run': None, 'logs': []}
+state = {
+    'running': False,
+    'last_run': None,
+    'last_result': None,
+    'logs': [],
+}
 state_lock = threading.Lock()
 
 
@@ -46,76 +72,368 @@ def log(msg: str):
             state['logs'] = state['logs'][-300:]
 
 
-def cancel_all_tasks():
-    """取消所有 waiting 和 running 状态的任务"""
+# ============================================================
+# 数据库（内存 SQLite）
+# ============================================================
+
+db_conn = None
+
+
+def init_db():
+    global db_conn
+    os.makedirs('/app/data', exist_ok=True)
+    db_conn = sqlite3.connect('/app/data/submit_history.db', check_same_thread=False)
+    db_conn.execute('''CREATE TABLE IF NOT EXISTS submitted (
+        model_id TEXT, gpu TEXT, task_id TEXT, status TEXT,
+        submitted_at TEXT, checked_at TEXT,
+        PRIMARY KEY(model_id, gpu)
+    )''')
+    db_conn.execute('''CREATE TABLE IF NOT EXISTS failed (
+        model_id TEXT, gpu TEXT, reason TEXT, failed_at TEXT,
+        PRIMARY KEY(model_id, gpu)
+    )''')
+    db_conn.commit()
+def is_model_failed(model_id: str) -> bool:
+    """检查模型是否已知失败"""
+    if db_conn:
+        row = db_conn.execute(
+            'SELECT 1 FROM failed WHERE model_id=? AND gpu=?',
+            (model_id, TARGET_GPU)
+        ).fetchone()
+        return row is not None
+    return False
+
+def record_failed(model_id: str, reason: str):
+    """记录失败的模型"""
+    if db_conn:
+        db_conn.execute(
+            'INSERT OR REPLACE INTO failed VALUES (?,?,?,?)',
+            (model_id, TARGET_GPU, reason, datetime.now().isoformat())
+        )
+        db_conn.commit()
+
+
+# ============================================================
+# ModelScope 搜索
+# ============================================================
+
+MODELSCOPE_API = "https://modelscope.cn/api/v1"
+DOWNLOAD_MIN = 50
+DOWNLOAD_MAX = 5000
+SEARCH_PAGES = 5  # 每个关键词搜5页（50*5=250个结果）
+
+
+def search_models(keyword: str) -> list:
+    """从 ModelScope 搜索模型（多页，筛选下载量50-5000的冷门模型）"""
+    url = "https://modelscope.cn/openapi/v1/models"
+    models = []
+    for page in range(1, SEARCH_PAGES + 1):
+        params = {
+            'search': keyword,
+            'page_size': 50,
+            'page_number': page,
+            'sort': 'downloads',
+        }
+        try:
+            resp = requests.get(url, params=params, timeout=20,
+                                headers={'User-Agent': 'Mozilla/5.0'})
+            data = resp.json()
+            if data.get('success'):
+                page_models = data.get('data', {}).get('models', [])
+                for m in page_models:
+                    dl = m.get('downloads', 0)
+                    if DOWNLOAD_MIN <= dl <= DOWNLOAD_MAX:
+                        models.append({'id': m.get('id'), 'downloads': dl})
+                if len(page_models) < 50:
+                    break  # 最后一页，不继续
+            else:
+                break
+        except Exception as e:
+            log(f"  [{keyword}] page={page}: {e}")
+            break
+        time.sleep(0.3)
+    log(f"  [{keyword}]: {len(models)} 个 (50<={DOWNLOAD_MAX})")
+    return models
+
+
+def check_architecture(model_id: str) -> tuple:
+    """检查模型架构"""
+    try:
+        cfg_url = f"{MODELSCOPE_API}/models/{model_id}/repo?Revision=master&FilePath=config.json"
+        resp = requests.get(cfg_url, timeout=10)
+        if resp.status_code == 200:
+            cfg = resp.json()
+            archs = cfg.get('architectures', [])
+            mtype = cfg.get('model_type', '')
+            arch_str = str(archs)
+            for special in SUPPORTED_SPECIAL_ARCHS:
+                if special in arch_str:
+                    return True, special
+            for kw in SUPPORTED_ARCH_KEYWORDS:
+                if kw in arch_str:
+                    return True, kw
+            if mtype in SUPPORTED_MODEL_TYPES:
+                return True, mtype
+            return False, f"arch={archs} type={mtype}"
+        mid_upper = model_id.upper()
+        if 'QWEN3' in mid_upper or 'QWEN2' in mid_upper:
+            return True, "GGUF"
+        return False, "no config, not Qwen"
+    except Exception as e:
+        return True, f"check error: {e}"
+
+
+def normalize_model_url(model_url: str) -> str:
+    """标准化 URL 格式"""
+    if '/models/' in model_url:
+        return model_url
+    if 'modelscope.cn/' in model_url:
+        parts = model_url.split('modelscope.cn/')
+        if len(parts) == 2:
