code: def text_to_semantic(
      text: str,
      history_prompt: Optional[Union[Dict, str]] = None,
      temp: float = 0.7,
      silent: bool = False,
  ):
      """Generate semantic array from text.
  
      Args:
          text: text to be turned into audio
          history_prompt: history choice for audio cloning
          temp: generation temperature (1.0 more diverse, 0.0 more conservative)
          silent: disable progress bar
  
      Returns:
          numpy semantic array to be fed into `semantic_to_waveform`
      """
      x_semantic = generate_text_semantic(
          text,
          history_prompt=history_prompt,
          temp=temp,
          silent=silent,
          use_kv_caching=True,
      )
      return x_semantic
  
imports: from typing import Dict, Optional, Union
  import numpy
  from .generation import codec_decode, generate_coarse, generate_fine, generate_text_semantic
label_desc: Use image node_id 1 for calling a global function with example usage: text_to_semantic(text, history_prompt, temp, silent) and returns: x_semantic