AI Development with TypeScript 2026

Introduction

TypeScript is used for web apps, React, Node.js, APIs. This guide shows you the best AI tools, SDKs, and patterns for TypeScript developers building AI-powered applications.

Top AI SDKs for TypeScript

Recommended: Vercel AI SDK, OpenAI SDK

1. Vercel AI SDK

The Vercel AI SDK library is well-maintained and production-tested.

bash
Install
npm install vercel-ai-sdk

2. OpenAI SDK

The OpenAI SDK library is well-maintained and production-tested.

bash
Install
npm install openai-sdk

Quick Start

typescript
// TypeScript AI quick start
import OpenAI from 'openai';
const client = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
async function aiChat(message: string): Promise {
  const response = await client.chat.completions.create({
    model: 'gpt-4o-mini',
    messages: [{ role: 'user', content: message }]
  });
  return response.choices[0].message.content || '';
}
aiChat('Hello from TypeScript!').then(console.log);

TypeScript-Specific Best Practices

Error Handling

typescript
import { RateLimitError } from 'openai';
async function safeAICall(message: string, maxRetries = 3): Promise {
  for (let i = 0; i < maxRetries; i++) {
    try {
      return await aiChat(message);
    } catch (error) {
      if (error instanceof RateLimitError && i < maxRetries - 1) {
        await new Promise(r => setTimeout(r, 1000 * Math.pow(2, i)));
      } else {
        throw error;
      }
    }
  }
  throw new Error('Max retries exceeded');
}

Streaming

typescript
// TypeScript streaming
async function* streamResponse(prompt: string): AsyncGenerator {
  const stream = await client.chat.completions.create({
    model: 'gpt-4o-mini',
    messages: [{ role: 'user', content: prompt }],
    stream: true
  });
  
  for await (const chunk of stream) {
    const content = chunk.choices[0]?.delta?.content;
    if (content) yield content;
  }
}
// Usage
for await (const token of streamResponse("Tell me about AI")) {
  process.stdout.write(token);
}

Structured Output

typescript
import { z } from 'zod';
const AnalysisSchema = z.object({
  summary: z.string(),
  keyPoints: z.array(z.string()),
  sentiment: z.enum(['positive', 'negative', 'neutral'])
});
type Analysis = z.infer;
async function analyze(text: string): Promise {
  const response = await client.chat.completions.create({
    model: 'gpt-4o',
    messages: [{
      role: 'user',
      content: Analyze: ${text}. Return JSON with summary, keyPoints array, sentiment.
    }],
    response_format: { type: 'json_object' }
  });
  
  const data = JSON.parse(response.choices[0].message.content || '{}');
  return AnalysisSchema.parse(data);
}

Real-World TypeScript AI Project

typescript
// Complete TypeScript AI application
import express from 'express';
import OpenAI from 'openai';
const app = express();
const openai = new OpenAI();
app.use(express.json());
app.post('/generate', async (req, res) => {
  const { prompt, model = 'gpt-4o-mini' } = req.body;
  
  const response = await openai.chat.completions.create({
    model,
    messages: [{ role: 'user', content: prompt }]
  });
  
  res.json({
    response: response.choices[0].message.content,
    model,
    tokens: response.usage?.total_tokens
  });
});
app.listen(3000);

Useful Libraries for TypeScript AI Development

Vercel AI SDK: Core AI SDK

LangChain.js: High-level AI orchestration

Pydantic (Zod for TS): Data validation for AI outputs

Instructor: Structured output from LLMs

RAGAS: Evaluate RAG system quality

Conclusion

TypeScript has an excellent ecosystem for AI development. With Vercel AI SDK, OpenAI SDK, you can build everything from simple chatbots to complex AI agents.

The patterns in this guide are production-tested and will save you significant development time.

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*AI development with TypeScript | May 2026*