🔧 Update ITextEmbedding interface and its implementations

- Update ITextEmbedding interface to use async methods for getting vectors
- Update KnowledgeService to use async methods for getting vectors
- Update TextEmbeddingProvider and fastTextEmbeddingProvider to use async methods for getting vectors
- Update IntentClassifier to use async methods for getting vectors
- Update SemanticKernelTextEmbeddingProvider to use async methods for getting vectors

src/Infrastructure/BotSharp.Abstraction/MLTasks/ITextEmbedding.cs

@@ -1,8 +1,10 @@
+using System.Threading;
+
 namespace BotSharp.Abstraction.MLTasks;
 
 public interface ITextEmbedding
 {
     int Dimension { get; }
-    float[] GetVector(string text);
-    List<float[]> GetVectors(List<string> texts);
+    Task<float[]> GetVectorAsync(string text);
+    Task<List<float[]>> GetVectorsAsync(List<string> texts);
 }

src/Plugins/BotSharp.Plugin.KnowledgeBase/Services/KnowledgeService.cs

@@ -31,7 +31,7 @@ public class KnowledgeService : IKnowledgeService
         await db.CreateCollection(knowledge.AgentId, textEmbedding.Dimension);
         foreach (var line in lines)
         {
-            var vec = textEmbedding.GetVector(line);
+            var vec = await textEmbedding.GetVectorAsync(line);
             await db.Upsert(knowledge.AgentId, idStart, vec, line);
             idStart++;
             Console.WriteLine($"Saved vector {idStart}/{lines.Count}: {line}\n");
@@ -41,7 +41,7 @@ public class KnowledgeService : IKnowledgeService
     public async Task<string> GetKnowledges(KnowledgeRetrievalModel retrievalModel)
     {
         var textEmbedding = GetTextEmbedding();
-        var vector = textEmbedding.GetVector(retrievalModel.Question);
+        var vector = await textEmbedding.GetVectorAsync(retrievalModel.Question);
 
         // Vector search
         var result = await GetVectorDb().Search(retrievalModel.AgentId, vector, limit: 10);

src/Plugins/BotSharp.Plugin.LLamaSharp/Providers/TextEmbeddingProvider.cs

@@ -15,7 +15,7 @@ public class TextEmbeddingProvider : ITextEmbedding
         _settings = settings;
     }
 
-    public float[] GetVector(string text)
+    public Task<float[]> GetVectorAsync(string text)
     {
         if (_embedder == null)
         {
@@ -23,10 +23,10 @@ public class TextEmbeddingProvider : ITextEmbedding
             _embedder = new LLamaEmbedder(new ModelParams(path));
         }
 
-        return _embedder.GetEmbeddings(text);
+        return Task.FromResult(_embedder.GetEmbeddings(text));
     }
 
-    public List<float[]> GetVectors(List<string> texts)
+    public Task<List<float[]>> GetVectorsAsync(List<string> texts)
     {
         throw new NotImplementedException();
     }

src/Plugins/BotSharp.Plugin.MetaAI/Providers/fastTextEmbeddingProvider.cs

@@ -3,6 +3,7 @@ using BotSharp.Plugin.MetaAI.Settings;
 using FastText.NetWrapper;
 using System.Collections.Generic;
 using System.IO;
+using System.Threading.Tasks;
 
 namespace BotSharp.Plugin.MetaAI.Providers;
 
@@ -26,19 +27,19 @@ public class fastTextEmbeddingProvider : ITextEmbedding
 
     }
 
-    public float[] GetVector(string text)
+    public Task<float[]> GetVectorAsync(string text)
     {
         LoadModel();
-        return _fastText.GetSentenceVector(text);
+        return Task.FromResult(_fastText.GetSentenceVector(text));
     }
 
-    public List<float[]> GetVectors(List<string> texts)
+    public async Task<List<float[]>> GetVectorsAsync(List<string> texts)
     {
         LoadModel();
         var vectors = new List<float[]>();
         for (int i = 0; i < texts.Count; i++)
         {
-            vectors.Add(GetVector(texts[i]));
+            vectors.Add(await GetVectorAsync(texts[i]));
         }
         return vectors;
     }

src/Plugins/BotSharp.Plugin.RoutingSpeeder/Providers/IntentClassifier.cs

@@ -33,8 +33,8 @@ public class IntentClassifier
     private string[] _labels;
     public string[] Labels => _labels == null ? GetLabels() : _labels;
 
