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Zero/ZeroLevel.Qdrant/Models/Requests/SearchRequest.cs

85 lines
2.3 KiB

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

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