Update chat template dependencies, fix OpenAI/Aspire config, and address build warnings (#6280)

* Update chat template dependencies

* Update test snapshots

* Update Aspire version

* Revert Aspire + update CommunityToolkit.Aspire

* Open README in VS after project creation

* Add Known Issue to Aspire README for Qdrant

* Update survey template URL

* Set the Project Template package version to -preview.2

* Update template baseline

* Update template pinned versions

* Do not append template args to snapshot names

* Fix vector store index in the README. Add an AzureAISearch template test.

* Add a note to the Aspire README for trusting the development certificate

* Use AddOpenAIClient for OpenAI and AddAzureOpenAIClient for Azure OpenAI

* Remove duplicated using System.ClientModel

* Update Aspire README to specify the exception thrown for the known issue

* Augment the Aspire README for more Docker notes for Ollama and Qdrant

* Fix Microsoft.Extensions.Http.Resilience warnings with separate pinned versions

* Update test baseline for: Rename EmbeddingGeneratorExtensions.GenerateEmbedding extension methods (#6295)

* Add --managed-identity to the template developer README

* Apply the Ollama timeout recommendation in the template code

* Call http.RemoveAllResilienceHandlers before adding the handler

* Update template test baseline

---------

Co-authored-by: Jeff Handley <[email protected]>
Co-authored-by: David Cantu <[email protected]>

Author: 3 people

test/ProjectTemplates/Microsoft.Extensions.AI.Templates.IntegrationTests/Snapshots/aichatweb.OpenAI_AzureAISearch.verified/aichatweb/Services/SemanticSearch.cs

@@ -9,7 +9,7 @@ public class SemanticSearch(
 {
     public async Task<IReadOnlyList<SemanticSearchRecord>> SearchAsync(string text, string? filenameFilter, int maxResults)
     {
-        var queryEmbedding = await embeddingGenerator.GenerateEmbeddingVectorAsync(text);
+        var queryEmbedding = await embeddingGenerator.GenerateVectorAsync(text);
         var vectorCollection = vectorStore.GetCollection<string, SemanticSearchRecord>("data-aichatweb-ingested");
 
         var nearest = await vectorCollection.VectorizedSearchAsync(queryEmbedding, new VectorSearchOptions<SemanticSearchRecord>