-    public IntentClassifier(IServiceProvider services, 
-        ClassifierSetting settings, 
+    public IntentClassifier(IServiceProvider services,
+        ClassifierSetting settings,
         KnowledgeBaseSettings knowledgeBaseSettings,
         ILogger logger)
     {
@@ -140,7 +140,7 @@ public class IntentClassifier
             .FirstOrDefault(x => x.GetType().FullName.EndsWith(knowledgeSettings.TextEmbedding));
 
         var x = np.zeros((1, embedding.Dimension), dtype: np.float32);
-        x[0] = embedding.GetVector(text);
+        x[0] = embedding.GetVectorAsync(text).GetAwaiter().GetResult();
         return x;
     }
 
@@ -178,7 +178,7 @@ public class IntentClassifier
         {
             var texts = File.ReadAllLines(filePath, Encoding.UTF8).ToList();
 
-            vectorList.AddRange(vector.GetVectors(texts));
+            vectorList.AddRange(vector.GetVectorsAsync(texts).GetAwaiter().GetResult());
             string fileName = Path.GetFileNameWithoutExtension(filePath);
             labelList.AddRange(Enumerable.Repeat(fileName, texts.Count).ToList());
         }

src/Plugins/BotSharp.Plugin.SemanticKernel/SemanticKernelTextEmbeddingProvider.cs

@@ -7,6 +7,7 @@ using System;
 using System.Collections.Generic;
 using System.Linq;
 using System.Text;
+using System.Threading.Tasks;
 
 namespace BotSharp.Plugin.SemanticKernel
 {
@@ -20,29 +21,27 @@ namespace BotSharp.Plugin.SemanticKernel
         /// <summary>
         /// Constructor of <see cref="SemanticKernelTextEmbeddingProvider"/>
         /// </summary>
-        /// <param name="kernel"></param>
         public SemanticKernelTextEmbeddingProvider(ITextEmbeddingGeneration embedding, int dimension)
         {
             this._embedding = embedding;
             Dimension = dimension;
         }
 
+        /// <inheritdoc/>
         public int Dimension { get; }
 
-        public float[] GetVector(string text)
+        /// <inheritdoc/>
+        public async Task<float[]> GetVectorAsync(string text)
         {
-            return this._embedding.GenerateEmbeddingAsync(text)
-                .ConfigureAwait(false)
-                .GetAwaiter()
-                .GetResult()
-                .ToArray();
+            return (await this._embedding.GenerateEmbeddingAsync(text)).ToArray();
         }
 
-        public List<float[]> GetVectors(List<string> texts)
+        /// <inheritdoc/>
+        public async Task<List<float[]>> GetVectorsAsync(List<string> texts)
         {
-            return this._embedding.GenerateEmbeddingsAsync(texts).ConfigureAwait(false).GetAwaiter().GetResult()
-                .Select(_ => _.ToArray())
-                .ToList();
+            var embeddings = await this._embedding.GenerateEmbeddingsAsync(texts);
+            return embeddings.Select(_ => _.ToArray())
+                             .ToList();
         }
     }
 }

tests/BotSharp.Plugin.SemanticKernel.UnitTests/Helpers/SemanticKernelHelper.cs

@@ -12,6 +12,7 @@ namespace BotSharp.Plugin.SemanticKernel.UnitTests.Helpers
 {
     internal class SemanticKernelHelper : IChatCompletion, ITextCompletion, IAIService
     {
+        private Dictionary<string, string> _attributes = new();
         private readonly string _excepted;
 
         public SemanticKernelHelper(string excepted)
@@ -19,6 +20,8 @@ namespace BotSharp.Plugin.SemanticKernel.UnitTests.Helpers
             this._excepted = excepted;
         }
 
+        public IReadOnlyDictionary<string, string> Attributes => _attributes;
+
         public ChatHistory CreateNewChat(string? instructions = null)
         {
             return new ChatHistory();
@@ -26,7 +29,7 @@ namespace BotSharp.Plugin.SemanticKernel.UnitTests.Helpers
 
         public Task<IReadOnlyList<IChatResult>> GetChatCompletionsAsync(ChatHistory chat, AIRequestSettings? requestSettings = null, CancellationToken cancellationToken = default)
         {
-            return Task.FromResult<IReadOnlyList<IChatResult>>( new List<IChatResult> { new ResultHelper(_excepted) });
+            return Task.FromResult<IReadOnlyList<IChatResult>>(new List<IChatResult> { new ResultHelper(_excepted) });
         }
 
         public Task<IReadOnlyList<ITextResult>> GetCompletionsAsync(string text, AIRequestSettings? requestSettings = null, CancellationToken cancellationToken = default)