class Qdrant::Api::RecommendRequest

Overview

Recommendation request. Provides positive and negative examples of the vectors, which can be ids of points that are already stored in the collection, raw vectors, or even ids and vectors combined. Service should look for the points which are closer to positive examples and at the same time further to negative examples. The concrete way of how to compare negative and positive distances is up to the #strategy chosen.

Included Modules

Defined in:

qdrant-api/models/recommend_request.cr

Constructors

Instance Method Summary

Macros inherited from module Qdrant::Api::Validation

validates(name, klass, nilable, **rules) validates

Instance methods inherited from module Qdrant::Api::Serializable

eql?(other) eql?, to_body : Hash(String, JSON::Any) to_body, to_h : Hash(String, JSON::Any) to_h, to_s(io : IO) : Nil to_s

Constructor Detail

def self.new(ctx : YAML::ParseContext, node : YAML::Nodes::Node) #

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def self.new(pull : JSON::PullParser) #

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def self.new(limit : Int32, shard_key : ShardKeySelector | Nil = nil, positive : Array(RecommendExample) | Nil = nil, negative : Array(RecommendExample) | Nil = nil, strategy : RecommendStrategy | Nil = nil, filter : Filter | Nil = nil, params : SearchParams | Nil = nil, offset : Int32 | Nil = nil, with_payload : WithPayloadInterface | Nil = nil, with_vector : WithVector | Nil = nil, score_threshold : Float32 | Nil = nil, using : String | Nil = nil, lookup_from : LookupLocation | Nil = nil) #

Initializes the object @param [Hash] attributes Model attributes in the form of hash


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def self.new(*, __pull_for_json_serializable pull : JSON::PullParser) #

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def self.new(*, __context_for_yaml_serializable ctx : YAML::ParseContext, __node_for_yaml_serializable node : YAML::Nodes::Node) #

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Instance Method Detail

def ==(other : self) #
Description copied from class Reference

Returns true if this reference is the same as other. Invokes same?.


def filter : Filter | Nil #

Look only for points which satisfies this conditions


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def filter=(filter : Filter | Nil) #

Look only for points which satisfies this conditions


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def hash(hasher) #
Description copied from class Reference

See Object#hash(hasher)


def limit : Int32 #

Required properties Max number of result to return


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def limit=(value : Int32) #

Required properties Max number of result to return


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def limit_validation_error(value) : String | Nil #

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def list_invalid_properties #

Show invalid properties with the reasons. Usually used together with valid? @return Array for valid properties with the reasons


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def lookup_from : LookupLocation | Nil #

The location used to lookup vectors. If not specified - use current collection. Note: the other collection should have the same vector size as the current collection


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def lookup_from=(lookup_from : LookupLocation | Nil) #

The location used to lookup vectors. If not specified - use current collection. Note: the other collection should have the same vector size as the current collection


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def negative : Array(RecommendExample) | Nil #

Try to avoid vectors like this


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def negative=(negative : Array(RecommendExample) | Nil) #

Try to avoid vectors like this


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def offset : Int32 | Nil #

Offset of the first result to return. May be used to paginate results. Note: large offset values may cause performance issues.


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def offset=(value : Int32 | Nil) #

Offset of the first result to return. May be used to paginate results. Note: large offset values may cause performance issues.


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def offset_validation_error(value) : String | Nil #

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def params : SearchParams | Nil #

Additional search params


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def params=(params : SearchParams | Nil) #

Additional search params


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def positive : Array(RecommendExample) | Nil #

Look for vectors closest to those


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def positive=(positive : Array(RecommendExample) | Nil) #

Look for vectors closest to those


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def score_threshold : Float32 | Nil #

Define a minimal score threshold for the result. If defined, less similar results will not be returned. Score of the returned result might be higher or smaller than the threshold depending on the Distance function used. E.g. for cosine similarity only higher scores will be returned.


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def score_threshold=(score_threshold : Float32 | Nil) #

Define a minimal score threshold for the result. If defined, less similar results will not be returned. Score of the returned result might be higher or smaller than the threshold depending on the Distance function used. E.g. for cosine similarity only higher scores will be returned.


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def shard_key : ShardKeySelector | Nil #

Optional properties Specify in which shards to look for the points, if not specified - look in all shards


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def shard_key=(shard_key : ShardKeySelector | Nil) #

Optional properties Specify in which shards to look for the points, if not specified - look in all shards


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def strategy : RecommendStrategy | Nil #

How to use positive and negative examples to find the results


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def strategy=(strategy : RecommendStrategy | Nil) #

How to use positive and negative examples to find the results


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def using : String | Nil #

Define which vector to use for recommendation, if not specified - try to use default vector


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def using=(using : String | Nil) #

Define which vector to use for recommendation, if not specified - try to use default vector


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def valid? #

Check to see if the all the properties in the model are valid @return true if the model is valid


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def with_payload : WithPayloadInterface | Nil #

Select which payload to return with the response. Default is false.


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def with_payload=(with_payload : WithPayloadInterface | Nil) #

Select which payload to return with the response. Default is false.


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def with_vector : WithVector | Nil #

Options for specifying which vectors to include into response. Default is false.


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def with_vector=(with_vector : WithVector | Nil) #

Options for specifying which vectors to include into response. Default is false.


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