Generated banner for Azure AI Projects TS
Generated logo for Azure AI Projects TS

Azure AI Projects TS

MicrosoftOfficialCreated by Microsoft

  • Skill
  • Tool integration
  • Software development
  • MIT
  • No issues found

From the author

Build AI applications using Azure AI Projects SDK for JavaScript (@azure/ai-projects). Use when working with Foundry project clients, agents, connections, deployments, datasets, indexes, evaluations, or getting OpenAI clients.
— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The Azure AI Projects SDK for TypeScript provides a high-level interface for interacting with Azure AI Foundry projects. It enables developers to manage AI agents, model deployments, connections to Azure resources, datasets, search indexes, and evaluation metrics. The SDK simplifies the integration of various AI tools, including code interpreters, file search, and custom function calling, while providing access to OpenAI clients for conversational workflows.

What it does

  • Create and manage AI agents with custom instructions and tools
  • List and retrieve connections to Azure resources like OpenAI and AI Search
  • Upload and manage datasets for AI model training or evaluation
  • Configure and manage search indexes for RAG applications
  • Execute and monitor evaluations to assess model output quality
  • Access OpenAI clients for generating responses and managing conversations

When to use it

  • When building AI applications within the Azure AI Foundry ecosystem
  • When you need to programmatically manage agent lifecycles and versions
  • When integrating Azure AI Search or other data sources into AI workflows
  • When performing automated quality assessments on model outputs
  • When managing connections to Azure services securely within your application

Advantages

  • Unified interface for diverse AI project components
  • Supports complex agent tools like code interpreters and web search
  • Provides built-in support for evaluation metrics like groundedness and relevance
  • Simplifies authentication using standard Azure identity credentials
  • Enables programmatic management of datasets and model deployments

Usage examples

“How do I create an AI agent with a code interpreter tool using the SDK?”
The agent is created using client.agents.createVersion with the 'code_interpreter' tool type and 'auto' container configuration.
“How can I list all available model deployments in my project?”
You iterate through client.deployments.list() and filter by type or publisher to identify specific model deployments.
“How do I run a groundedness evaluation on my RAG application?”
You use client.evaluations.create with your dataset and specify 'groundedness' as a builtin evaluator to receive metrics.
“How do I get an OpenAI client from my project connection?”
You call await client.getOpenAIClient() to retrieve an instance configured for your project's resources.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/microsoft/azure-ai-projects-ts/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip azure-ai-projects-ts.zip -d .agents/skills

Documentation by Microsoft

Azure AI Projects SDK for TypeScript

High-level SDK for Azure AI Foundry projects with agents, connections, deployments, and evaluations.

Installation

npm install @azure/ai-projects @azure/identity

For tracing:

npm install @azure/monitor-opentelemetry @opentelemetry/api

Environment Variables

AZURE_AI_PROJECT_ENDPOINT=https://<resource>.services.ai.azure.com/api/projects/<project>
MODEL_DEPLOYMENT_NAME=gpt-4o
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production

Authentication

import { AIProjectClient } from "@azure/ai-projects";
import { DefaultAzureCredential, ManagedIdentityCredential } from "@azure/identity";

// Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
const credential = new DefaultAzureCredential({requiredEnvVars: ["AZURE_TOKEN_CREDENTIALS"]});
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/javascript/api/overview/azure/identity-readme?view=azure-node-latest#credential-classes
// const credential = new ManagedIdentityCredential();

const client = new AIProjectClient(
  process.env.AZURE_AI_PROJECT_ENDPOINT!,
  credential
);

Operation Groups

GroupPurpose
client.agentsCreate and manage AI agents
client.connectionsList connected Azure resources
client.deploymentsList model deployments
client.datasetsUpload and manage datasets
client.indexesCreate and manage search indexes
client.evaluatorsManage evaluation metrics
client.memoryStoresManage agent memory

Getting OpenAI Client

const openAIClient = await client.getOpenAIClient();

// Use for responses
const response = await openAIClient.responses.create({
  model: "gpt-4o",
  input: "What is the capital of France?"
});

// Use for conversations
const conversation = await openAIClient.conversations.create({
  items: [{ type: "message", role: "user", content: "Hello!" }]
});

Agents

Create Agent
const agent = await client.agents.createVersion("my-agent", {
  kind: "prompt",
  model: "gpt-4o",
  instructions: "You are a helpful assistant."
});
Agent with Tools
// Code Interpreter
const agent = await client.agents.createVersion("code-agent", {
  kind: "prompt",
  model: "gpt-4o",
  instructions: "You can execute code.",
  tools: [{ type: "code_interpreter", container: { type: "auto" } }]
});

