Merge branch 'main' into py-openapi-param-fix

dotnet/samples/Demos/HomeAutomation/HomeAutomation.csproj

@@ -15,6 +15,7 @@
   </ItemGroup>
 
   <ItemGroup>
+    <ProjectReference Include="..\..\..\src\Connectors\Connectors.AzureOpenAI\Connectors.AzureOpenAI.csproj" />
     <ProjectReference Include="..\..\..\src\Connectors\Connectors.OpenAI\Connectors.OpenAI.csproj" />
     <ProjectReference Include="..\..\..\src\SemanticKernel.Abstractions\SemanticKernel.Abstractions.csproj" />
   </ItemGroup>

dotnet/samples/Demos/HomeAutomation/Options/AzureOpenAIOptions.cs

@@ -9,6 +9,8 @@ namespace HomeAutomation.Options;
 /// </summary>
 public sealed class AzureOpenAIOptions
 {
+    public const string SectionName = "AzureOpenAI";
+
     [Required]
     public string ChatDeploymentName { get; set; } = string.Empty;
 

dotnet/samples/Demos/HomeAutomation/Options/OpenAIOptions.cs

@@ -9,6 +9,8 @@ namespace HomeAutomation.Options;
 /// </summary>
 public sealed class OpenAIOptions
 {
+    public const string SectionName = "OpenAI";
+
     [Required]
     public string ChatModelId { get; set; } = string.Empty;
 

dotnet/samples/Demos/HomeAutomation/Program.cs

@@ -13,11 +13,15 @@ Example that demonstrates how to use Semantic Kernel in conjunction with depende
 
 using HomeAutomation.Options;
 using HomeAutomation.Plugins;
+using Microsoft.Extensions.Configuration;
 using Microsoft.Extensions.DependencyInjection;
 using Microsoft.Extensions.Hosting;
 using Microsoft.Extensions.Options;
 using Microsoft.SemanticKernel;
 using Microsoft.SemanticKernel.ChatCompletion;
+// For Azure OpenAI configuration
+#pragma warning disable IDE0005 // Using directive is unnecessary.
+using Microsoft.SemanticKernel.Connectors.AzureOpenAI;
 using Microsoft.SemanticKernel.Connectors.OpenAI;
 
 namespace HomeAutomation;
@@ -27,30 +31,40 @@ internal static class Program
     internal static async Task Main(string[] args)
     {
         HostApplicationBuilder builder = Host.CreateApplicationBuilder(args);
+        builder.Configuration.AddUserSecrets<Worker>();
 
         // Actual code to execute is found in Worker class
         builder.Services.AddHostedService<Worker>();
 
         // Get configuration
+        builder.Services.AddOptions<OpenAIOptions>()
+                        .Bind(builder.Configuration.GetSection(OpenAIOptions.SectionName))
+                        .ValidateDataAnnotations()
+                        .ValidateOnStart();
+
+        /* Alternatively, you can use plain, Azure OpenAI after loading AzureOpenAIOptions instead  of OpenAI
+        
         builder.Services.AddOptions<AzureOpenAIOptions>()
-                        .Bind(builder.Configuration.GetSection(nameof(AzureOpenAIOptions)))
+                        .Bind(builder.Configuration.GetSection(AzureOpenAIOptions.SectionName))
                         .ValidateDataAnnotations()
                         .ValidateOnStart();
+        */
 
         // Chat completion service that kernels will use
         builder.Services.AddSingleton<IChatCompletionService>(sp =>
         {
-            OpenAIOptions options = sp.GetRequiredService<IOptions<OpenAIOptions>>().Value;
+            OpenAIOptions openAIOptions = sp.GetRequiredService<IOptions<OpenAIOptions>>().Value;
 
             // A custom HttpClient can be provided to this constructor
-            return new OpenAIChatCompletionService(options.ChatModelId, options.ApiKey);
+            return new OpenAIChatCompletionService(openAIOptions.ChatModelId, openAIOptions.ApiKey);
 
             /* Alternatively, you can use plain, Azure OpenAI after loading AzureOpenAIOptions instead
                of OpenAI options with builder.Services.AddOptions:
+            
+            AzureOpenAIOptions azureOpenAIOptions  = sp.GetRequiredService<IOptions<AzureOpenAIOptions>>().Value;
+            return new AzureOpenAIChatCompletionService(azureOpenAIOptions.ChatDeploymentName, azureOpenAIOptions.Endpoint, azureOpenAIOptions.ApiKey);
 
