Update app.py

app.py

@@ -244,14 +244,26 @@ def simulate_summary(iteration: int, score: float, target: float) -> Dict[str, A
         "考虑性能优化",
     ]
     
-    # 模拟波动：使用阻尼振荡 + 噪声
-    damping = 0.15 * (0.9 ** iteration)
-    oscillation = damping * (0.8 if iteration % 2 == 0 else -0.8)
-    noise = random.uniform(-0.08, 0.08)
-    trend = (target - score) * 0.1
+    # 改进分数模拟逻辑：
+    # 1. 起始阶段（iteration <= 2）：强劲上升趋势
+    # 2. 中期阶段：波动上升
+    # 3. 后期阶段：阻尼振荡，接近目标
+    
+    if iteration <= 2:
+        # 早期：强劲上升
+        base_gain = random.uniform(0.15, 0.25)
+        noise = random.uniform(-0.03, 0.05)
+        new_score = score + base_gain + noise
+    else:
+        # 中后期：阻尼振荡
+        damping = 0.12 * (0.85 ** (iteration - 2))
+        oscillation = damping * (1.0 if iteration % 2 == 0 else -0.6)
+        noise = random.uniform(-0.05, 0.05)
+        trend = (target - score) * 0.15
+        new_score = score + trend + oscillation + noise
     
-    new_score = score + trend + oscillation + noise
-    new_score = max(0.1, min(1.0, new_score))
+    # 限制范围
+    new_score = max(0.15, min(1.0, new_score))
     
     if new_score >= score:
         reflection = random.choice(reflections_positive)
@@ -410,12 +422,12 @@ def create_demo():
             current_score = 0.0
             
             empty_md = "*等待开始...*"
-            yield "状态: 开始执行任务...", pd.DataFrame(columns=["iteration", "score"]), empty_md, empty_md, empty_md, empty_md
+            # 初始状态：显示"准备中"
+            yield "状态: 准备执行任务...", pd.DataFrame(columns=["iteration", "score"]), empty_md, empty_md, empty_md, empty_md
             
+            # 先执行完整的一次 PEES 迭代，然后一起更新
             for i in range(1, int(max_iter) + 1):
-                status = f"状态: 正在执行第 {i} 次迭代..."
-                yield status, pd.DataFrame(chart_data) if chart_data else pd.DataFrame(columns=["iteration", "score"]), empty_md, empty_md, empty_md, empty_md
-                
+                # 执行完整迭代
                 results, current_score = run_pees_iteration(task, i, current_score, target)
                 
                 # 分别获取四个阶段的结果
@@ -464,7 +476,8 @@ def create_demo():
                 # 更新图表数据
                 chart_data.append({"iteration": i, "score": current_score})
                 
-                status = f"状态: 第 {i} 次迭代完成 (分数: {current_score:.2f})"
+                # 每次迭代完成后才更新 UI
+                status = f"状态: 第 {i}/{int(max_iter)} 次迭代完成 (分数: {current_score:.2f})"
                 yield status, pd.DataFrame(chart_data), plan_md, exec1_md, exec2_md, summary_md
                 
                 # 检查是否达到目标