Python: Bump agent-framework-devui to 1.0.0b260414 for release (#5259)

Update devui version and changelog for the streaming memory fix release.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

.github/workflows/dotnet-verify-samples.yml

@@ -48,7 +48,8 @@ jobs:
             .
             .github
             dotnet
-            workflow-samples
+            python
+            declarative-agents
 
       - name: Setup dotnet
         uses: actions/setup-dotnet@v5.2.0
@@ -63,6 +64,20 @@ jobs:
           tenant-id: ${{ secrets.AZURE_TENANT_ID }}
           subscription-id: ${{ secrets.AZURE_SUBSCRIPTION_ID }}
 
+      - name: Generate filtered solution
+        shell: pwsh
+        run: |
+          ./dotnet/eng/scripts/New-FilteredSolution.ps1 `
+            -Solution dotnet/agent-framework-dotnet.slnx `
+            -TargetFramework net10.0 `
+            -Configuration Debug `
+            -OutputPath dotnet/filtered.slnx `
+            -Verbose
+
+      - name: Build solution
+        shell: bash
+        run: dotnet build dotnet/filtered.slnx -f net10.0 --warnaserror
+
       - name: Run verify-samples
         id: verify
         working-directory: dotnet

.github/workflows/python-merge-tests.yml

@@ -115,12 +115,13 @@ jobs:
           -m "not integration"
           --timeout=120 --session-timeout=900 --timeout_method thread
           --retries 2 --retry-delay 5
+          --junitxml=pytest.xml
         working-directory: ./python
       - name: Surface failing tests
         if: always()
         uses: pmeier/pytest-results-action@v0.7.2
         with:
-          path: ./python/**.xml
+          path: ./python/pytest.xml
           summary: true
           display-options: fEX
           fail-on-empty: false
@@ -163,6 +164,7 @@ jobs:
           -n logical --dist worksteal
           --timeout=120 --session-timeout=900 --timeout_method thread
           --retries 2 --retry-delay 5
+          --junitxml=pytest.xml
         working-directory: ./python
       - name: Test OpenAI samples
         timeout-minutes: 10
@@ -173,7 +175,7 @@ jobs:
         if: always()
         uses: pmeier/pytest-results-action@v0.7.2
         with:
-          path: ./python/**.xml
+          path: ./python/pytest.xml
           summary: true
           display-options: fEX
           fail-on-empty: false
@@ -225,6 +227,7 @@ jobs:
           -n logical --dist worksteal
           --timeout=120 --session-timeout=900 --timeout_method thread
           --retries 2 --retry-delay 5
+          --junitxml=pytest.xml
         working-directory: ./python
       - name: Test Azure samples
         timeout-minutes: 10
@@ -235,7 +238,7 @@ jobs:
         if: always()
         uses: pmeier/pytest-results-action@v0.7.2
         with:
-          path: ./python/**.xml
+          path: ./python/pytest.xml
           summary: true
           display-options: fEX
           fail-on-empty: false
@@ -285,6 +288,7 @@ jobs:
           -n logical --dist worksteal
           --timeout=120 --session-timeout=900 --timeout_method thread
           --retries 2 --retry-delay 5
+          --junitxml=pytest.xml
         working-directory: ./python
       - name: Stop local MCP server
         if: always()
@@ -310,7 +314,7 @@ jobs:
         if: always()
         uses: pmeier/pytest-results-action@v0.7.2
         with:
-          path: ./python/**.xml
+          path: ./python/pytest.xml
           summary: true
           display-options: fEX
           fail-on-empty: false
@@ -375,12 +379,13 @@ jobs:
           -x
           --timeout=360 --session-timeout=900 --timeout_method thread
           --retries 2 --retry-delay 5
+          --junitxml=pytest.xml
         working-directory: ./python
       - name: Surface failing tests
         if: always()
         uses: pmeier/pytest-results-action@v0.7.2
         with:
-          path: ./python/**.xml
+          path: ./python/pytest.xml
           summary: true
           display-options: fEX
           fail-on-empty: false
@@ -430,12 +435,13 @@ jobs:
           -n logical --dist worksteal
           --timeout=120 --session-timeout=900 --timeout_method thread
           --retries 2 --retry-delay 5
+          --junitxml=pytest.xml
         working-directory: ./python
       - name: Surface failing tests
         if: always()
         uses: pmeier/pytest-results-action@v0.7.2
         with:
-          path: ./python/**.xml
+          path: ./python/pytest.xml
           summary: true
           display-options: fEX
           fail-on-empty: false
@@ -489,13 +495,13 @@ jobs:
           echo "Cosmos DB emulator did not become ready in time." >&2
           exit 1
       - name: Test with pytest (Cosmos integration)
-        run: uv run --directory packages/azure-cosmos poe integration-tests -n logical --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5
+        run: uv run --directory packages/azure-cosmos poe integration-tests -n logical --dist worksteal --timeout=120 --session-timeout=900 --timeout_method thread --retries 2 --retry-delay 5 --junitxml=pytest.xml
         working-directory: ./python
       - name: Surface failing tests
         if: always()
         uses: pmeier/pytest-results-action@v0.7.2
         with:
-          path: ./python/**.xml
+          path: ./python/pytest.xml
           summary: true
           display-options: fEX
           fail-on-empty: false

.github/workflows/python-tests.yml

@@ -40,7 +40,7 @@ jobs:
           UV_CACHE_DIR: /tmp/.uv-cache
       # Unit tests
       - name: Run all tests
-        run: uv run poe test -A
+        run: uv run poe test -A --junitxml=pytest.xml
         working-directory: ./python
 
       # Surface failing tests
@@ -48,7 +48,7 @@ jobs:
         if: always()
         uses: pmeier/pytest-results-action@v0.7.2
         with:
-          path: ./python/**.xml
+          path: ./python/pytest.xml
           summary: true
           display-options: fEX
           fail-on-empty: false

.gitignore

@@ -47,6 +47,8 @@ htmlcov/
 .cache
 nosetests.xml
 coverage.xml
+pytest.xml
+python-coverage.xml
 *.cover
 *.py,cover
 .hypothesis/

dotnet/.github/skills/verify-samples-tool/SKILL.md

@@ -9,9 +9,16 @@ The `verify-samples` project (`dotnet/eng/verify-samples/`) is an automated tool
 
 ## Running verify-samples
 
+**Important:** By default, samples must be pre-built before running verify-samples. Build the solution first, or pass `--build` to build samples during the run:
+
 ```bash
 cd dotnet
+dotnet build agent-framework-dotnet.slnx -f net10.0
+```
 
+Then run verify-samples:
+
+```bash
 # Run all samples across all categories
 dotnet run --project eng/verify-samples -- --log results.log --csv results.csv
 
@@ -24,6 +31,10 @@ dotnet run --project eng/verify-samples -- Agent_Step02_StructuredOutput Agent_S
 # Control parallelism (default 8)
 dotnet run --project eng/verify-samples -- --parallel 8 --log results.log
 
+# Build samples during run (skips the need for a prior build step)
+# This may cause build conflicts as multiple samples are built in parallel, so use with caution
+dotnet run --project eng/verify-samples -- --build --log results.log
+
 # Combine options
 dotnet run --project eng/verify-samples -- --category 03-workflows --parallel 4 --log results.log --csv results.csv --md results.md
 ```

dotnet/eng/verify-samples/AgentsSamples.cs

@@ -246,7 +246,7 @@ internal static class AgentsSamples
             ExpectedOutputDescription =
             [
                 "The output should contain information about both the current time and the weather in Seattle.",
-                "The weather information should reference the plugin result: cloudy with a high of 15°C.",
+                "The weather information should be similar to: cloudy with a high of 15°C. Exact phrasing may vary.",
                 "The output should not contain error messages or stack traces.",
             ],
         },
@@ -521,7 +521,7 @@ internal static class AgentsSamples
             OptionalEnvironmentVariables = ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
             ExpectedOutputDescription =
             [
-                "The output should demonstrate server-side conversation sessions with non-streaming and streaming turns.",
+                "The output should contain multiple joke responses showing a multi-turn conversation.",
                 "The output should not contain error messages or stack traces.",
             ],
         },