+            return f"https://www.modelscope.cn/models/{parts[1]}"
+    return model_url
+
+
+# ============================================================
+# 平台 API
+# ============================================================
+
+def check_platform_verify(model_id: str) -> dict:
+    """查询全平台验证状态"""
+    headers = {'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json'}
+    url = f"{MODELHUB_API}/computility/models/search-by-model-id"
+    try:
+        resp = requests.get(url, headers=headers, params={'modelId': model_id}, timeout=10)
+        data = resp.json()
+        if data.get('code') == 0:
+            result = data.get('data', {}).get('verifyResult', {})
+            return result if isinstance(result, dict) else {}
+    except Exception:
+        pass
+    return {}
+
+
+def check_my_submitted(model_id: str) -> bool:
+    """检查自己是否已提交"""
+    headers = {'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json'}
+    url = f"{MODELHUB_API}/adapt/task/page"
+    try:
+        resp = requests.get(url, headers=headers, params={
+            'current': 1, 'pageSize': 100, 'onlyMine': 'true',
+            'gpuType': TARGET_GPU, 'modelId': model_id,
+        }, timeout=10)
+        data = resp.json()
+        if data.get('code') == 0:
+            records = data.get('data', {}).get('records', [])
+            for r in records:
+                if r.get('modelId') == model_id and r.get('gpuType') == gpu:
+                    status = r.get('status', '')
+                    if status in ('waiting', 'running', 'success'):
+                        return True
+    except Exception:
+        pass
+    return False
+
+
+def check_queue_available() -> int:
+    """查询队列可用位置"""
+    headers = {'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json'}
+    url = f"{MODELHUB_API}/adapt/task/page"
+    try:
+        resp = requests.get(url, headers=headers, params={
+            'current': 1, 'pageSize': 1, 'onlyMine': 'true',
+            'gpuType': TARGET_GPU, 'status': 'waiting',
+        }, timeout=10)
+        data = resp.json()
+        if data.get('code') == 0:
+            waiting = int(data['data'].get('total', 0))
+            return max(0, 100 - waiting)
+    except Exception:
+        pass
+    return -1
+
+
+def build_config_params() -> str:
+    """构建 YAML 配置 - llama.cpp (支持 GGUF)"""
+    params = {
+        'framework': 'llama.cpp',
+        'nv_framework': 'llama.cpp',
+        'api': 'completion',
+        'max_tokens': 1024,
+        'temperature': 0.7,
+        'repetition_penalty': 1.2,
+        'top_p': 0.9,
+        'lang': 'zh',
+        'max_model_len': 4096,
+        'sut_config': {
+            'gpu_num': 1,
+            'values': {
+                'command': [
+                    'llama-server', '--model', '/model', '--alias', 'llm',
+                    '--threads', '20', '--n-gpu-layers', '999', '--prio', '3',
+                    '--min_p', '0.01', '--ctx-size', '4096',
+                    '--host', '0.0.0.0', '--port', '8000',
+                    '--jinja', '--flash-attn', 'off',
+                ]
+            }
+        },
+        'ref_config': {
+            'gpu_num': 1,
+            'values': {
+                'command': [
+                    'llama-server', '--model', '/model', '--alias', 'llm',
+                    '--threads', '20', '--n-gpu-layers', '999',
+                    '--ctx-size', '4096', '--host', '0.0.0.0', '--port', '8000',
+                ]
+            }
+        },
+    }
+    return yaml.dump(params, default_flow_style=False, allow_unicode=True, width=1000)
+
+
+def submit_model(model_url: str) -> tuple:
+    """提交单个模型"""
     headers = {
         'Xc-Token': TARGET_TOKEN,
         'Accept': 'application/json',
         'Content-Type': 'application/json',
     }
+    url = f"{MODELHUB_API}/adapt/task/add"
+    payload = {
+        'modelAddress': normalize_model_url(model_url),
+        'taskType': 'text-generation',
+        'targetGpu': TARGET_GPU,
+        'framework': 'llama.cpp',
+        'strategyId': STRATEGY_ID,
+        'configParams': build_config_params(),
+    }
+    try:
+        resp = requests.post(url, headers=headers, json=payload, timeout=30)
+        data = resp.json()
+        if data.get('code') == 0:
+            task_id = data.get('data', {}).get('id')
+            return True, task_id, 'success'
+        return False, None, data.get('message', 'unknown error')
+    except Exception as e:
+        return False, None, str(e)
 
