public sealed class RagEmbeddingModelConfig.Types.HybridSearchConfig : IMessage<RagEmbeddingModelConfig.Types.HybridSearchConfig>, IEquatable<RagEmbeddingModelConfig.Types.HybridSearchConfig>, IDeepCloneable<RagEmbeddingModelConfig.Types.HybridSearchConfig>, IBufferMessage, IMessage
Reference documentation and code samples for the Vertex AI v1beta1 API class RagEmbeddingModelConfig.Types.HybridSearchConfig.
public RagEmbeddingModelConfig.Types.SparseEmbeddingConfig SparseEmbeddingConfig { get; set; }
Optional. The configuration for sparse embedding generation. This field
is optional the default behavior depends on the vector database choice on
the RagCorpus.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-14 UTC."],[[["\u003cp\u003eThis documentation provides details for the \u003ccode\u003eRagEmbeddingModelConfig.Types.HybridSearchConfig\u003c/code\u003e class within the Vertex AI v1beta1 API.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eHybridSearchConfig\u003c/code\u003e class is designed for configuring hybrid search capabilities, inheriting from the base \u003ccode\u003eobject\u003c/code\u003e class and implementing multiple interfaces, including \u003ccode\u003eIMessage\u003c/code\u003e, \u003ccode\u003eIEquatable\u003c/code\u003e, \u003ccode\u003eIDeepCloneable\u003c/code\u003e, and \u003ccode\u003eIBufferMessage\u003c/code\u003e.\u003c/p\u003e\n"],["\u003cp\u003eIt includes a constructor for creating instances of \u003ccode\u003eHybridSearchConfig\u003c/code\u003e and another for cloning existing instances, both of which are detailed.\u003c/p\u003e\n"],["\u003cp\u003eThe class has properties for configuring dense embedding generation via \u003ccode\u003eDenseEmbeddingModelPredictionEndpoint\u003c/code\u003e which is required, and sparse embedding generation via \u003ccode\u003eSparseEmbeddingConfig\u003c/code\u003e which is optional, and depends on the vector database choice on the RagCorpus.\u003c/p\u003e\n"],["\u003cp\u003eThe most recent documentation available is for version 1.0.0-beta21 of this class, with version 1.0.0-beta20 also being available.\u003c/p\u003e\n"]]],[],null,[]]
