Update app.py

app.py

@@ -4,22 +4,77 @@ import requests
 import inspect
 import pandas as pd
 
-# (Keep Constants as is)
+# --- Import Smart Agent Libraries ---
+from smolagents import CodeAgent, HfModel, tool
+from duckduckgo_search import DDGS
+
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# --- Basic Agent Definition ---
-# ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
+# --- Custom Secure Search Tool ---
+@tool
+def web_search(query: str) -> str:
+    """Executes a live DuckDuckGo web search to find current information on a topic.
+
+    Args:
+        query: The search query string to look up.
+
+    Returns:
+        A text string summarizing the top web snippets found.
+    """
+    try:
+        with DDGS() as ddgs:
+            results = [r for r in ddgs.text(query, max_results=5)]
+            if not results:
+                return f"No web search results found for query: '{query}'"
+            
+            summary = []
+            for i, result in enumerate(results):
+                summary.append(f"[{i+1}] Source: {result.get('href')}\nSnippet: {result.get('body')}\n")
+            return "\n".join(summary)
+    except Exception as e:
+        return f"Search temporary error occurred: {str(e)}"
+
+# --- Upgraded Agent Definition ---
 class BasicAgent:
     def __init__(self):
-        print("BasicAgent initialized.")
+        # Using HfModel standard serverless configuration
+        self.model = HfModel(
+            model_id="Qwen/Qwen2.5-Coder-32B-Instruct",
+            timeout=60
+        )
+        
+        # Pass the reliable custom web_search tool directly to the loop
+        tools_list = [web_search]
+            
+        # Initialize the dynamic code-executing agent engine
+        self.agent = CodeAgent(
+            model=self.model,
+            tools=tools_list,
+            max_steps=10,
+            verbosity_level=1
+        )
+        print("Smart Agent customized framework 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
+        
+        # Strict prompting forcing exact match short answers for the GAIA benchmark
+        system_instruction = (
+            f"{question}\n\n"
+            "CRITICAL: Utilize the web_search tool if any factual lookup or verification is required. "
+            "Provide ONLY the definitive, final answer matching the expected value or data type. "
+            "Do not include conversational preamble, markdown formatting labels, or phrases like 'FINAL ANSWER:'."
+        )
+        try:
+            output = self.agent.run(system_instruction)
+            return str(output).strip()
+        except Exception as e:
+            print(f"Processing error: {e}")
+            return f"Error processing task: {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.
@@ -28,7 +83,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     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.")
@@ -38,13 +93,14 @@ 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 (modified to use your smart agent implementation)
     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)
+        
+    # 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(agent_code)
 
@@ -146,24 +202,18 @@ with gr.Blocks() as demo:
     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.
-
+        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.
         ---
         **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.
         """
     )
-
     gr.LoginButton()
-
     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(
@@ -173,17 +223,15 @@ 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}")
         print(f"   Runtime URL should be: https://{space_host_startup}.hf.space")
     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")
@@ -191,6 +239,5 @@ if __name__ == "__main__":
         print("ℹ️  SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined.")
 
     print("-"*(60 + len(" App Starting ")) + "\n")
-
     print("Launching Gradio Interface for Basic Agent Evaluation...")
     demo.launch(debug=True, share=False)