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# agents/debugger.py
from agents.base_agent import BaseAgent, ACPMessage
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":
debug_question = self.generate_debug_question(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."
)
else:
return self.create_message(
receiver=message.sender,
performative="request",
content="Can you show me some Python code?"
)
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