+
+# ============================================================
+# 主流程
+# ============================================================
+
+def run_pipeline(submit_limit: int = 2):
+    """完整流程：搜索→筛选→提交（只针对目标GPU）"""
+    init_db()
     log("=" * 50)
-    log("开始取消所有任务")
+    log("开始执行流程")
     log(f"目标GPU: {TARGET_GPU}")
+    log(f"提交限制: {submit_limit} 个")
 
-    # 1. 查询所有任务
-    all_tasks = []
-    page = 1
-    while True:
-        try:
-            resp = requests.get(
-                f"{MODELHUB_API}/adapt/task/page",
-                headers={'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json'},
-                params={'current': page, 'pageSize': 100, 'onlyMine': 'true',
-                        'gpuType': TARGET_GPU},
-                timeout=15
+    # 1. 搜索
+    log("\n--- 阶段1: 搜索 ModelScope ---")
+    seen = set()
+    all_models = []
+    for kw in SEARCH_KEYWORDS:
+        models = search_models(kw)
+        for m in models:
+            mid = m.get('id', '')
+            if mid and mid not in seen:
+                seen.add(mid)
+                all_models.append({
+                    'model_id': mid,
+                    'url': f"https://modelscope.cn/{mid}",
+                    'downloads': m.get('downloads', 0),
+                })
+        time.sleep(0.3)
+    log(f"搜索完成: {len(seen)} 个唯一模型, {len(all_models)} 个下载量{DOWNLOAD_MIN}-{DOWNLOAD_MAX}")
+
+    # 2. 格式筛选（排除 GPTQ/AWQ，保留 GGUF 和 HuggingFace）
+    log("\n--- 阶段2: 格式筛选 ---")
+    hf_models = []
+    format_skipped = 0
+    SKIP_FORMATS = ['GPTQ', 'AWQ']
+    for m in all_models:
+        mid_upper = m['model_id'].upper()
+        skip = False
+        for fmt in SKIP_FORMATS:
+            if fmt in mid_upper:
+                format_skipped += 1
+                log(f"  x {m['model_id']}: {fmt}格式，跳过")
+                skip = True
+                break
+        if not skip:
+            hf_models.append(m)
+    log(f"格式筛选: {len(hf_models)} 通过, {format_skipped} 跳过 (GPTQ/AWQ)")
+
+    # 3. 架构筛选（参考检查，不做严格过滤，让平台决定兼容性）
+    log("\n--- 阶段3: 架构检查 ---")
+    for m in hf_models:
+        ok, reason = check_architecture(m['model_id'])
+        if not ok:
+            log(f"  ! {m['model_id']}: {reason} (仍保留)")
+        time.sleep(0.1)
+    log(f"架构检查: {len(hf_models)} 个模型进入下一阶段")
+
+    # 4. 筛选并提交（只针对目标GPU）
+    log(f"\n--- 阶段4: 筛选并提交 [{TARGET_GPU}] ---")
+
+    # 检查队列
+    available = check_queue_available()
+    if available <= 0:
+        log(f"  队列满，跳过")
+        return 0
+    log(f"  队列可用: {available}")
+
+    # 筛选
+    to_submit = []
+    for m in hf_models:
+        model_id = m['model_id']
+
+        # 检查全平台验证状态
+        verify = check_platform_verify(model_id)
+        if TARGET_GPU in verify:
+            continue  # 已有记录，跳过
+
+        # 检查自己是否已提交
+        if check_my_submitted(model_id):
+            continue
+
+        # 检查是否已知失败（避免重复提交）
+        if is_model_failed(model_id):
+            continue
+
+        to_submit.append(m)
+        if len(to_submit) >= min(submit_limit, available):
+            break
+        time.sleep(0.2)
+
+    log(f"  待提交: {len(to_submit)}")
+
+    # 提交
+    submitted = 0
+    for m in to_submit:
+        ok, task_id, msg = submit_model(m['url'])
+        if ok:
+            submitted += 1
+            log(f"  ✅ {m['model_id']}")
+            db_conn.execute(
+                'INSERT OR REPLACE INTO submitted VALUES (?,?,?,?)',
+                (m['model_id'], TARGET_GPU, str(task_id), datetime.now().isoformat())
             )
-            data = resp.json()
-            if data.get('code') != 0:
-                log(f"查询失败: code={data.get('code')}")
-                break
-            records = data['data'].get('records', [])
-            if not records:
-                break
-            all_tasks.extend(records)
-            total = data['data'].get('total', 0)
-            log(f"  第{page}页: {len(records)} 条, 累计 {len(all_tasks)} / {total}")
-            if len(all_tasks) >= int(total):
-                break
-            page += 1
-        except Exception as e:
-            log(f"  查询异常: {e}")
-            return
+        else:
+            log(f"  ❌ {m['model_id']}: {msg}")
+            # 永久失败类型记录到 failed 表
+            if any(kw in str(msg) for kw in ['保护期', '白名单', '唯一性']):
+                record_failed(m['model_id'], msg)
+        time.sleep(0.5)
 
-    # 2. 筛选 waiting/running 状态
-    cancellable = [t for t in all_tasks if t.get('status') in ('waiting', 'running')]
-    if not cancellable:
-        log(f"  没有可取消的任务 (总任务 {len(all_tasks)} 个)")
-        log("=" * 50)
-        return
+    log(f"  提交完成: {submitted}/{len(to_submit)}")
 
-    task_ids = [int(t.get('taskId')) for t in cancellable if t.get('taskId')]
-    log(f"  总任务 {len(all_tasks)} 个, 可取消 {len(task_ids)} 个")
-
-    # 3. 分批取消
-    url = f"{MODELHUB_API}/async/task/stop-create-contest-task"
-    cancelled = 0
-    for i in range(0, len(task_ids), BATCH_SIZE):
-        batch = task_ids[i:i + BATCH_SIZE]
-        try:
-            resp = requests.put(url, headers=headers, json={'taskIds': batch}, timeout=15)
-            data = resp.json()
-            if data.get('code') == 0:
-                cancelled += len(batch)
-                log(f"  批次 {i // BATCH_SIZE + 1}: 取消 {len(batch)} 个 OK")
-            else:
-                log(f"  批次 {i // BATCH_SIZE + 1}: 失败 code={data.get('code')} msg={data.get('message', '')[:80]}")
-        except Exception as e:
-            log(f"  批次 {i // BATCH_SIZE + 1}: 异常 {e}")
-        time.sleep(1)
-
-    log(f"  取消完成: {cancelled} / {len(task_ids)}")
-    log("=" * 50)
+    db_conn.commit()
+    log(f"\n{'=' * 50}")
+    log(f"流程完成，共提交 {submitted} 个模型")
+    return submitted
 
 
 # ============================================================
@@ -124,21 +442,148 @@ def cancel_all_tasks():
 
 class AgentHandler(BaseHTTPRequestHandler):
     def do_GET(self):
-        if self.path == '/health':
+        parsed = urlparse(self.path)
+        path = parsed.path
+
+        if path == '/health':
             self._json({'status': 'ok'})
-        elif self.path == '/':
+        elif path == '/':
             self._json({
-                'name': 'modelhub-cancel-all',
-                'gpu': TARGET_GPU,
+                'name': 'modelhub-submit-agent',
+                'strategy_id': STRATEGY_ID,
                 'status': 'running' if state['running'] else 'idle',
-                'last_result': state.get('last_result'),
+                'last_run': state['last_run'],
+                'last_result': state['last_result'],
             })
-        elif self.path.startswith('/logs'):
-            lines = 100
+        elif path == '/test':
+            self._json(self._run_connectivity_test())
+        elif path == '/status':
+            self._json({
+                'running': state['running'],
+                'last_run': state['last_run'],
+                'last_result': state['last_result'],
+                'queue_count': db_conn.execute('SELECT COUNT(*) FROM queue').fetchone()[0] if db_conn else 0,
+                'submitted_count': db_conn.execute('SELECT COUNT(*) FROM submitted').fetchone()[0] if db_conn else 0,
+            })
+        elif path == '/logs':
+            lines = int(parse_qs(parsed.query).get('lines', ['50'])[0])
             self._json({'logs': state['logs'][-lines:]})
         else:
             self._json({'error': 'not found'}, 404)
 
