Lots of groundwork and the app runs but not currently working to generate embeddings.

VectorSearchApp/Configuration/AppConfiguration.cs

@@ -0,0 +1,27 @@
+namespace VectorSearchApp.Configuration;
+
+public class AppConfiguration
+{
+    public QdrantConfiguration Qdrant { get; set; } = new();
+    public EmbeddingConfiguration Embedding { get; set; } = new();
+    public AppSettings App { get; set; } = new();
+}
+
+public class QdrantConfiguration
+{
+    public string Host { get; set; } = "localhost";
+    public int GrpcPort { get; set; } = 6334;
+    public int HttpPort { get; set; } = 6333;
+    public string CollectionName { get; set; } = "addresses";
+}
+
+public class EmbeddingConfiguration
+{
+    public string ModelName { get; set; } = "sentence-transformers/all-MiniLM-L6-v2";
+    public int Dimension { get; set; } = 384;
+}
+
+public class AppSettings
+{
+    public int BatchSize { get; set; } = 10;
+}

VectorSearchApp/Models/Address.cs

@@ -0,0 +1,8 @@
+namespace VectorSearchApp.Models;
+
+public class Address
+{
+    public Guid Id { get; set; } = Guid.NewGuid();
+    public string FullAddress { get; set; } = string.Empty;
+    public DateTime CreatedAt { get; set; } = DateTime.UtcNow;
+}

VectorSearchApp/Models/AddressEmbedding.cs

@@ -0,0 +1,8 @@
+namespace VectorSearchApp.Models;
+
+public class AddressEmbedding
+{
+    public Guid Id { get; set; }
+    public string FullAddress { get; set; } = string.Empty;
+    public float[] Vector { get; set; } = Array.Empty<float>();
+}