dotnet/eng/verify-samples/Program.cs

@@ -14,6 +14,9 @@
 //   dotnet run -- --log results.log                     # Write sequential log to file
 //   dotnet run -- --csv results.csv                     # Write CSV summary to file
 //   dotnet run -- --md results.md                       # Write Markdown summary to file
+//   dotnet run -- --build                                # Build samples during run (default: --no-build)
+// Note: By default, this tool expects sample build outputs to already exist.
+// Pre-build the solution before running, or pass --build to avoid missing build output failures.
 //
 // Required environment variables (for AI-powered samples):
 //   AZURE_OPENAI_ENDPOINT
@@ -63,7 +66,7 @@ try
     // Run all samples
     var reporter = new ConsoleReporter();
     var verifier = new SampleVerifier(chatClient);
-    var orchestrator = new VerificationOrchestrator(verifier, reporter, dotnetRoot, TimeSpan.FromMinutes(3), logWriter);
+    var orchestrator = new VerificationOrchestrator(verifier, reporter, dotnetRoot, TimeSpan.FromMinutes(3), logWriter, buildSamples: options.BuildSamples);
 
     var run = await orchestrator.RunAllAsync(options.Samples, options.MaxParallelism);
 

dotnet/eng/verify-samples/SampleRunner.cs

@@ -20,23 +20,32 @@ internal static class SampleRunner
 {
     /// <summary>
     /// Runs <c>dotnet run --framework net10.0</c> in the given project directory.
+    /// When <paramref name="build"/> is false (the default), <c>--no-build</c> is passed
+    /// to skip building, assuming the project was pre-built.
     /// </summary>
     public static Task<SampleRunResult> RunAsync(
         string projectPath,
         TimeSpan timeout,
+        bool build = false,
         CancellationToken cancellationToken = default)
-        => RunAsync(projectPath, "run --framework net10.0", timeout, inputs: null, inputDelayMs: 0, cancellationToken: cancellationToken);
+        => RunAsync(projectPath, DotnetRunArgs(build), timeout, inputs: null, inputDelayMs: 0, cancellationToken: cancellationToken);
 
     /// <summary>
     /// Runs <c>dotnet run --framework net10.0</c> with stdin inputs.
+    /// When <paramref name="build"/> is false (the default), <c>--no-build</c> is passed
+    /// to skip building, assuming the project was pre-built.
     /// </summary>
     public static Task<SampleRunResult> RunAsync(
         string projectPath,
         TimeSpan timeout,
         string?[]? inputs,
         int inputDelayMs = 2000,
+        bool build = false,
         CancellationToken cancellationToken = default)
-        => RunAsync(projectPath, "run --framework net10.0", timeout, inputs, inputDelayMs, cancellationToken);
+        => RunAsync(projectPath, DotnetRunArgs(build), timeout, inputs, inputDelayMs, cancellationToken);
+
+    private static string DotnetRunArgs(bool build) =>
+        $"run {(build ? "" : "--no-build")} --framework net10.0";
 
     /// <summary>
     /// Runs an arbitrary <c>dotnet</c> command in the given working directory.

dotnet/eng/verify-samples/SampleVerifier.cs

@@ -1,5 +1,6 @@
 // Copyright (c) Microsoft. All rights reserved.
 
+using System.ComponentModel;
 using System.Text.Json.Serialization;
 using Microsoft.Agents.AI;
 using Microsoft.Extensions.AI;
@@ -27,11 +28,19 @@ internal sealed class SampleVerifier
                 instructions: """
                     You are a test output verifier. You will be given:
                     1. The actual stdout output of a program
-                    2. A list of expectations about what the output should contain or demonstrate
+                    2. The stderr output (if any)
+                    3. A list of expectations about what the output should contain or demonstrate
 
                     Your job is to determine whether the actual output satisfies each expectation.
                     Be reasonable — the output comes from an LLM so exact wording won't match, but the
                     semantic intent should be clearly satisfied.
+
+                    In your response, you MUST:
+                    - Always provide ai_reasoning with a brief overall assessment.
+                    - Always provide exactly one entry in expectation_results for each expectation,
+                      in the same order as the input list.
+                    - For each expectation_results entry, echo the expectation text in the expectation
+                      field and explain your assessment in the detail field, citing evidence from the output.
                     """,
                 name: "OutputVerifier");
         }
@@ -78,7 +87,7 @@ internal sealed class SampleVerifier
             }
             else
             {
-                var aiResult = await this.VerifyWithAIAsync(run.Stdout, sample.ExpectedOutputDescription);
+                var aiResult = await this.VerifyWithAIAsync(run.Stdout, run.Stderr, sample.ExpectedOutputDescription);
                 aiReasoning = aiResult.Reasoning;
 
                 foreach (var unmet in aiResult.UnmetExpectations)
@@ -100,16 +109,28 @@ internal sealed class SampleVerifier
     }
 
     private async Task<(string Reasoning, List<string> UnmetExpectations)> VerifyWithAIAsync(
-        string actualOutput,
+        string stdout,
+        string stderr,
         string[] expectations)
     {
         var expectationList = string.Join("\n", expectations.Select((e, i) => $"  {i + 1}. {e}"));
+
+        var stderrSection = string.IsNullOrWhiteSpace(stderr)
+            ? ""
+            : $"""
+
+                Stderr output:
+                ---
+                {Truncate(stderr, 2000)}
+                ---
+                """;
+
         var prompt = $"""
             Actual program output:
             ---
-            {Truncate(actualOutput, 4000)}
+            {Truncate(stdout, 4000)}
             ---
-
+            {stderrSection}
             Expectations to verify:
             {expectationList}
 
@@ -126,7 +147,9 @@ internal sealed class SampleVerifier
                 return ($"AI verification returned null result. Raw: {response.Text}", ["AI verification returned null result."]);
             }
 
-            var reasoning = result.Reasoning ?? "(no reasoning provided)";
+            var reasoning = string.IsNullOrWhiteSpace(result.AIReasoning)
+                ? "(no reasoning provided)"
+                : result.AIReasoning;
 
             // Collect unmet expectations as individual failures
             var unmet = new List<string>();
@@ -174,12 +197,14 @@ internal sealed class AIVerificationResponse
     public bool Pass { get; set; }
 
     /// <summary>Brief explanation of the overall assessment.</summary>
-    [JsonPropertyName("reasoning")]
-    public string? Reasoning { get; set; }
+    [JsonPropertyName("ai_reasoning")]
+    [Description("Always required. Brief explanation of the overall assessment, covering all expectations.")]
+    public string AIReasoning { get; set; } = string.Empty;
 
     /// <summary>Per-expectation results.</summary>
     [JsonPropertyName("expectation_results")]
-    public List<ExpectationResult>? ExpectationResults { get; set; }
+    [Description("Always required. One entry per expectation, in the same order as the input list.")]
+    public List<ExpectationResult> ExpectationResults { get; set; } = [];
 }
 
 /// <summary>
@@ -190,7 +215,8 @@ internal sealed class ExpectationResult
 {
     /// <summary>The expectation text that was evaluated.</summary>
     [JsonPropertyName("expectation")]
-    public string? Expectation { get; set; }
+    [Description("Echo back the expectation text being evaluated.")]
+    public string Expectation { get; set; } = string.Empty;
 
     /// <summary>Whether this expectation was met.</summary>
     [JsonPropertyName("met")]
@@ -198,5 +224,6 @@ internal sealed class ExpectationResult
 
     /// <summary>Detail about how the expectation was or was not met.</summary>
     [JsonPropertyName("detail")]
-    public string? Detail { get; set; }
+    [Description("Explain how the expectation was or was not met, citing specific evidence from the output.")]
+    public string Detail { get; set; } = string.Empty;
 }

dotnet/eng/verify-samples/VerificationOrchestrator.cs

@@ -14,19 +14,22 @@ internal sealed class VerificationOrchestrator
     private readonly LogFileWriter? _logWriter;
     private readonly string _dotnetRoot;
     private readonly TimeSpan _timeout;
+    private readonly bool _buildSamples;
 
     public VerificationOrchestrator(
         SampleVerifier verifier,
         ConsoleReporter reporter,
         string dotnetRoot,
         TimeSpan timeout,
-        LogFileWriter? logWriter = null)
+        LogFileWriter? logWriter = null,
+        bool buildSamples = false)
     {
         this._verifier = verifier;
         this._reporter = reporter;
         this._logWriter = logWriter;
         this._dotnetRoot = dotnetRoot;
         this._timeout = timeout;
+        this._buildSamples = buildSamples;
     }
 
     /// <summary>
@@ -136,8 +139,8 @@ internal sealed class VerificationOrchestrator
 
             var projectPath = Path.Combine(this._dotnetRoot, sample.ProjectPath);
             var run = sample.Inputs.Length > 0
-                ? await SampleRunner.RunAsync(projectPath, this._timeout, sample.Inputs, sample.InputDelayMs)
-                : await SampleRunner.RunAsync(projectPath, this._timeout);
+                ? await SampleRunner.RunAsync(projectPath, this._timeout, sample.Inputs, sample.InputDelayMs, build: this._buildSamples)
+                : await SampleRunner.RunAsync(projectPath, this._timeout, build: this._buildSamples);
 
             log.Add($"[{sample.Name}] Completed ({run.Elapsed.TotalSeconds:F1}s, exit={run.ExitCode})");
             this._reporter.WriteLineWithPrefix(

dotnet/eng/verify-samples/VerifyOptions.cs

@@ -27,6 +27,12 @@ internal sealed class VerifyOptions
     /// </summary>
     public string? LogFilePath { get; init; }
 
