Update app.py

app.py

@@ -7,7 +7,7 @@ import requests
 import pandas as pd
 from dotenv import load_dotenv
 from agent import Agent  # 引入你自己写的简易 agent.py
-
+agent = Agent() 
 # 加载 .env 中的 GOOGLE_API_KEY（agent.py 会使用）
 load_dotenv()
 
@@ -44,38 +44,33 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         return f"Error fetching questions: {e}", None
 
     # 2. 遍历题目并调用 Agent 获取答案
-    results_log     = []
+    results_log = []
     answers_payload = []
 
     for item in questions_data:
-        task_id      = item.get("task_id")
-        question_text = item.get("question")
-        if not task_id or question_text is None:
+        task_id  = item.get("task_id")
+        question = item.get("question")
+        if not task_id or question is None:
             continue
-
         try:
-            # 调用你在 agent.py 中定义的 Agent
-            submitted_answer = agent(question_text)
+        # 只调用一次，带 task_id
+            answer = agent(question, task_id=task_id)
 
             answers_payload.append({
                 "task_id": task_id,
-                "submitted_answer": submitted_answer
+                "submitted_answer": answer
             })
             results_log.append({
                 "Task ID": task_id,
-                "Question": question_text,
-                "Submitted Answer": submitted_answer
+                "Question": question,
+                "Submitted Answer": answer
             })
 
-            # 避免 API 速率限制
-            time.sleep(0.5)
+        time.sleep(0.3)          # 小延迟防止 QPS 超限
         except Exception as e:
             err = f"ERROR: {e}"
-            results_log.append({
-                "Task ID": task_id,
-                "Question": question_text,
-                "Submitted Answer": err
-            })
+            answers_payload.append({"task_id": task_id, "submitted_answer": err})
+            results_log.append({"Task ID": task_id, "Question": question, "Submitted Answer": err})
 
     if not answers_payload:
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)