Update agents/debugger.py

agents/debugger.py

@@ -1,35 +1,45 @@
 # agents/debugger.py
 
 from agents.base_agent import BaseAgent, ACPMessage
-import random
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
 
 class DebuggerAgent(BaseAgent):
     def __init__(self):
         super().__init__(name="BugBot", role="Debugger")
+        self.tokenizer = AutoTokenizer.from_pretrained("distilgpt2")
+        self.model = AutoModelForCausalLM.from_pretrained("distilgpt2")
+
+    def generate_debug_question(self, code_snippet: str) -> str:
+        prompt = f"Review this Python function and ask a relevant question or suggest improvement:\n\n{code_snippet}\n\nQuestion:"
+        inputs = self.tokenizer(prompt, return_tensors="pt", truncation=True)
+        outputs = self.model.generate(
+            inputs["input_ids"],
+            max_length=100,
+            do_sample=True,
+            temperature=0.8,
+            pad_token_id=self.tokenizer.eos_token_id
+        )
+        reply = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
+        return reply[len(prompt):].strip()
 
     def receive_message(self, message: ACPMessage) -> ACPMessage:
         if message.performative == "inform":
-            feedback_options = [
-                "Looks good! Does it handle empty lists?",
-                "Nice. Can you add error handling?",
-                "Cool. What about performance with large inputs?",
-                "Thanks. Let me run a test on it.",
-                "Interesting approach. Can we optimize it?"
-            ]
+            debug_question = self.generate_debug_question(message.content)
             return self.create_message(
                 receiver=message.sender,
                 performative="request",
-                content=random.choice(feedback_options)
+                content=debug_question or "Can you add error handling?"
             )
         elif message.performative == "acknowledge":
             return self.create_message(
                 receiver=message.sender,
                 performative="inform",
-                content="Alright. Waiting for next response."
+                content="Got it. Let me know when you have more code."
             )
         else:
             return self.create_message(
                 receiver=message.sender,
                 performative="request",
-                content="Can you show me a simple function in Python?"
+                content="Can you show me some Python code?"
             )