Vercel AI SDK Guidelines

The Vercel AI SDK is the de facto standard for building streaming AI applications in TypeScript and React.

1. Core API (@ai-sdk/core)

• Text Generation: Use streamText for any user-facing chat or text response to minimize perceived latency. Only use generateText for background tasks where the user is not waiting for a real-time response.
• Structured Outputs: Use streamObject or generateObject paired with Zod schemas to guarantee type-safe JSON outputs. Never prompt the model manually to "return JSON".
• Tool Calling: Define tools using the tool() helper with strict Zod schemas.

import { streamText, tool } from 'ai'
import { z } from 'zod'

const result = streamText({
  model: myModel,
  messages,
  tools: {
    weather: tool({
      description: 'Get the weather in a location',
      parameters: z.object({ location: z.string() }),
      execute: async ({ location }) => fetchWeather(location),
    }),
  },
})

2. UI Hooks (@ai-sdk/react)

• `useChat`: The primary hook for conversational interfaces. It automatically manages message history, streaming state, and tool invocations.
• Error Handling: Implement the onError callback in useChat to gracefully handle API rate limits or network failures.
• Data Streaming: Use the data property exported from useChat to stream auxiliary data (like tool execution metadata or citations) alongside the main text stream.

3. Server Actions & Next.js Integration

• App Router: When using Next.js App Router, implement Route Handlers (app/api/chat/route.ts) that return result.toDataStreamResponse() for seamless streaming to useChat.
• RSC (React Server Components): For generative UI, use the ai/rsc module to stream React components directly from the server to the client.

4. Security & Safety

• Rate Limiting: Always apply rate limiting to your chat endpoints, as LLM APIs are expensive and vulnerable to abuse.
• Provider API Keys: Ensure OPENAI_API_KEY (or equivalent) is strictly kept server-side. Never expose these keys to the client.