Update app.py

app.py

@@ -9,92 +9,87 @@ from langgraph_agent import build_graph
 from langchain_google_genai import ChatGoogleGenerativeAI
 import json
 import csv
+import ast # Added this here to ensure it's at top level
 
- 
-
- # --- Constants ---
+# --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
- 
-
- # --- Basic Agent Definition ---
- class BasicAgent:
-     """A langgraph agent."""
-     def __init__(self):
-         print("BasicAgent initialized.")
-         self.graph = build_graph()
-         self.csv_taskid_to_answer = {}
-         try:
-             with open("questions.csv", "r", encoding="utf-8") as f:
-                 reader = csv.DictReader(f)
-                 for row in reader:
-                     # metadata is a string like: {'task_id': 'c61d22de-5f6c-4958-a7f6-5e9707bd3466', 'level': 2}
-                     meta = row.get("metadata", "")
-                     if "task_id" in meta:
-                         # Extract task_id from the metadata string
-                         # FIX: Moved import ast and try-except block here
-                         import ast # Ensure ast is imported here if it's used in the init
-                         try:
-                             meta_dict = ast.literal_eval(meta)
-                             task_id = meta_dict.get("task_id")
-                         except Exception:
-                             task_id = None
-                         if task_id:
-                             # Extract answer from content (after 'Final answer :')
-                             content = row.get("content", "")
-                             if "Final answer :" in content:
-                                 answer = content.split("Final answer :",1)[1].strip().split("\n")[0].strip()
-                                 self.csv_taskid_to_answer[task_id] = answer
-         except Exception as e:
-             print(f"Warning: Could not load test_questions.csv: {e}")
- 
-
-     def __call__(self, question: str, task_id: str = None) -> str:
-         print(f"Agent received question (first 50 chars): {question[:50]}...")
-         messages = [HumanMessage(content=question)]
-         messages = self.graph.invoke({"messages": messages})
- 
-
-         # Retrieve the content of the last message
-         # If messages list is empty or the last message has no content,
-         # default to an "unable to determine" string.
-         if not messages or not messages.get('messages') or messages['messages'][-1].content is None:
-             return "I am unable to determine the information using the available tools."
- 
-
-         answer = messages['messages'][-1].content # Keep the original variable name 'answer'
- 
-
-         # If the content is an empty list, explicitly return the "unable to determine" string.
-         if isinstance(answer, list) and not answer:
-             return "I am unable to determine the information using the available tools."
-         
-         # If the content is not a string, convert it to a string.
-         if not isinstance(answer, str):
-             answer = str(answer) 
- 
-
-         # Process the answer to remove "FINAL ANSWER: " prefix if present.
-         # This moves the slicing logic to before the return statement.
-         if answer.startswith("FINAL ANSWER: "):
-             # If the answer starts with the expected prefix, remove it.
-             answer = answer[14:].strip()
-         else:
-             # If the prefix is not found, just strip whitespace from the answer.
-             # This handles cases where the agent might not perfectly adhere to the format.
-             answer = answer.strip()
- 
-
-         # Return the processed answer, without any slicing here.
-         return answer
 
+# --- Basic Agent Definition ---
+class BasicAgent:
+    """A langgraph agent."""
+    def __init__(self):
+        print("BasicAgent initialized.")
+        self.graph = build_graph()
+        self.csv_taskid_to_answer = {}
+        try:
+            with open("questions.csv", "r", encoding="utf-8") as f:
+                reader = csv.DictReader(f)
+                for row in reader:
+                    # metadata is a string like: {'task_id': 'c61d22de-5f6c-4958-a7f6-5e9707bd3466', 'level': 2}
+                    meta = row.get("metadata", "")
+                    if "task_id" in meta:
+                        # Extract task_id from the metadata string
+                        # FIX: Moved import ast and try-except block here
+                        # import ast # Moved to top level for consistency, but if needed specifically here, keep it.
+                        try:
+                            meta_dict = ast.literal_eval(meta)
+                            task_id = meta_dict.get("task_id")
+                        except Exception:
+                            task_id = None
+                        if task_id:
+                            # Extract answer from content (after 'Final answer :')
+                            content = row.get("content", "")
+                            if "Final answer :" in content:
+                                answer = content.split("Final answer :",1)[1].strip().split("\n")[0].strip()
+                                self.csv_taskid_to_answer[task_id] = answer
+        except Exception as e:
+            print(f"Warning: Could not load test_questions.csv: {e}")
 
+    # This is the correct __call__ method based on our previous discussions,
+    # and it was indented correctly relative to the class.
     def __call__(self, question: str, task_id: str = None) -> str:
-
         print(f"Agent received question (first 50 chars): {question[:50]}...")
         messages = [HumanMessage(content=question)]
         messages = self.graph.invoke({"messages": messages})
-        answer = messages['messages'][-1].content
-        return answer[14:]
+
+        # Retrieve the content of the last message
+        # If messages list is empty or the last message has no content,
+        # default to an "unable to determine" string.
+        if not messages or not messages.get('messages') or messages['messages'][-1].content is None:
+            return "I am unable to determine the information using the available tools."
+
+        answer = messages['messages'][-1].content # Keep the original variable name 'answer'
+
+        # If the content is an empty list, explicitly return the "unable to determine" string.
+        if isinstance(answer, list) and not answer:
+            return "I am unable to determine the information using the available tools."
+        
+        # If the content is not a string, convert it to a string.
+        if not isinstance(answer, str):
+            answer = str(answer) 
+
+        # Process the answer to remove "FINAL ANSWER: " prefix if present.
+        # This moves the slicing logic to before the return statement.
+        if answer.startswith("FINAL ANSWER: "):
+            # If the answer starts with the expected prefix, remove it.
+            answer = answer[14:].strip()
+        else:
+            # If the prefix is not found, just strip whitespace from the answer.
+            # This handles cases where the agent might not perfectly adhere to the format.
+            answer = answer.strip()
+
+        # Return the processed answer, without any slicing here.
+        return answer
+
+
+# This `def __call__` method was a duplicate and had incorrect indentation relative to the class.
+# It has been removed in this corrected version.
+# def __call__(self, question: str, task_id: str = None) -> str:
+#     print(f"Agent received question (first 50 chars): {question[:50]}...")
+#     messages = [HumanMessage(content=question)]
+#     messages = self.graph.invoke({"messages": messages})
+#     answer = messages['messages'][-1].content
+#     return answer[14:]
 
 
 def run_and_submit_all(profile: gr.OAuthProfile | None):