azure-ai-projects-dotnet

📁 microsoft/skills 📅 9 days ago
0
总安装量
4
周安装量
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全站排名
安装命令
npx skills add https://github.com/microsoft/skills --skill azure-ai-projects-dotnet

Agent 安装分布

opencode 3
gemini-cli 3
claude-code 3
github-copilot 3
codex 3
kimi-cli 2

Skill 文档

Azure.AI.Projects (.NET)

High-level SDK for Azure AI Foundry project operations including agents, connections, datasets, deployments, evaluations, and indexes.

Installation

dotnet add package Azure.AI.Projects
dotnet add package Azure.Identity

# Optional: For versioned agents with OpenAI extensions
dotnet add package Azure.AI.Projects.OpenAI --prerelease

# Optional: For low-level agent operations
dotnet add package Azure.AI.Agents.Persistent --prerelease

Current Versions: GA v1.1.0, Preview v1.2.0-beta.5

Environment Variables

PROJECT_ENDPOINT=https://<resource>.services.ai.azure.com/api/projects/<project>
MODEL_DEPLOYMENT_NAME=gpt-4o-mini
CONNECTION_NAME=<your-connection-name>
AI_SEARCH_CONNECTION_NAME=<ai-search-connection>

Authentication

using Azure.Identity;
using Azure.AI.Projects;

var endpoint = Environment.GetEnvironmentVariable("PROJECT_ENDPOINT");
AIProjectClient projectClient = new AIProjectClient(
    new Uri(endpoint), 
    new DefaultAzureCredential());

Client Hierarchy

AIProjectClient
├── Agents          → AIProjectAgentsOperations (versioned agents)
├── Connections     → ConnectionsClient
├── Datasets        → DatasetsClient
├── Deployments     → DeploymentsClient
├── Evaluations     → EvaluationsClient
├── Evaluators      → EvaluatorsClient
├── Indexes         → IndexesClient
├── Telemetry       → AIProjectTelemetry
├── OpenAI          → ProjectOpenAIClient (preview)
└── GetPersistentAgentsClient() → PersistentAgentsClient

Core Workflows

1. Get Persistent Agents Client

// Get low-level agents client from project client
PersistentAgentsClient agentsClient = projectClient.GetPersistentAgentsClient();

// Create agent
PersistentAgent agent = await agentsClient.Administration.CreateAgentAsync(
    model: "gpt-4o-mini",
    name: "Math Tutor",
    instructions: "You are a personal math tutor.");

// Create thread and run
PersistentAgentThread thread = await agentsClient.Threads.CreateThreadAsync();
await agentsClient.Messages.CreateMessageAsync(thread.Id, MessageRole.User, "Solve 3x + 11 = 14");
ThreadRun run = await agentsClient.Runs.CreateRunAsync(thread.Id, agent.Id);

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

// Get messages
await foreach (var msg in agentsClient.Messages.GetMessagesAsync(thread.Id))
{
    foreach (var content in msg.ContentItems)
    {
        if (content is MessageTextContent textContent)
            Console.WriteLine(textContent.Text);
    }
}

// Cleanup
await agentsClient.Threads.DeleteThreadAsync(thread.Id);
await agentsClient.Administration.DeleteAgentAsync(agent.Id);

2. Versioned Agents with Tools (Preview)

using Azure.AI.Projects.OpenAI;

// Create agent with web search tool
PromptAgentDefinition agentDefinition = new(model: "gpt-4o-mini")
{
    Instructions = "You are a helpful assistant that can search the web",
    Tools = {
        ResponseTool.CreateWebSearchTool(
            userLocation: WebSearchToolLocation.CreateApproximateLocation(
                country: "US",
                city: "Seattle",
                region: "Washington"
            )
        ),
    }
};

AgentVersion agentVersion = await projectClient.Agents.CreateAgentVersionAsync(
    agentName: "myAgent",
    options: new(agentDefinition));

// Get response client
ProjectResponsesClient responseClient = projectClient.OpenAI.GetProjectResponsesClientForAgent(agentVersion.Name);

// Create response
ResponseResult response = responseClient.CreateResponse("What's the weather in Seattle?");
Console.WriteLine(response.GetOutputText());

// Cleanup
projectClient.Agents.DeleteAgentVersion(agentName: agentVersion.Name, agentVersion: agentVersion.Version);

3. Connections

// List all connections
foreach (AIProjectConnection connection in projectClient.Connections.GetConnections())
{
    Console.WriteLine($"{connection.Name}: {connection.ConnectionType}");
}

// Get specific connection
AIProjectConnection conn = projectClient.Connections.GetConnection(
    connectionName, 
    includeCredentials: true);

// Get default connection
AIProjectConnection defaultConn = projectClient.Connections.GetDefaultConnection(
    includeCredentials: false);

4. Deployments

// List all deployments
foreach (AIProjectDeployment deployment in projectClient.Deployments.GetDeployments())
{
    Console.WriteLine($"{deployment.Name}: {deployment.ModelName}");
}

// Filter by publisher
foreach (var deployment in projectClient.Deployments.GetDeployments(modelPublisher: "Microsoft"))
{
    Console.WriteLine(deployment.Name);
}

// Get specific deployment
ModelDeployment details = (ModelDeployment)projectClient.Deployments.GetDeployment("gpt-4o-mini");

