Function

A Function instance for generating vector embeddings from user-provided raw data in Milvus.

class pymilvus.Function

Constructor

This constructor initializes a new Function instance designed to transform user’s raw data into vector embeddings. This is achieved through an automated process that simplifies similarity search operations.

Function(
    name: str,
    function_type: FunctionType,
    input_field_names: Union[str, List[str]],
    output_field_names: Union[str, List[str]],
    description: str = "",
    params: Optional[Dict] = None,
)

PARAMETERS:

• name (str) -

  [REQUIRED]

  The name of the function. This identifier is used to reference the function within queries and collections.

• function_type (FunctionType) -

  [REQUIRED]

  The type of function for processing raw data. Possible values:

  • FunctionType.BM25: Uses the BM25 algorithm for generating sparse embeddings from a VARCHAR field.

• input_field_names (Union[str, List[str]]) -

  [REQUIRED]

  The name of the field containing the raw data that requires conversion to vector representation. For functions using FunctionType.BM25, this parameter accepts only one field name.

• output_field_names (Union[str, List[str]]) -

  [REQUIRED]

  The name of the field where the generated embeddings will be stored. This should correspond to a vector field defined in the collection schema. For functions using FunctionType.BM25, this parameter accepts only one field name.

• description (str) -

  [OPTIONAL]

  A brief description of the function’s purpose. This can be useful for documentation or clarity in larger projects and defaults to an empty string.

• params (dict) -

  [OPTIONAL]

  A dictionary of additional parameters specific to the function type. For FunctionType.BM25, the following custom parameters can be defined to adjust the embedding behavior.

  • bm25_k1 (float) -

    Controls the term frequency saturation. Higher values increase the importance of term frequencies in document ranking. Value range: [1.2, 2.0].

  • bm25_b (float) -

    Controls the extent to which document length is normalized. Values between 0 and 1 are typically used, with a common default around 0.75. A value of 1 means no length normalization, while a value of 0 means full normalization.

  Example configuration:

  params={
      "bm25_k1": 1.5,  # Example for term frequency saturation
      "bm25_b": 0.75,   # Example for document length normalization
  }
  

RETURN TYPE:

Instance of Function that encapsulates the specific processing behavior for converting raw data to vector embeddings.

RETURNS:

A Function object that can be registered with a Milvus collection, facilitating automatic embedding generation during data insertion.

EXCEPTIONS:

• UnknownFunctionType

  This exception will be raised when an unsupported or unrecognized function type is specified.

• FunctionIncorrectInputOutputType

  This exception will be raised when one or more field names in input_field_names or output_field_names are not strings.

• FunctionDuplicateInputs

  This exception will be raised when there are duplicate field names in input_field_names.

• FunctionDuplicateOutputs

  This exception will be raised when there are duplicate field names in output_field_names.

• FunctionCommonInputOutput

  This exception will be raised when there is an overlap between input_field_names and output_field_names, meaning that the same field name is present in both.

Examples

from pymilvus import Function, FunctionType

bm25_function = Function(
    name="bm25_fn",
    input_field_names=["document_content"],
    output_field_names="sparse_vector",
    function_type=FunctionType.BM25,
)