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FunctionScore

Addedv2.6.x

A FunctionScore instance combines multiple **Function**s in a configurable manner. You can use a FunctionScore instance as a ranker to combine multiple reranking **Function**s.

class pymilvus.FunctionScore

Constructor

Constructs a FunctionScore instance that combines multiple **Function**s in a configurable manner.

FunctionScore(
    functions: Union[Function, List[Function]],
    params: Optional[Dict] = None,
)

PARAMETERS:

• functions (Function, List[Function]) -

  A Function instance or a list of Function instances that are to be combined in the current FunctionScore instance.

• params (Dict) -

  Specifies how the above Function instances are to be combined. It provides the following settings:

  • boost_mode (str) -

    Specifies how the specified weights influence the scores of any matching entities. Possible values are:

    • Multiply

      Indicates that the weighted value is equal to the original score of a matching entity multiplied by the specified weight.

      This is the default value.

    • Sum

      Indicates that the weighted value is equal to the sum of the original score of a matching entity and the specified weight

  • function_mode (str) -

    Specifies how the weighted values from various Boost Rankers are processed. Possible values are:

    • Multiply

      Indicates that the final score of a matching entity is equal to the product of the weighted values from all Boost Rankers.

      This is the default value.

    • Sum

      Indicates that the final score of a matching entity is equal to the sum of the weighted values from all Boost Rankers.

  RETURN TYPE:

  FunctionScore

  RETURNS:

  A set of Functions that are combined in the configured manner

  Examples

  from pymilvus import Function, FunctionType, FunctionScore
  
  # Create a Boost Ranker with a fixed weight
  fix_weight_ranker = Function(
      name="boost",
      input_field_names=[], # Must be an empty list
      function_type=FunctionType.RERANK,
      params={
          "reranker": "boost",
          "weight": 0.8
      }
  )
  
  # Create a Boost Ranker with a randomly generated weight between 0 and 0.4
  random_weight_ranker = Function(
      name="boost",
      input_field_names=[], # Must be an empty list
      function_type=FunctionType.RERANK,
      params={
          "reranker": "boost",
          "random_score": {
              "seed": 126,
          },
          "weight": 0.4
      }
  )
  
  # Create a Function Score
  ranker = FunctionScore(
      functions=[
          fix_weight_ranker, 
          random_weight_ranker
      ],
      params={
          "boost_mode": "Multiply",
          "function_mode": "Sum"
      }
  )