Update app.py

app.py

@@ -2,10 +2,11 @@ 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 (DeepSeek R1 專用修復版) ---
+# --- 搜尋工具 (Lite 後門版) ---
 try:
     from duckduckgo_search import DDGS
 except ImportError:
@@ -16,27 +17,31 @@ except ImportError:
 @tool
 def web_search(query: str) -> str:
     """
-    Performs a web search using DuckDuckGo.
+    Performs a web search using the 'lite' backend to bypass rate limits.
     Args:
         query: The search query string.
     """
-    print(f"🕵️ [Debug] Searching: {query}")
+    print(f"🕵️ [Debug] Searching (Lite): {query}")
     try:
-        # 使用 backend='html' 來繞過 IP 封鎖
+        # 關鍵修改：使用 backend='lite'
+        # 這是最原始的 HTML 介面，極少被封鎖
         with DDGS() as ddgs:
-            results = ddgs.text(query, max_results=4, backend="html")
+            results = ddgs.text(query, max_results=3, backend="lite")
         
         if not results:
-            return "No results found. The search tool is being rate-limited."
+            return "No results found."
             
         formatted = []
         for r in results:
-            formatted.append(f"Title: {r.get('title')}\nSnippet: {r.get('body')}")
+            title = r.get('title', 'No Title')
+            body = r.get('body', 'No Description')
+            formatted.append(f"Title: {title}\nSnippet: {body}")
+            
         return "\n---\n".join(formatted)
         
     except Exception as e:
         print(f"❌ Search Error: {e}")
-        return "Search failed."
+        return "Search failed. Ignore this and guess based on your knowledge."
 
 # -----------------------------------------------------------
 
@@ -49,10 +54,9 @@ class GroqAgent:
             self.agent = None
             return
             
-        # 🔥 關鍵修改：使用 DeepSeek R1 (70B)
-        # 它的推理能力比 Llama 3.3 強，非常適合解決這種邏輯題
+        # 堅持使用 Llama 3.3 (目前唯一活著且聰明的模型)
         model = OpenAIServerModel(
-            model_id="deepseek-r1-distill-llama-70b",
+            model_id="llama-3.3-70b-versatile",
             api_base="https://api.groq.com/openai/v1",
             api_key=self.api_key
         )
@@ -69,12 +73,12 @@ class GroqAgent:
             return "Error: GROQ_API_KEY not configured."
         
         try:
-            # 針對 DeepSeek R1 的思維鏈提示詞
+            # 提示詞：強調「如果 Lite 搜尋失敗就直接回答」
             prompt = f"""
-            Answer the question concisely.
+            You are a helpful assistant. Answer the question concisely.
             1. Use 'web_search' to find facts.
-            2. If search fails or returns no results, use your internal knowledge to GUESS immediately.
-            3. Do not try to search more than once if it fails.
+            2. If search returns "No results" or fails, DO NOT RETRY. Make your BEST GUESS from your training data immediately.
+            3. Answer directly.
             
             Question: {question}
             """
@@ -134,8 +138,8 @@ 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 (DeepSeek R1)") as demo:
-    gr.Markdown("# 🚀 Final Agent (DeepSeek R1 70B)")
+with gr.Blocks(title="Final Agent (Lite Backend)") as demo:
+    gr.Markdown("# 🚀 Final Agent (Lite Mode)")
     with gr.Row():
         gr.LoginButton()
         btn = gr.Button("Run Evaluation", variant="primary")