Merge pull request #83 from Encamina/@apicazo/add-named-memory-providers

Add KeyedNamed services

CHANGELOG.md

@@ -56,6 +56,7 @@ Previous classification is not required if changes are simple or all belong to t
 - Changes in the prompt of `QuestionAnsweringPlugin` to enhance language detection in the response.
 - Slight improvement in the `DeleteAsync` method in `CosmosRepository`.
 - Some boy scouting and typo fixes in comments.
+- Added new extension method to add Qdrant and Azure Search AI as Keyed Memory Store.
 
 ## [8.1.4]
 

Directory.Build.props

@@ -17,7 +17,7 @@
 
   <PropertyGroup>
     <VersionPrefix>8.1.5</VersionPrefix>
-    <VersionSuffix>preview-03</VersionSuffix>
+    <VersionSuffix>preview-04</VersionSuffix>
   </PropertyGroup>
 
   <!--

src/Encamina.Enmarcha.SemanticKernel.Connectors.Memory/Extensions/IServiceCollectionExtensions.cs

@@ -106,4 +106,71 @@ public static IServiceCollection AddSemanticTextMemory(this IServiceCollection s
                 .Build();
         });
     }
+
+    /// <summary>
+    /// Adds Azure AI Search as a named vector database for a memory store (<see cref="IMemoryStore"/>) to the <see cref="IServiceCollection"/> as a singleton service.
+    /// </summary>
+    /// <remarks>
+    /// This extension methods requires a <see cref="AzureAISearchOptions"/> to be already configured.
+    /// </remarks>
+    /// <param name="services"> The <see cref="IServiceCollection"/> to add services to.</param>
+    /// <param name="memoryProviderName">The name or key for the memory provider.</param>
+    /// <returns>The <see cref="IServiceCollection"/> so that additional calls can be chained.</returns>
+    public static IServiceCollection AddAzureAISearchNamedMemoryStore(this IServiceCollection services, string memoryProviderName)
+    {
+        return services.AddKeyedSingleton<IMemoryStore>(memoryProviderName, (serviceProvider, _) =>
+        {
+            var optionsMonitor = serviceProvider.GetRequiredService<IOptionsMonitor<AzureAISearchOptions>>();
+
+            static AzureAISearchMemoryStore Builder(AzureAISearchOptions options)
+            {
+                return new AzureAISearchMemoryStore(options.Endpoint.AbsoluteUri, options.Key);
+            }
+
+            var debouncedBuilder = Debouncer.Debounce<AzureAISearchOptions>(options => Builder(options), 300);
+
+            var memory = Builder(optionsMonitor.CurrentValue);
+
+            optionsMonitor.OnChange(debouncedBuilder);
+
+            return memory;
+        });
+    }
+
+    /// <summary>
+    /// Adds Qdrant vector database as a named memory store (<see cref="IMemoryStore"/>) to the <see cref="IServiceCollection"/> as a singleton service.
+    /// </summary>
+    /// <remarks>
+    /// This extension methods requires a <see cref="QdrantOptions"/> to be already configured.
+    /// </remarks>
+    /// <param name="services"> The <see cref="IServiceCollection"/> to add services to.</param>
+    /// <param name="memoryProviderName">The name or key for the memory provider.</param>
+    /// <returns>The <see cref="IServiceCollection"/> so that additional calls can be chained.</returns>
+    public static IServiceCollection AddQdrantNamedMemoryStore(this IServiceCollection services, string memoryProviderName)
+    {
+        return services.AddKeyedSingleton<IMemoryStore>(memoryProviderName, (serviceProvider, _) =>
+        {
+            var optionsMonitor = serviceProvider.GetRequiredService<IOptionsMonitor<QdrantOptions>>();
+
+            var httpClient = new HttpClient(new HttpClientHandler()
+            {
+                CheckCertificateRevocationList = true,
+            }, disposeHandler: false);
+
+            static QdrantMemoryStore Builder(IServiceProvider serviceProvider, HttpClient httpClient, QdrantOptions options)
+            {
+                httpClient.ConfigureHttpClientForQdrant(options);
+
+                return new QdrantMemoryStore(httpClient, options.VectorSize, loggerFactory: serviceProvider.GetService<ILoggerFactory>());
+            }
+
+            var debouncedBuilder = Debouncer.Debounce<QdrantOptions>(options => Builder(serviceProvider, httpClient, options), 300);
+
+            var memory = Builder(serviceProvider, httpClient, optionsMonitor.CurrentValue);
+
+            optionsMonitor.OnChange(debouncedBuilder);
+
+            return memory;
+        });
+    }
 }

src/Encamina.Enmarcha.SemanticKernel.Connectors.Memory/README.md

@@ -20,7 +20,7 @@ First, [install NuGet](http://docs.nuget.org/docs/start-here/installing-nuget).
 
