content: #  Copyright (c) ZenML GmbH 2023. All Rights Reserved.
  #
  #  Licensed under the Apache License, Version 2.0 (the "License");
  #  you may not use this file except in compliance with the License.
  #  You may obtain a copy of the License at:
  #
  #       https://www.apache.org/licenses/LICENSE-2.0
  #
  #  Unless required by applicable law or agreed to in writing, software
  #  distributed under the License is distributed on an "AS IS" BASIS,
  #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
  #  or implied. See the License for the specific language governing
  #  permissions and limitations under the License.
  """Implementation of ZenML's Langchain Document materializer."""
  
  import os
  from typing import TYPE_CHECKING, Any, ClassVar, Dict, Tuple, Type
  
  from langchain.docstore.document import Document
  
  from zenml.enums import ArtifactType
  from zenml.materializers.base_materializer import BaseMaterializer
  from zenml.utils import yaml_utils
  
  if TYPE_CHECKING:
      from zenml.metadata.metadata_types import MetadataType
  
  DEFAULT_FILENAME = "data.json"
  
  
  class LangchainDocumentMaterializer(BaseMaterializer):
      """Handle Langchain Document objects."""
  
      ASSOCIATED_ARTIFACT_TYPE: ClassVar[ArtifactType] = ArtifactType.DATA
      ASSOCIATED_TYPES: ClassVar[Tuple[Type[Any], ...]] = (Document,)
  
      def load(self, data_type: Type["Document"]) -> Any:
          """Reads BaseModel from JSON.
  
          Args:
              data_type: The type of the data to read.
  
          Returns:
              The data read.
          """
          data_path = os.path.join(self.uri, DEFAULT_FILENAME)
          contents = yaml_utils.read_json(data_path)
          return data_type.parse_raw(contents)
  
      def save(self, data: "Document") -> None:
          """Serialize a BaseModel to JSON.
  
          Args:
              data: The data to store.
          """
          data_path = os.path.join(self.uri, DEFAULT_FILENAME)
          yaml_utils.write_json(data_path, data.json())
  
      def extract_metadata(self, data: Document) -> Dict[str, "MetadataType"]:
          """Extract metadata from the given BaseModel object.
  
          Args:
              data: The BaseModel object to extract metadata from.
  
          Returns:
              The extracted metadata as a dictionary.
          """
          return {"schema": data.schema()}
  