-            AzureOpenAIOptions options = sp.GetRequiredService<IOptions<AzureOpenAI>>().Value;
-
-            return new AzureOpenAIChatCompletionService(options.ChatDeploymentName, options.Endpoint, options.ApiKey); */
+            */
         });
 
         // Add plugins that can be used by kernels

dotnet/src/Connectors/Connectors.HuggingFace/HuggingFacePromptExecutionSettings.cs

@@ -10,6 +10,7 @@ namespace Microsoft.SemanticKernel.Connectors.HuggingFace;
 /// <summary>
 /// HuggingFace Execution Settings.
 /// </summary>
+[JsonNumberHandling(JsonNumberHandling.AllowReadingFromString)]
 public sealed class HuggingFacePromptExecutionSettings : PromptExecutionSettings
 {
     /// <summary>

dotnet/src/Connectors/Connectors.Ollama/Settings/OllamaPromptExecutionSettings.cs

@@ -11,6 +11,7 @@ namespace Microsoft.SemanticKernel.Connectors.Ollama;
 /// <summary>
 /// Ollama Prompt Execution Settings.
 /// </summary>
+[JsonNumberHandling(JsonNumberHandling.AllowReadingFromString)]
 public sealed class OllamaPromptExecutionSettings : PromptExecutionSettings
 {
     /// <summary>

dotnet/src/Connectors/Connectors.OpenAI/Settings/OpenAIAudioToTextExecutionSettings.cs

@@ -12,6 +12,7 @@ namespace Microsoft.SemanticKernel.Connectors.OpenAI;
 /// Execution settings for OpenAI audio-to-text request.
 /// </summary>
 [Experimental("SKEXP0010")]
+[JsonNumberHandling(JsonNumberHandling.AllowReadingFromString)]
 public sealed class OpenAIAudioToTextExecutionSettings : PromptExecutionSettings
 {
     /// <summary>

dotnet/src/Connectors/Connectors.OpenAI/Settings/OpenAITextToAudioExecutionSettings.cs

@@ -12,6 +12,7 @@ namespace Microsoft.SemanticKernel.Connectors.OpenAI;
 /// Execution settings for OpenAI text-to-audio request.
 /// </summary>
 [Experimental("SKEXP0001")]
+[JsonNumberHandling(JsonNumberHandling.AllowReadingFromString)]
 public sealed class OpenAITextToAudioExecutionSettings : PromptExecutionSettings
 {
     /// <summary>

python/semantic_kernel/data/vector_storage/vector_store_record_collection.py

@@ -518,10 +518,10 @@ def _serialize_data_model_to_dict(self, record: TModel, **kwargs: Any) -> OneOrM
         """
         if self.data_model_definition.to_dict:
             return self.data_model_definition.to_dict(record, **kwargs)
-        if isinstance(record, BaseModel):
-            return self._serialize_vectors(record.model_dump())
         if isinstance(record, ToDictMethodProtocol):
             return self._serialize_vectors(record.to_dict())
+        if isinstance(record, BaseModel):
+            return self._serialize_vectors(record.model_dump())
 
         store_model = {}
         for field_name in self.data_model_definition.field_names:
@@ -611,14 +611,14 @@ def _deserialize_dict_to_data_model(self, record: OneOrMany[dict[str, Any]], **k
                     "Cannot deserialize multiple records to a single record unless you are using a container."
                 )
             record = record[0]
-        if issubclass(self.data_model_type, BaseModel):
-            if include_vectors:
-                record = self._deserialize_vector(record)
-            return self.data_model_type.model_validate(record)  # type: ignore
         if func := getattr(self.data_model_type, "from_dict", None):
             if include_vectors:
                 record = self._deserialize_vector(record)
             return func(record)
+        if issubclass(self.data_model_type, BaseModel):
+            if include_vectors:
+                record = self._deserialize_vector(record)
+            return self.data_model_type.model_validate(record)  # type: ignore
         data_model_dict: dict[str, Any] = {}
         for field_name in self.data_model_definition.fields:
             if not include_vectors and field_name in self.data_model_definition.vector_field_names: