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AzureDocumentDB: CosineDistance returns similarity scores, and ScoreThreshold filters the wrong way

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#72 0 comentarios 0 reacciones 0 asignados Ver en GitHub

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Evaluación

Dificultad
4/5
Tiempo estimado
3-5 días
Aptitud para principiantes
45/100
Tipo de issue
Error
Claridad
Bastante claro
Estado de actividad
Activo
Stack tecnológico
azure, csharp, docker, mongodb
Área
databases, testing-qa

Línea de trabajo

Read MEVD/src/AzureDocumentDB/DocumentDBCollectionCreateMapping.cs, MEVD/src/AzureDocumentDB/DocumentDBCollectionSearchMapping.cs, and MEVD/src/AzureDocumentDB/DocumentDBCollection.cs to compare the provider’s cosine score and threshold semantics with InMemory. Run the supplied dotnet run repro.cs, then inspect MEVD/test/AzureDocumentDB.ConformanceTests/DocumentDBDistanceFunctionTests.cs for the current score assertions. Completion requires agreeing whether to normalize similarity into distance, adjusting the threshold comparison, and updating conformance coverage without silently changing existing behavior.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

bug

With CosineDistance, the default, AzureDocumentDB returns the cosine similarity as Score, and ScoreThreshold keeps scores >= the threshold. InMemory returns the distance and keeps scores <= it.

Repro: with Docker running, dotnet run repro.cs.

#:package [email protected]
#:package [email protected]
#:package [email protected]
#:property PublishAot=false

using System.Security.Authentication;
using CommunityToolkit.VectorData.AzureDocumentDB;
using CommunityToolkit.VectorData.InMemory;
using DotNet.Testcontainers.Builders;
using Microsoft.Extensions.VectorData;
using MongoDB.Driver;

// Starts DocumentDB local in Docker, then compares InMemory and AzureDocumentDB with CosineDistance.
await using var container = new ContainerBuilder("ghcr.io/microsoft/documentdb/documentdb-local:latest")
    .WithEnvironment("USERNAME", "user")
    .WithEnvironment("PASSWORD", "Pass123!")
    .WithPortBinding(10260, true)
    .WithWaitStrategy(Wait.ForUnixContainer().UntilInternalTcpPortIsAvailable(10260))
    .Build();
await container.StartAsync();

var settings = MongoClientSettings.FromConnectionString($"mongodb://user:Pass123!@{container.Hostname}:{container.GetMappedPublicPort(10260)}/?tls=true");
settings.SslSettings = new SslSettings { EnabledSslProtocols = SslProtocols.Tls12, ServerCertificateValidationCallback = (_, _, _, _) => true };
var documentDb = new DocumentDBVectorStore(new MongoClient(settings).GetDatabase("repro"));
var inMemory = new InMemoryVectorStore();

Hotel[] hotels =
[
    new() { Id = "same", Vector = new float[] { 1, 0, 0 } },
    new() { Id = "orthogonal", Vector = new float[] { 0, 1, 0 } },
    new() { Id = "opposite", Vector = new float[] { -1, 0, 0 } },
];
ReadOnlyMemory<float> query = new float[] { 1, 0, 0 };

foreach (var (name, store) in new (string, VectorStore)[] { ("InMemory", inMemory), ("DocumentDB", documentDb) })
{
    var collection = store.GetCollection<string, Hotel>("hotels");
    await collection.EnsureCollectionDeletedAsync();
    await collection.EnsureCollectionExistsAsync();
    await collection.UpsertAsync(hotels);
    await Task.Delay(1000);

    Console.WriteLine($"{name} CosineDistance");
    await foreach (var r in collection.SearchAsync(query, 3))
        Console.WriteLine($"  {r.Record.Id,-10} score {r.Score:0.##}");
    var within = await collection.SearchAsync(query, 3, new() { ScoreThreshold = 1.5 }).Select(r => r.Record.Id).ToListAsync();
    Console.WriteLine($"  ScoreThreshold = 1.5 -> [{string.Join(", ", within)}]");
}

public sealed class Hotel
{
    [VectorStoreKey] public string Id { get; set; } = "";
    [VectorStoreVector(3, DistanceFunction = DistanceFunction.CosineDistance)] public ReadOnlyMemory<float> Vector { get; set; }
}

InMemory CosineDistance
  same       score 0
  orthogonal score 1
  opposite   score 2
  ScoreThreshold = 1.5 -> [same, orthogonal]
DocumentDB CosineDistance
  same       score 1
  orthogonal score 0
  opposite   score -1
  ScoreThreshold = 1.5 -> []

Cause:

Returning 1 - similarity and filtering with $lte would match the other providers, but it changes the scores existing users get. Which way do you prefer? I can send the PR.

Lenguaje dominante
C#
Estrellas
8
Forks
8
Merge medio
1 d 8 h
PR fusionados (30 d)
10

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