Skip to contentazure-ai-projects-ts · agentic-awesome-skills · FlowyHigh-level SDK for Azure AI Foundry projects with agents, connections, deployments, and evaluations.
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High-level SDK for Azure AI Foundry projects with agents, connections, deployments, and evaluations.
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azure-ai-projects-ts.SKILL.md
---
name: azure-ai-projects-ts
description: "High-level SDK for Azure AI Foundry projects with agents, connections, deployments, and evaluations."
risk: unknown
source: community
date_added: "2026-02-27"
---
# Azure AI Projects SDK for TypeScript
High-level SDK for Azure AI Foundry projects with agents, connections, deployments, and evaluations.
## Installation
```bash
npm install @azure/ai-projects @azure/identity
```
For tracing:
```bash
npm install @azure/monitor-opentelemetry @opentelemetry/api
```
## Environment Variables
```bash
AZURE_AI_PROJECT_ENDPOINT=https://<resource>.services.ai.azure.com/api/projects/<project>
MODEL_DEPLOYMENT_NAME=gpt-4o
```
## Authentication
```typescript
import { AIProjectClient } from "@azure/ai-projects";
import { DefaultAzureCredential } from "@azure/identity";
const client = new AIProjectClient(
process.env.AZURE_AI_PROJECT_ENDPOINT!,
new DefaultAzureCredential()
);
```
## Operation Groups
| Group | Purpose |
|-------|---------|
| `client.agents` | Create and manage AI agents |
| `client.connections` | List connected Azure resources |
| `client.deployments` | List model deployments |
| `client.datasets` | Upload and manage datasets |
| `client.indexes` | Create and manage search indexes |
| `client.evaluators` | Manage evaluation metrics |
| `client.memoryStores` | Manage agent memory |
## Getting OpenAI Client
```typescript
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
```typescript
const agent = await client.agents.createVersion("my-agent", {
kind: "prompt",
model: "gpt-4o",
instructions: "You are a helpful assistant."
});
```
### Agent with Tools
```typescript
// 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
```typescript
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
```typescript
// 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
```typescript
// 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
```typescript
// 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
```typescript
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
```typescript
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
## 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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