VectorSearchApp/Program.cs

@@ -0,0 +1,173 @@
+using Microsoft.Extensions.Configuration;
+using VectorSearchApp.Configuration;
+using VectorSearchApp.Models;
+using VectorSearchApp.Services;
+
+Console.WriteLine("=== Vector Search Address Application ===");
+Console.WriteLine("Using sentence-transformers/all-MiniLM-L6-v2 model and Qdrant vector database");
+Console.WriteLine();
+
+// Load configuration
+var configuration = new ConfigurationBuilder()
+    .SetBasePath(AppContext.BaseDirectory)
+    .AddJsonFile("appsettings.json", optional: false, reloadOnChange: true)
+    .Build();
+
+var appConfig = new AppConfiguration();
+configuration.GetSection("Qdrant").Bind(appConfig.Qdrant);
+configuration.GetSection("Embedding").Bind(appConfig.Embedding);
+configuration.GetSection("App").Bind(appConfig.App);
+
+// Initialize services
+Console.WriteLine("Initializing services...");
+var embeddingService = new EmbeddingService(appConfig.Embedding);
+IQdrantService? qdrantService = null;
+
+try
+{
+    qdrantService = new QdrantService(appConfig.Qdrant, appConfig.Embedding.Dimension);
+    Console.WriteLine("Initializing Qdrant collection...");
+    await qdrantService.InitializeCollectionAsync();
+    Console.WriteLine($"Collection '{appConfig.Qdrant.CollectionName}' is ready.");
+}
+catch (Exception ex)
+{
+    Console.WriteLine($"Warning: Could not connect to Qdrant at {appConfig.Qdrant.Host}:{appConfig.Qdrant.GrpcPort}");
+    Console.WriteLine($"Error: {ex.Message}");
+    Console.WriteLine();
+    Console.WriteLine("Please ensure Qdrant is running. You can start it with:");
+    Console.WriteLine("  cd VectorSearchApp && docker-compose up -d");
+    Console.WriteLine();
+    Console.WriteLine("The application will continue, but address storage/search will not be available.");
+    Console.WriteLine();
+}
+
+Console.WriteLine("Type 'exit' to quit at any time.");
+Console.WriteLine();
+
+while (true)
+{
+    Console.WriteLine("Options:");
+    Console.WriteLine("  1. Add a new address");
+    Console.WriteLine("  2. Search for similar addresses");
+    Console.WriteLine("  3. Exit");
+    Console.Write("Select an option: ");
+
+    var option = Console.ReadLine()?.Trim();
+
+    if (option?.ToLower() == "exit" || option == "3")
+    {
+        Console.WriteLine("Goodbye!");
+        return;
+    }
+
+    switch (option)
+    {
+        case "1":
+            await AddAddressAsync(embeddingService, qdrantService, appConfig);
+            break;
+        case "2":
+            await SearchAddressesAsync(embeddingService, qdrantService, appConfig);
+            break;
+        default:
+            Console.WriteLine("Invalid option. Please try again.");
+            break;
+    }
+
+    Console.WriteLine();
+}
+
+async Task AddAddressAsync(IEmbeddingService embeddingService, IQdrantService? qdrantService, AppConfiguration config)
+{
+    Console.Write("Enter the address: ");
+    var addressText = Console.ReadLine()?.Trim();
+
+    if (string.IsNullOrWhiteSpace(addressText))
+    {
+        Console.WriteLine("Address cannot be empty.");
+        return;
+    }
+
+    Console.WriteLine("Generating embedding...");
+    try
+    {
+        var embedding = await embeddingService.GenerateEmbeddingAsync(addressText);
+        Console.WriteLine($"Embedding generated (dimension: {embedding.Length})");
+
+        if (qdrantService != null)
+        {
+            var address = new Address
+            {
+                Id = Guid.NewGuid(),
+                FullAddress = addressText,
+                CreatedAt = DateTime.UtcNow
+            };
+
+            Console.WriteLine("Storing in Qdrant...");
+            await qdrantService.StoreAddressAsync(address, embedding);
+            Console.WriteLine($"Address stored successfully! (ID: {address.Id})");
+        }
+        else
+        {
+            Console.WriteLine("Address embedding generated but not stored (Qdrant not available).");
+        }
+
+        // Display first few values of embedding as confirmation
+        Console.Write("Embedding preview: [");
+        var previewCount = Math.Min(10, embedding.Length);
+        for (int i = 0; i < previewCount; i++)
+        {
+            Console.Write($"{embedding[i]:F4}");
+            if (i < previewCount - 1) Console.Write(", ");
+        }
+        if (embedding.Length > previewCount) Console.Write(", ...");
+        Console.WriteLine("]");
+    }
+    catch (Exception ex)
+    {
+        Console.WriteLine($"Error generating embedding: {ex.Message}");
+    }
+}
+
+async Task SearchAddressesAsync(IEmbeddingService embeddingService, IQdrantService? qdrantService, AppConfiguration config)
+{
+    if (qdrantService == null)
+    {
+        Console.WriteLine("Search is not available because Qdrant is not connected.");
+        return;
+    }
+
+    Console.Write("Enter search query: ");
+    var query = Console.ReadLine()?.Trim();
+
+    if (string.IsNullOrWhiteSpace(query))
+    {
+        Console.WriteLine("Query cannot be empty.");
+        return;
+    }
+
+    Console.WriteLine("Generating query embedding...");
+    try
+    {
+        var queryEmbedding = await embeddingService.GenerateEmbeddingAsync(query);
+        Console.WriteLine($"Searching for similar addresses...");
+
+        var results = await qdrantService.SearchSimilarAddressesAsync(queryEmbedding, limit: 5);
+
+        if (results.Count == 0)
+        {
+            Console.WriteLine("No similar addresses found.");
+            return;
+        }
+
+        Console.WriteLine($"\nFound {results.Count} similar address(es):");
+        for (int i = 0; i < results.Count; i++)
+        {
+            Console.WriteLine($"  {i + 1}. {results[i].FullAddress}");
+        }
+    }
+    catch (Exception ex)
+    {
+        Console.WriteLine($"Error during search: {ex.Message}");
+    }
+}

VectorSearchApp/Services/EmbeddingService.cs

@@ -0,0 +1,52 @@
+using System.Net.Http.Json;
+using VectorSearchApp.Configuration;
+using VectorSearchApp.Models;
+
+namespace VectorSearchApp.Services;
+
+public interface IEmbeddingService
+{
+    Task<float[]> GenerateEmbeddingAsync(string text, CancellationToken cancellationToken = default);
+}
+
+public class EmbeddingService : IEmbeddingService
+{
+    private readonly HttpClient _httpClient;
+    private readonly string _modelName;
+    private readonly int _dimension;
+
+    public EmbeddingService(EmbeddingConfiguration config)
+    {
+        _modelName = config.ModelName;
+        _dimension = config.Dimension;
+        _httpClient = new HttpClient
+        {
+            BaseAddress = new Uri("https://api-inference.huggingface.co/models/")
+        };
+        _httpClient.DefaultRequestHeaders.Add("User-Agent", "VectorSearchApp");
+    }
+
+    public async Task<float[]> GenerateEmbeddingAsync(string text, CancellationToken cancellationToken = default)
+    {
+        var request = new
+        {
+            inputs = text
+        };
+
+        var response = await _httpClient.PostAsJsonAsync(_modelName, request, cancellationToken);
+        
+        if (!response.IsSuccessStatusCode)
+        {
+            throw new InvalidOperationException($"Failed to generate embedding: {response.StatusCode}");
+        }
+
+        var result = await response.Content.ReadFromJsonAsync<float[][]>(cancellationToken: cancellationToken);
+        
+        if (result?.Length > 0 && result[0].Length > 0)
+        {
+            return result[0];
+        }
+
+        throw new InvalidOperationException("Failed to generate embedding");
+    }
+}

