feat: Refactor providers (#131)

* refactor: Moved provider abstractions to separate package.

* feat: Converted OpenAI provider.

* feat: Converted Ollama.

* feat: Implemented LLamaSharp.

* feat: Implemented LeonardoAi.

* feat: Implemented HuggingFace.

* feat: Implemented Google.

* feat: Implemented Settings.Calculate for OpenAI.

* feat: Implemented Automatic1111.

* feat: Implemented Anyscale.

* feat: Implemented Azure.

* feat: Implemented Anthropic.

* fix: Fixed WithDebugExtensions.

* fix: Small fixes.

* test: Fixed some tests.

* feat: Adapted other code to new changes.

* feat: Implemented Bedrock.

* fix: Small fixes.

* fix: Fixed conflicts.

* feat: Added new Amazon Bedrock implementations.

* feat: Adapted Amazon.SageMaker.

* fix: Models constructors now require provider.

* fix: Removed unused FileMemory example.

LangChain.sln

@@ -172,13 +172,13 @@ Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "LangChain.Providers.Automat
 EndProject
 Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "LangChain.Providers.Automatic1111.IntegrationTests", "src\tests\LangChain.Providers.Automatic1111.IntegrationTests\LangChain.Providers.Automatic1111.IntegrationTests.csproj", "{A6CF79BC-8365-46E8-9230-1A4AD615D40B}"
 EndProject
-Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "LangChain.Providers.Bedrock", "src\libs\Providers\LangChain.Providers.Bedrock\LangChain.Providers.Bedrock.csproj", "{67985CCB-F606-41F8-9D36-513459F58882}"
+Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "LangChain.Providers.Abstractions", "src\libs\Providers\LangChain.Providers.Abstractions\LangChain.Providers.Abstractions.csproj", "{628DDC9D-28A1-4C2F-BA13-171BD8CF711C}"
 EndProject
-Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "LangChain.Providers.Amazon.Bedrock", "src\libs\Providers\LangChain.Providers.Amazon.Bedrock\LangChain.Providers.Amazon.Bedrock.csproj", "{67985CCB-F606-41F8-9D36-513459F58882}"
+Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "LangChain.Providers.Amazon.Bedrock.IntegrationTests", "src\tests\LangChain.Providers.Amazon.Bedrock.IntegrationTests\LangChain.Providers.Amazon.Bedrock.IntegrationTests.csproj", "{73C76E80-95C5-4C96-A319-4F32043C903E}"
 EndProject
-Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "LangChain.Providers.Amazon.SageMaker", "src\libs\Providers\LangChain.Providers.Amazon.Sagemaker\LangChain.Providers.Amazon.SageMaker.csproj", "{F1AD6925-219C-4B17-B8D8-0ACCA6F401C4}"
+Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "LangChain.Providers.Amazon.Bedrock", "src\libs\Providers\LangChain.Providers.Amazon.Bedrock\LangChain.Providers.Amazon.Bedrock.csproj", "{67985CCB-F606-41F8-9D36-513459F58882}"
 EndProject
-Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "LangChain.Providers.Bedrock.IntegrationTests", "src\tests\LangChain.Providers.Bedrock.IntegrationTests\LangChain.Providers.Bedrock.IntegrationTests.csproj", "{4F37D6C5-38C9-485B-AD87-2691EED225E1}"
+Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "LangChain.Providers.Amazon.SageMaker", "src\libs\Providers\LangChain.Providers.Amazon.Sagemaker\LangChain.Providers.Amazon.SageMaker.csproj", "{534CEFB8-AA11-43A2-9A38-4F6D3A6633AB}"
 EndProject
 Global
 	GlobalSection(SolutionConfigurationPlatforms) = preSolution
@@ -410,22 +410,22 @@ Global
 		{A6CF79BC-8365-46E8-9230-1A4AD615D40B}.Debug|Any CPU.Build.0 = Debug|Any CPU
 		{A6CF79BC-8365-46E8-9230-1A4AD615D40B}.Release|Any CPU.ActiveCfg = Release|Any CPU
