chore: switch target GPU to Iluvatar_bi-150

main.py

@@ -31,7 +31,7 @@ PORT = 8080
 STRATEGY_ID = os.getenv("STRATEGY_ID", "")
 
 # 目标GPU
-TARGET_GPU = "ppu_zw_810e"
+TARGET_GPU = "Iluvatar_bi-150"
 
 # 账号Token
 TARGET_TOKEN = "f45f1aae2c094426be237c88b1085015"
@@ -98,20 +98,28 @@ def init_db():
 # ModelScope 搜索
 # ============================================================
 
+MODELSCOPE_API = "https://modelscope.cn/api/v1"
+
+
 def search_models(keyword: str, limit: int = 50) -> list:
-    """从 HuggingFace 搜索模型"""
-    url = "https://huggingface.co/api/models"
+    """从 ModelScope 搜索模型"""
+    url = "https://modelscope.cn/openapi/v1/models"
     params = {
         'search': keyword,
-        'limit': limit,
+        'page_size': min(limit, 50),
+        'page_number': 1,
         'sort': 'downloads',
-        'direction': -1,
     }
     try:
-        resp = requests.get(url, params=params, timeout=20)
+        resp = requests.get(url, params=params, timeout=20,
+                            headers={'User-Agent': 'Mozilla/5.0'})
         data = resp.json()
-        log(f"  [{keyword}]: {len(data)} 个结果")
-        return [{'id': m.get('id'), 'downloads': m.get('downloads', 0)} for m in data]
+        if data.get('success'):
+            models = data.get('data', {}).get('models', [])
+            log(f"  [{keyword}]: {len(models)} 个结果")
+            return [{'id': m.get('id'), 'downloads': m.get('downloads', 0)} for m in models]
+        else:
+            log(f"  [{keyword}]: success=false")
     except Exception as e:
         log(f"  [{keyword}]: 失败 {e}")
     return []
@@ -120,7 +128,7 @@ def search_models(keyword: str, limit: int = 50) -> list:
 def check_architecture(model_id: str) -> tuple:
     """检查模型架构"""
     try:
-        cfg_url = f"https://huggingface.co/{model_id}/raw/main/config.json"
+        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()
@@ -145,7 +153,13 @@ def check_architecture(model_id: str) -> tuple:
 
 
 def normalize_model_url(model_url: str) -> str:
-    """标准化 URL 格式 - 直接返回 HuggingFace URL"""
+    """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
 
 
@@ -285,7 +299,7 @@ def run_pipeline(submit_limit: int = 30):
     log(f"提交限制: {submit_limit} 个")
 
     # 1. 搜索
-    log("\n--- 阶段1: 搜索 HuggingFace ---")
+    log("\n--- 阶段1: 搜索 ModelScope ---")
     seen = set()
     all_models = []
     for kw in SEARCH_KEYWORDS:
@@ -298,7 +312,7 @@ def run_pipeline(submit_limit: int = 30):
                 if downloads >= 50:
                     all_models.append({
                         'model_id': mid,
-                        'url': f"https://huggingface.co/{mid}",
+                        'url': f"https://modelscope.cn/{mid}",
                         'downloads': downloads,
                     })
         time.sleep(0.3)
@@ -492,10 +506,9 @@ class AgentHandler(BaseHTTPRequestHandler):
 
         # 3. ModelHub 查询 API
         try:
-            token = list(ACCOUNTS.values())[0]
             resp = requests.get(
                 'https://modelhub.org.cn/api/adapt/task/page',
-                headers={'Xc-Token': token, 'Accept': 'application/json'},
+                headers={'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json'},
                 params={'current': 1, 'pageSize': 1, 'onlyMine': 'true'},
                 timeout=10,
             )
@@ -510,17 +523,16 @@ class AgentHandler(BaseHTTPRequestHandler):
 
         # 4. ModelHub 提交 API (dry test)
         try:
-            token = list(ACCOUNTS.values())[0]
             resp = requests.post(
                 'https://modelhub.org.cn/api/adapt/task/add',
-                headers={'Xc-Token': token, 'Accept': 'application/json', 'Content-Type': 'application/json'},
+                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': 'Kunlunxin_p-800',
+                    'targetGpu': TARGET_GPU,
                     'framework': 'vllm',
                     'strategyId': STRATEGY_ID,
-                    'configParams': 'framework: vllm\n',
+                    'configParams': build_config_params(),
                 },
                 timeout=10,
             )
@@ -614,10 +626,9 @@ def main():
 
         # 3. ModelHub 查询
         try:
-            token = list(ACCOUNTS.values())[0]
             resp = requests.get(
                 'https://modelhub.org.cn/api/adapt/task/page',
-                headers={'Xc-Token': token, 'Accept': 'application/json'},
+                headers={'Xc-Token': TARGET_TOKEN, 'Accept': 'application/json'},
                 params={'current': 1, 'pageSize': 1, 'onlyMine': 'true'},
                 timeout=10
             )
@@ -631,15 +642,14 @@ def main():
 
         # 4. ModelHub 提交
         try:
-            token = list(ACCOUNTS.values())[0]
             resp = requests.post(
                 'https://modelhub.org.cn/api/adapt/task/add',
-                headers={'Xc-Token': token, 'Accept': 'application/json', 'Content-Type': 'application/json'},
+                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': 'Kunlunxin_p-800',
+                    'taskType': 'text-generation', 'targetGpu': TARGET_GPU,
                     'framework': 'vllm', 'strategyId': STRATEGY_ID,
-                    'configParams': 'framework: vllm\n',
+                    'configParams': build_config_params(),
                 }, timeout=10
             )
             data = resp.json()