code: def test_text_environment_tool_truncation(self):
      env = TextEnvironment(
          self.gpt2_model,
          self.gpt2_tokenizer,
          tools={"dummy": lambda x: "a" * 1000},
          reward_fn=lambda x: torch.tensor(1),
          prompt="I am a prompt!\n",
      )
  
      env.max_tool_response = 100
      history = env.step(
          TextHistory(
              "<request><dummy>Hello there!<call>",
              torch.tensor([1, 2, 3]),
          )
      )
      self.assertEqual(
          len(history.last_text_segment) - len(env.response_token), 100
      )
  
      env.max_tool_response = 500
      history = env.step(
          TextHistory(
              "<request><dummy>Hello there!<call>",
              torch.tensor([1, 2, 3]),
          )
      )
      self.assertEqual(
          len(history.last_text_segment) - len(env.response_token), 500
      )
  
      env.max_tool_response = 1001
      history = env.step(
          TextHistory(
              "<request><dummy>Hello there!<call>",
              torch.tensor([1, 2, 3]),
          )
      )
      self.assertEqual(
          len(history.last_text_segment) - len(env.response_token), 1000
      )
  
      env.max_tool_response = 2000
      history = env.step(
          TextHistory(
              "<request><dummy>Hello there!<call>",
              torch.tensor([1, 2, 3]),
          )
      )
      self.assertEqual(
          len(history.last_text_segment) - len(env.response_token), 1000
      )
  
imports: import unittest
  from unittest.mock import patch
  import torch
  from transformers import AutoTokenizer
  from trl import AutoModelForCausalLMWithValueHead, TextEnvironment, TextHistory
label_desc: Use image node_id 5 for calling the TextEnvironmentTester obj's underlying member method code with example usage: obj.test_text_environment_tool_truncation() without return types