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85 lines
2.3 KiB
85 lines
2.3 KiB
using ZeroLevel.Qdrant.Models.Filters;
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using System;
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using System.Linq;
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using System.Text;
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namespace ZeroLevel.Qdrant.Models.Requests
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{
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internal sealed class SearchRequest
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{
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/// <summary>
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/// Look only for points which satisfies this conditions
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/// </summary>
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public Filter Filter { get; set; }
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/// <summary>
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/// Look for vectors closest to this
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/// </summary>
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public double[] FloatVector { get; set; }
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public long[] IntegerVector { get; set; }
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/// <summary>
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/// Max number of result to return
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/// </summary>
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public uint Top { get; set; }
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/// <summary>
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/// Params relevant to HNSW index /// Size of the beam in a beam-search. Larger the value - more accurate the result, more time required for search.
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/// </summary>
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public uint? HNSW { get; set; } = null;
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/*
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{
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"filter": {
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"must": [
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{
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"key": "city",
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"match": {
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"keyword": "London"
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}
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}
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]
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},
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"params": {
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"hnsw_ef": 128
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},
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"vector": [0.2, 0.1, 0.9, 0.7],
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"top": 3
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}
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*/
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public string ToJson()
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{
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var json = new StringBuilder();
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json.Append("{");
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if (Filter == null || Filter.IsEmpty)
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{
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json.Append("\"filter\": null,");
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}
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else
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{
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json.Append(Filter.ToJSON());
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json.Append(',');
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}
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if (HNSW != null)
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{
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json.Append($"\"params\": {{ \"hnsw_ef\": {HNSW.Value} }},");
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}
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if (FloatVector != null)
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{
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json.Append($"\"vector\": [{string.Join(",", FloatVector.Select(f => f.ConvertToString()))}],");
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}
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else if (IntegerVector != null)
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{
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json.Append($"\"vector\": [{string.Join(",", IntegerVector)}],");
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}
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else
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{
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throw new ArgumentException("No one vectors is set");
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}
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json.Append($"\"top\": {Top}");
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json.Append("}");
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return json.ToString();
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}
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}
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}
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