Update app.py

app.py

@@ -3,45 +3,62 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
-from smolagents import CodeAgent, HfApiModel
+from smolagents import CodeAgent, HfApiModel, DuckDuckGoSearchTool, VisitWebpageTool
 
 # --- Constants ---
-DEFAULT_API_URL = "https://agents-course-unit4-scoring. hf.space"
+DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# --- Agent Definition ---
-class BasicAgent: 
+# --- Intelligent Agent Definition ---
+class BasicAgent:
     def __init__(self):
         print("BasicAgent initialized.")
-        # Initialize the model and agent here
         try:
+            # Initialize the model
             model = HfApiModel()
-            self.agent = CodeAgent(tools=[], model=model, max_steps=4)
-        except Exception as e: 
+            
+            # Initialize tools for the agent
+            tools = [
+                DuckDuckGoSearchTool(),
+                VisitWebpageTool()
+            ]
+            
+            # Create the CodeAgent with tools
+            self.agent = CodeAgent(
+                tools=tools,
+                model=model,
+                max_steps=10,
+                verbosity_level=2
+            )
+            print("Agent successfully initialized with tools.")
+        except Exception as e:
             print(f"Error initializing agent: {e}")
             self.agent = None
 
     def __call__(self, question: str) -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
         
-        if self.agent is None:
+        if self. agent is None:
             return "Agent failed to initialize properly."
         
         try:
             # Run the agent with the question
-            answer = self.agent. run(question)
-            print(f"Agent returning answer: {str(answer)[:100]}...")
-            return str(answer)
+            result = self. agent.run(question)
+            answer = str(result)
+            print(f"Agent returning answer (first 100 chars): {answer[:100]}...")
+            return answer
         except Exception as e:
-            print(f"Error running agent: {e}")
-            return f"Error processing question: {str(e)}"
+            print(f"Error running agent on question: {e}")
+            # Return a fallback answer
+            return f"I encountered an error: {str(e)}"
 
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     """
     Fetches all questions, runs the BasicAgent on them, submits all answers, and displays the results.
     """
-    space_id = os.getenv("SPACE_ID")
+    # --- Determine HF Space Runtime URL and Repo URL ---
+    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.")
@@ -52,17 +69,18 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     submit_url = f"{api_url}/submit"
 
     # 1. Instantiate Agent
-    try: 
+    try:
         agent = BasicAgent()
-    except Exception as e:
+    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
     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
     print(f"Agent code URL: {agent_code}")
 
     # 2. Fetch Questions
-    print(f"Fetching questions from: {questions_url}")
+    print(f"Fetching questions from:  {questions_url}")
     try:
         response = requests.get(questions_url, timeout=30)
         response.raise_for_status()
@@ -76,8 +94,8 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         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"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
@@ -86,65 +104,86 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     results_log = []
     answers_payload = []
     print(f"Running agent on {len(questions_data)} questions...")
-    
-    for item in questions_data: 
-        task_id = item. get("task_id")
+    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}")
+        if not task_id or question_text is None:
+            print(f"Skipping item with missing task_id or question:  {item}")
             continue
 
         try:
             answer = agent(question_text)
             answers_payload.append({"task_id": task_id, "answer": answer})
-            results_log.append({"task_id": task_id, "question": question_text[: 50], "answer": str(answer)[:100]})
+            results_log.append({
+                "task_id": task_id,
+                "question":  question_text[: 50] + ".. .",
+                "answer": str(answer)[:100] + "..."
+            })
         except Exception as e:
             print(f"Error processing task {task_id}: {e}")
             answers_payload.append({"task_id": task_id, "answer": f"Error: {str(e)}"})
 
     # 4. Submit answers
-    print(f"Submitting {len(answers_payload)} answers...")
+    print(f"Submitting {len(answers_payload)} answers to {submit_url}...")
     try:
-        payload = {
-            "username": username,
-            "agent_code": agent_code,
-            "answers": answers_payload
-        }
-        
-        response = requests.post(submit_url, json=payload, timeout=30)
-        response.raise_for_status()
-        result = response.json()
-        
-        print(f"Submission successful:  {result}")
-        
-        # Create results dataframe
-        df = pd.DataFrame(results_log)
-        
-        return f"✅ Submission successful! Score: {result. get('score', 'N/A')}", df
-        
+        submit_response = requests.post(
+            submit_url,
+            json={"answers": answers_payload, "username": username, "agent_code": agent_code},
+            timeout=60
+        )
+        submit_response.raise_for_status()
+        result_data = submit_response.json()
+        print("Submission response received.")
     except requests.exceptions.RequestException as e:
         print(f"Error submitting answers: {e}")
         return f"Error submitting answers: {e}", pd.DataFrame(results_log)
+    except requests.exceptions.JSONDecodeError as e:
+        print(f"Error decoding submit response JSON: {e}")
+        print(f"Response text: {submit_response.text[:500]}")
+        return f"Error decoding server response after submitting answers: {e}", pd. DataFrame(results_log)
+    except Exception as e:
+        print(f"An unexpected error occurred submitting answers: {e}")
+        return f"An unexpected error occurred submitting answers: {e}", pd. DataFrame(results_log)
+
+    # Format the results for display
+    try: 
+        # If result_data is a dict with results list
+        if isinstance(result_data, dict):
+            score_str = result_data.get('score', "N/A")
+            df = pd.DataFrame(results_log)
+        else:
+            df = pd.DataFrame(result_data)
+            score_str = "N/A"
+        print("Results dataframe created.")
     except Exception as e:
-        print(f"Unexpected error during submission: {e}")
-        return f"Unexpected error during submission:  {e}", pd.DataFrame(results_log)
+        print(f"Error creating results dataframe:  {e}")
+        df = pd.DataFrame(results_log)
+        score_str = "N/A"
+
+    result_message = f"✅ Submission completed!  Score: {score_str}\n\n[View Agent Codebase]({agent_code})"
+    return result_message, df
 
-# --- Gradio Interface ---
 with gr.Blocks() as demo:
-    gr.Markdown("# 🤖 Agent Assignment Submission")
-    gr.Markdown("Click the button below to run your agent on all questions and submit your answers.")
+    gr.Markdown("<h1 align='center'>🤖 Agent Final Assignment</h1>")
+    gr.Markdown("To see your score, log in using the Hugging Face button below and click 'Run & Submit'.")
     
     with gr.Row():
-        submit_btn = gr.Button("🚀 Run & Submit All", variant="primary")
+        profile = gr.OAuthProfile()
     
-    status_output = gr.Textbox(label="Status", lines=3)
-    results_output = gr. Dataframe(label="Results")
+    with gr.Row():
+        run_button = gr.Button("🚀 Run & Submit Agent", variant="primary")
     
-    submit_btn. click(
-        fn=run_and_submit_all,
-        inputs=[],
-        outputs=[status_output, results_output]
+    result_md = gr.Markdown()
+    result_table = gr.Dataframe(label="Results Preview")
+
+    def run_wrapper(profile):
+        result, df = run_and_submit_all(profile)
+        return result, df
+
+    run_button.click(
+        run_wrapper,
+        inputs=[profile],
+        outputs=[result_md, result_table]
     )
 
-if __name__ == "__main__": 
-    demo.launch()
+demo.launch()