ai-sdk-setup skill

Overview

This skill guides you through installing the Vercel AI SDK and AI Elements components, then building a streaming chat interface using the useChat hook. It focuses on a minimal, production-ready pattern that integrates with Shadcn UI primitives and common full-stack deployment flows. Follow the steps to get a streaming, incremental chat UI with server-side handlers and client hooks.

How this skill works

Install the Vercel AI SDK and the AI Elements package, wire up the SDK on the server to handle model calls, and use the client-side useChat hook to manage streaming messages and UI state. The hook provides event hooks for tokens and partial responses so the interface updates incrementally as the model streams. Recipes include server endpoints (or MCP links) and component examples compatible with TypeScript and Shadcn styling.

When to use it

• You need a fast way to add a streaming conversational UI to a TypeScript full-stack app.
• You want prebuilt AI Elements components that integrate with Shadcn and Tailwind.
• You need token-level streaming updates to show partial responses in real time.
• You are deploying on Vercel or similar platforms and want standard SDK patterns.

Best practices

• Keep model calls server-side to protect API keys and enforce rate limits.
• Use useChat streaming handlers to append tokens incrementally rather than waiting for full responses.
• Sanitize and validate user input on the server before forwarding to the model.
• Implement incremental UI feedback (loading states, partial messages) for better UX.
• Use TypeScript types for messages and API responses to catch issues early.

Example use cases

• Customer support chat that streams answers as the model generates them.
• Interactive assistant embedded in a dashboard that provides code snippets or explanations.
• Live pair-programming helper that streams suggestions and updates in real time.
• FAQ bot on a marketing site that shows partial answers to reduce perceived latency.

FAQ