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azure-ai-agents-persistent-dotnet

azure-ai-agents-persistent-dotnet

github.com/sickn33Agent workflows48.7k77 installsUpdated today
Repository

About azure-ai-agents-persistent-dotnet

A low-level .NET SDK for creating and managing persistent AI agents, threads, messages, runs, and tools. It supports asynchronous execution and streaming, with built-in and custom tool options.

Key features

  1. 01Create and manage agents and threads
  2. 02Send messages and execute runs
  3. 03Stream run status and text updates
  4. 04Configure file search and vector stores
  5. 05Connect functions and other tools

Use cases

  1. 01Building persistent AI agent applications
  2. 02Adding file search to an agent
  3. 03Handling custom function calls
  4. 04Showing run progress through streaming updates

MCP support

The SDK provides MCPToolDefinition for configuring MCP tools for an agent. The README does not describe MCP server connection or management details.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/sickn33/agentic-awesome-skills --skill azure-ai-agents-persistent-dotnet

After installing, type/azure-ai-agents-persistent-dotnetin Claude Code to confirm it loaded.

Details

From the project README

Azure.AI.Agents.Persistent (.NET)

Low-level SDK for creating and managing persistent AI agents with threads, messages, runs, and tools.

Installation

dotnet add package Azure.AI.Agents.Persistent --prerelease
dotnet add package Azure.Identity

Current Versions: Stable v1.1.0, Preview v1.2.0-beta.8

Environment Variables

PROJECT_ENDPOINT=https://<resource>.services.ai.azure.com/api/projects/<project>
MODEL_DEPLOYMENT_NAME=gpt-4o-mini
AZURE_BING_CONNECTION_ID=<bing-connection-resource-id>
AZURE_AI_SEARCH_CONNECTION_ID=<search-connection-resource-id>

Authentication

using Azure.AI.Agents.Persistent;
using Azure.Identity;

var projectEndpoint = Environment.GetEnvironmentVariable("PROJECT_ENDPOINT");
PersistentAgentsClient client = new(projectEndpoint, new DefaultAzureCredential());

Client Hierarchy

PersistentAgentsClient
├── Administration  → Agent CRUD operations
├── Threads         → Thread management
├── Messages        → Message operations
├── Runs            → Run execution and streaming
├── Files           → File upload/download
└── VectorStores    → Vector store management

Core Workflow

Pin compatible package versions and verify the linked SDK signatures; fragments use project-defined helper functions and are not a complete application. Confirm endpoint/deployment, authorized tool actions, upload scope and budget before runs. Use a finite cancellation deadline for polling/streaming and distinguish completed, failed, cancelled, expired and requires-action states before reading a final answer. Validate/allowlist each function name and typed argument set before execution; never execute raw model arguments as code or SQL. Delete only resources created by the current run in a finally block, preserving needed evidence.

1. Create Agent
var modelDeploymentName = Environment.GetEnvironmentVariable("MODEL_DEPLOYMENT_NAME");

PersistentAgent agent = await client.Administration.CreateAgentAsync(
    model: modelDeploymentName,
    name: "Math Tutor",
    instructions: "You are a personal math tutor. Write and run code to answer math questions.",
    tools: [new CodeInterpreterToolDefinition()]
);
2. Create Thread and Message
// Create thread
PersistentAgentThread thread = await client.Threads.CreateThreadAsync();

// Create message
await client.Messages.CreateMessageAsync(
    thread.Id,
    MessageRole.User,
    "I need to solve the equation `3x + 11 = 14`. Can you help me?"
);
3. Run Agent (Polling)
// Create run
ThreadRun run = await client.Runs.CreateRunAsync(
    thread.Id,
    agent.Id,
    additionalInstructions: "Please address the user as Jane Doe."
);

// Poll for completion
do
{
    await Task.Delay(TimeSpan.FromMilliseconds(500));
    run = await client.Runs.GetRunAsync(thread.Id, run.Id);
}
while (run.Status == RunStatus.Queued || run.Status == RunStatus.InProgress);

