feat:任务执行结果性能优化

backend/server.py

@@ -1,7 +1,8 @@
-from flask import Flask, request, jsonify
+from flask import Flask, request, jsonify, Response, stream_with_context
 import json
 from DataProcess import Add_Collaboration_Brief_FrontEnd
 from AgentCoord.RehearsalEngine_V2.ExecutePlan import executePlan
+from AgentCoord.RehearsalEngine_V2.ExecutePlan_Optimized import executePlan_streaming
 from AgentCoord.PlanEngine.basePlan_Generator import generate_basePlan
 from AgentCoord.PlanEngine.fill_stepTask import fill_stepTask
 from AgentCoord.PlanEngine.fill_stepTask_TaskProcess import (
@@ -257,6 +258,45 @@ def Handle_executePlan():
     return response
 
 
+@app.route("/executePlanOptimized", methods=["post"])
+def Handle_executePlanOptimized():
+    """
+    优化版流式执行计划（阶段1+2：步骤级流式 + 动作级智能并行）
+
+    返回 SSE 流，每完成一个动作就返回结果
+    - 无依赖关系的动作并行执行
+    - 有依赖关系的动作串行执行
+
+    前端使用 EventSource 接收
+    """
+    incoming_data = request.get_json()
+
+    def generate():
+        try:
+            for chunk in executePlan_streaming(
+                plan=incoming_data["plan"],
+                num_StepToRun=incoming_data.get("num_StepToRun"),
+                RehearsalLog=incoming_data.get("RehearsalLog", []),
+                AgentProfile_Dict=AgentProfile_Dict,
+            ):
+                yield chunk
+        except Exception as e:
+            error_event = json.dumps({
+                "type": "error",
+                "message": str(e)
+            }, ensure_ascii=False)
+            yield f"data: {error_event}\n\n"
+
+    return Response(
+        stream_with_context(generate()),
+        mimetype="text/event-stream",
+        headers={
+            "Cache-Control": "no-cache",
+            "X-Accel-Buffering": "no",
+        }
+    )
+
+
 @app.route("/_saveRequestCashe", methods=["post"])
 def Handle_saveRequestCashe():
     with open(