+    def do_POST(self):
+        parsed = urlparse(self.path)
+        path = parsed.path
+
+        if path == '/run':
+            if state['running']:
+                self._json({'error': 'already running'}, 409)
+                return
+
+            # 读取请求体
+            content_len = int(self.headers.get('Content-Length', 0))
+            body = {}
+            if content_len > 0:
+                body = json.loads(self.rfile.read(content_len))
+
+            limit = body.get('limit', 2)
+
+            self._json({'status': 'started', 'gpu': TARGET_GPU, 'limit': limit})
+
+            # 后台运行
+            def _run():
+                try:
+                    state['running'] = True
+                    state['last_run'] = datetime.now().isoformat()
+                    count = run_pipeline(submit_limit=limit)
+                    state['last_result'] = {'submitted': count, 'success': True}
+                except Exception as e:
+                    log(f"流程异常: {traceback.format_exc()}")
+                    state['last_result'] = {'error': str(e), 'success': False}
+                finally:
+                    state['running'] = False
+
+            threading.Thread(target=_run, daemon=True).start()
+        else:
+            self._json({'error': 'not found'}, 404)
+
+    def _run_connectivity_test(self) -> dict:
+        """测试各 API 连通性"""
+        results = {}
+
+        # 1. ModelScope 搜索 API
+        try:
+            resp = requests.get(
+                'https://modelscope.cn/openapi/v1/models',
+                params={'search': 'qwen', 'page_size': 2, 'sort': 'downloads'},
+                timeout=10,
+                headers={'User-Agent': 'Mozilla/5.0'}
+            )
+            results['modelscope_search'] = {
+                'status': resp.status_code,
+                'ok': resp.status_code == 200,
+                'body_preview': resp.text[:200] if resp.status_code == 200 else resp.text[:100],
+            }
+        except Exception as e:
+            results['modelscope_search'] = {'ok': False, 'error': str(e)}
+
+        # 2. ModelScope config.json API
+        try:
+            resp = requests.get(
+                'https://modelscope.cn/api/v1/models/Qwen/Qwen3-8B/repo?Revision=master&FilePath=config.json',
+                timeout=10,
+            )
+            results['modelscope_config'] = {
+                'status': resp.status_code,
+                'ok': resp.status_code == 200,
+                'body_preview': resp.text[:200] if resp.status_code == 200 else resp.text[:100],
+            }
+        except Exception as e:
+            results['modelscope_config'] = {'ok': False, 'error': str(e)}
+
+        # 3. ModelHub 查询 API
+        try:
+            resp = requests.get(
+                'https://modelhub.org.cn/api/adapt/task/page',
+                headers={'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json'},
+                params={'current': 1, 'pageSize': 1, 'onlyMine': 'true'},
+                timeout=10,
+            )
+            data = resp.json()
+            results['modelhub_query'] = {
+                'ok': data.get('code') == 0,
+                'code': data.get('code'),
+                'total': data.get('data', {}).get('total'),
+            }
+        except Exception as e:
+            results['modelhub_query'] = {'ok': False, 'error': str(e)}
+
+        # 4. ModelHub 提交 API (dry test)
+        try:
+            resp = requests.post(
+                'https://modelhub.org.cn/api/adapt/task/add',
+                headers={'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json', 'Content-Type': 'application/json'},
+                json={
+                    'modelAddress': 'https://www.modelscope.cn/models/Qwen/Qwen3-8B',
+                    'taskType': 'text-generation',
+                    'targetGpu': TARGET_GPU,
+                    'framework': 'llama.cpp',
+                    'strategyId': STRATEGY_ID,
+                    'configParams': build_config_params(),
+                },
+                timeout=10,
+            )
+            data = resp.json()
+            results['modelhub_submit'] = {
+                'ok': data.get('code') == 0,
+                'code': data.get('code'),
+                'message': data.get('message', '')[:100],
+            }
+        except Exception as e:
+            results['modelhub_submit'] = {'ok': False, 'error': str(e)}
+
+        return results
+
     def _json(self, body: dict, status: int = 200):
         payload = json.dumps(body, ensure_ascii=False).encode()
         self.send_response(status)
@@ -148,7 +593,7 @@ class AgentHandler(BaseHTTPRequestHandler):
         self.wfile.write(payload)
 
     def log_message(self, fmt, *args):
-        pass
+        pass  # 静默 HTTP 日志
 
 
 # ============================================================
@@ -168,27 +613,105 @@ def main():
     signal.signal(signal.SIGTERM, _handle_signal)
     signal.signal(signal.SIGINT, _handle_signal)
 
