azure-ai-projects-dotnet
Cloud, DevOps & Systèmes|
Documentation
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 --prereleaseCurrent 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() → PersistentAgentsClientCore 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
DefaultAzureCredential for production authentication*Async) for all I/O operationsAzure.AI.Projects.OpenAI) for production scenariosincludeCredentials: true only when credentials are neededAsyncPageable for listing operationsError 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 |
Compétences similaires
Explorez d'autres agents de la catégorie Cloud, DevOps & Systèmes
azure-cosmos-db-py
Build Azure Cosmos DB NoSQL services with Python/FastAPI following production-grade patterns. Use when implementing database client setup with dual auth (DefaultAzureCredential + emulator), service layer classes with CRUD operations, partition key strategies, parameterized queries, or TDD patterns for Cosmos. Triggers on phrases like "Cosmos DB", "NoSQL database", "document store", "add persistence", "database service layer", or "Python Cosmos SDK".
azure-eventgrid-py
|
azure-functions
"Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js programming models. Use when: azure function, azure functions, durable functions, azure serverless, function app."