fix: fix SQLite INSERT column count, fix architecture check for all arch types

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

@@ -31,7 +31,7 @@ PORT = 8080
 STRATEGY_ID = os.getenv("STRATEGY_ID", "")
 
 # 目标GPU
-TARGET_GPU = "Iluvatar_bi-150"
+TARGET_GPU = "Iluvatar_bi-100"
 
 # 账号Token
 TARGET_TOKEN = "f45f1aae2c094426be237c88b1085015"
@@ -47,7 +47,7 @@ SUPPORTED_SPECIAL_ARCHS = ['Eagle3Speculator', 'LlamaForCausalLMEagle3']
 MODELHUB_API = "https://modelhub.org.cn/api"
 
 # 搜索关键词
-SEARCH_KEYWORDS = ['qwen', 'Qwen2', 'Qwen3', 'Qwen3.5', 'Qwen1.5', 'Qwen-']
+SEARCH_KEYWORDS = ['Llama-3', 'Llama-3.1', 'Llama-3.2', 'Meta-Llama', 'Llama-4']
 
 # ============================================================
 # 全局状态
@@ -81,17 +81,36 @@ db_conn = None
 
 def init_db():
     global db_conn
-    db_conn = sqlite3.connect(':memory:', check_same_thread=False)
+    os.makedirs('/app/data', exist_ok=True)
-    db_conn.execute('''CREATE TABLE IF NOT EXISTS queue (
+    db_conn = sqlite3.connect('/app/data/submit_history.db', check_same_thread=False)
-        model_id TEXT, gpu TEXT, url TEXT, downloads INTEGER,
+    db_conn.execute('''CREATE TABLE IF NOT EXISTS submitted (
-        params TEXT, category TEXT, score REAL,
+        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 submitted (
+    db_conn.execute('''CREATE TABLE IF NOT EXISTS failed (
-        model_id TEXT, gpu TEXT, task_id TEXT, submitted_at TEXT,
+        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()
 
 
 # ============================================================
@@ -99,34 +118,46 @@ def init_db():
 # ============================================================
 
 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, limit: int = 50) -> list:
+def search_models(keyword: str) -> list:
-    """从 ModelScope 搜索模型"""
+    """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"
-    params = {
+    models = []
-        'search': keyword,
+    for page in range(1, SEARCH_PAGES + 1):
-        'page_size': min(limit, 50),
+        params = {
-        'page_number': 1,
+            'search': keyword,
-        'sort': 'downloads',
+            'page_size': 50,
-    }
+            'page_number': page,
-    try:
+            'sort': 'downloads',
-        resp = requests.get(url, params=params, timeout=20,
+        }
-                            headers={'User-Agent': 'Mozilla/5.0'})
+        try:
-        data = resp.json()
+            resp = requests.get(url, params=params, timeout=20,
-        if data.get('success'):
+                                headers={'User-Agent': 'Mozilla/5.0'})
-            models = data.get('data', {}).get('models', [])
+            data = resp.json()
-            log(f"  [{keyword}]: {len(models)} 个结果")
+            if data.get('success'):
-            return [{'id': m.get('id'), 'downloads': m.get('downloads', 0)} for m in models]
+                page_models = data.get('data', {}).get('models', [])
-        else:
+                for m in page_models:
-            log(f"  [{keyword}]: success=false")
+                    dl = m.get('downloads', 0)
-    except Exception as e:
+                    if DOWNLOAD_MIN <= dl <= DOWNLOAD_MAX:
-        log(f"  [{keyword}]: 失败 {e}")
+                        models.append({'id': m.get('id'), 'downloads': dl})
-    return []
+                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"""
+    """检查模型是否有有效的 config.json（不限架构类型）"""
     try:
         cfg_url = f"{MODELSCOPE_API}/models/{model_id}/repo?Revision=master&FilePath=config.json"
         resp = requests.get(cfg_url, timeout=10)
@@ -134,20 +165,13 @@ def check_architecture(model_id: str) -> tuple:
             cfg = resp.json()
             archs = cfg.get('architectures', [])
             mtype = cfg.get('model_type', '')
-            arch_str = str(archs)
+            if archs or mtype:
-            for special in SUPPORTED_SPECIAL_ARCHS:
+                return True, f"arch={archs} type={mtype}"
-                if special in arch_str:
+            return False, "empty config"
-                    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:
+        if 'LLAMA' in mid_upper:
-            return True, "GGUF"
+            return True, "Llama(GGUF)"
-        return False, "no config, not Qwen"
+        return False, "no config"
     except Exception as e:
         return True, f"check error: {e}"
 
