Update app.py

app.py

@@ -3,21 +3,67 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
-
+from transformers import pipeline
+import torch
+import re
 # (Keep Constants as is)
 # --- Constants ---
 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):
+  #      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."
+      #  print(f"Agent returning fixed answer: {fixed_answer}")
+       # return fixed_answer
+
 class BasicAgent:
     def __init__(self):
-        print("BasicAgent initialized.")
+        print("Free Local Agent initialized.")
+
+        self.system_prompt = """You are a general AI assistant. I will ask you a question. Report your thoughts, and finish your answer with the following template:
+FINAL ANSWER: [YOUR FINAL ANSWER].
+YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. Do not repeat instructions."""
+
+        self.pipe = pipeline(
+            "text-generation",
+            model="Qwen/Qwen2-0.5B-Instruct",
+            torch_dtype=torch.float32,
+            device_map="cpu"
+        )
+
+    def extract_final_answer(self, text):
+        match = re.search(r"FINAL ANSWER:\s*(.+)", text, re.IGNORECASE)
+        if match:
+            return match.group(1).split("\n")[0].strip()
+        return text.strip()
+
     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
+
+        prompt = f"""<|system|>
+{self.system_prompt}
+<|user|>
+{question}
+<|assistant|>
+"""
+
+        output = self.pipe(
+            prompt,
+            max_new_tokens=128,
+            do_sample=False
+        )[0]["generated_text"]
+
+        # Remove prompt from output
+        answer_part = output[len(prompt):]
+
+        final_answer = self.extract_final_answer(answer_part)
+
+        return final_answer
+
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """