Function process_references

onecite/core.py:186–225

Process references and return formatted citations with a report. This is the main public API entry point. It creates a :class:`PipelineController` and runs the full 4-stage pipeline. Args: input_content: The raw text or BibTeX content to process. input_type: Format of

(
    input_content: str,
    input_type: str,
    template_name: str,
    output_format: str,
    interactive_callback: Callable[[List[Dict]], int],
    use_google_scholar: bool = False,
)

def process_references(
    input_content: str,
    input_type: str,
    template_name: str,
    output_format: str,
    interactive_callback: Callable[[List[Dict]], int],
    use_google_scholar: bool = False,
) -> Dict[str, Any]:
    """Process references and return formatted citations with a report.

    This is the main public API entry point.  It creates a
    :class:`PipelineController` and runs the full 4-stage pipeline.

    Args:
        input_content: The raw text or BibTeX content to process.
        input_type: Format of *input_content* — ``"txt"`` or ``"bib"``.
        template_name: Name of the YAML template (e.g.
            ``"journal_article_full"``).
        output_format: Output format. Only ``"bibtex"`` is supported;
            any other value raises ``FormatError``.
        interactive_callback: A callable that receives a list of
            candidate dictionaries and returns the index of the selected
            candidate.

    Returns:
        A dictionary with two keys:

        * ``results`` — a list of formatted citation strings.
        * ``report`` — a dict with ``total``, ``succeeded``, and
          ``failed_entries``.

    Raises:
        ValidationError: If the input content is empty or invalid.
        ParseError: If the input cannot be parsed.
        ResolverError: If no data source can resolve a reference.
    """
    if not input_content or not input_content.strip():
        raise ValidationError("input_content must not be empty.")
    pipeline = PipelineController(use_google_scholar=use_google_scholar)
    return pipeline.process(input_content, input_type, template_name, output_format, interactive_callback)