+    /// <summary>
+    /// When true, samples are built as part of <c>dotnet run</c>.
+    /// When false (the default), <c>--no-build</c> is passed, assuming a prior build step.
+    /// </summary>
+    public bool BuildSamples { get; init; }
+
     /// <summary>
     /// The filtered list of samples to process.
     /// </summary>
@@ -55,6 +61,7 @@ internal sealed class VerifyOptions
         var logFilePath = ExtractArg(argList, "--log");
         var csvFilePath = ExtractArg(argList, "--csv");
         var markdownFilePath = ExtractArg(argList, "--md");
+        var buildSamples = ExtractFlag(argList, "--build");
 
         int maxParallelism = 8;
         var parallelArg = ExtractArg(argList, "--parallel");
@@ -105,6 +112,7 @@ internal sealed class VerifyOptions
             LogFilePath = logFilePath,
             CsvFilePath = csvFilePath,
             MarkdownFilePath = markdownFilePath,
+            BuildSamples = buildSamples,
             Samples = samples,
         };
     }
@@ -128,4 +136,16 @@ internal sealed class VerifyOptions
         list.RemoveRange(idx, 2);
         return value;
     }
+
+    private static bool ExtractFlag(List<string> list, string flag)
+    {
+        var idx = list.IndexOf(flag);
+        if (idx < 0)
+        {
+            return false;
+        }
+
+        list.RemoveAt(idx);
+        return true;
+    }
 }

dotnet/nuget/nuget-package.props

@@ -1,21 +1,21 @@
 <Project>
   <PropertyGroup>
     <!-- Central version prefix - applies to all nuget packages. -->
-    <VersionPrefix>1.0.0</VersionPrefix>
-    <RCNumber>6</RCNumber>
+    <VersionPrefix>1.1.0</VersionPrefix>
+    <RCNumber>1</RCNumber>
     <PackageVersion Condition="'$(IsReleaseCandidate)' == 'true'">$(VersionPrefix)-rc$(RCNumber)</PackageVersion>
-    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).260402.1</PackageVersion>
-    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' == ''">$(VersionPrefix)-preview.260402.1</PackageVersion>
+    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).260410.1</PackageVersion>
+    <PackageVersion Condition="'$(IsReleaseCandidate)' != 'true' AND '$(VersionSuffix)' == ''">$(VersionPrefix)-preview.260410.1</PackageVersion>
     <PackageVersion Condition="'$(IsReleased)' == 'true'">$(VersionPrefix)</PackageVersion>
-    <GitTag>1.0.0</GitTag>
+    <GitTag>1.1.0</GitTag>
 
     <Configurations>Debug;Release;Publish</Configurations>
     <IsPackable>true</IsPackable>
 
     <!-- Package validation. Baseline Version should be the latest version available on NuGet. -->
-    <PackageValidationBaselineVersion>1.0.0-rc5</PackageValidationBaselineVersion>
-    <!-- Enable validation for RC packages and GA packages -->
-    <EnablePackageValidation Condition="'$(IsReleaseCandidate)' == 'true' OR '$(IsReleased)' == 'true'">true</EnablePackageValidation>
+    <PackageValidationBaselineVersion>1.0.0</PackageValidationBaselineVersion>
+    <!-- Enable validation for GA packages -->
+    <EnablePackageValidation Condition="'$(IsReleased)' == 'true'">true</EnablePackageValidation>
     <!-- Validate assembly attributes only for Publish builds -->
     <NoWarn Condition="'$(Configuration)' != 'Publish'">$(NoWarn);CP0003</NoWarn>
     <!-- Do not validate reference assemblies -->

dotnet/samples/01-get-started/01_hello_agent/Program.cs

@@ -8,7 +8,7 @@ using Microsoft.Agents.AI;
 using OpenAI.Chat;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/01-get-started/02_add_tools/Program.cs

@@ -11,7 +11,7 @@ using Microsoft.Extensions.AI;
 using OpenAI.Chat;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 [Description("Get the weather for a given location.")]
 static string GetWeather([Description("The location to get the weather for.")] string location)

dotnet/samples/01-get-started/03_multi_turn/Program.cs

@@ -8,7 +8,7 @@ using Microsoft.Agents.AI;
 using OpenAI.Chat;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/01-get-started/04_memory/Program.cs

@@ -16,7 +16,7 @@ using OpenAI.Chat;
 using SampleApp;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/01-get-started/06_host_your_agent/Program.cs

@@ -8,7 +8,7 @@
 //
 // Environment variables:
 //   AZURE_OPENAI_ENDPOINT
-//   AZURE_OPENAI_DEPLOYMENT_NAME (defaults to "gpt-4o-mini")
+//   AZURE_OPENAI_DEPLOYMENT_NAME (defaults to "gpt-5.4-mini")
 //
 // Run with: func start
 // Then call: POST http://localhost:7071/api/agents/HostedAgent/run
@@ -23,7 +23,7 @@ using OpenAI.Chat;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
     ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // Set up an AI agent following the standard Microsoft Agent Framework pattern.
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.

dotnet/samples/02-agents/AGUI/README.md

@@ -15,7 +15,7 @@ All samples require the following environment variables:
 
 ```bash
 export AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/"
-export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"
+export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
 ```
 
 For the client samples, you can optionally set:

dotnet/samples/02-agents/AgentOpenTelemetry/Program.cs

@@ -97,7 +97,7 @@ Console.WriteLine("""
     """);
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT environment variable is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // Log application startup
 appLogger.LogInformation("OpenTelemetry Aspire Demo application started");

dotnet/samples/02-agents/AgentOpenTelemetry/README.md

@@ -34,7 +34,7 @@ graph TD
 Set the following environment variables:
 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/"
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```
 
 **Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure OpenAI resource.

dotnet/samples/02-agents/AgentProviders/Agent_With_AzureAIAgentsPersistent/Program.cs

@@ -9,7 +9,7 @@ using Azure.Identity;
 using Microsoft.Agents.AI;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 const string JokerName = "Joker";
 const string JokerInstructions = "You are good at telling jokes.";

dotnet/samples/02-agents/AgentProviders/Agent_With_AzureAIAgentsPersistent/README.md

@@ -22,5 +22,5 @@ Set the following environment variables:
 
 ```powershell
 $env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Microsoft Foundry resource endpoint
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```

dotnet/samples/02-agents/AgentProviders/Agent_With_AzureAIProject/Program.cs

@@ -9,7 +9,7 @@ using Microsoft.Agents.AI;
 using Microsoft.Agents.AI.Foundry;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 const string JokerName = "JokerAgent";
 

dotnet/samples/02-agents/AgentProviders/Agent_With_AzureAIProject/README.md

@@ -22,5 +22,5 @@ Set the following environment variables:
 
 ```powershell
 $env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Microsoft Foundry resource endpoint
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```

dotnet/samples/02-agents/AgentProviders/Agent_With_AzureOpenAIChatCompletion/Program.cs

@@ -8,7 +8,7 @@ using Microsoft.Agents.AI;
 using OpenAI.Chat;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentProviders/Agent_With_AzureOpenAIChatCompletion/README.md

@@ -12,5 +12,5 @@ Set the following environment variables:
 
 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```

dotnet/samples/02-agents/AgentProviders/Agent_With_AzureOpenAIResponses/Program.cs

@@ -9,7 +9,7 @@ using Microsoft.Extensions.AI;
 using OpenAI.Responses;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentProviders/Agent_With_AzureOpenAIResponses/README.md

@@ -12,5 +12,5 @@ Set the following environment variables:
 
 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```

dotnet/samples/02-agents/AgentProviders/Agent_With_OpenAIChatCompletion/Program.cs

@@ -8,7 +8,7 @@ using OpenAI;
 using OpenAI.Chat;
 
 var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-4o-mini";
+var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5.4-mini";
 
 AIAgent agent = new OpenAIClient(
     apiKey)

dotnet/samples/02-agents/AgentProviders/Agent_With_OpenAIChatCompletion/README.md

@@ -9,5 +9,5 @@ Set the following environment variables:
 
 ```powershell
 $env:OPENAI_API_KEY="*****" # Replace with your OpenAI api key
-$env:OPENAI_CHAT_MODEL_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:OPENAI_CHAT_MODEL_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```

dotnet/samples/02-agents/AgentProviders/Agent_With_OpenAIResponses/Program.cs

@@ -7,7 +7,7 @@ using OpenAI;
 using OpenAI.Responses;
 
 var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-4o-mini";
+var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5.4-mini";
 
 AIAgent agent = new OpenAIClient(
     apiKey)

dotnet/samples/02-agents/AgentProviders/Agent_With_OpenAIResponses/README.md

@@ -9,5 +9,5 @@ Set the following environment variables:
 
 ```powershell
 $env:OPENAI_API_KEY="*****" # Replace with your OpenAI api key
-$env:OPENAI_CHAT_MODEL_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:OPENAI_CHAT_MODEL_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```

dotnet/samples/02-agents/AgentSkills/Agent_Step01_FileBasedSkills/Program.cs

@@ -16,7 +16,7 @@ using OpenAI.Responses;
 
 // --- Configuration ---
 string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // --- Skills Provider ---
 // Discovers skills from the 'skills' directory containing SKILL.md files.

dotnet/samples/02-agents/AgentSkills/Agent_Step01_FileBasedSkills/README.md

@@ -30,7 +30,7 @@ Converts between common units (miles↔km, pounds↔kg) using a multiplication f
 
 ```bash
 export AZURE_OPENAI_ENDPOINT="https://your-endpoint.openai.azure.com/"
-export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"
+export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
 ```
 
 ### Run

dotnet/samples/02-agents/AgentSkills/Agent_Step02_CodeDefinedSkills/Program.cs

@@ -16,7 +16,7 @@ using OpenAI.Responses;
 
 // --- Configuration ---
 string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // --- Build the code-defined skill ---
 var unitConverterSkill = new AgentInlineSkill(

dotnet/samples/02-agents/AgentSkills/Agent_Step02_CodeDefinedSkills/README.md

@@ -31,7 +31,7 @@ Converts between common units using multiplication factors. Defined entirely in
 
 ```bash
 export AZURE_OPENAI_ENDPOINT="https://your-endpoint.openai.azure.com/"
-export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"
+export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
 ```
 
 ### Run

dotnet/samples/02-agents/AgentSkills/Agent_Step03_ClassBasedSkills/Agent_Step03_ClassBasedSkills.csproj

@@ -6,7 +6,7 @@
 
     <Nullable>enable</Nullable>
     <ImplicitUsings>enable</ImplicitUsings>
-    <NoWarn>$(NoWarn);MAAI001</NoWarn>
+    <NoWarn>$(NoWarn);MAAI001;IDE0051</NoWarn>
   </PropertyGroup>
 
   <ItemGroup>

dotnet/samples/02-agents/AgentSkills/Agent_Step03_ClassBasedSkills/Program.cs

@@ -1,8 +1,9 @@
 // Copyright (c) Microsoft. All rights reserved.
 
-// This sample demonstrates how to define Agent Skills as C# classes using AgentClassSkill.
-// Class-based skills bundle all components into a single class implementation.
+// This sample demonstrates how to define Agent Skills as C# classes using AgentClassSkill
+// with attributes for automatic script and resource discovery.
 
+using System.ComponentModel;
 using System.Text.Json;
 using Azure.AI.OpenAI;
 using Azure.Identity;
@@ -11,7 +12,7 @@ using OpenAI.Responses;
 
 // --- Configuration ---
 string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // --- Class-Based Skill ---
 // Instantiate the skill class.
@@ -44,17 +45,16 @@ AgentResponse response = await agent.RunAsync(
 Console.WriteLine($"Agent: {response.Text}");
 
 /// <summary>
-/// A unit-converter skill defined as a C# class.
+/// A unit-converter skill defined as a C# class using attributes for discovery.
 /// </summary>
 /// <remarks>
-/// Class-based skills bundle all components (name, description, body, resources, scripts)
-/// into a single class.
+/// Properties annotated with <see cref="AgentSkillResourceAttribute"/> are automatically
+/// discovered as skill resources, and methods annotated with <see cref="AgentSkillScriptAttribute"/>
+/// are automatically discovered as skill scripts. Alternatively,
+/// <see cref="AgentSkill.Resources"/> and <see cref="AgentSkill.Scripts"/> can be overridden.
 /// </remarks>
-internal sealed class UnitConverterSkill : AgentClassSkill
+internal sealed class UnitConverterSkill : AgentClassSkill<UnitConverterSkill>
 {
-    private IReadOnlyList<AgentSkillResource>? _resources;
-    private IReadOnlyList<AgentSkillScript>? _scripts;
-
     /// <inheritdoc/>
     public override AgentSkillFrontmatter Frontmatter { get; } = new(
         "unit-converter",
@@ -69,31 +69,40 @@ internal sealed class UnitConverterSkill : AgentClassSkill
         3. Present the result clearly with both units.
         """;
 
-    /// <inheritdoc/>
-    public override IReadOnlyList<AgentSkillResource>? Resources => this._resources ??=
-    [
-        CreateResource(
-            "conversion-table",
-            """
-            # Conversion Tables
+    /// <summary>
+    /// Gets the <see cref="JsonSerializerOptions"/> used to marshal parameters and return values
+    /// for scripts and resources.
+    /// </summary>
+    /// <remarks>
+    /// This override is not necessary for this sample, but can be used to provide custom
+    /// serialization options, for example a source-generated <c>JsonTypeInfoResolver</c>
+    /// for Native AOT compatibility.
+    /// </remarks>
+    protected override JsonSerializerOptions? SerializerOptions => null;
 
-            Formula: **result = value × factor**
+    /// <summary>
+    /// A conversion table resource providing multiplication factors.
+    /// </summary>
+    [AgentSkillResource("conversion-table")]
+    [Description("Lookup table of multiplication factors for common unit conversions.")]
+    public string ConversionTable => """
+        # Conversion Tables
 
-            | From        | To          | Factor   |
-            |-------------|-------------|----------|
-            | miles       | kilometers  | 1.60934  |
-            | kilometers  | miles       | 0.621371 |
-            | pounds      | kilograms   | 0.453592 |
-            | kilograms   | pounds      | 2.20462  |
-            """),
-    ];
+        Formula: **result = value × factor**
 
-    /// <inheritdoc/>
-    public override IReadOnlyList<AgentSkillScript>? Scripts => this._scripts ??=
-    [
-        CreateScript("convert", ConvertUnits),
-    ];
+        | From        | To          | Factor   |
+        |-------------|-------------|----------|
+        | miles       | kilometers  | 1.60934  |
+        | kilometers  | miles       | 0.621371 |
+        | pounds      | kilograms   | 0.453592 |
+        | kilograms   | pounds      | 2.20462  |
+        """;
 
+    /// <summary>
+    /// Converts a value by the given factor.
+    /// </summary>
+    [AgentSkillScript("convert")]
+    [Description("Multiplies a value by a conversion factor and returns the result as JSON.")]
     private static string ConvertUnits(double value, double factor)
     {
         double result = Math.Round(value * factor, 4);

dotnet/samples/02-agents/AgentSkills/Agent_Step03_ClassBasedSkills/README.md

@@ -1,12 +1,16 @@
 # Class-Based Agent Skills Sample
 
-This sample demonstrates how to define **Agent Skills as C# classes** using `AgentClassSkill`.
+This sample demonstrates how to define **Agent Skills as C# classes** using `AgentClassSkill`
+with **attributes** for automatic script and resource discovery.
 
 ## What it demonstrates
 
 - Creating skills as classes that extend `AgentClassSkill`
-- Bundling name, description, body, resources, and scripts into a single class
+- Using `[AgentSkillResource]` on properties to define resources
+- Using `[AgentSkillScript]` on methods to define scripts
+- Automatic discovery (no need to override `Resources`/`Scripts`)
 - Using the `AgentSkillsProvider` constructor with class-based skills
+- Overriding `SerializerOptions` for Native AOT compatibility
 
 ## Skills Included
 
@@ -28,7 +32,7 @@ A `UnitConverterSkill` class that converts between common units. Defined in `Pro
 
 ```bash
 export AZURE_OPENAI_ENDPOINT="https://your-endpoint.openai.azure.com/"
-export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"
+export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
 ```
 
 ### Run

dotnet/samples/02-agents/AgentSkills/Agent_Step04_MixedSkills/Agent_Step04_MixedSkills.csproj

@@ -6,7 +6,7 @@
 
     <Nullable>enable</Nullable>
     <ImplicitUsings>enable</ImplicitUsings>
-    <NoWarn>$(NoWarn);MAAI001</NoWarn>
+    <NoWarn>$(NoWarn);MAAI001;IDE0051</NoWarn>
   </PropertyGroup>
 
   <ItemGroup>

dotnet/samples/02-agents/AgentSkills/Agent_Step04_MixedSkills/Program.cs

@@ -8,11 +8,12 @@
 // Three different skill sources are registered here:
 // 1. File-based: unit-converter (miles↔km, pounds↔kg) from SKILL.md on disk
 // 2. Code-defined: volume-converter (gallons↔liters) using AgentInlineSkill
-// 3. Class-based: temperature-converter (°F↔°C↔K) using AgentClassSkill
+// 3. Class-based: temperature-converter (°F↔°C↔K) using AgentClassSkill with attributes
 //
 // For simpler, single-source scenarios, see the earlier steps in this sample series
 // (e.g., Step01 for file-based, Step02 for code-defined, Step03 for class-based).
 