@@ -223,7 +247,7 @@ def check_queue_available() -> int:
 
 
 def build_config_params() -> str:
-    """构建 YAML 配置 - 完全匹配平台自动生成的格式（只支持vllm）"""
+    """构建 YAML 配置 - vllm"""
     params = {
         'framework': 'vllm',
         'nv_framework': 'vllm',
@@ -290,7 +314,7 @@ def submit_model(model_url: str) -> tuple:
 # 主流程
 # ============================================================
 
-def run_pipeline(submit_limit: int = 30):
+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)
@@ -303,47 +327,53 @@ def run_pipeline(submit_limit: int = 30):
     seen = set()
     all_models = []
     for kw in SEARCH_KEYWORDS:
-        models = search_models(kw, limit=100)
+        models = search_models(kw)
         for m in models:
             mid = m.get('id', '')
             if mid and mid not in seen:
                 seen.add(mid)
-                downloads = m.get('downloads', 0)
+                all_models.append({
-                if downloads >= 50:
+                    'model_id': mid,
-                    all_models.append({
+                    'url': f"https://modelscope.cn/{mid}",
-                        'model_id': mid,
+                    'downloads': m.get('downloads', 0),
-                        'url': f"https://modelscope.cn/{mid}",
+                })
-                        'downloads': downloads,
-                    })
         time.sleep(0.3)
-    log(f"搜索完成: {len(seen)} 个唯一模型, {len(all_models)} 个下载量>=50")
+    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（只保留HuggingFace格式，排除GGUF）
+    # 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 = []
-    gguf_skipped = 0
+    format_skipped = 0
+    SKIP_FORMATS = ['GPTQ', 'AWQ']
     for m in all_models:
-        mid = m['model_id'].upper()
+        mid_upper = m['model_id'].upper()
-        if 'GGUF' in mid:
+        skip = False
-            gguf_skipped += 1
+        for fmt in SKIP_FORMATS:
-            log(f"  ✗ {m['model_id']}: GGUF格式，跳过")
+            if fmt in mid_upper:
-        else:
+                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 (HuggingFace), {gguf_skipped} 跳过 (GGUF)")
+    log(f"格式筛选: {len(hf_models)} 通过, {format_skipped} 跳过 (GPTQ/AWQ)")
 
-    # 3. 架构筛选
+    # 3. 架构筛选（只保留有标准config.json的模型，排除无效格式）
-    log("\n--- 阶段3: 架构筛选 ---")
+    log("\n--- 阶段3: 架构检查 ---")
     arch_passed = []
     arch_rejected = 0
     for m in hf_models:
         ok, reason = check_architecture(m['model_id'])
-        if ok:
+        if not ok:
-            arch_passed.append(m)
-        else:
             arch_rejected += 1
-            log(f"  ✗ {m['model_id']}: {reason}")
+            log(f"  x {m['model_id']}: {reason}")
-        time.sleep(0.15)
+        elif reason == 'GGUF':
-    log(f"架构筛选: {len(arch_passed)} 通过, {arch_rejected} 拒绝")
+            arch_rejected += 1
+            log(f"  x {m['model_id']}: GGUF(无config)")
+        else:
+            arch_passed.append(m)
+        time.sleep(0.1)
+    log(f"架构检查: {len(arch_passed)} 通过, {arch_rejected} 拒绝")
 
     # 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}] ---")
@@ -369,6 +399,10 @@ def run_pipeline(submit_limit: int = 30):
         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
@@ -384,11 +418,15 @@ def run_pipeline(submit_limit: int = 30):
             submitted += 1
             log(f"  ✅ {m['model_id']}")
             db_conn.execute(
-                'INSERT OR REPLACE INTO submitted VALUES (?,?,?,?)',
+                'INSERT OR REPLACE INTO submitted VALUES (?,?,?,?,?,?)',
-                (m['model_id'], gpu, str(task_id), datetime.now().isoformat())
+                (m['model_id'], TARGET_GPU, str(task_id), 'submitted',
+                 datetime.now().isoformat(), None)
             )
         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)
 
     log(f"  提交完成: {submitted}/{len(to_submit)}")
@@ -449,7 +487,7 @@ class AgentHandler(BaseHTTPRequestHandler):
             if content_len > 0:
                 body = json.loads(self.rfile.read(content_len))
 
-            limit = body.get('limit', 30)
+            limit = body.get('limit', 2)
 
             self._json({'status': 'started', 'gpu': TARGET_GPU, 'limit': limit})
 
@@ -666,7 +704,7 @@ def main():
         try:
             state['running'] = True
             state['last_run'] = datetime.now().isoformat()
-            count = run_pipeline(submit_limit=30)
+            count = run_pipeline(submit_limit=2)
             state['last_result'] = {'submitted': count, 'success': True}
         except Exception as e:
             log(f"流程异常: {traceback.format_exc()}")