5. Datasets

// Upload single file
FileDataset fileDataset = projectClient.Datasets.UploadFile(
    name: "my-dataset",
    version: "1.0",
    filePath: "data/training.txt",
    connectionName: connectionName);

// Upload folder
FolderDataset folderDataset = projectClient.Datasets.UploadFolder(
    name: "my-dataset",
    version: "2.0",
    folderPath: "data/training",
    connectionName: connectionName,
    filePattern: new Regex(".*\\.txt"));

// Get dataset
AIProjectDataset dataset = projectClient.Datasets.GetDataset("my-dataset", "1.0");

// Delete dataset
projectClient.Datasets.Delete("my-dataset", "1.0");

6. Indexes

// Create Azure AI Search index
AzureAISearchIndex searchIndex = new(aiSearchConnectionName, aiSearchIndexName)
{
    Description = "Sample Index"
};

searchIndex = (AzureAISearchIndex)projectClient.Indexes.CreateOrUpdate(
    name: "my-index",
    version: "1.0",
    index: searchIndex);

// List indexes
foreach (AIProjectIndex index in projectClient.Indexes.GetIndexes())
{
    Console.WriteLine(index.Name);
}

// Delete index
projectClient.Indexes.Delete(name: "my-index", version: "1.0");

7. Evaluations

// Create evaluation configuration
var evaluatorConfig = new EvaluatorConfiguration(id: EvaluatorIDs.Relevance);
evaluatorConfig.InitParams.Add("deployment_name", BinaryData.FromObjectAsJson("gpt-4o"));

// Create evaluation
Evaluation evaluation = new Evaluation(
    data: new InputDataset("<dataset_id>"),
    evaluators: new Dictionary<string, EvaluatorConfiguration> 
    { 
        { "relevance", evaluatorConfig } 
    }
)
{
    DisplayName = "Sample Evaluation"
};

// Run evaluation
Evaluation result = projectClient.Evaluations.Create(evaluation: evaluation);

// Get evaluation
Evaluation getResult = projectClient.Evaluations.Get(result.Name);

// List evaluations
foreach (var eval in projectClient.Evaluations.GetAll())
{
    Console.WriteLine($"{eval.DisplayName}: {eval.Status}");
}

8. Get Azure OpenAI Chat Client

using Azure.AI.OpenAI;
using OpenAI.Chat;

ClientConnection connection = projectClient.GetConnection(typeof(AzureOpenAIClient).FullName!);

if (!connection.TryGetLocatorAsUri(out Uri uri) || uri is null)
    throw new InvalidOperationException("Invalid URI.");

uri = new Uri($"https://{uri.Host}");

AzureOpenAIClient azureOpenAIClient = new AzureOpenAIClient(uri, new DefaultAzureCredential());
ChatClient chatClient = azureOpenAIClient.GetChatClient("gpt-4o-mini");

ChatCompletion result = chatClient.CompleteChat("List all rainbow colors");
Console.WriteLine(result.Content[0].Text);

Available Agent Tools

Tool Class Purpose
Code Interpreter CodeInterpreterToolDefinition Execute Python code
File Search FileSearchToolDefinition Search uploaded files
Function Calling FunctionToolDefinition Call custom functions
Bing Grounding BingGroundingToolDefinition Web search via Bing
Azure AI Search AzureAISearchToolDefinition Search Azure AI indexes
OpenAPI OpenApiToolDefinition Call external APIs
Azure Functions AzureFunctionToolDefinition Invoke Azure Functions
MCP MCPToolDefinition Model Context Protocol tools

Key Types Reference

Type Purpose
AIProjectClient Main entry point
PersistentAgentsClient Low-level agent operations
PromptAgentDefinition Versioned agent definition
AgentVersion Versioned agent instance
AIProjectConnection Connection to Azure resource
AIProjectDeployment Model deployment info
AIProjectDataset Dataset metadata
AIProjectIndex Search index metadata
Evaluation Evaluation configuration and results

Best Practices

  1. Use DefaultAzureCredential for production authentication
  2. Use async methods (*Async) for all I/O operations
  3. Poll with appropriate delays (500ms recommended) when waiting for runs
  4. Clean up resources — delete threads, agents, and files when done
  5. Use versioned agents (via Azure.AI.Projects.OpenAI) for production scenarios
  6. Store connection IDs rather than names for tool configurations
  7. Use includeCredentials: true only when credentials are needed
  8. Handle pagination — use AsyncPageable<T> for listing operations

Error Handling

using Azure;

try
{
    var result = await projectClient.Evaluations.CreateAsync(evaluation);
}
catch (RequestFailedException ex)
{
    Console.WriteLine($"Error: {ex.Status} - {ex.ErrorCode}: {ex.Message}");
}

Related SDKs

SDK Purpose Install
Azure.AI.Projects High-level project client (this SDK) dotnet add package Azure.AI.Projects
Azure.AI.Agents.Persistent Low-level agent operations dotnet add package Azure.AI.Agents.Persistent
Azure.AI.Projects.OpenAI Versioned agents with OpenAI dotnet add package Azure.AI.Projects.OpenAI

Reference Links

Resource URL
NuGet Package https://www.nuget.org/packages/Azure.AI.Projects
API Reference https://learn.microsoft.com/dotnet/api/azure.ai.projects
GitHub Source https://github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.Projects
Samples https://github.com/Azure/azure-sdk-for-net/tree/main/sdk/ai/Azure.AI.Projects/samples