first try

app.py

@@ -1,24 +1,33 @@
 import os
 import gradio as gr
 import requests
+from smolagents import CodeAgent, InferenceClientModel, tool,ToolCallingAgent , PythonInterpreterTool,DuckDuckGoSearchTool,VisitWebpageTool
 import inspect
 import pandas as pd
 
 # (Keep Constants as is)
 # --- Constants ---
+key = os.environ['access_token']
+
 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):
+        model = InferenceClientModel(
+    model_id="Qwen/Qwen3-32B",
+    token=key)
+        interpreter = PythonInterpreterTool()  
+        self.agentic = ToolCallingAgent(model=model,tools = [interpreter,DuckDuckGoSearchTool(),VisitWebpageTool()])
         print("BasicAgent initialized.")
     def __call__(self, question: str) -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
-        fixed_answer = "This is a default answer."
+        answer  = self.agentic.run(question)
+        fixed_answer = answer
         print(f"Agent returning fixed answer: {fixed_answer}")
         return fixed_answer
-
+    
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """
     Fetches all questions, runs the BasicAgent on them, submits all answers,
@@ -45,8 +54,8 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         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)
+    # agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
+    # print(agent_code)
 
     # 2. Fetch Questions
     print(f"Fetching questions from: {questions_url}")
@@ -72,6 +81,32 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     # 3. Run your Agent
     results_log = []
     answers_payload = []
+    sytem_prompt = """You are an intelligent machine capable of reasoning and solving complex problems by breaking them down into smaller, manageable subtasks.
+
+Your thought process follows this structured approach:
+
+Understand the main concept or problem.
+
+Check if additional context or clarification is needed.
+
+Decompose the problem into relevant subtasks, if necessary.
+
+Use the available data to explore at least three potential solution strategies.
+
+Evaluate and select the most effective solution.
+
+Clearly explain the reasoning and methodology behind the chosen approach.
+
+Apply the selected solution using the data to resolve the original problem.
+
+You can use tools [interpreter]  for calculation by generating a python code for calculus
+Here re others tool at your disposal [DuckDuckGoSearchTool,VisitWebpageTool]
+
+here is the task 
+{}
+    """
+
+
     print(f"Running agent on {len(questions_data)} questions...")
     for item in questions_data:
         task_id = item.get("task_id")
@@ -80,7 +115,8 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
             print(f"Skipping item with missing task_id or question: {item}")
             continue
         try:
-            submitted_answer = agent(question_text)
+            prompt =  sytem_prompt.format(question_text)
+            submitted_answer = agent(prompt)
             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:

requirements.txt

@@ -1,2 +1,6 @@
 gradio
-requests
+requests
+smolagents
+mistralai
+duckduckgo-search
+markdownify

tools.py

@@ -0,0 +1,3 @@
+from smolagents import CodeAgent, InferenceClientModel, tool
+
+