Update app.py

app.py

@@ -11,14 +11,35 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
+# class BasicAgent:
+#     def __init__(self):
+#         print("BasicAgent initialized.")
+#     def __call__(self, question: str) -> str:
+#         print(f"Agent received question (first 50 chars): {question[:50]}...")
+#         fixed_answer = "This is a default answer."
+#         print(f"Agent returning fixed answer: {fixed_answer}")
+#         return fixed_answer
 class BasicAgent:
     def __init__(self):
         print("BasicAgent initialized.")
+        self.agent_graph = build_graph()
     def __call__(self, question: str) -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
-        fixed_answer = "This is a default answer."
-        print(f"Agent returning fixed answer: {fixed_answer}")
-        return fixed_answer
+        # fixed_answer = "This is a default answer."
+        # print(f"Agent returning fixed answer: {fixed_answer}")
+        # return fixed_answer
+        messages = [HumanMessage(content=f"Can you answer this question please ? {question}")]
+
+        messages = self.agent_graph.invoke({"messages": messages, "question": question}, {"recursion_limit": 10})
+
+        try:
+            regex_result = re.search(r"FINAL ANSWER:\s*(?P<answer>.*)$", messages['messages'][-1].content)
+            answer = regex_result.group("answer")
+        except:
+            regex_result = re.search(r"\s*(?P<answer>.*)$", messages['messages'][-1].content)
+            answer = regex_result.group("answer")
+        
+        return answer
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """
@@ -26,7 +47,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     and displays the results.
     """
     # --- Determine HF Space Runtime URL and Repo URL ---
-    space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
+    space_id = os.getenv("SPACE_ID", "local") # Get the SPACE_ID for sending link to the code
 
     if profile:
         username= f"{profile.username}"
@@ -37,28 +58,35 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
 
     api_url = DEFAULT_API_URL
     questions_url = f"{api_url}/questions"
+    one_question_url = f"{api_url}/random-question"
     submit_url = f"{api_url}/submit"
 
     # 1. Instantiate Agent ( modify this part to create your agent)
-    # try:
-    #     agent = BasicAgent()
-    # except Exception as e:
-    #     print(f"Error instantiating agent: {e}")
-    #     return f"Error initializing agent: {e}", None
-    # # In the case of an app running as a hugging Face space, this link points toward your codebase ( usefull for others so please keep it public)
-    # agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
-    # print(agent_code)
+    try:
+        agent = BasicAgent()
+    except Exception as e:
+        print(f"Error instantiating agent: {e}")
+        return f"Error initializing agent: {e}", None
+    # In the case of an app running as a hugging Face space, this link points toward your codebase ( usefull for others so please keep it public)
+    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
+    print(agent_code)
 
     # 2. Fetch Questions
-    print(f"Fetching questions from: {questions_url}")
+    # print(f"Fetching questions from: {questions_url}")
+    print(f"Fetching questions from: {one_question_url}")
     try:
-        response = requests.get(questions_url, timeout=15)
+        # response = requests.get(questions_url, timeout=15)
+        response = requests.get(one_question_url, timeout=15)
         response.raise_for_status()
         questions_data = response.json()
         if not questions_data:
              print("Fetched questions list is empty.")
              return "Fetched questions list is empty or invalid format.", None
-        print(f"Fetched {len(questions_data)} questions.")
+        if isinstance(questions_data, dict) and "question" in questions_data:
+            print("Fetched a single question instead of a list.")
+            questions_data = [questions_data]
+        elif isinstance(questions_data, list):
+            print(f"Fetched {len(questions_data)} questions.")
     except requests.exceptions.RequestException as e:
         print(f"Error fetching questions: {e}")
         return f"Error fetching questions: {e}", None
@@ -70,36 +98,32 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         print(f"An unexpected error occurred fetching questions: {e}")
         return f"An unexpected error occurred fetching questions: {e}", None
 
-    print(questions_data)
-
-    return None, None
-
     # 3. Run your Agent
-    # results_log = []
-    # answers_payload = []
-    # print(f"Running agent on {len(questions_data)} questions...")
-    # for item in questions_data:
-    #     task_id = item.get("task_id")
-    #     question_text = item.get("question")
-    #     if not task_id or question_text is None:
-    #         print(f"Skipping item with missing task_id or question: {item}")
-    #         continue
-    #     try:
-    #         submitted_answer = agent(question_text)
-    #         answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
-    #         results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
-    #     except Exception as e:
-    #          print(f"Error running agent on task {task_id}: {e}")
-    #          results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
-
-    # if not answers_payload:
-    #     print("Agent did not produce any answers to submit.")
-    #     return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
-
-    # # 4. Prepare Submission 
-    # submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
-    # status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
-    # print(status_update)
+    results_log = []
+    answers_payload = []
+    print(f"Running agent on {len(questions_data)} questions...")
+    for item in questions_data:
+        task_id = item.get("task_id")
+        question_text = item.get("question")
+        if not task_id or question_text is None:
+            print(f"Skipping item with missing task_id or question: {item}")
+            continue
+        try:
+            submitted_answer = agent(question_text)
+            answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
+            results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
+        except Exception as e:
+             print(f"Error running agent on task {task_id}: {e}")
+             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
+
+    if not answers_payload:
+        print("Agent did not produce any answers to submit.")
+        return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
+
+    # 4. Prepare Submission 
+    submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
+    status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
+    print(status_update)
 
     # # 5. Submit
     # print(f"Submitting {len(answers_payload)} answers to: {submit_url}")