init() — langchain Function Reference

Architecture documentation for the __init__() function in json_distance.py from the langchain codebase.

Function python LangChainCore MessageInterface

Entity Profile

LangChainCore→ MessageInterface→ __init__() — langchain Function Reference

Dependency Diagram

graph TD
  d0762f64_a7cc_0f12_772c_aac695ded0ec["__init__()"]
  481593b0_ea9f_1093_bbdc_d3bd06c33d40["JsonEditDistanceEvaluator"]
  d0762f64_a7cc_0f12_772c_aac695ded0ec -->|defined in| 481593b0_ea9f_1093_bbdc_d3bd06c33d40
  style d0762f64_a7cc_0f12_772c_aac695ded0ec fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/langchain/langchain_classic/evaluation/parsing/json_distance.py lines 34–77

    def __init__(
        self,
        string_distance: Callable[[str, str], float] | None = None,
        canonicalize: Callable[[Any], Any] | None = None,
        **_: Any,
    ) -> None:
        """Initialize the JsonEditDistanceEvaluator.

        Args:
            string_distance: A callable that computes the distance between two strings.
                If not provided, a Damerau-Levenshtein distance from the `rapidfuzz`
                package will be used.
            canonicalize: A callable that converts a parsed JSON object into its
                canonical string form.
                If not provided, the default behavior is to serialize the JSON with
                sorted keys and no extra whitespace.

        Raises:
            ImportError: If the `rapidfuzz` package is not installed and no
                `string_distance` function is provided.
        """
        super().__init__()
        if string_distance is not None:
            self._string_distance = string_distance
        else:
            try:
                from rapidfuzz import distance as rfd
            except ImportError as e:
                msg = (
                    "The default string_distance operator for the "
                    " JsonEditDistanceEvaluator requires installation of "
                    "the rapidfuzz package. "
                    "Please install it with `pip install rapidfuzz`."
                )
                raise ImportError(msg) from e
            self._string_distance = rfd.DamerauLevenshtein.normalized_distance
        if canonicalize is not None:
            self._canonicalize = canonicalize
        else:
            self._canonicalize = lambda x: json.dumps(
                x,
                separators=(",", ":"),
                sort_keys=True,  # eliminate whitespace
            )