Vector

The Vector class in RedisVL is a container that encapsulates a numerical vector, it’s datatype, corresponding index field name, and optional importance weight. It is used when constructing multi-vector queries using the MultiVectorQuery class.

Vector

class Vector(*, vector, field_name, dtype='float32', weight=1.0)

Simple object containing the necessary arguments to perform a multi vector query.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

• vector (List[float] | bytes)

• field_name (str)

• dtype (str)

• weight (float)

validate_vector()

If the vector passed in is an array of float convert it to a byte string.

Return type:

Self

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].