// Retrieve messages
await foreach (PersistentThreadMessage message in client.Messages.GetMessagesAsync(
    threadId: thread.Id, 
    order: ListSortOrder.Ascending))
{
    Console.Write($"{message.Role}: ");
    foreach (MessageContent content in message.ContentItems)
    {
        if (content is MessageTextContent textContent)
            Console.WriteLine(textContent.Text);
    }
}
4. Streaming Response
AsyncCollectionResult<StreamingUpdate> stream = client.Runs.CreateRunStreamingAsync(
    thread.Id, 
    agent.Id
);

await foreach (StreamingUpdate update in stream)
{
    if (update.UpdateKind == StreamingUpdateReason.RunCreated)
    {
        Console.WriteLine("--- Run started! ---");
    }
    else if (update is MessageContentUpdate contentUpdate)
    {
        Console.Write(contentUpdate.Text);
    }
    else if (update.UpdateKind == StreamingUpdateReason.RunCompleted)
    {
        Console.WriteLine("\n--- Run completed! ---");
    }
}
5. Function Calling
// Define function tool
FunctionToolDefinition weatherTool = new(
    name: "getCurrentWeather",
    description: "Gets the current weather at a location.",
    parameters: BinaryData.FromObjectAsJson(new
    {
        Type = "object",
        Properties = new
        {
            Location = new { Type = "string", Description = "City and state, e.g. San Francisco, CA" },
            Unit = new { Type = "string", Enum = new[] { "c", "f" } }
        },
        Required = new[] { "location" }
    }, new JsonSerializerOptions { PropertyNamingPolicy = JsonNamingPolicy.CamelCase })
);

// Create agent with function
PersistentAgent agent = await client.Administration.CreateAgentAsync(
    model: modelDeploymentName,
    name: "Weather Bot",
    instructions: "You are a weather bot.",
    tools: [weatherTool]
);

// Handle function calls during polling
do
{
    await Task.Delay(500);
    run = await client.Runs.GetRunAsync(thread.Id, run.Id);

    if (run.Status == RunStatus.RequiresAction 
        && run.RequiredAction is SubmitToolOutputsAction submitAction)
    {
        List<ToolOutput> outputs = [];
        foreach (RequiredToolCall toolCall in submitAction.ToolCalls)
        {
            if (toolCall is RequiredFunctionToolCall funcCall)
            {
                // Execute function and get result
                string result = ExecuteFunction(funcCall.Name, funcCall.Arguments);
                outputs.Add(new ToolOutput(toolCall, result));
            }
        }
        run = await client.Runs.SubmitToolOutputsToRunAsync(run, outputs, toolApprovals: null);
    }
}
while (run.Status == RunStatus.Queued || run.Status == RunStatus.InProgress);
6. File Search with Vector Store
// Upload file
PersistentAgentFileInfo file = await client.Files.UploadFileAsync(
    filePath: "document.txt",
    purpose: PersistentAgentFilePurpose.Agents
);

// Create vector store
PersistentAgentsVectorStore vectorStore = await client.VectorStores.CreateVectorStoreAsync(
    fileIds: [file.Id],
    name: "my_vector_store"
);

// Create file search resource
FileSearchToolResource fileSearchResource = new();
fileSearchResource.VectorStoreIds.Add(vectorStore.Id);

// Create agent with file search
PersistentAgent agent = await client.Administration.CreateAgentAsync(
    model: modelDeploymentName,
    name: "Document Assistant",
    instructions: "You help users find information in documents.",
    tools: [new FileSearchToolDefinition()],
    toolResources: new ToolResources { FileSearch = fileSearchResource }
);
7. Bing Grounding
var bingConnectionId = Environment.GetEnvironmentVariable("AZURE_BING_CONNECTION_ID");

BingGroundingToolDefinition bingTool = new(
    new BingGroundingSearchToolParameters(
        [new BingGroundingSearchConfiguration(bingConnectionId)]
    )
);

