Update app.py

app.py

@@ -2,46 +2,46 @@ import os
 import gradio as gr
 import requests
 import pandas as pd
-import time
 from typing import Optional
 from smolagents import CodeAgent, OpenAIServerModel, tool
 
-# --- 搜尋工具 (Lite 後門版) ---
+# --- 搜尋工具 (極速減肥版) ---
 try:
     from duckduckgo_search import DDGS
 except ImportError:
     import os
-    os.system('pip install duckduckgo-search>=6.0.0')
+    os.system('pip install ddgs')
     from duckduckgo_search import DDGS
 
 @tool
 def web_search(query: str) -> str:
     """
-    Performs a web search using the 'lite' backend to bypass rate limits.
+    Search with strict length limits to prevent model hanging.
     Args:
         query: The search query string.
     """
-    print(f"🕵️ [Debug] Searching (Lite): {query}")
+    print(f"🕵️ [Debug] Searching: {query}")
     try:
-        # 關鍵修改：使用 backend='lite'
-        # 這是最原始的 HTML 介面，極少被封鎖
+        # 1. 使用 Lite 模式 (最快、不被擋)
+        # 2. 只抓 1 筆結果 (減少資料量)
         with DDGS() as ddgs:
-            results = ddgs.text(query, max_results=3, backend="lite")
+            results = list(ddgs.text(query, max_results=1, backend="lite"))
         
         if not results:
-            return "No results found."
+            return "No results. Guess the answer."
             
-        formatted = []
-        for r in results:
-            title = r.get('title', 'No Title')
-            body = r.get('body', 'No Description')
-            formatted.append(f"Title: {title}\nSnippet: {body}")
-            
-        return "\n---\n".join(formatted)
+        # 3. 關鍵修改：強制截斷文字！
+        # 只回傳前 400 個字，避免 70B 模型「噎住」
+        first_result = results[0]
+        title = first_result.get('title', '')
+        body = first_result.get('body', '')
+        summary = f"Title: {title}\nInfo: {body}"
+        
+        return summary[:400] # <--- 這裡就是防卡死的關鍵
         
     except Exception as e:
-        print(f"❌ Search Error: {e}")
-        return "Search failed. Ignore this and guess based on your knowledge."
+        print(f"❌ Error: {e}")
+        return "Search error. Guess answer."
 
 # -----------------------------------------------------------
 
@@ -54,7 +54,7 @@ class GroqAgent:
             self.agent = None
             return
             
-        # 堅持使用 Llama 3.3 (目前唯一活著且聰明的模型)
+        # 堅持使用 Llama 3.3 70B (它是唯一夠聰明能過關的)
         model = OpenAIServerModel(
             model_id="llama-3.3-70b-versatile",
             api_base="https://api.groq.com/openai/v1",
@@ -64,7 +64,7 @@ class GroqAgent:
         self.agent = CodeAgent(
             tools=[web_search], 
             model=model,
-            max_steps=3, 
+            max_steps=2, # 減少步數，逼它快點回答
             verbosity_level=1
         )
     
@@ -73,18 +73,18 @@ class GroqAgent:
             return "Error: GROQ_API_KEY not configured."
         
         try:
-            # 提示詞：強調「如果 Lite 搜尋失敗就直接回答」
+            # 提示詞：極度簡化，逼它直接回答
             prompt = f"""
-            You are a helpful assistant. Answer the question concisely.
-            1. Use 'web_search' to find facts.
-            2. If search returns "No results" or fails, DO NOT RETRY. Make your BEST GUESS from your training data immediately.
-            3. Answer directly.
+            Task: Answer concisely.
+            1. Search ONCE.
+            2. If search fails, GUESS immediately.
+            3. Do not overthink.
             
             Question: {question}
             """
             return str(self.agent.run(prompt))
         except Exception as e:
-            return f"Error: {str(e)[:150]}"
+            return f"Error: {str(e)[:100]}"
 
 def run_and_submit_all(profile: Optional[gr.OAuthProfile] = None):
     if profile is None:
@@ -118,6 +118,7 @@ def run_and_submit_all(profile: Optional[gr.OAuthProfile] = None):
         
         print(f"🚀 [{idx}/{total}] Task: {tid}")
         
+        # 執行 Agent
         ans = agent_wrapper(q)
         
         answers.append({"task_id": tid, "submitted_answer": ans})
@@ -138,8 +139,8 @@ def run_and_submit_all(profile: Optional[gr.OAuthProfile] = None):
     except Exception as e:
         return f"Submit error: {str(e)}", pd.DataFrame(logs)
 
-with gr.Blocks(title="Final Agent (Lite Backend)") as demo:
-    gr.Markdown("# 🚀 Final Agent (Lite Mode)")
+with gr.Blocks(title="Final Agent (Truncated)") as demo:
+    gr.Markdown("# 🚀 Final Agent (Anti-Hang Version)")
     with gr.Row():
         gr.LoginButton()
         btn = gr.Button("Run Evaluation", variant="primary")