feat: improve agent collaboration observability

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

@@ -163,6 +163,7 @@ class LLMNode(BaseNode):
             
             # 调用 LLM（异步）
             llm_service = LLMService(context.db_session)
+            model_id = await llm_service.resolve_chat_model_id(model_id)
             output_var = self.config.get('output_variable', 'llm_response')
             
             # 根据输出模式选择执行方式
@@ -172,6 +173,11 @@ class LLMNode(BaseNode):
                     llm_service, model_id, messages, temperature, max_tokens,
                     output_schema, output_var, start_time
                 )
+                result.metadata = {
+                    **(result.metadata or {}),
+                    'model_id': str(model_id),
+                    'output_variable': output_var,
+                }
                 return result
             else:
                 # 普通文本输出模式（异步）
@@ -194,9 +200,11 @@ class LLMNode(BaseNode):
                     tokens_used=response.total_tokens,
                     elapsed_time=elapsed_time,
                     metadata={
+                        'model_id': str(model_id),
                         'model': response.model,
                         'prompt_tokens': response.prompt_tokens,
                         'completion_tokens': response.completion_tokens,
+                        'output_variable': output_var,
                     },
                 )
             
@@ -314,6 +322,11 @@ class LLMNode(BaseNode):
                     llm_service, model_id, messages, temperature, max_tokens,
                     output_schema, output_var, start_time
                 )
+                result.metadata = {
+                    **(result.metadata or {}),
+                    'model_id': str(model_id),
+                    'output_variable': output_var,
+                }
                 return result
             else:
                 # 普通文本输出模式
@@ -350,6 +363,10 @@ class LLMNode(BaseNode):
                     },
                     tokens_used=total_tokens,
                     elapsed_time=elapsed_time,
+                    metadata={
+                        'model_id': str(model_id),
+                        'output_variable': output_var,
+                    },
                 )
             
         except Exception as e: