Source code for langchain_core.documents.transformers

from __future__ import annotations

from abc import ABC, abstractmethod
from typing import TYPE_CHECKING, Any, Sequence

from langchain_core.runnables.config import run_in_executor

if TYPE_CHECKING:
    from langchain_core.documents import Document




class BaseDocumentTransformer(ABC):
    """Abstract base class for document transformation.

    A document transformation takes a sequence of Documents and returns a
    sequence of transformed Documents.

    Example:
        .. code-block:: python

            class EmbeddingsRedundantFilter(BaseDocumentTransformer, BaseModel):
                embeddings: Embeddings
                similarity_fn: Callable = cosine_similarity
                similarity_threshold: float = 0.95

                class Config:
                    arbitrary_types_allowed = True

                def transform_documents(
                    self, documents: Sequence[Document], **kwargs: Any
                ) -> Sequence[Document]:
                    stateful_documents = get_stateful_documents(documents)
                    embedded_documents = _get_embeddings_from_stateful_docs(
                        self.embeddings, stateful_documents
                    )
                    included_idxs = _filter_similar_embeddings(
                        embedded_documents, self.similarity_fn, self.similarity_threshold
                    )
                    return [stateful_documents[i] for i in sorted(included_idxs)]

                async def atransform_documents(
                    self, documents: Sequence[Document], **kwargs: Any
                ) -> Sequence[Document]:
                    raise NotImplementedError

    """  # noqa: E501



    @abstractmethod
    def transform_documents(
        self, documents: Sequence[Document], **kwargs: Any
    ) -> Sequence[Document]:
        """Transform a list of documents.

        Args:
            documents: A sequence of Documents to be transformed.

        Returns:
            A sequence of transformed Documents.
        """




    async def atransform_documents(
        self, documents: Sequence[Document], **kwargs: Any
    ) -> Sequence[Document]:
        """Asynchronously transform a list of documents.

        Args:
            documents: A sequence of Documents to be transformed.

        Returns:
            A sequence of transformed Documents.
        """
        return await run_in_executor(
            None, self.transform_documents, documents, **kwargs
        )