PersistentAgent agent = await client.Administration.CreateAgentAsync(
    model: modelDeploymentName,
    name: "Search Agent",
    instructions: "Use Bing to answer questions about current events.",
    tools: [bingTool]
);
8. Azure AI Search
AzureAISearchToolResource searchResource = new(
    connectionId: searchConnectionId,
    indexName: "my_index",
    topK: 5,
    filter: "category eq 'documentation'",
    queryType: AzureAISearchQueryType.Simple
);

PersistentAgent agent = await client.Administration.CreateAgentAsync(
    model: modelDeploymentName,
    name: "Search Agent",
    instructions: "Search the documentation index to answer questions.",
    tools: [new AzureAISearchToolDefinition()],
    toolResources: new ToolResources { AzureAISearch = searchResource }
);
9. Cleanup
await client.Threads.DeleteThreadAsync(thread.Id);
await client.Administration.DeleteAgentAsync(agent.Id);
await client.VectorStores.DeleteVectorStoreAsync(vectorStore.Id);
await client.Files.DeleteFileAsync(file.Id);

Available Tools

ToolClassPurpose
Code InterpreterCodeInterpreterToolDefinitionExecute Python code, generate visualizations
File SearchFileSearchToolDefinitionSearch uploaded files via vector stores
Function CallingFunctionToolDefinitionCall custom functions
Bing GroundingBingGroundingToolDefinitionWeb search via Bing
Azure AI SearchAzureAISearchToolDefinitionSearch Azure AI Search indexes
OpenAPIOpenApiToolDefinitionCall external APIs via OpenAPI spec
Azure FunctionsAzureFunctionToolDefinitionInvoke Azure Functions
MCPMCPToolDefinitionModel Context Protocol tools
SharePointSharepointToolDefinitionAccess SharePoint content
Microsoft FabricMicrosoftFabricToolDefinitionAccess Fabric data

Streaming Update Types

Update TypeDescription
StreamingUpdateReason.RunCreatedRun started
StreamingUpdateReason.RunInProgressRun processing
StreamingUpdateReason.RunCompletedRun finished
StreamingUpdateReason.RunFailedRun errored
MessageContentUpdateText content chunk
RunStepUpdateStep status change

Key Types Reference

TypePurpose
PersistentAgentsClientMain entry point
PersistentAgentAgent with model, instructions, tools
PersistentAgentThreadConversation thread
PersistentThreadMessageMessage in thread
ThreadRunExecution of agent against thread
RunStatusQueued, InProgress, RequiresAction, Completed, Failed
ToolResourcesCombined tool resources
ToolOutputFunction call response

Best Practices

  1. Reuse SDK clients according to the installed SDK lifetime guidance; do not assume every client implements IDisposable
  2. Poll with appropriate delays — 500ms recommended between status checks
  3. Clean up resources — Delete threads and agents when done
  4. Handle all run statuses — Check for RequiresAction, Failed, Cancelled
  5. Use streaming for real-time UX — Better user experience than polling
  6. Store IDs not objects — Reference agents/threads by ID
  7. Use async methods — All operations should be async

Error Handling

using Azure;

try
{
    var agent = await client.Administration.CreateAgentAsync(...);
}
catch (RequestFailedException ex) when (ex.Status == 404)
{
    Console.WriteLine("Resource not found");
}
catch (RequestFailedException ex)
{
    Console.WriteLine($"Error: {ex.Status} - {ex.ErrorCode}: {ex.Message}");
}

Related SDKs

SDKPurposeInstall
Azure.AI.Agents.PersistentLow-level agents (this SDK)dotnet add package Azure.AI.Agents.Persistent
Azure.AI.ProjectsHigh-level project clientdotnet add package Azure.AI.Projects

Reference Links

ResourceURL
NuGet Packagehttps://www.nuget.org/packages/Azure.AI.Agents.Persistent
API Referencehttps://learn.microsoft.com/dotnet/api/azure.ai.agents.persistent
GitHub Sourcehttps://github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.Agents.Persistent
Sampleshttps://github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.Agents.Persistent/samples

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

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