/* SPDX-License-Identifier: Apache-2.0
*
* The OpenSearch Contributors require contributions made to
* this file be licensed under the Apache-2.0 license or a
* compatible open source license.
*/
/*
* Modifications Copyright OpenSearch Contributors. See
* GitHub history for details.
*
*  Licensed to Elasticsearch B.V. under one or more contributor
*  license agreements. See the NOTICE file distributed with
*  this work for additional information regarding copyright
*  ownership. Elasticsearch B.V. licenses this file to you under
*  the Apache License, Version 2.0 (the "License"); you may
*  not use this file except in compliance with the License.
*  You may obtain a copy of the License at
*
* 	http://www.apache.org/licenses/LICENSE-2.0
*
*  Unless required by applicable law or agreed to in writing,
*  software distributed under the License is distributed on an
*  "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
*  KIND, either express or implied.  See the License for the
*  specific language governing permissions and limitations
*  under the License.
*/

using System.Runtime.Serialization;
using OpenSearch.Net;


namespace OpenSearch.Client
{
	/// <summary>
	/// String distance implementation to use for comparing how similar suggested terms are
	/// </summary>
	[StringEnum]
	public enum StringDistance
	{
		/// <summary>
		/// The default based on damerau_levenshtein but highly optimized for comparing string distance for terms inside the index.
		/// </summary>
		[EnumMember(Value = "internal")]
		Internal,

		/// <summary>
		/// String distance algorithm based on Damerau-Levenshtein algorithm.
		/// </summary>
		[EnumMember(Value = "damerau_levenshtein")]
		DamerauLevenshtein,

		/// <summary>
		/// String distance algorithm based on Levenshtein edit distance algorithm.
		/// </summary>
		[EnumMember(Value = "levenshtein")]
		Levenshtein,

		/// <summary>
		/// String distance algorithm based on Jaro-Winkler algorithm.
		/// </summary>
		[EnumMember(Value = "jaro_winkler")]
		Jarowinkler,

		/// <summary>
		/// String distance algorithm based on character n-grams.
		/// </summary>
		[EnumMember(Value = "ngram")]
		Ngram
	}
}