Building a Proactive AI Assistant with TypeScript

What We’re Building

In this tutorial, we will build a proactive AI assistant integrated into a development environment using TypeScript. This assistant will provide intelligent code suggestions, help with debugging, and offer proactive assistance based on the developer’s activity. The AI will be capable of understanding the context of the current code and suggest improvements or corrections in real-time.

The finished project will be a TypeScript-based application that listens for changes in the code editor, analyzes the code, and uses AI to provide helpful suggestions and corrections. This will significantly enhance developer productivity by reducing the time spent on finding errors and improving code quality.

Setup and Installation

To begin, we need to set up a TypeScript environment and install necessary packages. We will be using Node.js for our server-side logic and OpenAI’s API for AI functionalities.

npm init -y
npm install typescript ts-node @types/node express openai dotenv

Next, we need to configure our environment variables to securely store our OpenAI API key. Create a new file named .env in the root directory of your project.

OPENAI_API_KEY=your-openai-api-key-here

Step 1: Setting Up the Server

In this step, we will set up a basic Express server to handle our AI requests. This server will receive code snippets from the client, process them, and return AI-generated suggestions.

import express from 'express';
import OpenAI from 'openai';
import dotenv from 'dotenv';dotenv.config();const app = express();
const port = 3000;const openai = new OpenAI({
apiKey: process.env.OPENAI_API_KEY,
});app.use(express.json());app.post('/suggest', async (req, res) => {
try {
const { code } = req.body;
const response = await openai.chat.completions.create({
model: "gpt-4o",
messages: [
{ role: "system", content: "You are a helpful coding assistant." },
...
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