New attempt.

app.py

@@ -3,7 +3,9 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
-from smolagents import CodeAgent
+from smolagents.agent import PythonInterpreterAgent
+from smolagents.search import WebSummarySearch
+from smolagents.task_manager import PythonInterpreterTaskManager
 
 # (Keep Constants as is)
 # --- Constants ---
@@ -11,42 +13,46 @@ 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 with smolagents.")
-        # Initialize CodeAgent with required 'tools' and 'model' parameters
-        # Using Qwen code model instead of gpt-3.5-turbo
-        tools = []  # Empty list of tools or define your specific tools here
-        model = "Qwen/Qwen1.5-14B-Chat"  # Using Qwen code model
-        self.agent = CodeAgent(tools=tools, model=model)
-
+        print("BasicAgent initialized.")
+        # Initialize web search capability
+        self.search_tool = WebSummarySearch()
+        # Initialize Python interpreter agent with search tool
+        self.task_manager = PythonInterpreterTaskManager(
+            tools=[self.search_tool],
+        )
+        self.agent = PythonInterpreterAgent(self.task_manager)
+        print("Search capability initialized.")
+        
     def __call__(self, question: str) -> str:
-        print(f"Agent received question: {question[:50]}...")
-
+        print(f"Agent received question (first 50 chars): {question[:50]}...")
         try:
-            # Format the question as a proper prompt for CodeAgent
-            prompt = f"Answer this question: {question}"
-            search_result = self.agent.run(prompt)  # Pass the prompt as a positional argument
-            answer = search_result  # Return the direct result from the agent
+            # Process the question with the agent
+            prompt = f"""
+            You are a helpful AI assistant. Please answer the following question:
+            {question}
+            
+            If you need to search for information, use the search tool.
+            Provide a clear, concise, and accurate answer.
+            """
+            response = self.agent.run(prompt)
+            print(f"Agent processed question and generated response.")
+            return response
         except Exception as e:
-            answer = f"Error during search: {e}"
-
-        print(f"Agent returning answer: {answer[:100]}...")  # Print just a preview
-        return answer
-
+            print(f"Error in agent processing: {e}")
+            return f"I encountered an error while processing your question: {str(e)}"
 
-def run_and_submit_all(profile: gr.OAuthProfile | None):
+def run_and_submit_all( profile: gr.OAuthProfile | None):
     """
     Fetches all questions, runs the BasicAgent on them, submits all answers,
     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") # Get the SPACE_ID for sending link to the code
 
     if profile:
-        username = f"{profile.username}"
+        username= f"{profile.username}"
         print(f"User logged in: {username}")
     else:
         print("User not logged in.")
@@ -73,16 +79,16 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         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("Fetched questions list is empty.")
+             return "Fetched questions list is empty or invalid format.", None
         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
     except requests.exceptions.JSONDecodeError as e:
-        print(f"Error decoding JSON response from questions endpoint: {e}")
-        print(f"Response text: {response.text[:500]}")
-        return f"Error decoding server response for questions: {e}", None
+         print(f"Error decoding JSON response from questions endpoint: {e}")
+         print(f"Response text: {response.text[:500]}")
+         return f"Error decoding server response for questions: {e}", None
     except Exception as e:
         print(f"An unexpected error occurred fetching questions: {e}")
         return f"An unexpected error occurred fetching questions: {e}", None
@@ -102,14 +108,14 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
             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}"})
+             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
+    # 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)
@@ -160,7 +166,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
 
 # --- Build Gradio Interface using Blocks ---
 with gr.Blocks() as demo:
-    gr.Markdown("# Basic Agent Evaluation Runner (Test #4)")
+    gr.Markdown("# Basic Agent Evaluation Runner (Test #1)")
     gr.Markdown(
         """
         **Instructions:**
@@ -190,10 +196,10 @@ with gr.Blocks() as demo:
     )
 
 if __name__ == "__main__":
-    print("\n" + "-" * 30 + " App Starting " + "-" * 30)
+    print("\n" + "-"*30 + " App Starting " + "-"*30)
     # Check for SPACE_HOST and SPACE_ID at startup for information
     space_host_startup = os.getenv("SPACE_HOST")
-    space_id_startup = os.getenv("SPACE_ID")  # Get SPACE_ID at startup
+    space_id_startup = os.getenv("SPACE_ID") # Get SPACE_ID at startup
 
     if space_host_startup:
         print(f"✅ SPACE_HOST found: {space_host_startup}")
@@ -201,14 +207,14 @@ if __name__ == "__main__":
     else:
         print("ℹ️  SPACE_HOST environment variable not found (running locally?).")
 
-    if space_id_startup:  # Print repo URLs if SPACE_ID is found
+    if space_id_startup: # Print repo URLs if SPACE_ID is found
         print(f"✅ SPACE_ID found: {space_id_startup}")
         print(f"   Repo URL: https://huggingface.co/spaces/{space_id_startup}")
         print(f"   Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main")
     else:
         print("ℹ️  SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined.")
 
-    print("-" * (60 + len(" App Starting ")) + "\n")
+    print("-"*(60 + len(" App Starting ")) + "\n")
 
     print("Launching Gradio Interface for Basic Agent Evaluation...")
-    demo.launch(debug=True, share=False)
+    demo.launch(debug=True, share=False)