+using System.ComponentModel;
 using System.Text.Json;
 using Azure.AI.OpenAI;
 using Azure.Identity;
@@ -22,7 +23,7 @@ using OpenAI.Responses;
 // --- Configuration ---
 string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
     ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // --- 1. Code-Defined Skill: volume-converter ---
 var volumeConverterSkill = new AgentInlineSkill(
@@ -89,13 +90,15 @@ AgentResponse response = await agent.RunAsync(
 Console.WriteLine($"Agent: {response.Text}");
 
 /// <summary>
-/// A temperature-converter skill defined as a C# class.
+/// A temperature-converter skill defined as a C# class using attributes for discovery.
 /// </summary>
-internal sealed class TemperatureConverterSkill : AgentClassSkill
+/// <remarks>
+/// Properties annotated with <see cref="AgentSkillResourceAttribute"/> are automatically
+/// discovered as skill resources, and methods annotated with <see cref="AgentSkillScriptAttribute"/>
+/// are automatically discovered as skill scripts.
+/// </remarks>
+internal sealed class TemperatureConverterSkill : AgentClassSkill<TemperatureConverterSkill>
 {
-    private IReadOnlyList<AgentSkillResource>? _resources;
-    private IReadOnlyList<AgentSkillScript>? _scripts;
-
     /// <inheritdoc/>
     public override AgentSkillFrontmatter Frontmatter { get; } = new(
         "temperature-converter",
@@ -110,29 +113,27 @@ internal sealed class TemperatureConverterSkill : AgentClassSkill
         3. Present the result clearly with both temperature scales.
         """;
 
-    /// <inheritdoc/>
-    public override IReadOnlyList<AgentSkillResource>? Resources => this._resources ??=
-    [
-        CreateResource(
-            "temperature-conversion-formulas",
-            """
-            # Temperature Conversion Formulas
+    /// <summary>
+    /// A reference table of temperature conversion formulas.
+    /// </summary>
+    [AgentSkillResource("temperature-conversion-formulas")]
+    [Description("Formulas for converting between Fahrenheit, Celsius, and Kelvin.")]
+    public string ConversionFormulas => """
+        # Temperature Conversion Formulas
 
-            | From        | To          | Formula                   |
-            |-------------|-------------|---------------------------|
-            | Fahrenheit  | Celsius     | °C = (°F − 32) × 5/9     |
-            | Celsius     | Fahrenheit  | °F = (°C × 9/5) + 32     |
-            | Celsius     | Kelvin      | K = °C + 273.15           |
-            | Kelvin      | Celsius     | °C = K − 273.15           |
-            """),
-    ];
-
-    /// <inheritdoc/>
-    public override IReadOnlyList<AgentSkillScript>? Scripts => this._scripts ??=
-    [
-        CreateScript("convert-temperature", ConvertTemperature),
-    ];
+        | From        | To          | Formula                   |
+        |-------------|-------------|---------------------------|
+        | Fahrenheit  | Celsius     | °C = (°F − 32) × 5/9     |
+        | Celsius     | Fahrenheit  | °F = (°C × 9/5) + 32     |
+        | Celsius     | Kelvin      | K = °C + 273.15           |
+        | Kelvin      | Celsius     | °C = K − 273.15           |
+        """;
 
+    /// <summary>
+    /// Converts a temperature value between scales.
+    /// </summary>
+    [AgentSkillScript("convert-temperature")]
+    [Description("Converts a temperature value from one scale to another.")]
     private static string ConvertTemperature(double value, string from, string to)
     {
         double result = (from.ToUpperInvariant(), to.ToUpperInvariant()) switch

dotnet/samples/02-agents/AgentSkills/Agent_Step04_MixedSkills/README.md

@@ -45,7 +45,7 @@ Defined as `TemperatureConverterSkill` class in `Program.cs`. Converts °F↔°C
 
 ```bash
 export AZURE_OPENAI_ENDPOINT="https://your-endpoint.openai.azure.com/"
-export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"
+export AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
 ```
 
 ### Run

dotnet/samples/02-agents/AgentSkills/Agent_Step05_SkillsWithDI/Agent_Step05_SkillsWithDI.csproj

@@ -6,7 +6,7 @@
 
     <Nullable>enable</Nullable>
     <ImplicitUsings>enable</ImplicitUsings>
-    <NoWarn>$(NoWarn);MAAI001;CA1812</NoWarn>
+    <NoWarn>$(NoWarn);MAAI001;CA1812;IDE0051</NoWarn>
   </PropertyGroup>
 
   <ItemGroup>

dotnet/samples/02-agents/AgentSkills/Agent_Step05_SkillsWithDI/Program.cs

@@ -13,6 +13,7 @@
 // showing that DI works identically regardless of how the skill is defined.
 // When prompted with a question spanning both domains, the agent uses both skills.
 
+using System.ComponentModel;
 using System.Text.Json;
 using Azure.AI.OpenAI;
 using Azure.Identity;
@@ -22,7 +23,7 @@ using OpenAI.Responses;
 
 // --- Configuration ---
 string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // --- DI Container ---
 // Register application services that skill resources and scripts can resolve at execution time.
@@ -62,8 +63,8 @@ var distanceSkill = new AgentInlineSkill(
 // Approach 2: Class-Based Skill with DI (AgentClassSkill)
 // =====================================================================
 // Handles weight conversions (pounds ↔ kilograms).
-// Resources and scripts are encapsulated in a class. Factory methods
-// CreateResource and CreateScript accept delegates with IServiceProvider.
+// Resources and scripts are discovered via reflection using attributes.
+// Methods with an IServiceProvider parameter receive DI automatically.
 //
 // Alternatively, class-based skills can accept dependencies through their
 // constructor. Register the skill class itself in the ServiceCollection and
@@ -113,14 +114,13 @@ Console.WriteLine($"Agent: {response.Text}");
 /// </summary>
 /// <remarks>
 /// This skill resolves <see cref="ConversionService"/> from the DI container
-/// in both its resource and script functions. This enables clean separation of
-/// concerns and testability while retaining the class-based skill pattern.
+/// in both its resource and script methods. Methods with an <see cref="IServiceProvider"/>
+/// parameter are automatically injected by the framework. Properties and methods annotated
+/// with <see cref="AgentSkillResourceAttribute"/> and <see cref="AgentSkillScriptAttribute"/>
+/// are automatically discovered via reflection.
 /// </remarks>
-internal sealed class WeightConverterSkill : AgentClassSkill
+internal sealed class WeightConverterSkill : AgentClassSkill<WeightConverterSkill>
 {
-    private IReadOnlyList<AgentSkillResource>? _resources;
-    private IReadOnlyList<AgentSkillScript>? _scripts;
-
     /// <inheritdoc/>
     public override AgentSkillFrontmatter Frontmatter { get; } = new(
         "weight-converter",
@@ -135,25 +135,27 @@ internal sealed class WeightConverterSkill : AgentClassSkill
         3. Present the result clearly with both units.
         """;
 
-    /// <inheritdoc/>
-    public override IReadOnlyList<AgentSkillResource>? Resources => this._resources ??=
-    [
-        CreateResource("weight-table", (IServiceProvider serviceProvider) =>
-        {
-            var service = serviceProvider.GetRequiredService<ConversionService>();
-            return service.GetWeightTable();
-        }),
-    ];
+    /// <summary>
+    /// Returns the weight conversion table from the DI-registered <see cref="ConversionService"/>.
+    /// </summary>
+    [AgentSkillResource("weight-table")]
+    [Description("Lookup table of multiplication factors for weight conversions.")]
+    private static string GetWeightTable(IServiceProvider serviceProvider)
+    {
+        var service = serviceProvider.GetRequiredService<ConversionService>();
+        return service.GetWeightTable();
+    }
 