+    init_db()
+
     server = ThreadingHTTPServer((HOST, PORT), AgentHandler)
     server.timeout = 1
 
-    log(f"Cancel-All 智能体启动 | {HOST}:{PORT}")
+    log(f"智能体启动 | {HOST}:{PORT}")
+    log(f"STRATEGY_ID: {STRATEGY_ID}")
     log(f"目标GPU: {TARGET_GPU}")
 
-    # 启动后自动取消所有任务
-    def _auto_cancel():
+    # 启动后自动运行连通性测试
+    def _startup_test():
         time.sleep(2)
+        log("=" * 50)
+        log("连通性测试开始")
+        log("=" * 50)
+
+        # 1. ModelScope 搜索
+        try:
+            resp = requests.get(
+                'https://modelscope.cn/openapi/v1/models',
+                params={'search': 'qwen', 'page_size': 2, 'sort': 'downloads'},
+                timeout=10, headers={'User-Agent': 'Mozilla/5.0'}
+            )
+            if resp.status_code == 200:
+                data = resp.json()
+                models = data.get('data', {}).get('models', [])
+                log(f"[ModelScope搜索] ✅ status={resp.status_code} models={len(models)}")
+                for m in models[:2]:
+                    log(f"  {m.get('id')} downloads={m.get('downloads')}")
+            else:
+                log(f"[ModelScope搜索] ❌ status={resp.status_code} body={resp.text[:100]}")
+        except Exception as e:
+            log(f"[ModelScope搜索] ❌ error={e}")
+
+        # 2. ModelScope config.json
+        try:
+            resp = requests.get(
+                'https://modelscope.cn/api/v1/models/Qwen/Qwen3-8B/repo?Revision=master&FilePath=config.json',
+                timeout=10
+            )
+            if resp.status_code == 200:
+                cfg = resp.json()
+                log(f"[ModelScope配置] ✅ arch={cfg.get('architectures')} type={cfg.get('model_type')}")
+            else:
+                log(f"[ModelScope配置] ❌ status={resp.status_code}")
+        except Exception as e:
+            log(f"[ModelScope配置] ❌ error={e}")
+
+        # 3. ModelHub 查询
+        try:
+            resp = requests.get(
+                'https://modelhub.org.cn/api/adapt/task/page',
+                headers={'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json'},
+                params={'current': 1, 'pageSize': 1, 'onlyMine': 'true'},
+                timeout=10
+            )
+            data = resp.json()
+            if data.get('code') == 0:
+                log(f"[ModelHub查询] ✅ total={data['data'].get('total')}")
+            else:
+                log(f"[ModelHub查询] ❌ code={data.get('code')} msg={data.get('message','')[:80]}")
+        except Exception as e:
+            log(f"[ModelHub查询] ❌ error={e}")
+
+        # 4. ModelHub 提交
+        try:
+            resp = requests.post(
+                'https://modelhub.org.cn/api/adapt/task/add',
+                headers={'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json', 'Content-Type': 'application/json'},
+                json={
+                    'modelAddress': 'https://www.modelscope.cn/models/Qwen/Qwen3-8B',
+                    'taskType': 'text-generation', 'targetGpu': TARGET_GPU,
+                    'framework': 'llama.cpp', 'strategyId': STRATEGY_ID,
+                    'configParams': build_config_params(),
+                }, timeout=10
+            )
+            data = resp.json()
+            log(f"[ModelHub提交] code={data.get('code')} msg={data.get('message','')[:80]}")
+        except Exception as e:
+            log(f"[ModelHub提交] ❌ error={e}")
+
+        log("=" * 50)
+        log("连通性测试完成")
+        log("=" * 50)
+
+        # 开始正式提交流程
+        log("\n自动触发提交流程...")
         try:
             state['running'] = True
             state['last_run'] = datetime.now().isoformat()
-            cancel_all_tasks()
-            state['last_result'] = {'success': True}
+            count = run_pipeline(submit_limit=2)
+            state['last_result'] = {'submitted': count, 'success': True}
         except Exception as e:
-            log(f"异常: {e}")
-            state['last_result'] = {'error': str(e)}
+            log(f"流程异常: {traceback.format_exc()}")
+            state['last_result'] = {'error': str(e), 'success': False}
         finally:
             state['running'] = False
 
-    threading.Thread(target=_auto_cancel, daemon=True).start()
+    threading.Thread(target=_startup_test, daemon=True).start()
 
     while not shutdown_requested:
         server.handle_request()