ExtensionsVectorData Lodestar.Extensions.VectorData

Development build. This page describes main, not a released package. The latest published Lodestar.Extensions.VectorData is 0.1.0 — read its documentation.

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Lodestar.Extensions.VectorData

An in-process Microsoft.Extensions.VectorData store: collections of records with vector search over Lodestar's EmbeddingIndex, keyword search over Bm25Index, and hybrid search fusing the two by reciprocal rank. Nothing to deploy: the store lives in the process that uses it.

Note is any record class carrying a key, a text and a vector property.

Install

dotnet add package Lodestar.Extensions.VectorData

Example

using Lodestar.Extensions.VectorData;
using Microsoft.Extensions.VectorData;

static async Task<string> FuseAsync()
{
    using var notes = new LodestarVectorStoreCollection<string, Note>("notes");
    await notes.UpsertAsync([
        new Note { Id = "a", Text = "the cat sat on the mat", Embedding = new float[] { 1f, 0f, 0f } },
        new Note { Id = "b", Text = "the dog ran in the park", Embedding = new float[] { 0f, 1f, 0f } },
        new Note { Id = "c", Text = "an elephant crossed the river", Embedding = new float[] { 0f, 0f, 1f } },
    ]);

    List<VectorSearchResult<Note>> hits = await notes
        .HybridSearchAsync(new float[] { 1f, 0f, 0f }, ["elephant", "zebra"], 2)
        .ToListAsync();
    return string.Join(",", hits.Select(hit => hit.Record.Id));   // c,a
}

Parity

Its search sits on Lodestar.Embeddings and Lodestar.Text, which carry the parity; the store follows the Microsoft.Extensions.VectorData contracts. docs/equivalence.md maps each Python call to its C# counterpart, with every deliberate divergence.

Dependencies

A interop package (decision 0003), built for net10.0 and netstandard2.0:

• Lodestar.Embeddings 0.8.0 or later
• Lodestar.Text 0.7.0 or later
• Microsoft.Extensions.VectorData.Abstractions 10.10.0 or later

Documentation

• Reference: extensions-vectordata/store
• Changelog
• Performance
• All packages