Update app.py

app.py

@@ -3,43 +3,73 @@ 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):
-        """初始化搜尋 Agent"""
+        """用 HuggingFace Inference API"""
+        self.hf_token = os.getenv("HF_TOKEN")
+        self.model_name = "meta-llama/Llama-2-7b-chat-hf"
+        
+        if not self.hf_token:
+            print("✗ HF_TOKEN not found")
+            self.agent = None
+            return
+        
+        self.agent_url = f"{HF_API_URL}/{self.model_name}"
         self.agent = True
-        print("✓ Search agent initialized")
+        print("✓ Agent initialized with HF API")
 
     def __call__(self, question: str) -> str:
-        """用 DuckDuckGo 搜尋回答問題"""
+        """透過 HF Inference API 呼叫模型"""
+        if self.agent is None:
+            return "HF_TOKEN not configured. Add to Secrets!"
+        
         try:
-            ddgs = DDGS()
-            results = ddgs.text(question, max_results=5)
+            headers = {"Authorization": f"Bearer {self.hf_token}"}
+            
+            payload = {
+                "inputs": question,
+                "parameters": {
+                    "max_new_tokens": 256,
+                    "temperature": 0.7,
+                    "top_p": 0.9
+                }
+            }
+            
+            response = requests.post(
+                self.agent_url,
+                headers=headers,
+                json=payload,
+                timeout=60
+            )
+            
+            if response.status_code != 200:
+                return f"API Error {response.status_code}"
+            
+            result = response.json()
             
-            if not results:
-                return "No search results found for this question."
+            if isinstance(result, list) and len(result) > 0:
+                answer = result[0].get("generated_text", "")
+                # 去除問題部分，只保留答案
+                answer = answer.replace(question, "").strip()
+                return answer[:1000] if answer else "No answer generated"
             
-            # 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"
+            return "Invalid response"
             
-            return answer.strip() if answer else "Could not find relevant information"
+        except requests.exceptions.Timeout:
+            return "API timeout - try again"
         except Exception as e:
-            print(f"Search error: {e}")
-            return f"Unable to search: Please try again"
+            print(f"Error: {e}")
+            return f"Error: {str(e)[:100]}"
 
 
 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
     
@@ -50,15 +80,13 @@ def run_and_submit_all(profile: Optional[gr.OAuthProfile] = None):
     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)}", None
+        return f"Error: {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()
@@ -69,7 +97,6 @@ def run_and_submit_all(profile: Optional[gr.OAuthProfile] = None):
     answers_payload = []
     results_log = []
 
-    # 逐個回答問題
     total = len(questions_data)
     for idx, item in enumerate(questions_data, 1):
         task_id = item.get("task_id")
@@ -100,7 +127,6 @@ 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, 
@@ -122,10 +148,9 @@ def run_and_submit_all(profile: Optional[gr.OAuthProfile] = None):
     return status_msg, pd.DataFrame(results_log)
 
 
-# Gradio UI
 with gr.Blocks(title="Unit 4 Final Assignment") as demo:
     gr.Markdown("# Unit 4 Final Project: AI Agent")
-    gr.Markdown("_Using DuckDuckGo Search to answer questions_")
+    gr.Markdown("_Using Hugging Face Inference API_")
     
     with gr.Row():
         gr.LoginButton(scale=1)