public sealed class RagQuery.Types.Ranking : IMessage<RagQuery.Types.Ranking>, IEquatable<RagQuery.Types.Ranking>, IDeepCloneable<RagQuery.Types.Ranking>, IBufferMessage, IMessage
Reference documentation and code samples for the Cloud AI Platform v1beta1 API class RagQuery.Types.Ranking.
Optional. Alpha value controls the weight between dense and sparse vector
search results. The range is [0, 1], while 0 means sparse vector search
only and 1 means dense vector search only. The default value is 0.5 which
balances sparse and dense vector search equally.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-03-21 UTC."],[[["This documentation covers the `RagQuery.Types.Ranking` class within the Google Cloud AI Platform v1beta1 API, specifically for versions beta20 and beta21."],["The `RagQuery.Types.Ranking` class is used to configure the ranking of hybrid search results and it inherits from the `object` class, implementing several interfaces like `IMessage`, `IEquatable`, and `IDeepCloneable`."],["The class provides properties like `Alpha`, which is a float that controls the weight between dense and sparse vector search results, and `HasAlpha`, which is a boolean to check if the \"alpha\" field is set."],["There are two constructors for the class: `Ranking()` which is default, and `Ranking(RagQuery.Types.Ranking other)` which allows the creation of a new instance based on an existing `RagQuery.Types.Ranking` object."]]],[]]
