Integrating AI into Your Web Applications

AI integration is no longer optional for modern applications. Here's how we approach adding AI capabilities to client projects.

Choosing the Right AI Service

Different AI providers excel at different tasks:

API Integration Patterns

Keep your API keys secure with environment variables:

// api/chat/route.ts
import { OpenAI } from 'openai';

const openai = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY,
});

export async function POST(req: Request) {
  const { message } = await req.json();

  const response = await openai.chat.completions.create({
    model: 'gpt-4',
    messages: [{ role: 'user', content: message }],
  });

  return Response.json({
    reply: response.choices[0].message.content
  });
}

Streaming Responses

For better UX, stream responses to show text as it's generated:

const stream = await openai.chat.completions.create({
  model: 'gpt-4',
  messages: [{ role: 'user', content: message }],
  stream: true,
});

for await (const chunk of stream) {
  // Send chunk to client
}

Cost Management

AI APIs can get expensive. Implement:

Conclusion

AI integration adds significant value to applications when done thoughtfully. Start small, measure impact, and iterate.