ai-sdk-6

Use this skill when developing AI-powered features using Vercel AI SDK v6 (ai package).

Docs location: bundled in node_modules/ai/docs/. In Bun/pnpm/Yarn workspace monorepos deps aren't hoisted — use apps/*/node_modules/ai/docs/ or packages/*/node_modules/ai/docs/ instead.

Quick Reference

Installation

bun add ai @ai-sdk/openai zod    # or @ai-sdk/anthropic, @ai-sdk/google, etc.

Core Functions

| Function | Purpose | | -------------- | ----------------------------------------------------------------- | | generateText | Non-streaming text generation (+ structured output with Output) | | streamText | Streaming text generation (+ structured output with Output) |

v6 Note: generateObject/streamObject are deprecated. Use generateText/streamText with output: Output.object({ schema }) instead.

Structured Output (v6)

import { generateText, Output } from "ai";
import { z } from "zod";

const { output } = await generateText({
  model: anthropic("claude-sonnet-5"),
  output: Output.object({
    schema: z.object({
      sentiment: z.enum(["positive", "neutral", "negative"]),
      topics: z.array(z.string()),
    }),
  }),
  prompt: "Analyze this feedback...",
});

Output types: Output.object(), Output.array(), Output.choice(), Output.json(), Output.text() (default)

Agent Class (v6 Key Feature)

import { ToolLoopAgent, tool, stepCountIs } from "ai";
import { anthropic } from "@ai-sdk/anthropic";
import { z } from "zod";

const myAgent = new ToolLoopAgent({
  model: anthropic("claude-sonnet-5"),
  instructions: "You are a helpful assistant.",
  tools: {
    getData: tool({
      description: "Fetch data from API",
      inputSchema: z.object({
        query: z.string(),
      }),
      execute: async ({ query }) => {
        return { result: "data" };
      },
    }),
  },
  stopWhen: stepCountIs(20),
});

// Usage
const { text } = await myAgent.generate({ prompt: "Hello" });
const stream = await myAgent.stream({ prompt: "Hello" });

API Route with Agent

// app/api/chat/route.ts
import { createAgentUIStreamResponse } from "ai";
import { myAgent } from "@/agents/my-agent";

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

  return createAgentUIStreamResponse({
    agent: myAgent,
    uiMessages: messages,
  });
}

Smooth Streaming

import { createAgentUIStreamResponse, smoothStream } from "ai";

return createAgentUIStreamResponse({
  agent: myAgent,
  uiMessages: messages,
  experimental_transform: smoothStream({
    delayInMs: 15,
    chunking: "word", // "word" | "line" | RegExp | Intl.Segmenter | callback
  }),
});

useChat Hook (Client)

"use client";
import { useChat } from "@ai-sdk/react";
import { DefaultChatTransport } from "ai";
import { useState } from "react";

export function Chat() {
  const [input, setInput] = useState("");
  const { messages, sendMessage, status } = useChat({
    transport: new DefaultChatTransport({
      api: "/api/chat",
    }),
  });

  return (
    <>
      {messages.map((msg) => (
        <div key={msg.id}>
          {msg.parts.map((part, i) =>
            part.type === "text" ? <span key={i}>{part.text}</span> : null
          )}
        </div>
      ))}
      <form
        onSubmit={(e) => {
          e.preventDefault();
          if (input.trim()) {
            sendMessage({ text: input });
            setInput("");
          }
        }}
      >
        <input
          value={input}
          onChange={(e) => setInput(e.target.value)}
          disabled={status !== "ready"}
        />
        <button type="submit" disabled={status !== "ready"}>
          Send
        </button>
      </form>
    </>
  );
}

v6 Note: useChat no longer manages input state internally. Use useState for controlled inputs.

Reference Documentation

For detailed information, see:

• agents.md - ToolLoopAgent, loop control, workflows
• core-functions.md - generateText, streamText, Output patterns
• tools.md - Tool definition with Zod schemas
• workflows.md - Sequential, parallel, routing, and orchestrator-worker patterns
• ui-hooks.md - useChat, UIMessage, streaming
• middleware.md - Custom middleware patterns
• mcp.md - MCP server integration
• examples.md - Canonical provider × feature examples from vercel/ai repo

Official Documentation

For the latest information, see AI SDK docs.