AI  

How to Build an AI Agent Using Azure

🔧 Step 1. Set Up Azure OpenAI

First, you’ll need an Azure account. Sign up here if you don’t already have one.

✅ Create an Azure OpenAI Resource

  1. Go to the Azure Portal
  2. Search for Azure OpenAI in the Marketplace.
  3. Click Create, select your Subscription, Resource Group, and Region.
  4. Agree to Microsoft’s responsible AI use terms and deploy.

✅ Deploy a GPT Model

Once the resource is live:

  • Go to the Deployments tab.
  • Deploy a model like gpt-3.5-turbo or gpt-4.

🔑 Step 2. Get Your API Credentials

After deployment:

  1. Go to the Keys and Endpoint section.
  2. Copy your:
    • Endpoint URL
    • API Key

You’ll use these to authenticate your requests.

⚙️ Step 3. Create the AI Agent Logic with Azure Functions

Let’s use Azure Functions (serverless backend) to handle user queries.

🧪 Sample Azure Function (Node.js)

const { OpenAIClient, AzureKeyCredential } = require("@azure/openai");

module.exports = async function (context, req) {
    const client = new OpenAIClient(
        "https://<your-resource-name>.openai.azure.com/",
        new AzureKeyCredential("<your-api-key>")
    );

    const deploymentId = "<your-deployment-id>";
    const userInput = req.body.message;

    const response = await client.getChatCompletions(deploymentId, [
        { role: "system", content: "You are a helpful assistant." },
        { role: "user", content: userInput }
    ]);

    context.res = {
        body: { response: response.choices[0].message.content }
    };
};

You can deploy this function using VS Code or the Azure CLI.

💬 Step 4. Add Chatbot Capabilities with Azure Bot Service

Want to turn your AI into a full chatbot?

  1. Create a Bot Channels Registration in Azure.
  2. Point it to your Azure Function endpoint.
  3. Connect it to platforms like:
    Microsoft Teams
    Telegram
    Web Chat (embed on your site)

This gives your AI agent a voice on your favorite platforms.

🖥️ Step 5. Integrate with Your Frontend

Use a simple fetch() or axios call from your frontend to send queries to the Azure Function.

const sendQuery = async (message) => {
  const res = await fetch("/api/ai-agent", {
    method: "POST",
    headers: { "Content-Type": "application/json" },
    body: JSON.stringify({ message }),
  });

  const data = await res.json();
  console.log(data.response);
};

Now you have a live AI assistant in your web or mobile app.

🔐 Step 6. Secure Your AI Agent

Don’t forget to secure it:

  • Use Azure API Management to expose your API safely.
  • Store secrets in Azure Key Vault.
  • Enable CORS, rate limiting, and auth tokens as needed.

🎯 Final Output Example

Here’s the kind of JSON response your AI agent can return.

{
  "response": "Sure! I can help you track your order. Please provide your order ID."
}

🧩 Wrap Up

Creating an AI agent on Azure is surprisingly straightforward. With a few clicks and some code, you can build a highly intelligent assistant for websites, apps, or chat platforms.

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