Update app.py

app.py

@@ -3,19 +3,22 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
+from smolagents import HfApiModel
 
 
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# --- Enhanced Agent Definition ---
 # --- Enhanced Agent Definition ---
 class GAIAAgent:
     def __init__(self):
-        self.api_token = os.getenv("HF_TOKEN")
-        self.model_id = "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B"
-        self.api_url = f"https://api-inference.huggingface.co/models/{self.model_id}"
-        print("GAIAAgent with Hugging Face Inference API initialized.")
+        print("GAIAAgent with HfApiModel initialized.")
+        self.model = HfApiModel(
+            model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
+            max_tokens=2096,
+            temperature=0.5,
+            custom_role_conversions=None,
+        )
 
     def format_prompt(self, question: str, file_content: str = None) -> str:
         prompt = (
@@ -31,24 +34,14 @@ class GAIAAgent:
         filepath = os.path.join("./", filename)
         if filename.endswith(".txt") and os.path.exists(filepath):
             with open(filepath, "r") as file:
-                return file.read()[:1000]  # limit to 1000 chars
+                return file.read()[:1000]
         return ""
 
     def __call__(self, question: str, file_name: str = None) -> str:
         file_content = self.read_file(file_name) if file_name else None
         prompt = self.format_prompt(question, file_content)
-        headers = {
-            "Authorization": f"Bearer {self.api_token}",
-            "Content-Type": "application/json",
-        }
-        response = requests.post(self.api_url, headers=headers, json={"inputs": prompt})
-        result = response.json()
-
-        if isinstance(result, list) and "generated_text" in result[0]:
-            return result[0]["generated_text"].split("Answer:")[-1].strip()
-        else:
-            print(f"Unexpected response: {result}")
-            return "AGENT ERROR: Model inference failed."
+        result = self.model(prompt)
+        return result.strip().split("Answer:")[-1].strip()
 
 
 def run_and_submit_all(profile: gr.OAuthProfile | None):