feat: improve ai workflow runtime observability

backend-fastapi/ai_platform/nodes/builtin/text_to_sql_node.py

@@ -225,11 +225,10 @@ class TextToSqlNode(BaseNode):
                     error='请输入要查询的问题',
                 )
             
-            if not model_id:
-                return NodeResult(
-                    success=False,
-                    error='请选择 LLM 模型',
-                )
+            from ai_platform.services.llm_service import LLMService
+
+            llm_service = LLMService(context.db_session)
+            model_id = await llm_service.resolve_chat_model_id(model_id)
             
             # Step 1: 获取数据库 Schema
             
@@ -248,10 +247,7 @@ class TextToSqlNode(BaseNode):
             
             # Step 2: 调用 LLM 生成 SQL
             from datetime import datetime
-            from ai_platform.services.llm_service import LLMService
-            
             db_type = await self._get_db_type(db_connection)
-            llm_service = LLMService(context.db_session)
             llm_result = None
             use_function_calling = self.config.get('use_function_calling', True)
             
@@ -354,6 +350,7 @@ class TextToSqlNode(BaseNode):
                 tokens_used=response.total_tokens,
                 elapsed_time=elapsed_time,
                 metadata={
+                    'model_id': str(model_id),
                     'model': response.model,
                     'thought': thought,
                     'suggested_next_node': 'db_sql',
@@ -404,13 +401,22 @@ class TextToSqlNode(BaseNode):
                 )
                 return NodeResult(success=False, error='请输入要查询的问题')
             
-            if not model_id:
+            import asyncio
+            from ai_platform.services.llm_service import LLMService
+
+            llm_service = LLMService(context.db_session)
+            try:
+                model_id = asyncio.get_event_loop().run_until_complete(
+                    llm_service.resolve_chat_model_id(model_id)
+                )
+            except Exception as e:
+                error_message = str(e)
                 yield TextToSqlStreamEvent(
                     event_type='error',
-                    content='请选择 LLM 模型',
+                    content=error_message,
                     is_finished=True,
                 )
-                return NodeResult(success=False, error='请选择 LLM 模型')
+                return NodeResult(success=False, error=error_message)
             
             # Step 1: 获取数据库 Schema
             yield TextToSqlStreamEvent(
@@ -420,7 +426,6 @@ class TextToSqlNode(BaseNode):
             
             table_relations = self.config.get('table_relations', [])  # 手动指定的表关系
             
-            import asyncio
             schema_context = asyncio.get_event_loop().run_until_complete(
                 self._get_schema_context(
                     db_connection,
@@ -449,13 +454,10 @@ class TextToSqlNode(BaseNode):
             )
             
             from datetime import datetime
-            from ai_platform.services.llm_service import LLMService
-            
             db_type = asyncio.get_event_loop().run_until_complete(
                 self._get_db_type(db_connection)
             )
             
-            llm_service = LLMService()
             accumulated_content = ''
             total_tokens = 0
             llm_result = None
@@ -566,6 +568,7 @@ class TextToSqlNode(BaseNode):
                 tokens_used=total_tokens,
                 elapsed_time=elapsed_time,
                 metadata={
+                    'model_id': str(model_id),
                     'thought': thought,
                     'suggested_next_node': 'db_sql',
                 },