def embeddings_store_output()

in azure/functions/decorators/function_app.py [0:0]

• 32 lines of code
• 1 McCabe index (conditional complexity)

    def embeddings_store_output(self,
                                arg_name: str,
                                input: str,
                                input_type: InputType,
                                connection_name: str,
                                collection: str,
                                model: Optional[OpenAIModels] = OpenAIModels.DefaultEmbeddingsModel,  # NoQA
                                max_chunk_length: Optional[int] = 8 * 1024,
                                max_overlap: Optional[int] = 128,
                                data_type: Optional[
                                    Union[DataType, str]] = None,
                                **kwargs) \
            -> Callable[..., Any]:
        """
        Supported list of embeddings store is extensible, and more can be
        added by authoring a specially crafted NuGet package. Visit the
        currently supported vector specific folder for specific usage
        information:

        - Azure AI Search
        - Azure Data Explorer
        - Azure Cosmos DB using MongoDB

        :param arg_name: The name of binding parameter in the function code.
        :param input: The input to generate embeddings for.
        :param input_type: The type of the input.
        :param connection_name: The name of an app setting or environment
        variable which contains a connection string value
        :param collection: The collection or table to search.
        :param model: The ID of the model to use.
        :param max_chunk_length: The maximum number of characters to chunk the
        input into.
        :param max_overlap: The maximum number of characters to overlap between
        chunks.
        :param data_type: Optional. Defines how Functions runtime should treat
        the parameter value. Default value: None
        :param kwargs: Keyword arguments for specifying additional binding
        fields to include in the binding json

        :return: Decorator function.
        """

        @self._configure_function_builder
        def wrap(fb):
            def decorator():
                fb.add_binding(
                    binding=EmbeddingsStoreOutput(
                        name=arg_name,
                        input=input,
                        input_type=input_type,
                        connection_name=connection_name,
                        collection=collection,
                        model=model,
                        max_chunk_length=max_chunk_length,
                        max_overlap=max_overlap,
                        data_type=parse_singular_param_to_enum(data_type,
                                                               DataType),
                        **kwargs))
                return fb

            return decorator()

        return wrap