from typing import Optional
from huggingface_hub import InferenceClient


def hf_summarize(text: str, *, model: str, api_token: Optional[str] = None, max_new_tokens: int = 200) -> str:
    """
    Call the Hugging Face Inference API for summarization.

    Args:
        text: Input text to summarize.
        model: Hugging Face model repo id (e.g., 'facebook/bart-large-cnn').
        api_token: Optional HF API token for higher rate limits / private models.
        max_new_tokens: Maximum tokens to generate in the summary.

    Returns:
        The summarized text.
    """
    client = InferenceClient(model=model, token=api_token)
    # The library returns either a string or a dict depending on the task helper used.
    # Using the summarization task helper yields a string.
    result = client.summarization(text, max_new_tokens=max_new_tokens)
    if isinstance(result, str):
        return result.strip()
    # Fallback if a different payload format is returned
    if isinstance(result, dict) and 'summary_text' in result:
        return str(result['summary_text']).strip()
    return str(result).strip()