Update app.py

app.py

@@ -5,38 +5,44 @@ import pandas as pd
 from typing import Optional
 from smolagents import CodeAgent, OpenAIServerModel, tool
 
-# --- 搜尋工具設定 ---
-# 把原本 import DDGS 的地方刪掉，換成這個：
+# --- 搜尋工具設定 (防封鎖版) ---
 try:
-    from googlesearch import search
+    from duckduckgo_search import DDGS
 except ImportError:
     import os
-    os.system('pip install googlesearch-python')
-    from googlesearch import search
+    os.system('pip install duckduckgo-search>=6.0.0')
+    from duckduckgo_search import DDGS
 
 @tool
 def web_search(query: str) -> str:
     """
-    Search the web using Google.
+    Search the web for information using DuckDuckGo.
     Args:
         query: The search query string.
     """
-    print(f"🕵️ [Debug] Google Searching: {query}")
+    print(f"🕵️ [Debug] Searching: {query}")
     try:
-        # Google search 只抓前 3 筆網址，Agent 沒辦法直接讀內容，
-        # 但 smolagents 有時候會聰明地只看標題。
-        # 這是目前救急的方法。
-        results = []
-        for j in search(query, num_results=3, advanced=True):
-            results.append(f"Title: {j.title}\nDescription: {j.description}")
-        
+        # 關鍵修正：使用 backend='html' 比較不容易被擋
+        # 限制 max_results=3 避免資料太多模型讀不完
+        with DDGS() as ddgs:
+            results = ddgs.text(query, max_results=3, backend="html")
+            
         if not results:
-            return "No results found."
-        return "\n---\n".join(results)
+            return "No search results found. Try a different query."
+            
+        # 整理結果成字串
+        formatted_results = []
+        for r in results:
+            title = r.get('title', 'No Title')
+            body = r.get('body', 'No Description')
+            formatted_results.append(f"Title: {title}\nSummary: {body}")
+            
+        return "\n---\n".join(formatted_results)
         
     except Exception as e:
         print(f"❌ Search Error: {e}")
-        return "Search failed."
+        return f"Search failed due to error: {e}"
+
 # -----------------------------------------------------------
 
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
@@ -48,17 +54,18 @@ class GroqAgent:
             self.agent = None
             return
             
-        # 修正：換回目前 Groq 支援的主力模型
+        # 回到聰明的 70B 模型
         model = OpenAIServerModel(
-            model_id="llama-3.1-8b-instant",
+            model_id="llama-3.3-70b-versatile",
             api_base="https://api.groq.com/openai/v1",
             api_key=self.api_key
         )
         
+        # 使用我們強化的 web_search
         self.agent = CodeAgent(
             tools=[web_search], 
             model=model,
-            max_steps=3, # 減少步數，避免想太久卡住
+            max_steps=3, 
             verbosity_level=1
         )
     
@@ -67,11 +74,12 @@ class GroqAgent:
             return "Error: GROQ_API_KEY not configured."
         
         try:
-            # 極簡化 Prompt，讓模型反應更快
+            # 提示詞優化：告訴模型如果找不到就猜，避免卡死
             prompt = f"""
-            Task: Answer the question concisely.
-            Tool: Use 'web_search' only for specific facts (names, dates).
-            Fallback: If search fails, guess.
+            You are a helpful assistant. Answer the question concisely.
+            1. Use 'web_search' to find facts (names, dates, numbers).
+            2. If the search tool returns 'No results', DO NOT retry endlessly. Just give your best guess based on the question context.
+            3. For image/audio questions, just search for the text description provided in the question.
             
             Question: {question}
             """
@@ -115,7 +123,7 @@ def run_and_submit_all(profile: Optional[gr.OAuthProfile] = None):
         ans = agent_wrapper(q)
         
         answers.append({"task_id": tid, "submitted_answer": ans})
-        logs.append({"Task": tid, "Answer": ans[:50] + "..."})
+        logs.append({"Task": tid, "Answer": str(ans)[:100]})
 
     try:
         print("Submitting...")
@@ -128,15 +136,14 @@ def run_and_submit_all(profile: Optional[gr.OAuthProfile] = None):
         data = res.json()
         score = data.get('score', 0)
         
-        # 只要有一題對就是成功，通常文字搜尋題會對，圖片題會錯
         msg = f"🎉 Final Score: {score}%" 
         return msg, pd.DataFrame(logs)
         
     except Exception as e:
         return f"Submit error: {str(e)}", pd.DataFrame(logs)
 
-with gr.Blocks(title="Final Agent (Fixed Model)") as demo:
-    gr.Markdown("# 🚀 Final Agent (Llama 3.3)")
+with gr.Blocks(title="Final Agent (Ultimate Fix)") as demo:
+    gr.Markdown("# 🚀 Final Agent (70B + Anti-Block Search)")
     with gr.Row():
         gr.LoginButton()
         btn = gr.Button("Run Evaluation", variant="primary")