 ## How to use
 
-First, you need to add the [QdrantOptions](../Encamina.Enmarcha.Data.Qdrant.Abstractions/QdrantOptions.cs) to your project configuration. You can achieve this by using any [configuration provider](https://learn.microsoft.com/en-us/dotnet/core/extensions/configuration). The followng code is an example of how the settings would appear using the `appsettings.json` file:
+First, if you want use Qdrant memory provider you need to add the [QdrantOptions](../Encamina.Enmarcha.Data.Qdrant.Abstractions/QdrantOptions.cs) to your project configuration. You can achieve this by using any [configuration provider](https://learn.microsoft.com/en-us/dotnet/core/extensions/configuration). The followng code is an example of how the settings would appear using the `appsettings.json` file:
 
 ```json
 // ...
@@ -33,6 +33,21 @@ First, you need to add the [QdrantOptions](../Encamina.Enmarcha.Data.Qdrant.Abst
 // ...
 ```
 
+If you want to use Azure AI Search as a memory provider, you need to add the [AzureSearchOptions](../Encamina.Enmarcha.Data.AzureAISearch.Abstractions/AzureAISearchOptions.cs) to your project configuration. You can achieve this by using any [configuration provider](https://learn.microsoft.com/en-us/dotnet/core/extensions/configuration). The following code is an example of how the settings would appear using the `appsettings.json` file:
+
+```json
+// ...
+  "AzureSearchOptions": {
+    "Endpoint": "https://sample-searchendpoint/", // Endpoint
+    "Key": "xxxxxxxxxx" // API Key used by Azure Search AI as a form of client authentication.
+  },
+// ...
+```
+
+
+```json
+
+
 Next, in `Program.cs` or a similar entry point file in your project, add the following code:
 
 ```csharp
@@ -53,8 +68,23 @@ builder.Services.AddOptions<QdrantOptions>().Bind(builder.Configuration.GetSecti
 
 // Adds Qdrant as IMemoryStore
 services.AddQdrantMemoryStore();
+
+// Or adds Azure AI Search as IMemoryStore
+services.AddAzureAISearchMemoryStore();
+
+```
+
+If you need add both memory providers, you can use the following code:
+
+```csharp
+
+
+   services.AddAzureAISearchNamedMemoryStore("AzureAISearchMemoryStore");  //AzureAISearchMemoryStore is the name of the memory store that you can use in the future to inject the IMemoryStore
+   services.AddQdrantNamedMemoryStore("QdrantMemoryStore"); //QdrantMemoryStore is the name of the memory store that you can use in the future to inject the IMemoryStore
+
 ```
 
+
 In the previous code, it can be observed that in the first part is necessary to add certain [Qdrant configurations](../Encamina.Enmarcha.Data.Qdrant.Abstractions/QdrantOptions.cs) that are available in the [Encamina.Enmarcha.Data.Qdrant.Abstractions](../Encamina.Enmarcha.Data.Qdrant.Abstractions/README.md) nuget package. The last line of code corresponds to an extension method that will add the specified implementation of the [IMemoryStore](https://github.com/microsoft/semantic-kernel/blob/76db027273371ea81e6db66afcb1d888cc53b459/dotnet/src/SemanticKernel.Abstractions/Memory/IMemoryStore.cs#L13) interface as a singleton. With this, you have Qdrant configured as the storage to save and retrieve embeddings.
 
 After the initial configuration, we typically configure Semantic Kernel as `Scoped`.
@@ -114,4 +144,31 @@ public class MyClass
             .ToListAsync(); // ToListAsync method is provided by System.Linq.Async nuget https://www.nuget.org/packages/System.Linq.Async
     }
 }
+```
+
+
+If use NamedKeys, you can use the following code:
+
+```csharp
+
+    internal class YourClassWithAzureSearch 
+    {
+        private readonly Kernel kernel;
+
+        public YourClass([FromKeyedServices("Your Provider Name , fe: 'AzureAISearchMemoryStore'")]Kernel kernel)
+        {
+            this.kernel = kernel;
+        }
+    }
+
+    internal class YourClassWithQdrant
+    {
+        private readonly Kernel kernel;
+
+        public YourClass([FromKeyedServices("Your Provider Name , fe: 'QdrantMemoryStore'")]Kernel kernel)
+        {
+            this.kernel = kernel;
+        }
+    }
+
 ```