Update app.py

app.py

@@ -2,7 +2,8 @@ import os
 import gradio as gr
 import requests
 import pandas as pd
-from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, VisitWebpageTool
+# Fixed Imports for 2026 smolagents version
+from smolagents import CodeAgent, DuckDuckGoSearchTool, LiteLLMModel, VisitWebpageTool
 
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
@@ -10,13 +11,12 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 # --- Agent Definition ---
 class AgentArchitect:
     def __init__(self):
-        # Using a high-parameter model for better reasoning on the GAIA benchmark
-        self.model = HfApiModel(model_id="Qwen/Qwen2.5-72B-Instruct")
+        # We use LiteLLMModel here - it's the updated, more stable way to call HF models
+        # and other providers in the current smolagents version.
+        self.model = LiteLLMModel(model_id="huggingface/Qwen/Qwen2.5-72B-Instruct")
         
-        # Tools allow the agent to reach outside its training data
         self.tools = [DuckDuckGoSearchTool(), VisitWebpageTool()]
         
-        # CodeAgent is superior here as it can write Python to solve the math/sorting questions
         self.agent = CodeAgent(
             tools=self.tools,
             model=self.model,
@@ -25,7 +25,6 @@ class AgentArchitect:
 
     def __call__(self, question: str) -> str:
         try:
-            # We enforce conciseness to match the 'exact match' scoring of the leaderboard
             prompt = f"{question}\n\nFinal Answer Requirement: Provide ONLY the specific answer requested (number, name, or list) with no extra text."
             result = self.agent.run(prompt)
             return str(result)
@@ -44,10 +43,8 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     submit_url = f"{api_url}/submit"
 
     try:
-        # Initialize the new agent logic
         agent_instance = AgentArchitect()
         
-        # Fetch Questions
         response = requests.get(questions_url, timeout=15)
         response.raise_for_status()
         questions_data = response.json()
@@ -59,13 +56,11 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
             task_id = item.get("task_id")
             question_text = item.get("question")
             
-            # This is where the agent actually 'thinks'
             submitted_answer = agent_instance(question_text)
             
             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})
 
-        # Submit to Leaderboard
         agent_code_link = f"https://huggingface.co/spaces/{space_id}/tree/main"
         submission_data = {"username": username.strip(), "agent_code": agent_code_link, "answers": answers_payload}