 		{A6CF79BC-8365-46E8-9230-1A4AD615D40B}.Release|Any CPU.Build.0 = Release|Any CPU
-		{BA701280-0BEB-4DA4-92B3-9C777082C2AF}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
-		{BA701280-0BEB-4DA4-92B3-9C777082C2AF}.Debug|Any CPU.Build.0 = Debug|Any CPU
-		{BA701280-0BEB-4DA4-92B3-9C777082C2AF}.Release|Any CPU.ActiveCfg = Release|Any CPU
-		{BA701280-0BEB-4DA4-92B3-9C777082C2AF}.Release|Any CPU.Build.0 = Release|Any CPU
+		{628DDC9D-28A1-4C2F-BA13-171BD8CF711C}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{628DDC9D-28A1-4C2F-BA13-171BD8CF711C}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{628DDC9D-28A1-4C2F-BA13-171BD8CF711C}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{628DDC9D-28A1-4C2F-BA13-171BD8CF711C}.Release|Any CPU.Build.0 = Release|Any CPU
+		{73C76E80-95C5-4C96-A319-4F32043C903E}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{73C76E80-95C5-4C96-A319-4F32043C903E}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{73C76E80-95C5-4C96-A319-4F32043C903E}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{73C76E80-95C5-4C96-A319-4F32043C903E}.Release|Any CPU.Build.0 = Release|Any CPU
 		{67985CCB-F606-41F8-9D36-513459F58882}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
 		{67985CCB-F606-41F8-9D36-513459F58882}.Debug|Any CPU.Build.0 = Debug|Any CPU
 		{67985CCB-F606-41F8-9D36-513459F58882}.Release|Any CPU.ActiveCfg = Release|Any CPU
 		{67985CCB-F606-41F8-9D36-513459F58882}.Release|Any CPU.Build.0 = Release|Any CPU
-		{F1AD6925-219C-4B17-B8D8-0ACCA6F401C4}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
-		{F1AD6925-219C-4B17-B8D8-0ACCA6F401C4}.Debug|Any CPU.Build.0 = Debug|Any CPU
-		{F1AD6925-219C-4B17-B8D8-0ACCA6F401C4}.Release|Any CPU.ActiveCfg = Release|Any CPU
-		{F1AD6925-219C-4B17-B8D8-0ACCA6F401C4}.Release|Any CPU.Build.0 = Release|Any CPU
-		{4F37D6C5-38C9-485B-AD87-2691EED225E1}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
-		{4F37D6C5-38C9-485B-AD87-2691EED225E1}.Debug|Any CPU.Build.0 = Debug|Any CPU
-		{4F37D6C5-38C9-485B-AD87-2691EED225E1}.Release|Any CPU.ActiveCfg = Release|Any CPU
-		{4F37D6C5-38C9-485B-AD87-2691EED225E1}.Release|Any CPU.Build.0 = Release|Any CPU
+		{534CEFB8-AA11-43A2-9A38-4F6D3A6633AB}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{534CEFB8-AA11-43A2-9A38-4F6D3A6633AB}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{534CEFB8-AA11-43A2-9A38-4F6D3A6633AB}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{534CEFB8-AA11-43A2-9A38-4F6D3A6633AB}.Release|Any CPU.Build.0 = Release|Any CPU
 	EndGlobalSection
 	GlobalSection(SolutionProperties) = preSolution
 		HideSolutionNode = FALSE
@@ -494,8 +494,10 @@ Global
 		{4913844F-74EC-4E74-AE8A-EA825569E6BA} = {E55391DE-F8F3-4CC2-A0E3-2406C76E9C68}
 		{BF4C7B87-0997-4208-84EF-D368DF7B9861} = {E55391DE-F8F3-4CC2-A0E3-2406C76E9C68}
 		{A6CF79BC-8365-46E8-9230-1A4AD615D40B} = {FDEE2E22-C239-4921-83B2-9797F765FD6A}
+		{628DDC9D-28A1-4C2F-BA13-171BD8CF711C} = {E55391DE-F8F3-4CC2-A0E3-2406C76E9C68}
+		{73C76E80-95C5-4C96-A319-4F32043C903E} = {FDEE2E22-C239-4921-83B2-9797F765FD6A}
 		{67985CCB-F606-41F8-9D36-513459F58882} = {E55391DE-F8F3-4CC2-A0E3-2406C76E9C68}
-		{4F37D6C5-38C9-485B-AD87-2691EED225E1} = {FDEE2E22-C239-4921-83B2-9797F765FD6A}
+		{534CEFB8-AA11-43A2-9A38-4F6D3A6633AB} = {E55391DE-F8F3-4CC2-A0E3-2406C76E9C68}
 	EndGlobalSection
 	GlobalSection(ExtensibilityGlobals) = postSolution
 		SolutionGuid = {5C00D0F1-6138-4ED9-846B-97E43D6DFF1C}

