feat: improve agent collaboration observability

backend-fastapi/ai_platform/services/llm_service.py

@@ -29,6 +29,38 @@ class LLMService:
     def __init__(self, db: Optional[AsyncSession] = None):
         self._provider_cache: Dict[str, BaseLLMProvider] = {}
         self._db = db
+
+    @staticmethod
+    def _is_missing_model_id(model_id: Optional[str]) -> bool:
+        if model_id is None:
+            return True
+        return str(model_id).strip().lower() in {"", "none", "null", "undefined"}
+
+    async def resolve_chat_model_id(self, model_id: Optional[str]) -> str:
+        """解析 chat 模型。未指定时使用当前启用的默认 chat 模型。"""
+        if not self._is_missing_model_id(model_id):
+            return str(model_id)
+
+        if not self._db:
+            raise ValueError("未找到可用的 chat 模型，请先在模型配置中启用一个模型")
+
+        from ai_platform.models import LLMModel
+
+        result = await self._db.execute(
+            select(LLMModel)
+            .where(
+                LLMModel.is_deleted == False,
+                LLMModel.is_active == True,
+                LLMModel.model_type == "chat",
+            )
+            .order_by(LLMModel.sort.desc(), LLMModel.sys_create_datetime.desc())
+        )
+        model = result.scalars().first()
+        if not model:
+            raise ValueError("未找到可用的 chat 模型，请先在模型配置中启用一个模型")
+
+        logger.info("No model_id supplied, fallback to default chat model %s", model.id)
+        return str(model.id)
     
     async def _get_provider_async(self, model_id: str) -> tuple:
         """
@@ -45,6 +77,8 @@ class LLMService:
         if not self._db:
             raise ValueError("数据库会话未初始化")
         
+        model_id = await self.resolve_chat_model_id(model_id)
+
         # 查询模型
         result = await self._db.execute(
             select(LLMModel).where(
@@ -319,14 +353,18 @@ class LLMService:
         async def get_provider():
             return await self._get_provider_async(model_id)
         
-        loop = asyncio.get_event_loop()
-        if loop.is_running():
-            # 如果已有事件循环在运行，使用线程池
-            with concurrent.futures.ThreadPoolExecutor() as executor:
-                future = executor.submit(asyncio.run, get_provider())
-                provider, model_name = future.result()
+        try:
+            loop = asyncio.get_event_loop()
+        except RuntimeError:
+            provider, model_name = asyncio.run(get_provider())
         else:
-            provider, model_name = loop.run_until_complete(get_provider())
+            if loop.is_running():
+                # 如果已有事件循环在运行，使用线程池
+                with concurrent.futures.ThreadPoolExecutor() as executor:
+                    future = executor.submit(asyncio.run, get_provider())
+                    provider, model_name = future.result()
+            else:
+                provider, model_name = loop.run_until_complete(get_provider())
         
         # 使用获取到的 provider 进行流式调用
         yield from self.chat_stream_sync_with_provider(