azure-ai-projects-dotnet — Управление проектами Azure AI Foundry на C#

--- name: azure-ai-projects-dotnet description: Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes. risk: unknown source: community date_added: '2026-02-27' --- # Azure.AI.Projects (.NET) High-level SDK for Azure AI Foundry project operations including agents, connections, datasets, deployments, evaluations, and indexes. ## Installation ```bash 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 ```bash 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 ```csharp 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 ```csharp // 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) ```csharp 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 ```csharp // List all connections foreach (AIProjectConnection connection in projectClient.Connections.GetConnections()) { Console.WriteLine($"{connection.Name}: {connection.ConnectionType}"); } // Get specific connection AIProjectConnection conn = projectClient.Connections.GetConnection( connectionName, includeCredentials: true); // Get default connection AIProjectConnection defaultConn = projectClient.Connections.GetDefaultConnection( includeCredentials: false); ``` ### 4. Deployments ```csharp // List all deployments foreach (AIProjectDeployment deployment in projectClient.Deployments.GetDeployments()) { Console.WriteLine($"{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 ```csharp // 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 ```csharp // 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 ```csharp // 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($"{eval.DisplayName}: {eval.Status}"); } ``` ### 8. Get Azure OpenAI Chat Client ```csharp using Azure.AI.OpenAI; using OpenAI.Chat; ClientConnection connection = projectClient.GetConnection(typeof(AzureOpenAIClient).FullName!); if (!connection.TryGetLocatorAsUri(out Uri uri) || uri is null) throw new InvalidOperationException("Invalid URI."); uri = new Uri($"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 ```csharp 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 | ## When to Use This skill is applicable to execute the workflow or actions described in the overview.