examples/LangChain.Samples.AspNet/Controllers/OpenAiSampleController.cs

@@ -1,17 +1,18 @@
 using LangChain.Providers.OpenAI;
 using Microsoft.AspNetCore.Mvc;
+using OpenAI.Constants;
 
 namespace LangChain.Samples.AspNet.Controllers;
 
 [ApiController]
 [Route("[controller]")]
 public class OpenAiSampleController : ControllerBase
 {
-    private readonly OpenAiModel _openAi;
+    private readonly OpenAiProvider _openAi;
     private readonly ILogger<OpenAiSampleController> _logger;
 
     public OpenAiSampleController(
-        OpenAiModel openAi,
+        OpenAiProvider openAi,
         ILogger<OpenAiSampleController> logger)
     {
         _openAi = openAi;
@@ -21,7 +22,8 @@ public OpenAiSampleController(
     [HttpGet(Name = "GetOpenAiResponse")]
     public async Task<string> Get()
     {
-        var response = await _openAi.GenerateAsync("What is a good name for a company that sells colourful socks?");
+        var llm = new OpenAiChatModel(_openAi, id: ChatModels.Gpt35Turbo);
+        var response = await llm.GenerateAsync("What is a good name for a company that sells colourful socks?");
 
         return response.LastMessageContent;
     }

examples/LangChain.Samples.Azure/Program.cs

@@ -1,9 +1,9 @@
-using LangChain.Providers;
-using LangChain.Providers.Azure;
+using LangChain.Providers.Azure;
 
-var model = new AzureOpenAIModel("AZURE_OPEN_AI_KEY", "ENDPOINT", "DEPLOYMENT_NAME");
+var provider = new AzureOpenAiProvider(apiKey: "AZURE_OPEN_AI_KEY", endpoint: "ENDPOINT");
+var llm = new AzureOpenAiChatModel(provider, id: "DEPLOYMENT_NAME");
 
-var result = await model.GenerateAsync("What is a good name for a company that sells colourful socks?");
+var result = await llm.GenerateAsync("What is a good name for a company that sells colourful socks?");
 
 Console.WriteLine(result);
 

examples/LangChain.Samples.HuggingFace/Program.cs

@@ -1,8 +1,9 @@
-using LangChain.Providers;
-using LangChain.Providers.HuggingFace;
+using LangChain.Providers.HuggingFace;
+using LangChain.Providers.HuggingFace.Predefined;
 
 using var client = new HttpClient();
-var gpt2Model = new Gpt2Model(apiKey: string.Empty, client);
+var provider = new HuggingFaceProvider(apiKey: string.Empty, client);
+var gpt2Model = new Gpt2Model(provider);
 
 var response = await gpt2Model.GenerateAsync("What would be a good company name be for name a company that makes colorful socks?");
 

examples/LangChain.Samples.Memory/Program.cs

@@ -2,6 +2,7 @@
 using LangChain.Providers;
 using LangChain.Providers.OpenAI;
 using System.Runtime.Serialization;
+using LangChain.Providers.OpenAI.Predefined;
 using static LangChain.Chains.Chain;
 
 internal class Program
@@ -13,7 +14,7 @@ private static async Task Main(string[] args)
             throw new InvalidOperationException("OPENAI_API_KEY environment variable is not found.");
 
