code: def main(
      ckpt_dir: str,
      tokenizer_path: str,
      temperature: float = 0.2,
      top_p: float = 0.9,
      max_seq_len: int = 256,
      max_batch_size: int = 4,
      max_gen_len: Optional[int] = None,
  ):
      generator = Llama.build(
          ckpt_dir=ckpt_dir,
          tokenizer_path=tokenizer_path,
          max_seq_len=max_seq_len,
          max_batch_size=max_batch_size,
      )
  
      prompts = [
          # For these prompts, the expected answer is the natural continuation of the prompt
          """\
  import socket
  
  def ping_exponential_backoff(host: str):""",
          """\
  import argparse
  
  def main(string: str):
      print(string)
      print(string[::-1])
  
  if __name__ == "__main__":""",
      ]
      results = generator.text_completion(
          prompts,
          max_gen_len=max_gen_len,
          temperature=temperature,
          top_p=top_p,
      )
      for prompt, result in zip(prompts, results):
          print(prompt)
          print(f"> {result['generation']}")
          print("\n==================================\n")
  
label_desc: Use image node_id 1 for calling a global function with example usage: main(ckpt_dir, tokenizer_path, temperature, top_p, max_seq_len, max_batch_size, max_gen_len) without return types