Azure OpenAI Integration

Updated on Aug 14, 2026

Use this integration when your app is implemented in Python, TypeScript, or .NET.

Setup

PythonTypeScript.NET

1. Install SDK

bash

pip install progress-observability

2. Instrument your app

python

Observability.instrument(
    app_name=os.getenv("OBSERVABILITY_APP_NAME"),
    api_key=os.getenv("OBSERVABILITY_API_KEY")
)

3. Complete example

python

import os

from dotenv import load_dotenv
from openai import AzureOpenAI

from progress.observability import Observability

load_dotenv()

# LLM INSTRUMENTATION
Observability.instrument(
    app_name=os.getenv("OBSERVABILITY_APP_NAME"),
    api_key=os.getenv("OBSERVABILITY_API_KEY"),
)


def main() -> None:
    client = AzureOpenAI(
        azure_endpoint=os.getenv("AZURE_API_ENDPOINT", ""),
        api_key=os.getenv("AZURE_API_KEY", ""),
        api_version=os.getenv("AZURE_API_VERSION", "2024-10-21"),
    )
    deployment = (
        os.getenv("AZURE_OPENAI_DEPLOYMENT")
        or os.getenv("AZURE_OPENAI_API_DEPLOYMENT_NAME")
        or "gpt-4o-mini"
    )

    response = client.chat.completions.create(
        model=deployment,
        max_tokens=256,
        messages=[
            {"role": "system", "content": "You are a helpful AI assistant."},
            {"role": "user", "content": "What is the capital of France?"},
        ],
    )



try:
    main()
finally:
    Observability.shutdown()

To get a richer trace tree when building agents on top of this provider, use the @agent, @tool, @workflow, or @task decorators. See the Python SDK for details.

1. Install SDK

bash

npm install @progress/observability

2. Instrument your app

TS

import '@progress/observability/register/hooks';
import { Observability } from '@progress/observability';
await Observability.instrument({
 appName: process.env.OBSERVABILITY_APP_NAME,
 apiKey: process.env.OBSERVABILITY_API_KEY
});

3. Complete example

TS

import '@progress/observability/register/hooks';
import 'dotenv/config';

import { AzureOpenAI } from 'openai';
import { Observability } from '@progress/observability';

const azureModel = 'gpt-4o-mini';
const azureApiVersion = process.env.AZURE_API_VERSION || '2024-06-01';
const azureDeployment =
  process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME || azureModel;

async function main() {
  await Observability.instrument({
    appName: process.env.OBSERVABILITY_APP_NAME ?? 'weather-agent-azure-sdk',
    apiKey: process.env.OBSERVABILITY_API_KEY,
  });

  try {
    const client = new AzureOpenAI({
      apiKey: process.env.AZURE_API_KEY,
      endpoint: process.env.AZURE_API_ENDPOINT,
      apiVersion: azureApiVersion,
      deployment: azureDeployment,
    });

    const result = await client.chat.completions.create({
      model: azureModel,
      max_completion_tokens: 256,
      messages: [
        { role: 'system', content: 'You are a helpful AI assistant.' },
        { role: 'user', content: 'What is the capital of France?' },
      ],
    });

  } finally {
    await Observability.shutdown();
  }
}

main().catch((error) => {
  console.error(error);
  process.exitCode = 1;
});

To get a richer trace tree when building agents on top of this provider, use the @agent, @tool, @workflow, or @task decorators. See the TypeScript SDK for details.

1. Install SDK

bash

dotnet add package Progress.Observability.Instrumentation

2. Instrument your app

cs

try
{
 chatClient = chatClient.AddObservability((options) =>
 {
 options.AppName = Environment.GetEnvironmentVariable("OBSERVABILITY_APP_NAME")!;
 options.ApiKey = Environment.GetEnvironmentVariable("OBSERVABILITY_API_KEY")!;
 });
 
 // Your code here.
}
finally
{
 // Call the Shutdown() method before exiting your agent to flush any remaining data.
 ObservabilityTracer.Shutdown();
}

3. Complete example

cs

using Microsoft.Extensions.AI;
using Azure.AI.OpenAI;
using System.ClientModel;
using Progress.Observability.Extensions.AI;
using DotNetEnv;

namespace Examples.AzureOpenAI;

public class Program
{
 public static async Task Main(string[] args)
 {
     try
     {
         Env.Load("../../.env");

         IChatClient chatClient = new AzureOpenAIClient(
             new Uri(Environment.GetEnvironmentVariable("AZURE_API_ENDPOINT")!),
             new ApiKeyCredential(Environment.GetEnvironmentVariable("AZURE_API_KEY")!))
             .GetChatClient("gpt-4o-mini")
             .AsIChatClient()
             .AddObservability((options) =>
             {
                 options.AppName = "AzureOpenAI Example";
                 options.ApiKey = Environment.GetEnvironmentVariable("OBSERVABILITY_API_KEY")!;
             });

         var response = await chatClient.GetResponseAsync(
             "What is the capital of France?");

         Console.WriteLine(response.Text ?? "No assistant text returned.");
     }
     finally
     {
         ObservabilityTracer.Shutdown();
     }
 }
}

To get a richer trace tree when building agents on top of this provider, use custom spans. See the .NET SDK for details.