         // Use a common, general-purpose LLM
-        var model = new OpenAiModel(apiKey, "gpt-3.5-turbo");
+        var model = new Gpt35TurboModel(apiKey);
 
         // Create a simple prompt template for the conversation to help the AI
         var template = @"

examples/LangChain.Samples.OpenAI/Program.cs

@@ -1,10 +1,9 @@
-using LangChain.Providers;
-using LangChain.Providers.OpenAI;
+using LangChain.Providers.OpenAI.Predefined;
 
 var apiKey =
     Environment.GetEnvironmentVariable("OPENAI_API_KEY") ??
     throw new InvalidOperationException("OPENAI_API_KEY environment variable is not found.");
-var model = new Gpt35TurboModel(apiKey: apiKey);
+var model = new Gpt35TurboModel(apiKey);
 
 var result = await model.GenerateAsync("What is a good name for a company that sells colourful socks?");
 

examples/LangChain.Samples.Prompts/Program.cs

@@ -1,6 +1,6 @@
 using LangChain.Chains.LLM;
 using LangChain.Prompts;
-using LangChain.Providers.OpenAI;
+using LangChain.Providers.OpenAI.Predefined;
 using LangChain.Schema;
 
 const string apiKey = "API-KEY";

examples/LangChain.Samples.SequentialChain/Program.cs

@@ -1,7 +1,8 @@
-using LangChain.Chains.LLM;
+using LangChain.Abstractions.Chains.Base;
+using LangChain.Chains.LLM;
 using LangChain.Chains.Sequentials;
 using LangChain.Prompts;
-using LangChain.Providers.OpenAI;
+using LangChain.Providers.OpenAI.Predefined;
 using LangChain.Schema;
 
 using var httpClient = new HttpClient();
@@ -22,7 +23,7 @@
 var chainTwo = new LlmChain(new LlmChainInput(llm, secondPrompt));
 
 var overallChain = new SequentialChain(new SequentialChainInput(
-    new[]
+    new IChain[]
     {
         chainOne,
         chainTwo

src/Directory.Packages.props

@@ -48,6 +48,7 @@
     <PackageVersion Include="StackExchange.Redis" Version="2.7.4" />
     <PackageVersion Include="System.Net.Http" Version="4.3.4" />
     <PackageVersion Include="System.Text.Json" Version="8.0.0" />
+    <PackageVersion Include="System.ValueTuple" Version="4.5.0" />
     <PackageVersion Include="Tiktoken" Version="1.1.3" />
     <PackageVersion Include="tryAGI.OpenAI" Version="2.0.0-alpha.9" />
     <PackageVersion Include="Microsoft.Extensions.DependencyInjection.Abstractions" Version="8.0.0" />

src/libs/Databases/LangChain.Databases.Chroma/ChromaVectorStore.cs

@@ -1,7 +1,7 @@
 using System.Text.Json;
-using LangChain.Abstractions.Embeddings.Base;
 using LangChain.Common.Converters;
 using LangChain.Docstore;
+using LangChain.Providers;
 using LangChain.VectorStores;
 using Microsoft.SemanticKernel.AI.Embeddings;
 using Microsoft.SemanticKernel.Connectors.Memory.Chroma;
@@ -31,7 +31,7 @@ public class ChromaVectorStore : VectorStore
     public ChromaVectorStore(
         HttpClient httpClient,
         string endpoint,
-        IEmbeddings embeddings,
+        IEmbeddingModel embeddings,
         string collectionName = LangchainDefaultCollectionName)
         : base(embeddings)
     {
@@ -166,8 +166,8 @@ public override async Task<IEnumerable<Document>> SimilaritySearchByVectorAsync(
         int k = 4,
         CancellationToken cancellationToken = default)
     {
-        var embeddings = await Embeddings
-            .EmbedQueryAsync(query, cancellationToken)
+        var embeddings = await EmbeddingModel
+            .CreateEmbeddingsAsync(query, null, cancellationToken)
             .ConfigureAwait(false);
 
