Hacktoberfest 2026: le issue che i maintainer hanno segnato per ottobre, aperte e adatte ai principianti. Sfoglia le issue Hacktoberfest

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

Aperta
  • Qualcosa non va?
#72 0 commenti 0 reazioni 0 assegnatari Vedi su GitHub

I maintainer di solito rispondono entro 1 giorno

Nessuno ha ancora preso questa issue.

Valutazione

Difficoltà
4/5
Tempo stimato
3-5 giorni
Idoneità per principianti
45/100
Tipo di issue
Bug
Chiarezza
Abbastanza chiara
Stato di attività
Attiva
Stack tecnologico
azure, csharp, docker, mongodb
Ambito
databases, testing-qa

Direzione di ricerca

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.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

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.

Lingua principale
C#
Stelle
8
Fork
8
Merge medio
1g 8h
PR unite (30g)
10

Preparare l'ambiente

Come iniziare

  1. Leggi tutta la issue e poi la guida ai contributi del progetto.
  2. Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
  3. Fai un fork del repository e lavora su un branch.
  4. Apri una pull request che faccia riferimento al numero della issue.

Altre issue di CommunityToolkit/AI

Tutte le issue di CommunityToolkit/AI

Issue simili

Altre issue su C#

Ricevi le nuove issue nella tua casella

Un breve riepilogo di issue GitHub adatte ai principianti.