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

This commit is contained in:
2026-01-13 21:48:42 -05:00
parent 5ce3a30588
commit 98ea050bd8
11 changed files with 431 additions and 0 deletions

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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");
}
}

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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();
}
}