code: def __call__(self, output_text, **kwargs):
      agent_type = kwargs.get("agent_type", AgentType.USER)
      user_prompt = kwargs.get("user_prompt", "")
  
      model_prompt = output_text.strip()
      if agent_type == AgentType.AGENT:
          if user_prompt == "":
              print(
                  "empty user prompt for agent check, returning unsafe"
              )
              return (
                  "Llama Guard",
                  False,
                  "Missing user_prompt from Agent response check",
              )
          else:
              model_prompt = model_prompt.replace(user_prompt, "")
              user_prompt = f"User: {user_prompt}"
              agent_prompt = f"Agent: {model_prompt}"
              chat = [
                  {"role": "user", "content": user_prompt},
                  {"role": "assistant", "content": agent_prompt},
              ]
      else:
          chat = [
              {"role": "user", "content": model_prompt},
          ]
  
      input_ids = self.tokenizer.apply_chat_template(
          chat, return_tensors="pt"
      ).to("cuda")
      prompt_len = input_ids.shape[-1]
      output = self.model.generate(
          input_ids=input_ids, max_new_tokens=100, pad_token_id=0
      )
      result = self.tokenizer.decode(
          output[0][prompt_len:], skip_special_tokens=True
      )
  
      splitted_result = result.split("\n")[0]
      is_safe = splitted_result == "safe"
  
      report = result
  
      return "Llama Guard", is_safe, report
  
imports: import os
  import torch
  import warnings
  from typing import List
  from string import Template
  from enum import Enum
label_desc: Use image node_id 2 for calling the LlamaGuardSafetyChecker obj's underlying member method code with example usage: obj.__call__(output_text) and returns: str,  is_safe,  report, str,  False,  str