initial release

Services/EmbeddingService.cs

@@ -0,0 +1,38 @@
+using System.Numerics.Tensors;
+
+namespace OpenQuery.Services;
+
+public class EmbeddingService
+{
+    private readonly OpenRouterClient _client;
+    private readonly string _embeddingModel;
+
+    public EmbeddingService(OpenRouterClient client, string embeddingModel = "openai/text-embedding-3-small")
+    {
+        _client = client;
+        _embeddingModel = embeddingModel;
+    }
+
+    public async Task<float[][]> GetEmbeddingsAsync(List<string> texts)
+    {
+        var results = new List<float[]>();
+        const int batchSize = 300;
+        
+        for (var i = 0; i < texts.Count; i += batchSize)
+        {
+            if (texts.Count > batchSize)
+                Console.WriteLine(
+                    $"[Generating {Math.Ceiling(i / (double)batchSize)}/{Math.Ceiling(texts.Count / (double)batchSize)} batch of embeddings]");
+            var batch = texts.Skip(i).Take(batchSize).ToList();
+            var batchResults = await _client.EmbedAsync(_embeddingModel, batch);
+            results.AddRange(batchResults);
+        }
+        
+        return results.ToArray();
+    }
+
+    public static float CosineSimilarity(float[] vector1, float[] vector2)
+    {
+        return TensorPrimitives.CosineSimilarity(vector1, vector2);
+    }
+}