Integrating AI into Web Apps: Best Practices

Building Smart Web Applications with AIConnecting Large Language Models (LLMs) to custom web applications has become a standard requirement for modern SaaS platforms. However, poor integration can result in slow page loads, high token costs, and security issues. Here are the best practices.---1. Securing Your API KeysNever request LLM APIs directly from the browser frontend. This exposes your keys and allows anyone to hijack your account. Always route requests through a secure server endpoint:typescript// Server-side route (e.g. Next.js Route Handler)import { NextRequest, NextResponse } from 'next/server';export async function POST(req: NextRequest) { const { prompt } = await req.json(); const res = await fetch('https://api.openai.com/v1/chat/completions', { method: 'POST', headers: { 'Authorization': Bearer ${process.env.OPENAI_API_KEY}, 'Content-Type': 'application/json' }, body: JSON.stringify({ model: 'gpt-4', messages: [{ role: 'user', content: prompt }] }) }); return NextResponse.json(await res.json());}---2. Implementing Streaming ResponsesLLM APIs can take seconds to complete requests. To keep interfaces feeling fast, use Streaming Responses to render text on the screen word-by-word as it is generated, instead of waiting for the full payload.Using these patterns keeps your AI integrations secure, fast, and highly interactive.