-    /// <inheritdoc/>
-    public override IReadOnlyList<AgentSkillScript>? Scripts => this._scripts ??=
-    [
-        CreateScript("convert", (double value, double factor, IServiceProvider serviceProvider) =>
-        {
-            var service = serviceProvider.GetRequiredService<ConversionService>();
-            return service.Convert(value, factor);
-        }),
-    ];
+    /// <summary>
+    /// Converts a value by the given factor using the DI-registered <see cref="ConversionService"/>.
+    /// </summary>
+    [AgentSkillScript("convert")]
+    [Description("Multiplies a value by a conversion factor and returns the result as JSON.")]
+    private static string Convert(double value, double factor, IServiceProvider serviceProvider)
+    {
+        var service = serviceProvider.GetRequiredService<ConversionService>();
+        return service.Convert(value, factor);
+    }
 }
 
 // ---------------------------------------------------------------------------

dotnet/samples/02-agents/AgentSkills/Agent_Step05_SkillsWithDI/README.md

@@ -45,7 +45,7 @@ Set the following environment variables:
 | Variable | Description |
 |---|---|
 | `AZURE_OPENAI_ENDPOINT` | Your Azure OpenAI endpoint URL |
-| `AZURE_OPENAI_DEPLOYMENT_NAME` | Model deployment name (defaults to `gpt-4o-mini`) |
+| `AZURE_OPENAI_DEPLOYMENT_NAME` | Model deployment name (defaults to `gpt-5.4-mini`) |
 
 ## Running the Sample
 

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step01_ChatHistoryMemory/Program.cs

@@ -12,7 +12,7 @@ using Microsoft.SemanticKernel.Connectors.InMemory;
 using OpenAI.Chat;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 var embeddingDeploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME") ?? "text-embedding-3-large";
 
 // Create a vector store to store the chat messages in.

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step02_MemoryUsingMem0/Program.cs

@@ -14,7 +14,7 @@ using Microsoft.Extensions.AI;
 using OpenAI.Chat;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 var mem0ServiceUri = Environment.GetEnvironmentVariable("MEM0_ENDPOINT") ?? throw new InvalidOperationException("MEM0_ENDPOINT is not set.");
 var mem0ApiKey = Environment.GetEnvironmentVariable("MEM0_API_KEY") ?? throw new InvalidOperationException("MEM0_API_KEY is not set.");

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step04_MemoryUsingFoundry/Program.cs

@@ -15,7 +15,7 @@ using Microsoft.Agents.AI.Foundry;
 
 string foundryEndpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
 string memoryStoreName = Environment.GetEnvironmentVariable("AZURE_AI_MEMORY_STORE_ID") ?? "memory-store-sample";
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 string embeddingModelName = Environment.GetEnvironmentVariable("AZURE_AI_EMBEDDING_DEPLOYMENT_NAME") ?? "text-embedding-ada-002";
 
 // Create an AIProjectClient for Foundry with Azure Identity authentication.

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step04_MemoryUsingFoundry/README.md

@@ -14,7 +14,7 @@ This sample demonstrates how to create and run an agent that uses Microsoft Foun
 ## Prerequisites
 
 1. Azure subscription with Microsoft Foundry project
-2. Azure OpenAI resource with a chat model deployment (e.g., gpt-4o-mini) and an embedding model deployment (e.g., text-embedding-ada-002)
+2. Azure OpenAI resource with a chat model deployment (e.g., gpt-5.4-mini) and an embedding model deployment (e.g., text-embedding-ada-002)
 3. .NET 10.0 SDK
 4. Azure CLI logged in (`az login`)
 
@@ -26,7 +26,7 @@ export AZURE_AI_PROJECT_ENDPOINT="https://your-account.services.ai.azure.com/api
 export AZURE_AI_MEMORY_STORE_ID="my_memory_store"
 
 # Model deployment names (models deployed in your Foundry project)
-export AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o-mini"
+export AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
 export AZURE_AI_EMBEDDING_DEPLOYMENT_NAME="text-embedding-ada-002"
 ```
 

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step05_BoundedChatHistory/Program.cs

@@ -15,7 +15,7 @@ using OpenAI.Chat;
 using SampleApp;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 var embeddingDeploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME") ?? "text-embedding-3-large";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.

dotnet/samples/02-agents/AgentWithMemory/AgentWithMemory_Step05_BoundedChatHistory/README.md

@@ -13,7 +13,7 @@ This sample demonstrates how to create a custom `ChatHistoryProvider` that keeps
 
 - [.NET 10 SDK](https://dotnet.microsoft.com/download/dotnet/10.0)
 - An Azure OpenAI resource with:
-  - A chat deployment (e.g., `gpt-4o-mini`)
+  - A chat deployment (e.g., `gpt-5.4-mini`)
   - An embedding deployment (e.g., `text-embedding-3-large`)
 
 ## Configuration
@@ -23,7 +23,7 @@ Set the following environment variables:
 | Variable | Description | Default |
 |---|---|---|
 | `AZURE_OPENAI_ENDPOINT` | Your Azure OpenAI endpoint URL | *(required)* |
-| `AZURE_OPENAI_DEPLOYMENT_NAME` | Chat model deployment name | `gpt-4o-mini` |
+| `AZURE_OPENAI_DEPLOYMENT_NAME` | Chat model deployment name | `gpt-5.4-mini` |
 | `AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME` | Embedding model deployment name | `text-embedding-3-large` |
 
 ## Running the Sample

dotnet/samples/02-agents/AgentWithOpenAI/Agent_OpenAI_Step01_Running/Program.cs

@@ -7,7 +7,7 @@ using Microsoft.Agents.AI;
 using OpenAI.Responses;
 
 var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-4o-mini";
+var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5.4-mini";
 
 AIAgent agent =
     new ResponsesClient(new ApiKeyCredential(apiKey))

dotnet/samples/02-agents/AgentWithOpenAI/Agent_OpenAI_Step02_Reasoning/Program.cs

@@ -7,7 +7,7 @@ using Microsoft.Extensions.AI;
 using OpenAI;
 
 var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5";
+var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5.4-mini";
 
 var client = new OpenAIClient(apiKey)
         .GetResponsesClient()

dotnet/samples/02-agents/AgentWithOpenAI/Agent_OpenAI_Step03_CreateFromChatClient/Program.cs

@@ -7,7 +7,7 @@ using OpenAI.Chat;
 using OpenAIChatClientSample;
 
 string apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-string model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-4o-mini";
+string model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5.4-mini";
 
 // Create a ChatClient directly from OpenAIClient
 ChatClient chatClient = new OpenAIClient(apiKey).GetChatClient(model);

dotnet/samples/02-agents/AgentWithOpenAI/Agent_OpenAI_Step03_CreateFromChatClient/README.md

@@ -13,7 +13,7 @@ This sample demonstrates how to create an AI agent directly from an `OpenAI.Chat
 1. Set the required environment variables:
    ```bash
    set OPENAI_API_KEY=your_api_key_here
-   set OPENAI_CHAT_MODEL_NAME=gpt-4o-mini
+   set OPENAI_CHAT_MODEL_NAME=gpt-5.4-mini
    ```
 
 2. Run the sample:

dotnet/samples/02-agents/AgentWithOpenAI/Agent_OpenAI_Step04_CreateFromOpenAIResponseClient/Program.cs

@@ -7,7 +7,7 @@ using OpenAI.Responses;
 using OpenAIResponseClientSample;
 
 var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-4o-mini";
+var model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5.4-mini";
 
 // Create a ResponsesClient directly from OpenAIClient
 ResponsesClient responseClient = new OpenAIClient(apiKey).GetResponsesClient();

dotnet/samples/02-agents/AgentWithOpenAI/Agent_OpenAI_Step04_CreateFromOpenAIResponseClient/README.md

@@ -13,7 +13,7 @@ This sample demonstrates how to create an AI agent directly from an `OpenAI.Resp
 1. Set the required environment variables:
    ```bash
    set OPENAI_API_KEY=your_api_key_here
-   set OPENAI_CHAT_MODEL_NAME=gpt-4o-mini
+   set OPENAI_CHAT_MODEL_NAME=gpt-5.4-mini
    ```
 
 2. Run the sample:

dotnet/samples/02-agents/AgentWithOpenAI/Agent_OpenAI_Step05_Conversation/Program.cs

@@ -15,7 +15,7 @@ using OpenAI.Chat;
 using OpenAI.Conversations;
 
 string apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
-string model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-4o-mini";
+string model = Environment.GetEnvironmentVariable("OPENAI_CHAT_MODEL_NAME") ?? "gpt-5.4-mini";
 
 // Create a ConversationClient directly from OpenAIClient
 OpenAIClient openAIClient = new(apiKey);

dotnet/samples/02-agents/AgentWithOpenAI/Agent_OpenAI_Step05_Conversation/README.md

@@ -69,7 +69,7 @@ foreach (ClientResult result in getConversationItemsResults.GetRawPages())
 1. Set the required environment variables:
    ```powershell
    $env:OPENAI_API_KEY = "your_api_key_here"
-   $env:OPENAI_CHAT_MODEL_NAME = "gpt-4o-mini"
+   $env:OPENAI_CHAT_MODEL_NAME = "gpt-5.4-mini"
    ```
 
 2. Run the sample:

dotnet/samples/02-agents/AgentWithRAG/AgentWithRAG_Step01_BasicTextRAG/Program.cs

@@ -15,7 +15,7 @@ using Microsoft.SemanticKernel.Connectors.InMemory;
 using OpenAI.Chat;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 var embeddingDeploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME") ?? "text-embedding-3-large";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.

dotnet/samples/02-agents/AgentWithRAG/AgentWithRAG_Step02_CustomVectorStoreRAG/Program.cs

@@ -14,7 +14,7 @@ using OpenAI.Chat;
 using Qdrant.Client;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 var embeddingDeploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME") ?? "text-embedding-3-large";
 var afOverviewUrl = "https://raw.githubusercontent.com/MicrosoftDocs/semantic-kernel-docs/refs/heads/main/agent-framework/overview/index.md";
 var afMigrationUrl = "https://raw.githubusercontent.com/MicrosoftDocs/semantic-kernel-docs/refs/heads/main/agent-framework/migration-guide/from-semantic-kernel/index.md";

dotnet/samples/02-agents/AgentWithRAG/AgentWithRAG_Step02_CustomVectorStoreRAG/README.md

@@ -23,7 +23,7 @@ Set the following environment variables:
 
 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 $env:AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME="text-embedding-3-large"  # Optional, defaults to text-embedding-3-large
 ```
 

dotnet/samples/02-agents/AgentWithRAG/AgentWithRAG_Step03_CustomRAGDataSource/Program.cs

@@ -13,7 +13,7 @@ using Microsoft.Extensions.AI;
 using OpenAI.Chat;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 TextSearchProviderOptions textSearchOptions = new()
 {

dotnet/samples/02-agents/AgentWithRAG/AgentWithRAG_Step04_FoundryServiceRAG/Program.cs

@@ -14,7 +14,7 @@ using OpenAI.Responses;
 using OpenAI.VectorStores;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // Create an AI Project client and get an OpenAI client that works with the foundry service.
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.

dotnet/samples/02-agents/AgentWithRAG/AgentWithRAG_Step05_Neo4jGraphRAG/Program.cs

@@ -8,7 +8,7 @@ using Neo4j.AgentFramework.GraphRAG;
 using Neo4j.Driver;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 var neo4jUri = Environment.GetEnvironmentVariable("NEO4J_URI") ?? throw new InvalidOperationException("NEO4J_URI is not set.");
 var neo4jUsername = Environment.GetEnvironmentVariable("NEO4J_USERNAME") ?? "neo4j";
 var neo4jPassword = Environment.GetEnvironmentVariable("NEO4J_PASSWORD") ?? throw new InvalidOperationException("NEO4J_PASSWORD is not set.");

dotnet/samples/02-agents/AgentWithRAG/AgentWithRAG_Step05_Neo4jGraphRAG/README.md

@@ -15,7 +15,7 @@ The sample uses a Neo4j fulltext index for retrieval and a Cypher `RetrievalQuer
 
 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/"
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
 $env:NEO4J_URI="neo4j+s://your-instance.databases.neo4j.io"
 $env:NEO4J_USERNAME="neo4j"
 $env:NEO4J_PASSWORD="your-password"

dotnet/samples/02-agents/Agents/Agent_Step01_UsingFunctionToolsWithApprovals/Program.cs

@@ -14,7 +14,7 @@ using OpenAI.Chat;
 using ChatMessage = Microsoft.Extensions.AI.ChatMessage;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // Create a sample function tool that the agent can use.
 [Description("Get the weather for a given location.")]

dotnet/samples/02-agents/Agents/Agent_Step02_StructuredOutput/Program.cs

@@ -14,7 +14,7 @@ using SampleApp;
 using ChatMessage = Microsoft.Extensions.AI.ChatMessage;
 
 string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // Create chat client to be used by chat client agents.
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.

dotnet/samples/02-agents/Agents/Agent_Step02_StructuredOutput/README.md

@@ -28,7 +28,7 @@ Set the following environment variables:
 
 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```
 
 ## Run the sample

dotnet/samples/02-agents/Agents/Agent_Step03_PersistedConversations/Program.cs

@@ -11,7 +11,7 @@ using Microsoft.Agents.AI;
 using OpenAI.Chat;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // Create the agent
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.

dotnet/samples/02-agents/Agents/Agent_Step04_3rdPartyChatHistoryStorage/Program.cs

@@ -18,7 +18,7 @@ using SampleApp;
 using ChatMessage = Microsoft.Extensions.AI.ChatMessage;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // Create a vector store to store the chat messages in.
 // Replace this with a vector store implementation of your choice if you want to persist the chat history to disk.

dotnet/samples/02-agents/Agents/Agent_Step05_Observability/Program.cs

@@ -11,7 +11,7 @@ using OpenTelemetry;
 using OpenTelemetry.Trace;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 var applicationInsightsConnectionString = Environment.GetEnvironmentVariable("APPLICATIONINSIGHTS_CONNECTION_STRING");
 
 // Create TracerProvider with console exporter

dotnet/samples/02-agents/Agents/Agent_Step06_DependencyInjection/Program.cs

@@ -12,7 +12,7 @@ using Microsoft.Extensions.DependencyInjection;
 using Microsoft.Extensions.Hosting;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // Create a host builder that we will register services with and then run.
 HostApplicationBuilder builder = Host.CreateApplicationBuilder(args);

dotnet/samples/02-agents/Agents/Agent_Step07_AsMcpTool/Program.cs

@@ -11,7 +11,7 @@ using Microsoft.Extensions.Hosting;
 using ModelContextProtocol.Server;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/Agents/Agent_Step07_AsMcpTool/README.md

@@ -22,7 +22,7 @@ To use the [MCP Inspector](https://modelcontextprotocol.io/docs/tools/inspector)
 1. Open a web browser and navigate to the URL displayed in the terminal. If not opened automatically, this will open the MCP Inspector interface.
 1. In the MCP Inspector interface, add the following environment variables to allow your MCP server to access Microsoft Foundry Project to create and run the agent:
     - AZURE_AI_PROJECT_ENDPOINT = https://your-resource.openai.azure.com/ # Replace with your Microsoft Foundry Project endpoint
-    - AZURE_AI_MODEL_DEPLOYMENT_NAME = gpt-4o-mini # Replace with your model deployment name
+    - AZURE_AI_MODEL_DEPLOYMENT_NAME = gpt-5.4-mini # Replace with your model deployment name
 1. Find and click the `Connect` button in the MCP Inspector interface to connect to the MCP server.
 1. As soon as the connection is established, open the `Tools` tab in the MCP Inspector interface and select the `Joker` tool from the list.
 1. Specify your prompt as a value for the `query` argument, for example: `Tell me a joke about a pirate` and click the `Run Tool` button to run the tool.

dotnet/samples/02-agents/Agents/Agent_Step08_UsingImages/Program.cs

@@ -9,7 +9,7 @@ using OpenAI.Chat;
 using ChatMessage = Microsoft.Extensions.AI.ChatMessage;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o";
+var deploymentName = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/Agents/Agent_Step08_UsingImages/README.md

@@ -20,7 +20,7 @@ This sample demonstrates how to use image multi-modality with an AI agent. It sh
 Before running this sample, ensure you have:
 
 1. An Azure OpenAI project set up
-2. A compatible model deployment (e.g., gpt-4o)
+2. A compatible model deployment (e.g., gpt-5.4-mini)
 3. Azure CLI installed and authenticated
 
