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ai-sdk-5

ai-sdk-5

github.com/gentleman-programmingDevelopment661135 installsUpdated 31w ago
Repository

About ai-sdk-5

ai-sdk-5 is a coding skill for implementing chat and text-generation interfaces with AI SDK 5. It focuses on v5 APIs, streaming, tool use, and migration differences from v4.

Key features

  1. 01AI SDK 4から5への移行点
  2. 02Reactのチャット設定
  3. 03UIMessageのparts構造
  4. 04サーバー側ストリーミング
  5. 05ツール付きストリーミング
  6. 06テキスト補完とエラー処理

Use cases

  1. 01既存のチャット実装をv5に更新
  2. 02ReactでチャットUIを構築
  3. 03LangChainメッセージをUI形式に変換

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/gentleman-programming/gentleman-skills --skill ai-sdk-5

After installing, type/ai-sdk-5in Claude Code to confirm it loaded.

Details

From the project README

Breaking Changes from AI SDK 4

// ❌ AI SDK 4 (OLD)
import { useChat } from "ai";
const { messages, handleSubmit, input, handleInputChange } = useChat({
  api: "/api/chat",
});

// ✅ AI SDK 5 (NEW)
import { useChat } from "@ai-sdk/react";
import { DefaultChatTransport } from "ai";

const { messages, sendMessage } = useChat({
  transport: new DefaultChatTransport({ api: "/api/chat" }),
});

Client Setup

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

export function Chat() {
  const [input, setInput] = useState("");

  const { messages, sendMessage, isLoading, error } = useChat({
    transport: new DefaultChatTransport({ api: "/api/chat" }),
  });

  const handleSubmit = (e: React.FormEvent) => {
    e.preventDefault();
    if (!input.trim()) return;
    sendMessage({ text: input });
    setInput("");
  };

  return (
    <div>
      <div>
        {messages.map((message) => (
          <Message key={message.id} message={message} />
        ))}
      </div>

      <form onSubmit={handleSubmit}>
        <input
          value={input}
          onChange={(e) => setInput(e.target.value)}
          placeholder="Type a message..."
          disabled={isLoading}
        />
        <button type="submit" disabled={isLoading}>
          Send
        </button>
      </form>

      {error && <div>Error: {error.message}</div>}
    </div>
  );
}

UIMessage Structure (v5)

// ❌ Old: message.content was a string
// ✅ New: message.parts is an array

interface UIMessage {
  id: string;
  role: "user" | "assistant" | "system";
  parts: MessagePart[];
}

type MessagePart =
  | { type: "text"; text: string }
  | { type: "image"; image: string }
  | { type: "tool-call"; toolCallId: string; toolName: string; args: unknown }
  | { type: "tool-result"; toolCallId: string; result: unknown };

// Extract text from parts
function getMessageText(message: UIMessage): string {
  return message.parts
    .filter((part): part is { type: "text"; text: string } => part.type === "text")
    .map((part) => part.text)
    .join("");
}

// Render message
function Message({ message }: { message: UIMessage }) {
  return (
    <div className={message.role === "user" ? "user" : "assistant"}>
      {message.parts.map((part, index) => {
        if (part.type === "text") {
          return <p key={index}>{part.text}</p>;
        }
        if (part.type === "image") {
          return <img key={index} src={part.image} alt="" />;
        }
        return null;
      })}
    </div>
  );
}

Server-Side (Route Handler)

// app/api/chat/route.ts
import { openai } from "@ai-sdk/openai";
import { streamText } from "ai";

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

  const result = await streamText({
    model: openai("gpt-4o"),
    messages,
    system: "You are a helpful assistant.",
  });

  return result.toDataStreamResponse();
}

With LangChain

// app/api/chat/route.ts
import { toUIMessageStream } from "@ai-sdk/langchain";
import { ChatOpenAI } from "@langchain/openai";
import { HumanMessage, AIMessage } from "@langchain/core/messages";

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

  const model = new ChatOpenAI({
    modelName: "gpt-4o",
    streaming: true,
  });

  // Convert UI messages to LangChain format
  const langchainMessages = messages.map((m) => {
    const text = m.parts
      .filter((p) => p.type === "text")
      .map((p) => p.text)
      .join("");
    return m.role === "user"
      ? new HumanMessage(text)
      : new AIMessage(text);
  });

  const stream = await model.stream(langchainMessages);

  return toUIMessageStream(stream).toDataStreamResponse();
}

Streaming with Tools

import { openai } from "@ai-sdk/openai";
import { streamText, tool } from "ai";
import { z } from "zod";

const result = await streamText({
  model: openai("gpt-4o"),
  messages,
  tools: {
    getWeather: tool({
      description: "Get weather for a location",
      parameters: z.object({
        location: z.string().describe("City name"),
      }),
      execute: async ({ location }) => {
        // Fetch weather data
        return { temperature: 72, condition: "sunny" };
      },
    }),
  },
});

useCompletion (Text Generation)

import { useCompletion } from "@ai-sdk/react";
import { DefaultCompletionTransport } from "ai";

const { completion, complete, isLoading } = useCompletion({
  transport: new DefaultCompletionTransport({ api: "/api/complete" }),
});

// Trigger completion
await complete("Write a haiku about");

Error Handling

const { error, messages, sendMessage } = useChat({
  transport: new DefaultChatTransport({ api: "/api/chat" }),
  onError: (error) => {
    console.error("Chat error:", error);
    toast.error("Failed to send message");
  },
});

// Display error
{error && (
  <div className="error">
    {error.message}
    <button onClick={() => sendMessage({ text: lastInput })}>
      Retry
    </button>
  </div>
)}

Keywords

ai sdk, vercel ai, chat, streaming, langchain, openai, llm

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