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Langchain

zenml.integrations.langchain special

Initialization of the langchain integration.

LangchainIntegration (Integration)

Definition of langchain integration for ZenML.

Source code in zenml/integrations/langchain/__init__.py 
class LangchainIntegration(Integration):
    """Definition of langchain integration for ZenML."""

    NAME = LANGCHAIN
    REQUIREMENTS = ["langchain==0.0.325", "pyyaml>=6.0.1"]

    @classmethod
    def activate(cls) -> None:
        """Activates the integration."""
        from zenml.integrations.langchain import materializers  # noqa

activate() classmethod

Activates the integration.

Source code in zenml/integrations/langchain/__init__.py 
@classmethod
def activate(cls) -> None:
    """Activates the integration."""
    from zenml.integrations.langchain import materializers  # noqa

materializers special

Initialization of the langchain materializer.

document_materializer

Implementation of ZenML's Langchain Document materializer.

LangchainDocumentMaterializer (PydanticMaterializer)

Handle Langchain Document objects.

Source code in zenml/integrations/langchain/materializers/document_materializer.py 
class LangchainDocumentMaterializer(PydanticMaterializer):
    """Handle Langchain Document objects."""

    ASSOCIATED_ARTIFACT_TYPE: ClassVar[ArtifactType] = ArtifactType.DATA
    ASSOCIATED_TYPES: ClassVar[Tuple[Type[Any], ...]] = (Document,)

openai_embedding_materializer

Implementation of the Langchain OpenAI embedding materializer.

LangchainOpenaiEmbeddingMaterializer (CloudpickleMaterializer)

Handle langchain OpenAI embedding objects.

Source code in zenml/integrations/langchain/materializers/openai_embedding_materializer.py 
class LangchainOpenaiEmbeddingMaterializer(CloudpickleMaterializer):
    """Handle langchain OpenAI embedding objects."""

    ASSOCIATED_ARTIFACT_TYPE: ClassVar[ArtifactType] = ArtifactType.MODEL
    ASSOCIATED_TYPES: ClassVar[Tuple[Type[Any], ...]] = (OpenAIEmbeddings,)

vector_store_materializer

Implementation of the langchain vector store materializer.

LangchainVectorStoreMaterializer (CloudpickleMaterializer)

Handle langchain vector store objects.

Source code in zenml/integrations/langchain/materializers/vector_store_materializer.py 
class LangchainVectorStoreMaterializer(CloudpickleMaterializer):
    """Handle langchain vector store objects."""

    ASSOCIATED_ARTIFACT_TYPE: ClassVar[ArtifactType] = ArtifactType.DATA
    ASSOCIATED_TYPES: ClassVar[Tuple[Type[Any], ...]] = (VectorStore,)