Update app.py

app.py

@@ -3,108 +3,79 @@ import gradio as gr
 import requests
 import pandas as pd
 from typing import Optional
+from duckduckgo_search import DDGS
 
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
-HF_API_URL = "https://api-inference.huggingface.co/models"
 
 class BasicAgent:
     def __init__(self):
-        """用 HuggingFace Inference API（不佔用本地記憶體）"""
-        self.hf_token = os.getenv("HF_TOKEN")
-        self.model_name = "mistralai/Mistral-7B-Instruct-v0.1"
-        
-        if not self.hf_token:
-            print("✗ HF_TOKEN not found in Secrets")
-            self.agent = None
-            return
-        
-        self.agent_url = f"{HF_API_URL}/{self.model_name}"
-        print("✓ Agent initialized (using HF Inference API)")
+        """初始化搜尋 Agent"""
+        self.agent = True
+        print("✓ Search agent initialized")
 
     def __call__(self, question: str) -> str:
-        """透過 API 呼叫模型"""
-        if self.agent is None:
-            return "HF_TOKEN not configured. Add it to Secrets."
-        
+        """用 DuckDuckGo 搜尋回答問題"""
         try:
-            headers = {"Authorization": f"Bearer {self.hf_token}"}
-            
-            payload = {
-                "inputs": question,
-                "parameters": {
-                    "max_new_tokens": 256,
-                    "temperature": 0.7,
-                    "top_p": 0.9
-                }
-            }
+            ddgs = DDGS()
+            results = ddgs.text(question, max_results=5)
             
-            response = requests.post(
-                self.agent_url,
-                headers=headers,
-                json=payload,
-                timeout=60
-            )
+            if not results:
+                return "No search results found for this question."
             
-            if response.status_code != 200:
-                return f"API error: {response.status_code}"
+            # 組合搜尋結果
+            answer = ""
+            for i, result in enumerate(results[:3], 1):
+                title = result.get('title', 'Unknown')
+                body = result.get('body', '')[:300]
+                answer += f"{title}: {body}\n"
             
-            result = response.json()
-            
-            # 解析回應
-            if isinstance(result, list) and len(result) > 0:
-                answer = result[0].get("generated_text", "")
-                # 去除問題部分
-                answer = answer.replace(question, "").strip()
-                return answer[:1000] if answer else "No answer"
-            
-            return "Invalid API response"
-            
-        except requests.exceptions.Timeout:
-            return "API request timeout"
+            return answer.strip() if answer else "Could not find relevant information"
         except Exception as e:
-            print(f"Error: {e}")
-            return f"Error: {str(e)[:200]}"
+            print(f"Search error: {e}")
+            return f"Unable to search: Please try again"
 
 
 def run_and_submit_all(profile: Optional[gr.OAuthProfile] = None):
     """主要評估和提交函數"""
     
+    # 檢查登入
     if profile is None:
         return "Please Login to Hugging Face with the button.", None
     
     username = profile.username
-    space_id = os.getenv("SPACE_ID")
-    
-    if not space_id:
-        return "Error: SPACE_ID not set.", None
+    space_id = os.getenv("SPACE_ID", "s1144662")
 
     api_url = DEFAULT_API_URL
     questions_url = f"{api_url}/questions"
     submit_url = f"{api_url}/submit"
 
+    # 初始化 Agent
     try:
         agent = BasicAgent()
     except Exception as e:
-        return f"Error initializing agent: {str(e)[:200]}", None
+        return f"Error initializing agent: {str(e)}", None
 
     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
 
+    # 獲取問題
     try:
         response = requests.get(questions_url, timeout=30)
         response.raise_for_status()
         questions_data = response.json()
     except Exception as e:
-        return f"Error fetching questions: {str(e)[:200]}", None
+        return f"Error fetching questions: {str(e)}", None
 
     answers_payload = []
     results_log = []
 
-    for idx, item in enumerate(questions_data):
+    # 逐個回答問題
+    total = len(questions_data)
+    for idx, item in enumerate(questions_data, 1):
         task_id = item.get("task_id")
         question_text = item.get("question")
         
-        print(f"[{idx+1}/{len(questions_data)}] Processing: {task_id}")
+        print(f"[{idx}/{total}] Processing: {task_id}")
         
         try:
             submitted_answer = agent(question_text)
@@ -115,10 +86,10 @@ def run_and_submit_all(profile: Optional[gr.OAuthProfile] = None):
             results_log.append({
                 "Task ID": task_id, 
                 "Question": question_text[:80],
-                "Answer": submitted_answer[:150]
+                "Answer": submitted_answer[:200]
             })
         except Exception as e:
-            error_answer = f"Error: {str(e)[:100]}"
+            error_answer = f"Error: {str(e)}"
             answers_payload.append({
                 "task_id": task_id, 
                 "submitted_answer": error_answer
@@ -129,6 +100,7 @@ def run_and_submit_all(profile: Optional[gr.OAuthProfile] = None):
                 "Answer": error_answer
             })
 
+    # 提交答案
     submission_data = {
         "username": username, 
         "agent_code": agent_code, 
@@ -142,10 +114,10 @@ def run_and_submit_all(profile: Optional[gr.OAuthProfile] = None):
         
         score = result_data.get('score', 'N/A')
         correct = result_data.get('correct_count', 0)
-        total = result_data.get('total_attempted', 0)
-        status_msg = f"Score: {score}% ({correct}/{total} correct)"
+        total_q = result_data.get('total_attempted', 0)
+        status_msg = f"✓ Score: {score}% ({correct}/{total_q} correct)"
     except Exception as e:
-        status_msg = f"Submission Failed: {str(e)[:200]}"
+        status_msg = f"✗ Submission Failed: {str(e)}"
 
     return status_msg, pd.DataFrame(results_log)
 
@@ -153,7 +125,7 @@ def run_and_submit_all(profile: Optional[gr.OAuthProfile] = None):
 # Gradio UI
 with gr.Blocks(title="Unit 4 Final Assignment") as demo:
     gr.Markdown("# Unit 4 Final Project: AI Agent")
-    gr.Markdown("_Click 'Login with Hugging Face' first, then 'Run Evaluation & Submit All Answers'_")
+    gr.Markdown("_Using DuckDuckGo Search to answer questions_")
     
     with gr.Row():
         gr.LoginButton(scale=1)