VectorSearchApp/Services/QdrantService.cs

@@ -0,0 +1,69 @@
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+using VectorSearchApp.Configuration;
+using VectorSearchApp.Models;
+
+namespace VectorSearchApp.Services;
+
+public interface IQdrantService
+{
+    Task InitializeCollectionAsync(CancellationToken cancellationToken = default);
+    Task StoreAddressAsync(Address address, float[] embedding, CancellationToken cancellationToken = default);
+    Task<List<AddressEmbedding>> SearchSimilarAddressesAsync(float[] queryEmbedding, int limit = 5, CancellationToken cancellationToken = default);
+}
+
+public class QdrantService : IQdrantService
+{
+    private readonly QdrantClient _client;
+    private readonly string _collectionName;
+    private readonly int _vectorDimension;
+
+    public QdrantService(QdrantConfiguration config, int vectorDimension)
+    {
+        _client = new QdrantClient(config.Host, config.GrpcPort);
+        _collectionName = config.CollectionName;
+        _vectorDimension = vectorDimension;
+    }
+
+    public async Task InitializeCollectionAsync(CancellationToken cancellationToken = default)
+    {
+        var collections = await _client.ListCollectionsAsync(cancellationToken: cancellationToken);
+        
+        if (!collections.Contains(_collectionName))
+        {
+            await _client.CreateCollectionAsync(_collectionName, new VectorParams
+            {
+                Size = (ulong)_vectorDimension,
+                Distance = Distance.Cosine
+            }, cancellationToken: cancellationToken);
+        }
+    }
+
+    public async Task StoreAddressAsync(Address address, float[] embedding, CancellationToken cancellationToken = default)
+    {
+        var point = new PointStruct
+        {
+            Id = new PointId { Uuid = address.Id.ToString() },
+            Vectors = embedding,
+            Payload =
+            {
+                ["address"] = address.FullAddress,
+                ["created_at"] = address.CreatedAt.ToString("O")
+            }
+        };
+
+        await _client.UpsertAsync(_collectionName, new[] { point }, cancellationToken: cancellationToken);
+    }
+
+    public async Task<List<AddressEmbedding>> SearchSimilarAddressesAsync(float[] queryEmbedding, int limit = 5, CancellationToken cancellationToken = default)
+    {
+        var results = await _client.SearchAsync(_collectionName, queryEmbedding, limit: (ulong)limit, cancellationToken: cancellationToken);
+        
+        return results.Select(r => new AddressEmbedding
+        {
+            Id = Guid.Parse(r.Id.Uuid),
+            FullAddress = r.Payload["address"].StringValue,
+            Vector = Array.Empty<float>()
+        }).ToList();
+    }
+}

VectorSearchApp/VectorSearchApp.csproj

@@ -0,0 +1,23 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net8.0</TargetFramework>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Microsoft.Extensions.Configuration.Binder" Version="10.0.2" />
+    <PackageReference Include="Microsoft.Extensions.Configuration.Json" Version="10.0.2" />
+    <PackageReference Include="Microsoft.ML.OnnxRuntime" Version="1.23.2" />
+    <PackageReference Include="Qdrant.Client" Version="1.16.1" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <None Update="appsettings.json">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+  </ItemGroup>
+
+</Project>

VectorSearchApp/appsettings.json

@@ -0,0 +1,15 @@
+{
+	"Qdrant": {
+		"Host": "localhost",
+		"GrpcPort": 6334,
+		"HttpPort": 6333,
+		"CollectionName": "addresses"
+	},
+	"Embedding": {
+		"ModelName": "sentence-transformers/all-MiniLM-L6-v2",
+		"Dimension": 384
+	},
+	"App": {
+		"BatchSize": 10
+	}
+}

VectorSearchApp/docker-compose.yml

@@ -0,0 +1,17 @@
+version: '3.8'
+
+services:
+  qdrant:
+    image: qdrant/qdrant:latest
+    container_name: vector-search-qdrant
+    ports:
+      - "6333:6333"
+      - "6334:6334"
+    volumes:
+      - qdrant_storage:/qdrant/storage
+    environment:
+      - QDRANT__SERVICE__API_GRPC_PORT=6334
+      - QDRANT__SERVICE__HTTP_PORT=6333
+
+volumes:
+  qdrant_storage: