Update app.py

app.py

@@ -1,34 +1,165 @@
 import os
 import gradio as gr
 import requests
-import inspect
 import pandas as pd
+from smolagents import CodeAgent, DuckDuckGoSearchTool, InferenceClientModel, tool
 
-# (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# --- Basic Agent Definition ---
-# ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
+# ============================================
+# CUSTOM TOOLS FOR THE AGENT
+# ============================================
+
+@tool
+def calculator(expression: str) -> str:
+    """
+    Performs mathematical calculations.
+    
+    Args:
+        expression: A math expression like "2 + 2" or "10 * 5 / 2"
+    
+    Returns:
+        The result of the calculation
+    """
+    try:
+        allowed_chars = set('0123456789+-*/(). ')
+        if all(c in allowed_chars for c in expression):
+            result = eval(expression)
+            return f"{result}"
+        else:
+            return "Invalid expression. Use only numbers and basic operators."
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+
+@tool
+def get_current_time() -> str:
+    """
+    Gets the current date and time in UTC.
+    
+    Returns:
+        The current date and time
+    """
+    from datetime import datetime
+    now = datetime.utcnow()
+    return f"Current date and time (UTC): {now.strftime('%Y-%m-%d %H:%M:%S')}"
+
+
+@tool  
+def reverse_text(text: str) -> str:
+    """
+    Reverses the given text string.
+    
+    Args:
+        text: The text to reverse
+    
+    Returns:
+        The reversed text
+    """
+    return text[::-1]
+
+
+@tool
+def count_words(text: str) -> str:
+    """
+    Counts the number of words in a text.
+    
+    Args:
+        text: The text to count words in
+    
+    Returns:
+        The word count
+    """
+    words = text.split()
+    return f"{len(words)}"
+
+
+@tool
+def string_length(text: str) -> str:
+    """
+    Returns the length of a string (number of characters).
+    
+    Args:
+        text: The text to measure
+    
+    Returns:
+        The number of characters
+    """
+    return f"{len(text)}"
+
+
+# ============================================
+# BASIC AGENT CLASS - USING SMOLAGENTS
+# ============================================
+
 class BasicAgent:
     def __init__(self):
-        print("BasicAgent initialized.")
+        print("Initializing BasicAgent with smolagents...")
+        
+        # Initialize the model
+        self.model = InferenceClientModel(
+            model_id="Qwen/Qwen2.5-7B-Instruct",
+            token=os.environ.get("HF_TOKEN"),
+        )
+        
+        # Create the agent with tools
+        self.agent = CodeAgent(
+            model=self.model,
+            tools=[
+                DuckDuckGoSearchTool(),  # Web search
+                calculator,               # Math calculations
+                get_current_time,         # Current time
+                reverse_text,             # Reverse strings
+                count_words,              # Count words
+                string_length,            # String length
+            ],
+            max_steps=6,
+            verbosity_level=1,
+        )
+        
+        print("BasicAgent initialized successfully!")
+    
     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
+        print(f"Agent received question: {question[:100]}...")
+        
+        try:
+            # Create a prompt that helps the agent understand its task
+            enhanced_question = f"""Please answer the following question accurately and concisely. 
+If you need to search for information, use the web search tool.
+If you need to do math, use the calculator tool.
+Give only the final answer without explanation unless asked.
 
-def run_and_submit_all( profile: gr.OAuthProfile | None):
+Question: {question}"""
+            
+            # Run the agent
+            answer = self.agent.run(enhanced_question)
+            
+            # Convert to string and clean up
+            answer = str(answer).strip()
+            
+            print(f"Agent answer: {answer[:100]}...")
+            return answer
+            
+        except Exception as e:
+            print(f"Agent error: {e}")
+            # Try a simpler approach if the agent fails
+            return f"I could not determine the answer. Error: {str(e)}"
+
+
+# ============================================
+# RUN AND SUBMIT FUNCTION
+# ============================================
+
+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")
 
     if profile:
-        username= f"{profile.username}"
+        username = f"{profile.username}"
         print(f"User logged in: {username}")
     else:
         print("User not logged in.")
@@ -38,13 +169,13 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     questions_url = f"{api_url}/questions"
     submit_url = f"{api_url}/submit"
 
-    # 1. Instantiate Agent ( modify this part to create your agent)
+    # 1. Instantiate 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)
 
@@ -55,16 +186,16 @@ 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
@@ -73,6 +204,7 @@ 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")
         question_text = item.get("question")
@@ -84,14 +216,14 @@ 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)
@@ -140,30 +272,38 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         return status_message, results_df
 
 
-# --- Build Gradio Interface using Blocks ---
+# ============================================
+# GRADIO INTERFACE
+# ============================================
+
 with gr.Blocks() as demo:
-    gr.Markdown("# Basic Agent Evaluation Runner")
+    gr.Markdown("# 🎯 GAIA Agent Evaluation Runner")
     gr.Markdown(
         """
-        **Instructions:**
-
-        1.  Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
-        2.  Log in to your Hugging Face account using the button below. This uses your HF username for submission.
-        3.  Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
-
+        **Unit 4 Final Project - HuggingFace AI Agents Course**
+        
+        This agent uses **smolagents** with the following tools:
+        - 🔍 **Web Search** - Search the internet for information
+        - 🧮 **Calculator** - Perform mathematical calculations
+        - 🕐 **Current Time** - Get the current date and time
+        - 🔄 **Reverse Text** - Reverse strings
+        - 📝 **Word Count** - Count words in text
+        - 📏 **String Length** - Measure string length
+        
         ---
-        **Disclaimers:**
-        Once clicking on the "submit button, it can take quite some time ( this is the time for the agent to go through all the questions).
-        This space provides a basic setup and is intentionally sub-optimal to encourage you to develop your own, more robust solution. For instance for the delay process of the submit button, a solution could be to cache the answers and submit in a seperate action or even to answer the questions in async.
+        **Instructions:**
+        1. Log in to your Hugging Face account using the button below
+        2. Click 'Run Evaluation & Submit All Answers'
+        3. Wait for the agent to process all questions (this may take a few minutes)
+        4. View your score on the leaderboard!
         """
     )
 
     gr.LoginButton()
 
-    run_button = gr.Button("Run Evaluation & Submit All Answers")
+    run_button = gr.Button("🚀 Run Evaluation & Submit All Answers")
 
     status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
-    # Removed max_rows=10 from DataFrame constructor
     results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
 
     run_button.click(
@@ -173,9 +313,8 @@ with gr.Blocks() as demo:
 
 if __name__ == "__main__":
     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")
 
     if space_host_startup:
         print(f"✅ SPACE_HOST found: {space_host_startup}")
@@ -183,7 +322,7 @@ 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(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")
@@ -192,5 +331,5 @@ if __name__ == "__main__":
 
     print("-"*(60 + len(" App Starting ")) + "\n")
 
-    print("Launching Gradio Interface for Basic Agent Evaluation...")
+    print("Launching Gradio Interface for GAIA Agent Evaluation...")
     demo.launch(debug=True, share=False)