         var documentsWithScores = await SimilaritySearchByVectorWithAsync(embeddings, k, cancellationToken).ConfigureAwait(false);
@@ -192,8 +192,8 @@ public override async Task<IEnumerable<Document>> MaxMarginalRelevanceSearch(
         float lambdaMult = 0.5f,
         CancellationToken cancellationToken = default)
     {
-        var embeddings = await Embeddings
-            .EmbedQueryAsync(query, cancellationToken)
+        float[] embeddings = await EmbeddingModel
+            .CreateEmbeddingsAsync(query, null, cancellationToken)
             .ConfigureAwait(false);
 
         var documents = await MaxMarginalRelevanceSearchByVector(
@@ -251,8 +251,8 @@ private async Task<IEnumerable<string>> AddCoreAsync(
         string[] ids,
         CancellationToken cancellationToken)
     {
-        var embeddings = await Embeddings
-            .EmbedDocumentsAsync(texts, cancellationToken)
+        float[][] embeddings = await EmbeddingModel
+            .CreateEmbeddingsAsync(texts, null, cancellationToken)
             .ConfigureAwait(false);
 
         var records = new MemoryRecord[texts.Length];

src/libs/Databases/LangChain.Databases.InMemory/InMemoryVectorStore.cs

@@ -1,6 +1,6 @@
-using LangChain.Abstractions.Embeddings.Base;
-using LangChain.Docstore;
+using LangChain.Docstore;
 using LangChain.Indexes;
+using LangChain.Providers;
 using LangChain.TextSplitters;
 using LangChain.VectorStores;
 
@@ -15,7 +15,7 @@ namespace LangChain.Databases.InMemory;
 /// <param name="embeddings"></param>
 /// <param name="distanceMetrics"></param>
 public class InMemoryVectorStore(
-    IEmbeddings embeddings,
+    IEmbeddingModel embeddings,
     EDistanceMetrics distanceMetrics = EDistanceMetrics.Euclidean)
     : VectorStore(embeddings)
 {
@@ -33,7 +33,7 @@ public class InMemoryVectorStore(
     /// <param name="documents"></param>
     /// <returns></returns>
     public static async Task<VectorStoreIndexWrapper> CreateIndexFromDocuments(
-        IEmbeddings embeddings,
+        IEmbeddingModel embeddings,
         IReadOnlyCollection<Document> documents)
     {
         var vectorStore = new InMemoryVectorStore(embeddings);
@@ -51,9 +51,9 @@ public override async Task<IEnumerable<string>> AddDocumentsAsync(
     {
         var docs = documents.ToArray();
 
-        var embeddings = await Embeddings.EmbedDocumentsAsync(docs
+        float[][] embeddings = await EmbeddingModel.CreateEmbeddingsAsync(docs
             .Select(x => x.PageContent)
-            .ToArray(), cancellationToken).ConfigureAwait(false);
+            .ToArray(), cancellationToken: cancellationToken).ConfigureAwait(false);
         var ids = new List<string>();
         for (var i = 0; i < docs.Length; i++)
         {
@@ -98,9 +98,9 @@ public override async Task<IEnumerable<Document>> SimilaritySearchAsync(
         int k = 4,
         CancellationToken cancellationToken = default)
     {
-        var embedding = await Embeddings.EmbedQueryAsync(
+        float[] embedding = await EmbeddingModel.CreateEmbeddingsAsync(
             query,
-            cancellationToken).ConfigureAwait(false);
+            cancellationToken: cancellationToken).ConfigureAwait(false);
 
         return await SimilaritySearchByVectorAsync(
             embedding,
@@ -129,15 +129,14 @@ public override Task<IEnumerable<Document>> SimilaritySearchByVectorAsync(
         int k = 4,
         CancellationToken cancellationToken = default)
     {
-        var embedding = await Embeddings.EmbedQueryAsync(
+        float[] embedding = await EmbeddingModel.CreateEmbeddingsAsync(
             query,
-            cancellationToken).ConfigureAwait(false);
-        var arr = embedding.ToArray();
+            cancellationToken: cancellationToken).ConfigureAwait(false);
         var distances = _storage.Select(s =>
             new
             {
                 doc = s.doc,
-                distance = _distanceFunction(s.vec, arr)
+                distance = _distanceFunction(s.vec, embedding)
             }).Take(k);
 
