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/// The name of the text field from your document model that is embedded.
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TextField(String),
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}
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/// A model parameter value of a specific type.
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#[derive(Clone,Debug,Serialize)]
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pubenumModelParameterValue{
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/// A string value type
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StringVal(String),
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/// An integer value type
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IntVal(i32),
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/// A floating point value type
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FloatVal(f32),
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/// A boolean value type.
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BoolVal(bool),
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}
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/// Configuration options for the index with integrated embedding.
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#[derive(Clone,Debug)]
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pubstructCreateIndexForModelOptions{
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/// The name of the embedding model to use for the index.
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pubmodel:String,
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/// Identifies the name of the field from your document model that will be embedded. (Only one
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/// field is supported for now.)
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pubfield_map:Vec<FieldMapEntry>,
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/// The distance metric to be used for similarity search. You can use 'euclidean', 'cosine', or 'dotproduct'. If not specified, the metric will be defaulted according to the model. Cannot be updated once set.
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pubmetric:Option<Metric>,
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/// The desired vector dimension, if supported by the model.
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