Build an AI Agent

TimeUnder 10 minutes

What you'll buildAn AI agent that connects to an LLM, uses tools, and responds to user queries in chat.

An AI agent uses an LLM to reason about user queries and call tools to retrieve information or perform actions. This quick start shows the full cycle: create a project, add an AI Chat Agent artifact, configure its instructions, and test it in the built-in chat panel.

Prerequisites

A working WSO2 Integrator environment.

WSO2 Cloud setupSign up and launch WSO2 Integrator in the browser-based cloud editor.

Architecture

Step 1: Create the integration

1. On the project home page, click Create on Cloud.

   

2. The WSO2 Integrator cloud editor opens in your browser. Add an artifact to your integration, then deploy it to WSO2 Cloud from the Deploy to WSO2 Cloud panel on the right.

   

Step 2: Add an AI chat agent

1. Select your integration from the project overview canvas.
2. Select + Add Artifact in the design canvas.
3. Select AI Chat Agent under AI Integration.
4. Set Name to Wso2IntegratorAssistant.
5. Select Create.

Step 3: Configure the AI agent

1. Select the Wso2IntegratorAssistant node on the canvas.
2. Set Instructions to You are a highly skilled WSO2 Integration Architect. Your goal is to assist developers in building, debugging, and optimizing integration flows..
3. Select Save.

Default model provider

By default, the agent is configured to use the WSO2 model provider. If you want to use a different LLM, see Model providers for the full list of supported providers (OpenAI, Azure OpenAI, Anthropic, and others).

If you are using the WSO2 model provider, the access token is obtained through WSO2 Integrator Copilot. If you have not already signed in, you will be prompted to do so.

Step 4: Run and test

1. Select Run.
2. Select Chat from the AI Chat Agent title bar or select Test from the pop-up.
3. Type Hello to check if it works.

Step 5: Deploy to WSO2 Cloud

Deploy your integration to WSO2 Cloud. Check Save and deploy.

Skip ahead: deploy a ready-made sample

Rather not build it yourself? One-click deploy the AIAgent sample straight to WSO2 Cloud.

Source code

View the generated Ballerina code

The steps above generate two files: agents.bal for the agent definition and main.bal for the listener and service.

agents.bal

import ballerina/ai;

final ai:Agent wso2IntegratorAssistantAgent = check new (
    systemPrompt = {
        role: string `Wso2IntegratorAssistant`,
        instructions: string `You are a highly skilled WSO2 Integration Architect. Your goal is to assist developers in building, debugging, and optimizing integration flows.`
    },
    model = wso2ModelProvider,
    tools = []
);

main.bal

import ballerina/ai;
import ballerina/http;

listener ai:Listener chatAgentListener = new (listenOn = check http:getDefaultListener());

service /wso2IntegratorAssistant on chatAgentListener {
    resource function post chat(@http:Payload ai:ChatReqMessage request) returns ai:ChatRespMessage|error {
        string stringResult = check wso2IntegratorAssistantAgent.run(request.message, request.sessionId);
        return {message: stringResult};
    }
}