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 Vertex AI 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 2025-03-25 UTC."],[[["This documentation covers the `RagQuery.Types.Ranking` class, which is part of the Vertex AI v1beta1 API and provides configurations for hybrid search results ranking."],["The `RagQuery.Types.Ranking` class implements several interfaces, including `IMessage`, `IEquatable`, `IDeepCloneable`, and `IBufferMessage`, and inherits from the base `object` class."],["The class includes a constructor `Ranking()` that creates an instance of the ranking class, as well as `Ranking(RagQuery.Types.Ranking other)` that takes another instance of the class to clone it."],["The `Alpha` property, which is a float, allows control over the weight balance between dense and sparse vector search results, ranging from 0 to 1, and has a `HasAlpha` boolean property to check if it's set."]]],[]]