         return distances.Select(d => new ValueTuple<Document, float>(d.doc, d.distance));

src/libs/Databases/LangChain.Databases.Postgres/PostgresVectorStore.cs

@@ -1,6 +1,6 @@
-using LangChain.Abstractions.Embeddings.Base;
 using LangChain.Databases.Postgres;
 using LangChain.Docstore;
+using LangChain.Providers;
 using LangChain.VectorStores;
 
 namespace LangChain.Databases;
@@ -25,12 +25,12 @@ public class PostgresVectorStore : VectorStore
     public PostgresVectorStore(
         string connectionString,
         int vectorSize,
-        IEmbeddings embeddings,
+        IEmbeddingModel embeddingModel,
         string schema = DefaultSchema,
         string collectionName = DefaultCollectionName,
         DistanceStrategy distanceStrategy = DistanceStrategy.Cosine,
         Func<float, float>? overrideRelevanceScoreFn = null)
-        : base(embeddings, overrideRelevanceScoreFn)
+        : base(embeddingModel, overrideRelevanceScoreFn)
     {
         _distanceStrategy = distanceStrategy;
         _collectionName = collectionName;
@@ -44,8 +44,10 @@ public override async Task<IEnumerable<string>> AddDocumentsAsync(
         CancellationToken cancellationToken = default)
     {
         var documentsArray = documents.ToArray();
-        var embeddings = await Embeddings
-            .EmbedDocumentsAsync(documentsArray.Select(d => d.PageContent).ToArray(), cancellationToken)
+        float[][] embeddings = await EmbeddingModel
+            .CreateEmbeddingsAsync(documentsArray
+                .Select(d => d.PageContent)
+                .ToArray(), null, cancellationToken)
             .ConfigureAwait(false);
 
         var ids = new string[documentsArray.Length];
@@ -75,8 +77,8 @@ public override async Task<IEnumerable<string>> AddTextsAsync(
         var textsArray = texts.ToArray();
         var metadatasArray = metadatas?.ToArray() ?? new Dictionary<string, object>?[textsArray.Length];
 
-        var embeddings = await Embeddings
-            .EmbedDocumentsAsync(textsArray, cancellationToken)
+        float[][] embeddings = await EmbeddingModel
+            .CreateEmbeddingsAsync(textsArray, null, cancellationToken)
             .ConfigureAwait(false);
 
         var ids = new string[textsArray.Length];
@@ -137,9 +139,11 @@ public override async Task<IEnumerable<Document>> SimilaritySearchByVectorAsync(
         string query, int k = 4,
         CancellationToken cancellationToken = default)
     {
-        var embedding = await Embeddings.EmbedQueryAsync(query, cancellationToken).ConfigureAwait(false);
+        float[] embedding = await EmbeddingModel.CreateEmbeddingsAsync(
+            query, null, cancellationToken).ConfigureAwait(false);
 
-        return await SimilaritySearchByVectorWithScoreAsync(embedding, k, cancellationToken)
+        return await SimilaritySearchByVectorWithScoreAsync(
+                embedding, k, cancellationToken)
             .ConfigureAwait(false);
     }
 
@@ -183,7 +187,7 @@ public override async Task<IEnumerable<Document>> MaxMarginalRelevanceSearch(
         int fetchK = 20, float lambdaMult = 0.5f,
         CancellationToken cancellationToken = default)
     {
-        var embedding = await Embeddings.EmbedQueryAsync(query, cancellationToken).ConfigureAwait(false);
+        float[] embedding = await EmbeddingModel.CreateEmbeddingsAsync(query, null, cancellationToken).ConfigureAwait(false);
 
         return await MaxMarginalRelevanceSearchByVector(embedding, k, fetchK, lambdaMult, cancellationToken)
             .ConfigureAwait(false);