Allow passing custom HttpClient (microsoft#743)

### Motivation and Context
My company network needs more custom set up in HttpClient to make calls,
but SK OpenAI code only allows me to pass a hander delegate factory. I
cannot use SK without more settings in HttpClient and I want to pass in
my own instances anyway so I can manage them from my application.

I think I am not the only one to need this:
 - microsoft#527
 - microsoft#133

See
https://learn.microsoft.com/en-us/dotnet/fundamentals/networking/http/httpclient-guidelines.

### Description
Changes included:
- The OpenAI and AzureOpenAI connectors take optional HttpClient? in the
constructor methods instead of IDelegatingHandlerFactory
- Note first approach was adding two new constructor methods to each
type so you could choose. But two constructors could not be there
together with optional HttpClient? in one and optional
IDelegatingHandlerFactory? in the other because it made calls ambiguous.
Then I tried making HttpClient not optional, but that made the parameter
order different because in some there are also other optional parameters
like openai `string? organization = null`. So the not optional
HttpClient would have to come BEFORE optional openai organization in one
constructor, but the optional IDelegatingHandlerFactory comes AFTER
optional openai organization in another constructor. In the end it
seemed better to just take HttpClient and do the custom client creation
in the extension methods. I hope this is okay I know it is a bigger
change than I planned.
- IDelegatingHandlerFactory is not being used as a factory in these Open
AI connector classes anyway. They use it one to create an HttpClient
instance in the constructor method anyway and never call it again so
it's just as easy to pass in the HttpClient you want.
- Updated the extension methods in `KernelConfigOpenAIExtensions` so
that they can optionally pass in a custom HttpClient and ILogger. If
null then it uses the same defaults as before.
- There was some mix use of `Logger log` and `ILogger logger` in
different places so on the parts I changed I set these all to "logger"
because it makes it more clear that it is a object and not a "log"
method. I can undo if you don't like this.
- Changed "credentials" to "credential" to match this is one
`TokenCredenial` not a credential collection. I can undo if you don't
like this.
- Made the default HttpClientHandler static and shared for new
HttpClients with `disposeHandler: false`
dotnet/runtime#16255
 - Updated a sample Program
 - I can add more tests if required

### Contribution Checklist
<!-- Before submitting this PR, please make sure: -->
- [X] The code builds clean without any errors or warnings
- [X] The PR follows SK Contribution Guidelines
(https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
- [X] The code follows the .NET coding conventions
(https://learn.microsoft.com/dotnet/csharp/fundamentals/coding-style/coding-conventions)
verified with `dotnet format`
- [X] All unit tests pass, and I have added new tests where possible
- Most tests pass but it skips some because I don't have keys for all
these model types so I hope your github build will run this and double
check.
- [ ] I didn't break anyone 😄
- I changed the constructor method args in the OpenAI code, and the will
break your users that are creating these open ai classes using their
constructors directly. If the users are using the extension methods
(AddAzureOpenAI) then they should not have problems.
- If you want I can put back all of the constructor methods so they can
be created with HttpClient or IDelegatingHandlerFactory but with
parameters orders different as explained
- I don't think those classes need to be aware of
IDelegatingHandlerFactory or have it included in the constructor
methods, since the extension method or calling code can always convert
to HttpClient before calling.

samples/apps/copilot-chat-app/webapi/SemanticKernelExtensions.cs

@@ -8,7 +8,6 @@
 using Microsoft.SemanticKernel.Connectors.AI.OpenAI.TextEmbedding;
 using Microsoft.SemanticKernel.Connectors.Memory.Qdrant;
 using Microsoft.SemanticKernel.Memory;
-using Microsoft.SemanticKernel.Reliability;
 using Microsoft.SemanticKernel.SkillDefinition;
 using Microsoft.SemanticKernel.TemplateEngine;
 using SemanticKernel.Service.Config;
@@ -66,7 +65,7 @@ internal static IServiceCollection AddSemanticKernelServices(this IServiceCollec
             => new SemanticTextMemory(
                 serviceProvider.GetRequiredService<IMemoryStore>(),
                 serviceProvider.GetRequiredService<IOptionsSnapshot<AIServiceOptions>>().Get(AIServiceOptions.EmbeddingPropertyName)
-                    .ToTextEmbeddingsService(serviceProvider.GetRequiredService<ILogger<AIServiceOptions>>())));
+                    .ToTextEmbeddingsService(logger: serviceProvider.GetRequiredService<ILogger<AIServiceOptions>>())));
 
         // Add the planner.
         services.AddScoped<CopilotChatPlanner>(sp =>
@@ -157,21 +156,27 @@ internal static KernelConfig AddEmbeddingBackend(this KernelConfig kernelConfig,
     /// <summary>
     /// Construct IEmbeddingGeneration from <see cref="AIServiceOptions"/>
     /// </summary>
+    /// <param name="serviceConfig">The service configuration</param>
+    /// <param name="httpClient">Custom <see cref="HttpClient"/> for HTTP requests.</param>
+    /// <param name="logger">Application logger</param>
     internal static IEmbeddingGeneration<string, float> ToTextEmbeddingsService(this AIServiceOptions serviceConfig,
-        ILogger? logger = null,
-        IDelegatingHandlerFactory? handlerFactory = null)
+        HttpClient? httpClient = null,
+        ILogger? logger = null)
     {
         return serviceConfig.AIService switch
         {
             AIServiceOptions.AIServiceType.AzureOpenAI => new AzureTextEmbeddingGeneration(
                 serviceConfig.DeploymentOrModelId,
                 serviceConfig.Endpoint,
                 serviceConfig.Key,
-                handlerFactory: handlerFactory,
-                log: logger),
+                httpClient: httpClient,
+                logger: logger),
 
             AIServiceOptions.AIServiceType.OpenAI => new OpenAITextEmbeddingGeneration(
-                serviceConfig.DeploymentOrModelId, serviceConfig.Key, handlerFactory: handlerFactory, log: logger),
+                serviceConfig.DeploymentOrModelId,
+                serviceConfig.Key,
+                httpClient: httpClient,
+                logger: logger),
 
             _ => throw new ArgumentException("Invalid AIService value in embeddings backend settings"),
         };