def from_llm_metadata(
        cls,
        llm_metadata: LLMMetadata,
        chunk_overlap_ratio: float = DEFAULT_CHUNK_OVERLAP_RATIO,
        chunk_size_limit: Optional[int] = None,
        tokenizer: Optional[Callable[[str], List]] = None,
        separator: str = " ",
    ) -> "PromptHelper":
        """
        Create from llm predictor.

        This will autofill values like context_window and num_output.

        """
        context_window = llm_metadata.context_window

        if llm_metadata.num_output == -1:
            num_output = DEFAULT_NUM_OUTPUTS
        else:
            num_output = llm_metadata.num_output

        return cls(
            context_window=context_window,
            num_output=num_output,
            chunk_overlap_ratio=chunk_overlap_ratio,
            chunk_size_limit=chunk_size_limit,
            tokenizer=tokenizer,
            separator=separator,
        )

        Create from llm predictor.

        This will autofill values like context_window and num_output.

        
llama-index-core/llama_index/core/indices/prompt_helper.py