Update app.py

app.py

@@ -10,52 +10,30 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
+from transformers import pipeline
+
 class BasicAgent:
     def __init__(self):
-        print("FLAN-T5 Agent initialized.")
-        self.api_token = os.getenv("HF_API_TOKEN")
-        self.api_url = "https://api-inference.huggingface.co/models/google/flan-t5-base"
-        self.headers = {
-            "Authorization": f"Bearer {self.api_token}",
-            "Content-Type": "application/json"
-        }
+        print("FLAN-T5-SMALL Local Agent initialized.")
+
+        self.pipeline = pipeline(
+            "text2text-generation",
+            model="google/flan-t5-small",
+            tokenizer="google/flan-t5-small",
+            device=-1 
+        )
 
     def __call__(self, question: str) -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
 
-        if not self.api_token:
-            return "Error: Missing Hugging Face API token."
-
-        prompt = f"Answer this question:\n{question.strip()}"
-
-        payload = {
-            "inputs": prompt,
-            "parameters": {
-                "max_new_tokens": 256,
-                "temperature": 0.5
-            }
-        }
-
         try:
-            response = requests.post(self.api_url, headers=self.headers, json=payload, timeout=30)
-            response.raise_for_status()
-            output = response.json()
-
-            # Extract output
-            if isinstance(output, list) and "generated_text" in output[0]:
-                return output[0]["generated_text"]
-            elif isinstance(output, dict) and "generated_text" in output:
-                return output["generated_text"]
-            elif isinstance(output, list) and "output" in output[0]:
-                return output[0]["output"]
-            else:
-                print(f"Unexpected response: {output}")
-                return "Model returned an unexpected format."
-
+            prompt = f"Answer the following question:\n{question.strip()}"
+            result = self.pipeline(prompt, max_new_tokens=128, temperature=0.5)
+            answer = result[0]["generated_text"]
+            return answer.strip()
         except Exception as e:
-            print(f"❌ Exception during inference: {e}")
-            return f"❌ API Error: {str(e)}"
-        
+            print(f"❌ Error during model inference: {e}")
+            return f"❌ Model Error: {str(e)}"
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """