feat: improve workflow collaboration trace UX

backend-fastapi/ai_platform/services/workflow_service.py

@@ -217,6 +217,7 @@ def _make_execution_log_entry(
     node_type: str,
     **extra: Any,
 ) -> dict:
+    extra.setdefault('timestamp', datetime.now().isoformat())
     metadata = dict(extra.pop('metadata', {}) or {})
     collaboration = _node_collaboration_metadata(node_map, node_id, node_type)
     branch_id = extra.get('branch') or extra.get('branch_id')
@@ -238,6 +239,7 @@ def _make_execution_log_entry(
         output=extra.get('output'),
         error=extra.get('error'),
     )
+    metadata['communication']['timestamp'] = extra.get('timestamp')
     return {
         'node_id': node_id,
         'node_type': node_type,
@@ -982,9 +984,18 @@ class AIWorkflowService:
                     current_id = next_nodes[0] if next_nodes else None
                     continue
                 
-                # 执行节点（异步）
+                node_inputs = _snapshot_node_inputs(branch_context)
+
+                # 执行节点（异步）。并行分支不能共享同一个 AsyncSession，否则模型/Provider 查询会并发抢占连接。
                 start_time = time.time()
-                result = await node_instance.execute_async(branch_context)
+                if context.db_session is not None:
+                    from app.database import AsyncSessionLocal
+
+                    async with AsyncSessionLocal() as branch_db:
+                        branch_context.db_session = branch_db
+                        result = await node_instance.execute_async(branch_context)
+                else:
+                    result = await node_instance.execute_async(branch_context)
                 elapsed = int((time.time() - start_time) * 1000)
                 target_node_id = _resolve_handoff_target(
                     current_id,
@@ -1004,6 +1015,7 @@ class AIWorkflowService:
                     elapsed_time=elapsed,
                     tokens_used=result.tokens_used,
                     metadata=_node_result_metadata(result),
+                    inputs=copy.deepcopy(node_inputs),
                     branch=branch_id,
                     branch_label=branch_labels.get(branch_id, branch_id),
                     target_node_id=target_node_id,
@@ -1027,6 +1039,12 @@ class AIWorkflowService:
                 branch_context.variables.update(result.output_variables)
                 branch_context.previous_output = result.output
                 branch_output = result.output
+
+                # 支持分支内后续节点使用 {{node_id.output_variable}} 引用当前节点输出。
+                branch_context.variables[f'_node_{current_id}'] = {
+                    'output': result.output,
+                    **result.output_variables,
+                }
                 
                 # 下一个节点
                 if result.next_node_id: