Researching Azure AI SDK

CRITICAL: Don’t guess SDK usage. Follow this research workflow.

Subagent Delegation for Research

Multi-repo research blows up context (1000+ tokens per file). Delegate to subagent for:

• Searching across 3+ repositories
• Reading 5+ files for patterns
• Comprehensive API surface exploration
• Finding all usages of a method/type

Delegation Pattern

runSubagent(
  prompt: "RESEARCH task - do NOT write code.
    
    **Question**: [specific SDK question]
    
    **Search these sources in order**:
    1. Azure.AI.Projects SDK: github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.Projects
    2. Azure.AI.Agents.Persistent samples: .../Azure.AI.Agents.Persistent/samples
    3. Microsoft Foundry Samples: github.com/microsoft-foundry/foundry-samples
    
    **Find**:
    - Method signatures for [specific API]
    - Usage examples (pseudocode only)
    - Any gotchas or edge cases
    
    **Return** (max 20 lines):
    - Key method name and signature
    - Code pattern (pseudocode)
    - File path where found (for later reference)
    
    Do NOT include full file contents.",
  description: "SDK research: [topic]"
)

When to Delegate vs Inline

SDK Architecture Overview

The Foundry Agent Service SDK has two API surfaces for agents:

This project uses v2 Agents API for human-readable agent IDs.

Azure.AI.Projects (Main Entry Point)
├── AIProjectClient
│   ├── .Agents.GetAgentAsync() → AgentRecord (v2 Agents API)
│   ├── .GetPersistentAgentsClient() → PersistentAgentsClient (Assistants API)
│   └── .OpenAI.GetProjectResponsesClientForAgent() → ProjectResponsesClient (Responses API)
└── Sub-namespaces:
    ├── Azure.AI.Projects.OpenAI (Responses API, conversations)
    └── OpenAI.Responses (streaming types)

1. Primary SDK Repository (Start Here)

Azure.AI.Projects SDK: https://github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.Projects

• README: Core client patterns, authentication, basic operations
• Samples: tests/Samples/ folder with full examples

Azure.AI.Agents.Persistent SDK: https://github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.Agents.Persistent

• 33+ samples covering streaming, file search, Bing grounding, MCP, Azure Functions
• Key samples:
  • Sample9_PersistentAgents_Streaming.md – Basic streaming pattern
  • Sample8_PersistentAgents_FunctionsWithStreaming.md – Tool calls with streaming
  • Sample27_PersistentAgents_MCP_Streaming.md – MCP server integration

2. Official Quickstart Samples

Microsoft Foundry Samples: https://github.com/microsoft-foundry/foundry-samples

• samples/csharp/quickstart/quickstart-chat-with-agent.cs – Responses API pattern
• samples/csharp/quickstart/ – Multiple quickstart examples

Key pattern from official quickstart:

AIProjectClient projectClient = new(new Uri(projectEndpoint), new AzureCliCredential());
ProjectConversation conversation = projectClient.OpenAI.Conversations.CreateProjectConversation();
ProjectResponsesClient responsesClient = projectClient.OpenAI.GetProjectResponsesClientForAgent(
    defaultAgent: agentName,
    defaultConversationId: conversation.Id);
ResponseResult response = responsesClient.CreateResponse("Your prompt");

3. Azure Architecture Center Samples

Baseline Chat App: https://github.com/Azure-Samples/microsoft-foundry-baseline

• Full production architecture with Entra ID auth
• website/chatui/Controllers/ChatController.cs – SSE streaming pattern

Basic Chat Example: https://github.com/Azure-Samples/microsoft-foundry-basic

• Simpler example of Foundry agent chat integration

Semantic Kernel + Foundry: https://github.com/Azure-Samples/app-service-agentic-semantic-kernel-ai-foundry-agent

• Integration pattern for Semantic Kernel with Foundry Agents

4. UI Reference Samples (React Patterns)

Primary UI Reference

Azure AI Agents React Sample: https://github.com/Azure-Samples/get-started-with-ai-agents

This is the primary UI reference for this project. Many UI patterns were borrowed from here:

• Chat interface components
• Message rendering with citations/annotations
• Streaming text display
• Responsive layout patterns

Agent Framework DevUI (Python)

Agent Framework DevUI: https://github.com/microsoft/agent-framework/tree/main/python/packages/devui

Alternative UI patterns for agent development:

• Development-focused chat interface
• Multi-agent visualization
• Tool call debugging UI

UI Component Inspiration

When implementing new UI features, check these sources in order:

1. get-started-with-ai-agents – React + TypeScript patterns for chat UI
2. agent-framework/devui – Development UI patterns
3. Fluent UI Copilot Components – Base component library (already used)

5. Semantic Kernel Integration

Repository: https://github.com/microsoft/semantic-kernel

Relevant paths:

• dotnet/src/Agents/OpenAI/ – OpenAI Responses API integration
• dotnet/samples/GettingStartedWithAgents/AzureAIAgent/
• dotnet/samples/Concepts/Agents/ (Step##_*.cs files)

6. OpenAI .NET SDK (Streaming Types)

Repository: https://github.com/openai/openai-dotnet

• docs/guides/streaming-responses/ – Streaming patterns
• Source of StreamingResponseOutputTextDeltaUpdate and related types

7. GitHub Code Search (For Specific Patterns)

Use GitHub search to find usage examples:

# Find streaming patterns
"StreamingResponseOutputTextDeltaUpdate language:csharp"

# Find Responses API usage
"ProjectResponsesClient CreateResponseStreamingAsync language:csharp"

# Find conversation patterns
"ProjectConversation GetProjectResponsesClientForAgent language:csharp"

Current SDK Packages

Note: This project uses Azure.AI.Projects beta for v2 Agents API access (AIProjectClient.Agents). The stable version does not include the v2 Agents API.

Sub-namespaces available (not separate packages):

• Azure.AI.Projects.OpenAI – Responses API, conversations
• OpenAI.Responses – Streaming types

Available Package: Microsoft.Agents.AI.AzureAI v1.0.0-rc1 supports v2 Agents API via AIProjectClient extension methods. See “Microsoft Agent Framework” section below for evaluation notes.

Key Resources:

• NuGet (Azure.AI.Projects): https://www.nuget.org/packages/Azure.AI.Projects
• SDK Source: https://github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.Projects
• v2 Migration Guide: https://learn.microsoft.com/en-us/azure/ai-foundry/agents/how-to/migrate
• API Reference: https://learn.microsoft.com/en-us/dotnet/api/azure.ai.projects
• Product Docs: https://learn.microsoft.com/azure/ai-studio/

Official Azure AI Foundry Agent Service Documentation

Start here when researching agent capabilities, limits, or new features:

Agent Framework (Microsoft.Agents) docs:

Annotation Types in Responses

The SDK provides several annotation types for citations (from OpenAI.Responses namespace):

Note: FileCitationMessageAnnotation uses Index (not StartIndex/EndIndex) per the SDK. See ExtractAnnotations() in AgentFrameworkService.cs for mapping to AnnotationInfo.

Streaming Response Types (from OpenAI.Responses namespace)

Pattern used in this project:

await foreach (var update in responsesClient.CreateResponseStreamingAsync(...))
{
    if (update is StreamingResponseOutputTextDeltaUpdate textUpdate)
        yield return new StreamChunk { Text = textUpdate.Delta };
    if (update is StreamingResponseOutputItemDoneUpdate itemDone)
        // Extract annotations from itemDone.Item
}

Microsoft Agent Framework (Used — Hybrid Approach)

Package: Microsoft.Agents.AI.AzureAI v1.0.0-rc1

Status: ✅ Installed and active. Agent Framework supports v2 Agents API via AIProjectClient extension methods.

Current Usage Pattern

This project uses a hybrid approach:

• Agent Framework for simplified agent loading and metadata
• Direct SDK for streaming (required for specialized response types)

// ✅ Agent loading via Agent Framework (simple)
ChatClientAgent agent = await aiProjectClient.GetAIAgentAsync(
    name: "dadjokes",           // Human-readable agent name
    cancellationToken: ct);

// Access AgentVersion for metadata
AgentVersion? version = agent.GetService<AgentVersion>();
var definition = version?.Definition as PromptAgentDefinition;

// ❌ Direct SDK for streaming (Agent Framework can't do this yet)
ProjectResponsesClient responsesClient = projectClient.OpenAI.GetProjectResponsesClientForAgent(
    new AgentReference(_agentId), conversationId);
await foreach (var update in responsesClient.CreateResponseStreamingAsync(...)) { }

Why Not Full Agent Framework for Streaming?

ChatClientAgent.RunStreamingAsync() returns IAsyncEnumerable<AgentRunResponseUpdate>, which provides:

• Text — text content (✅ works)
• RawRepresentation — underlying SDK object (can cast at runtime)

The problem: The IChatClient abstraction doesn’t directly expose:

• McpToolCallApprovalRequestItem for MCP approval flows
• FileSearchCallResponseItem for file search quotes
• MessageResponseItem.OutputTextAnnotations for citations

Workaround exists but adds complexity: Cast RawRepresentation to underlying types:

await foreach (var update in agent.RunStreamingAsync(message, thread))
{
    if (update.RawRepresentation is StreamingResponseOutputItemDoneUpdate itemDone)
    {
        if (itemDone.Item is McpToolCallApprovalRequestItem mcpApproval)
        {
            // Handle MCP approval...
        }
    }
}

Why we use direct SDK instead:

1. Casting RawRepresentation defeats the abstraction benefit
2. MCP approval flow requires ResponseItem.CreateMcpApprovalResponseItem() anyway
3. Direct SDK approach is clearer and matches SDK samples

What Agent Framework IS Good For

• Simple streaming — just text output with .Text property
• Multi-agent orchestration — sequential, concurrent, handoff patterns
• Graph-based workflows — streaming with checkpointing
• Built-in observability — OpenTelemetry integration
• Tool invocation — automatic AIFunction handling

Future Consideration

When Agent Framework matures to expose annotations/MCP through its abstractions, we could simplify to:

// Hypothetical future API
await foreach (var update in agent.RunStreamingAsync(message, thread))
{
    if (update.IsMcpApproval) { }       // Doesn't exist yet
    if (update.HasAnnotations) { }      // Doesn't exist yet  
}

Track progress at: https://github.com/microsoft/Agents-for-net

Resources:

• NuGet: https://www.nuget.org/packages/Microsoft.Agents.AI.AzureAI
• Documentation: https://learn.microsoft.com/agent-framework/
• Source: https://github.com/microsoft/Agents-for-net/tree/main/src/libraries
• API Reference: https://learn.microsoft.com/en-us/dotnet/api/microsoft.agents.ai.chatclientagent.runstreamingasync

Migration Notes

The SDK has evolved from connection string-based auth to project endpoint:

Old pattern (deprecated):

// DON'T USE - connection string deprecated in v1.0.0-beta.9+
var projectClient = new AIProjectClient(connectionString, new DefaultAzureCredential());

New pattern (current):

// USE THIS - project endpoint
var projectClient = new AIProjectClient(new Uri(projectEndpoint), new DefaultAzureCredential());

See: https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/ai/Azure.AI.Projects/AGENTS_MIGRATION_GUIDE.md

Additional SDK Resources

Fetch SDK Source from GitHub (Authoritative)

Type definitions live in these repos—read them directly:

• Azure.AI.Projects source: https://github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.Projects/src
• Azure.AI.Agents.Persistent samples: https://github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.Agents.Persistent/samples
• OpenAI.Responses types: https://github.com/openai/openai-dotnet/tree/main/src

GitHub Code Search

Search across all .NET codebases for real-world usage:

"ProjectResponsesClient CreateResponseStreamingAsync" language:csharp
"StreamingResponseOutputTextDeltaUpdate" language:csharp

This finds how other projects use these APIs, revealing patterns and edge cases.

PowerShell Reflection (When Docs Lag Behind)

Use when SDK docs are outdated or incomplete — the DLLs are the ground truth.

Works even when dotnet build fails (loads from NuGet cache):

cd backend/WebApp.Api; dotnet restore

# Option A: Load from build output (requires successful build)
$asm = [Reflection.Assembly]::LoadFrom((Resolve-Path "bin/Debug/net9.0/Azure.AI.Projects.dll"))

# Option B: Load from NuGet cache (works even if build fails — use for pre-release migrations)
$dll = Get-ChildItem "$env:USERPROFILE\.nuget\packages\azure.ai.projects" -Recurse -Filter "Azure.AI.Projects.dll" | Select-Object -Last 1
$asm = [Reflection.Assembly]::LoadFrom($dll.FullName)

# Find types matching a pattern
$asm.GetExportedTypes() | Where-Object { $_.Name -like "*Streaming*" } | ForEach-Object { $_.FullName }

# Get method signatures with parameter details
$type = $asm.GetType("Azure.AI.Projects.OpenAI.ProjectResponsesClient")
$type.GetMethods() | Where-Object { $_.Name -like "*Async*" } | Select-Object Name, ReturnType, @{N='Params';E={($_.GetParameters() | ForEach-Object { "$($_.ParameterType.Name) $($_.Name)" }) -join ', '}}

Agent Framework assemblies (for Microsoft.Agents.AI.AzureAI migrations):

# Load Agent Framework DLL from NuGet cache
$pkg = Get-ChildItem "$env:USERPROFILE\.nuget\packages\microsoft.agents.ai.azureai" -Recurse -Filter "Microsoft.Agents.AI.AzureAI.dll" | Select-Object -Last 1
$asm = [Reflection.Assembly]::LoadFrom($pkg.FullName)

# Dump all exported types to see what changed between versions
$asm.GetExportedTypes() | ForEach-Object { $_.FullName } | Sort-Object

# Check if types you depend on still exist
@("ChatClientAgent", "AgentVersion", "PromptAgentDefinition", "AgentReference") | ForEach-Object {
    $match = $asm.GetExportedTypes() | Where-Object { $_.Name -eq $_ }
    if ($match) { Write-Host "FOUND: $($match.FullName)" } else { Write-Host "MISSING: $_" -ForegroundColor Red }
}

# Inspect extension methods (GetAIAgentAsync, etc.)
$asm.GetExportedTypes() | Where-Object { $_.GetMethods([Reflection.BindingFlags]::Static -bor [Reflection.BindingFlags]::Public) | Where-Object { $_.IsDefined([Runtime.CompilerServices.ExtensionAttribute], $false) } } | ForEach-Object {
    $_.GetMethods() | Where-Object { $_.IsDefined([Runtime.CompilerServices.ExtensionAttribute], $false) } | ForEach-Object { Write-Host "$($_.DeclaringType.Name).$($_.Name)" }
}

When to use: SDK upgrade with breaking changes, pre-release packages where docs lag, verifying actual API surface before writing migration code.

Key insight: Load from NuGet cache ($env:USERPROFILE\.nuget\packages\) to inspect the new version’s types even when the build is broken.