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EasyAppDev.Blazor.AutoComplete.AI.CosmosDb 1.0.7

EasyAppDev.Blazor.AutoComplete.AI.CosmosDb

Azure Cosmos DB integration for semantic search with the Blazor AutoComplete component.

👁 NuGet
👁 License: MIT

Features

• Multi-Model Database: NoSQL + vector search
• Global Distribution: Low latency worldwide
• Integrated NoSQL: Store documents with embeddings
• Enterprise SLA: 99.999% availability

Installation

dotnet add package EasyAppDev.Blazor.AutoComplete.AI.CosmosDb

Quick Start

1. Configure Services

// Program.cs
builder.Services.AddAutoCompleteCosmosDb<Product>(
 endpoint: "https://myaccount.documents.azure.com:443/",
 key: "your-cosmos-key",
 databaseName: "myapp",
 containerName: "products",
 options => {
 options.VectorIndexType = VectorIndexType.DiskANN;
 options.Dimensions = 1536;
 },
 textSelector: p => $"{p.Name} {p.Description}",
 idSelector: p => p.Id.ToString());

// Register embedding generator
builder.Services.AddAutoCompleteVectorSearch<Product>(
 openAiApiKey: "sk-...");

2. Use the Component

@using EasyAppDev.Blazor.AutoComplete.AI

<VectorAutoComplete TItem="Product"
 TextField="@(p => p.Name)"
 @bind-Value="@selectedProduct"
 Placeholder="Semantic search..." />

Configuration Options

Vector Index Types

Container Setup

Enable vector search on container:

var containerProperties = new ContainerProperties("products", "/id")
{
 VectorEmbeddingPolicy = new VectorEmbeddingPolicy(
 new Collection<Embedding> {
 new Embedding {
 Path = "/embedding",
 DataType = VectorDataType.Float32,
 Dimensions = 1536,
 DistanceFunction = DistanceFunction.Cosine
 }
 })
};

Integrated Document Storage

Store full documents with embeddings:

public class ProductDocument
{
 public string Id { get; set; }
 public string Name { get; set; }
 public string Description { get; set; }
 public float[] Embedding { get; set; } // Auto-populated
}

License

MIT