| |
|
|
| 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("Salesforce/codegen-350M-multi") |
| self.model = AutoModelForCausalLM.from_pretrained("Salesforce/codegen-350M-multi") |
|
|
| 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=128, |
| do_sample=True, |
| 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 in ["inform", "request"]: |
| comment = self.generate_debug_comment(message.content) |
| return self.create_message( |
| receiver=message.sender, |
| performative="request", |
| content=comment or "Can you improve error handling?" |
| ) |
| else: |
| return self.create_message( |
| receiver=message.sender, |
| performative="request", |
| content="Can you show me some Python code?" |
| ) |
|
|
