Update agents/debugger.py

agents/debugger.py

@@ -7,35 +7,29 @@ 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")
+        self.tokenizer = AutoTokenizer.from_pretrained("Salesforce/codegen-350M-multi")
+        self.model = AutoModelForCausalLM.from_pretrained("Salesforce/codegen-350M-multi")
 
-    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:"
+    def generate_debug_comment(self, code: str) -> str:
+        prompt = f"# Review this Python code and ask a smart debugging or testing question:\n{code}\n# Question:"
         inputs = self.tokenizer(prompt, return_tensors="pt", truncation=True)
         outputs = self.model.generate(
             inputs["input_ids"],
-            max_length=100,
+            max_length=128,
             do_sample=True,
-            temperature=0.8,
+            temperature=0.7,
             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":
-            debug_question = self.generate_debug_question(message.content)
+        if message.performative in ["inform", "request"]:
+            comment = self.generate_debug_comment(message.content)
             return self.create_message(
                 receiver=message.sender,
                 performative="request",
-                content=debug_question or "Can you add error handling?"
-            )
-        elif message.performative == "acknowledge":
-            return self.create_message(
-                receiver=message.sender,
-                performative="inform",
-                content="Got it. Let me know when you have more code."
+                content=comment or "Can you improve error handling?"
             )
         else:
             return self.create_message(