// File Search
const agent = await client.agents.createVersion("search-agent", {
  kind: "prompt",
  model: "gpt-4o",
  tools: [{ type: "file_search", vector_store_ids: [vectorStoreId] }]
});

// Web Search
const agent = await client.agents.createVersion("web-agent", {
  kind: "prompt",
  model: "gpt-4o",
  tools: [{
    type: "web_search_preview",
    user_location: { type: "approximate", country: "US", city: "Seattle" }
  }]
});

// Azure AI Search
const agent = await client.agents.createVersion("aisearch-agent", {
  kind: "prompt",
  model: "gpt-4o",
  tools: [{
    type: "azure_ai_search",
    azure_ai_search: {
      indexes: [{
        project_connection_id: connectionId,
        index_name: "my-index",
        query_type: "simple"
      }]
    }
  }]
});

// Function Tool
const agent = await client.agents.createVersion("func-agent", {
  kind: "prompt",
  model: "gpt-4o",
  tools: [{
    type: "function",
    function: {
      name: "get_weather",
      description: "Get weather for a location",
      strict: true,
      parameters: {
        type: "object",
        properties: { location: { type: "string" } },
        required: ["location"]
      }
    }
  }]
});

// MCP Tool
const agent = await client.agents.createVersion("mcp-agent", {
  kind: "prompt",
  model: "gpt-4o",
  tools: [{
    type: "mcp",
    server_label: "my-mcp",
    server_url: "https://mcp-server.example.com",
    require_approval: "always"
  }]
});
Run Agent
const openAIClient = await client.getOpenAIClient();

// Create conversation
const conversation = await openAIClient.conversations.create({
  items: [{ type: "message", role: "user", content: "Hello!" }]
});

// Generate response using agent
const response = await openAIClient.responses.create(
  { conversation: conversation.id },
  { body: { agent: { name: agent.name, type: "agent_reference" } } }
);

// Cleanup
await openAIClient.conversations.delete(conversation.id);
await client.agents.deleteVersion(agent.name, agent.version);

Connections

// List all connections
for await (const conn of client.connections.list()) {
  console.log(conn.name, conn.type);
}

// Get connection by name
const conn = await client.connections.get("my-connection");

// Get connection with credentials
const connWithCreds = await client.connections.getWithCredentials("my-connection");

// Get default connection by type
const defaultAzureOpenAI = await client.connections.getDefault("AzureOpenAI", true);

Deployments

// List all deployments
for await (const deployment of client.deployments.list()) {
  if (deployment.type === "ModelDeployment") {
    console.log(deployment.name, deployment.modelName);
  }
}

// Filter by publisher
for await (const d of client.deployments.list({ modelPublisher: "OpenAI" })) {
  console.log(d.name);
}

// Get specific deployment
const deployment = await client.deployments.get("gpt-4o");

Datasets

// Upload single file
const dataset = await client.datasets.uploadFile(
  "my-dataset",
  "1.0",
  "./data/training.jsonl"
);

// Upload folder
const dataset = await client.datasets.uploadFolder(
  "my-dataset",
  "2.0",
  "./data/documents/"
);

// Get dataset
const ds = await client.datasets.get("my-dataset", "1.0");

// List versions
for await (const version of client.datasets.listVersions("my-dataset")) {
  console.log(version);
}

// Delete
await client.datasets.delete("my-dataset", "1.0");

Indexes

import { AzureAISearchIndex } from "@azure/ai-projects";

const indexConfig: AzureAISearchIndex = {
  name: "my-index",
  type: "AzureSearch",
  version: "1",
  indexName: "my-index",
  connectionName: "search-connection"
};

// Create index
const index = await client.indexes.createOrUpdate("my-index", "1", indexConfig);

// List indexes
for await (const idx of client.indexes.list()) {
  console.log(idx.name);
}

// Delete
await client.indexes.delete("my-index", "1");

Key Types

import {
  AIProjectClient,
  AIProjectClientOptionalParams,
  Connection,
  ModelDeployment,
  DatasetVersionUnion,
  AzureAISearchIndex
} from "@azure/ai-projects";

Best Practices

  1. Use getOpenAIClient() - For responses, conversations, files, and vector stores

  2. Version your agents - Use createVersion for reproducible agent definitions

  3. Clean up resources - Delete agents, conversations when done

  4. Use connections - Get credentials from project connections, don't hardcode

  5. Filter deployments - Use modelPublisher filter to find specific models

Files

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Node.js

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Microsoft
Publisher
Microsoft (Official)
Source
microsoft/skills · .github/plugins/azure-sdk-typescript/skills/azure-ai-projects-ts · commit 0696600
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Microsoft or Microsoft.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download azure-ai-projects-ts.zip