 ## Environment Variables
@@ -29,7 +29,7 @@ Set the following environment variables:
 
 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI endpoint
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o" # Replace with your model deployment name (optional, defaults to gpt-4o)
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini" # Replace with your model deployment name (optional, defaults to gpt-5.4-mini)
 ```
 
 ## Run the sample

dotnet/samples/02-agents/Agents/Agent_Step09_AsFunctionTool/Program.cs

@@ -10,7 +10,7 @@ using Microsoft.Extensions.AI;
 using OpenAI.Chat;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 [Description("Get the weather for a given location.")]
 static string GetWeather([Description("The location to get the weather for.")] string location)

dotnet/samples/02-agents/Agents/Agent_Step10_BackgroundResponsesWithToolsAndPersistence/Program.cs

@@ -15,7 +15,7 @@ using Microsoft.Extensions.AI;
 using OpenAI.Responses;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 var stateStore = new Dictionary<string, JsonElement?>();
 

dotnet/samples/02-agents/Agents/Agent_Step10_BackgroundResponsesWithToolsAndPersistence/README.md

@@ -24,5 +24,5 @@ Set the following environment variables:
 
 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5"  # Optional, defaults to gpt-5
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```

dotnet/samples/02-agents/Agents/Agent_Step11_Middleware/Program.cs

@@ -15,7 +15,7 @@ using Microsoft.Extensions.AI;
 
 // Get Microsoft Foundry configuration from environment variables
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o";
+var deploymentName = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // Get a client to create/retrieve server side agents with
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.

dotnet/samples/02-agents/Agents/Agent_Step11_Middleware/README.md

@@ -27,7 +27,7 @@ Attempting to use function middleware on agents that do not wrap a ChatClientAge
 
 1. Environment variables:
    - `AZURE_OPENAI_ENDPOINT`: Your Azure OpenAI endpoint
-   - `AZURE_OPENAI_DEPLOYMENT_NAME`: Chat deployment name (optional; defaults to `gpt-4o`)
+   - `AZURE_OPENAI_DEPLOYMENT_NAME`: Chat deployment name (optional; defaults to `gpt-5.4-mini`)
 2. Sign in with Azure CLI (PowerShell):
    ```powershell
    az login

dotnet/samples/02-agents/Agents/Agent_Step12_Plugins/Program.cs

@@ -17,7 +17,7 @@ using Microsoft.Extensions.DependencyInjection;
 using OpenAI.Chat;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // Create a service collection to hold the agent plugin and its dependencies.
 ServiceCollection services = new();

dotnet/samples/02-agents/Agents/Agent_Step13_ChatReduction/Program.cs

@@ -12,7 +12,7 @@ using Microsoft.Extensions.AI;
 using OpenAI.Chat;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // Construct the agent, and provide a factory to create an in-memory chat message store with a reducer that keeps only the last 2 non-system messages.
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.

dotnet/samples/02-agents/Agents/Agent_Step14_BackgroundResponses/Program.cs

@@ -8,7 +8,7 @@ using Microsoft.Agents.AI;
 using OpenAI.Responses;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/Agents/Agent_Step14_BackgroundResponses/README.md

@@ -23,5 +23,5 @@ Set the following environment variables:
 
 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```

dotnet/samples/02-agents/Agents/Agent_Step15_DeepResearch/Program.cs

@@ -10,7 +10,7 @@ using Microsoft.Agents.AI;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
 var deepResearchDeploymentName = Environment.GetEnvironmentVariable("AZURE_AI_REASONING_DEPLOYMENT_NAME") ?? "o3-deep-research";
-var modelDeploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o";
+var modelDeploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 var bingConnectionId = Environment.GetEnvironmentVariable("AZURE_AI_BING_CONNECTION_ID") ?? throw new InvalidOperationException("AZURE_AI_BING_CONNECTION_ID is not set.");
 
 // Configure extended network timeout for long-running Deep Research tasks.

dotnet/samples/02-agents/Agents/Agent_Step15_DeepResearch/README.md

@@ -13,7 +13,7 @@ Before running this sample, ensure you have:
 
 1. A Microsoft Foundry project set up
 2. A deep research model deployment (e.g., o3-deep-research)
-3. A model deployment (e.g., gpt-4o)
+3. A model deployment (e.g., gpt-5.4-mini)
 4. A Bing Connection configured in your Microsoft Foundry project
 5. Azure CLI installed and authenticated
 
@@ -45,5 +45,5 @@ $env:AZURE_AI_BING_CONNECTION_ID="/subscriptions/<sub-id>/resourceGroups/<rg>/pr
 # Optional, defaults to o3-deep-research
 $env:AZURE_AI_REASONING_DEPLOYMENT_NAME="o3-deep-research"
 
-# Optional, defaults to gpt-4o
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o"
+# Optional, defaults to gpt-5.4-mini
+$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"

dotnet/samples/02-agents/Agents/Agent_Step16_Declarative/Program.cs

@@ -8,7 +8,7 @@ using Microsoft.Agents.AI;
 using Microsoft.Extensions.AI;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // Create the chat client
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.

dotnet/samples/02-agents/Agents/Agent_Step17_AdditionalAIContext/Program.cs

@@ -18,7 +18,7 @@ using SampleApp;
 using MEAI = Microsoft.Extensions.AI;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // A sample function to load the next three calendar events for the user.
 Func<Task<string[]>> loadNextThreeCalendarEvents = async () =>

dotnet/samples/02-agents/Agents/Agent_Step18_CompactionPipeline/Program.cs

@@ -16,7 +16,7 @@ using Microsoft.Agents.AI.Compaction;
 using Microsoft.Extensions.AI;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/Agents/Agent_Step18_CompactionPipeline/README.md

@@ -68,7 +68,7 @@ Order strategies from **least aggressive** to **most aggressive**. The pipeline
 
 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/"  # Required
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"                       # Optional, defaults to gpt-4o-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"                      # Optional, defaults to gpt-5.4-mini
 ```
 
 ## Running the Sample
@@ -110,7 +110,7 @@ IEnumerable<ChatMessage> compacted = await CompactionProvider.CompactAsync(
 The `SummarizationCompactionStrategy` accepts any `IChatClient`. Use a smaller, cheaper model to reduce summarization cost:
 
 ```csharp
-IChatClient summarizerChatClient = openAIClient.GetChatClient("gpt-4o-mini").AsIChatClient();
+IChatClient summarizerChatClient = openAIClient.GetChatClient("gpt-5.4-mini").AsIChatClient();
 new SummarizationCompactionStrategy(summarizerChatClient, CompactionTriggers.TokensExceed(4000))
 ```
 

dotnet/samples/02-agents/Agents/Agent_Step19_InFunctionLoopCheckpointing/Program.cs

@@ -23,7 +23,7 @@ using Microsoft.Extensions.AI;
 using OpenAI.Responses;
 
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
-var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 var store = Environment.GetEnvironmentVariable("AZURE_OPENAI_RESPONSES_STORE") ?? "false";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.

dotnet/samples/02-agents/Agents/Agent_Step19_InFunctionLoopCheckpointing/README.md

@@ -45,7 +45,7 @@ ChatClientAgent
 
 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/"  # Required
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"                       # Optional, defaults to gpt-4o-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"                      # Optional, defaults to gpt-5.4-mini
 ```
 
 ## Running the Sample

dotnet/samples/02-agents/Agents/README.md

@@ -59,7 +59,7 @@ Set the following environment variables:
 
 ```powershell
 $env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
-$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"  # Optional, defaults to gpt-5.4-mini
 ```
 
 If the variables are not set, you will be prompted for the values when running the samples.

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step00_FoundryAgentLifecycle/Program.cs

@@ -10,7 +10,7 @@ using Azure.Identity;
 using Microsoft.Agents.AI.Foundry;
 
 string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 const string JokerName = "JokerAgent";
 

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step00_FoundryAgentLifecycle/README.md

@@ -5,7 +5,7 @@ This sample demonstrates the full lifecycle of a `FoundryAgent` backed by a serv
 ## Prerequisites
 
 - A Microsoft Foundry project endpoint
-- A model deployment name (defaults to `gpt-4o-mini`)
+- A model deployment name (defaults to `gpt-5.4-mini`)
 - Azure CLI installed and authenticated
 
 ## Environment Variables
@@ -13,7 +13,7 @@ This sample demonstrates the full lifecycle of a `FoundryAgent` backed by a serv
 | Variable | Description | Required |
 | --- | --- | --- |
 | `AZURE_AI_PROJECT_ENDPOINT` | Microsoft Foundry project endpoint | Yes |
-| `AZURE_AI_MODEL_DEPLOYMENT_NAME` | Model deployment name | No (defaults to `gpt-4o-mini`) |
+| `AZURE_AI_MODEL_DEPLOYMENT_NAME` | Model deployment name | No (defaults to `gpt-5.4-mini`) |
 
 ## Running the sample
 

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step01_Basics/Program.cs

@@ -7,7 +7,7 @@ using Azure.Identity;
 using Microsoft.Agents.AI;
 
 string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step01_Basics/README.md

@@ -22,7 +22,7 @@ Set the following environment variables:
 
 ```powershell
 $env:AZURE_AI_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
-$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o-mini"
+$env:AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5.4-mini"
 ```
 
 ## Run the sample

dotnet/samples/02-agents/AgentsWithFoundry/Agent_Step02.1_MultiturnConversation/Program.cs

@@ -8,7 +8,7 @@ using Azure.Identity;
 using Microsoft.Agents.AI;
 
 string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
-string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
 
 // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
 // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid