Update app.py

app.py

@@ -14,65 +14,62 @@ SUBMIT_URL = "https://agents-course-unit4-scoring.hf.space/submit"
 FILES_URL = "https://agents-course-unit4-scoring.hf.space/files"
 FILES_DIR = "files"
 SYSTEM_PROMPT = "You are a helpful AI assistant tasked with answering questions accurately. Provide concise and accurate answers in the format requested by the question."
-XAI_API_KEY = "xai-eW0NtAmIUlCMZewxaYtnXM0Wl5i4pUKFVFZmejBjYzGYq15z2RXxbOq2k9HmdEwVEHzqPSazslQxDIBV"
-XAI_API_URL = "https://api.x.ai/v1/chat/completions"
+GEMINI_API_KEY = "AIzaSyBvImpFo9o5Dz8OL_mfFEoRijeUyYBvXiI"
+GEMINI_API_URL = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key={GEMINI_API_KEY}"
 
 # --- AssistantAgent Implementation ---
 class AssistantAgent:
     def __init__(self, system_prompt: str):
         self.system_prompt = system_prompt
-        self.headers = {
-            "Authorization": f"Bearer {XAI_API_KEY}",
-            "Content-Type": "application/json"
-        }
+        self.headers = {"Content-Type": "application/json"}
 
-    def call_xai_api(self, prompt: str) -> str:
+    def call_gemini_api(self, prompt: str) -> str:
+        retry_delay = 60  # Chờ 60 giây nếu gặp lỗi quota
         payload = {
-            "messages": [
-                {"role": "system", "content": self.system_prompt},
-                {"role": "user", "content": prompt}
-            ],
-            "model": "grok-3-latest",
-            "stream": False,
-            "temperature": 0
+            "contents": [{
+                "parts": [{"text": prompt}]
+            }]
         }
-        try:
-            response = requests.post(XAI_API_URL, headers=self.headers, json=payload, timeout=10)
-            response.raise_for_status()
-            return response.json()["choices"][0]["message"]["content"].strip()
-        except requests.exceptions.RequestException as e:
-            return f"Error calling xAI API: {e}"
+        for attempt in range(3):
+            try:
+                response = requests.post(GEMINI_API_URL, headers=self.headers, json=payload, timeout=10)
+                response.raise_for_status()
+                return response.json()["candidates"][0]["content"]["parts"][0]["text"].strip()
+            except requests.exceptions.RequestException as e:
+                if "429" in str(e):
+                    retry_delay = max(retry_delay, 60)
+                    print(f"Quota error, retrying after {retry_delay} seconds... (Attempt {attempt + 1}/3)")
+                    time.sleep(retry_delay)
+                    retry_delay += 10
+                else:
+                    return f"Error calling Gemini API: {e}"
+        return "Error: Exceeded retry attempts due to quota limits."
 
     def check_commutative(self, table: str) -> str:
         try:
-            # Tách các dòng của bảng
             rows = table.strip().split('\n')
-            if len(rows) < 3:  # Cần ít nhất 3 dòng (header, phân cách, dữ liệu)
+            if len(rows) < 3:
                 return "Error: Table format is invalid (not enough rows)."
 
-            # Lấy danh sách phần tử từ dòng đầu tiên (header)
             header = rows[0].split('|')
-            if len(header) < 3:  # Cần ít nhất 3 cột (|, phần tử, |)
+            if len(header) < 3:
                 return "Error: Table format is invalid (header too short)."
 
-            elements = header[1:-1][1:]  # Bỏ cột đầu tiên (*) và cột cuối, bỏ ký hiệu |
+            elements = header[1:-1][1:]
             num_elements = len(elements)
             if num_elements < 1:
                 return "Error: No elements found in table header."
 
-            # Kiểm tra số dòng dữ liệu (phải khớp với số phần tử + 2 dòng header)
             if len(rows) != num_elements + 2:
                 return f"Error: Table row count ({len(rows)}) does not match expected ({num_elements + 2})."
 
-            # Kiểm tra định dạng dòng phân cách
             if not rows[1].startswith('|---'):
                 return "Error: Table format is invalid (missing separator row)."
 
-            # Xây dựng bảng phép toán
             operation = {}
             for i in range(2, len(rows)):
                 cols = rows[i].split('|')
-                if len(cols) != num_elements + 2:  # Số cột phải khớp với số phần tử + 2
+                if len(cols) != num_elements + 2:
                     return f"Error: Row {i} has incorrect number of columns (expected {num_elements + 2}, got {len(cols)})."
 
                 for j in range(1, len(cols) - 1):
@@ -81,7 +78,6 @@ class AssistantAgent:
                         return f"Error: Invalid value '{val}' in table (not in {elements})."
                     operation[(elements[i - 2], elements[j - 1])] = val
 
-            # Tìm các cặp không giao hoán: a*b != b*a
             non_commutative = set()
             for a in elements:
                 for b in elements:
@@ -121,11 +117,11 @@ class AssistantAgent:
         answers = []
         for i in range(0, len(questions), batch_size):
             batch = questions[i:i + batch_size]
-            prompt = "Answer the following questions concisely:\n"
+            prompt = f"{self.system_prompt}\nAnswer the following questions concisely:\n"
             for idx, (question, _) in enumerate(batch, 1):
                 prompt += f"{idx}. {question}\n"
 
-            batch_answers = self.call_xai_api(prompt)
+            batch_answers = self.call_gemini_api(prompt)
             if "Error" in batch_answers:
                 answers.extend([batch_answers] * len(batch))
             else:
@@ -134,8 +130,8 @@ class AssistantAgent:
                     answer = batch_answers[idx].split('. ', 1)[1] if idx < len(batch_answers) and '. ' in batch_answers[idx] else "Error: Could not parse answer."
                     answers.append(answer)
             if i + batch_size < len(questions):
-                print("Waiting 1 second before next batch to avoid rate limit...")
-                time.sleep(1)
+                print("Waiting 60 seconds before next batch to avoid rate limit...")
+                time.sleep(60)
         return answers
 
     def process_file(self, question: str, file_path: str) -> str:
@@ -175,7 +171,7 @@ class AssistantAgent:
             except Exception as e:
                 return f"Error reading Excel file: {e}"
         else:
-            return "Error: xAI API does not support non-text files (e.g., images). Please provide a text description instead."
+            return "Error: Gemini API does not support non-text files (e.g., images). Please provide a text description instead."
 
     def __call__(self, question: str, file_path: str = None) -> str:
         if "provide the subset of S involved in any possible counter-examples" in question:
@@ -351,7 +347,7 @@ with gr.Blocks() as demo:
         1. Log in to your Hugging Face account using the button below.
         2. Click 'Run Evaluation & Submit All Answers' to fetch questions, run the agent, and submit answers.
         ---
-        **Note:** This is a setup for the Final Assignment Template. Agent uses xAI API (Grok) with optimized batch processing.
+        **Note:** This is a setup for the Final Assignment Template. Agent uses Gemini API (gemini-2.0-flash) with optimized batch processing.
         """
     )