Ai Sdk 5 logo

Ai Sdk 5

OrganizationPopular
prowler-cloud
ai-sdk-5

Vercel AI SDK 5 patterns. Trigger: When building AI features with AI SDK v5 (chat, streaming, tools/function calling, UIMessage parts), including migration from v4.

Overview

Publisherprowler-cloud
Repositoryprowler
Skill nameai-sdk-5
Stars
14.8K
Forks
2.4K
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by prowler-cloud on GitHub. Read the source before you install it.

Installation

Install the Ai Sdk 5 AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/prowler-cloud/prowler.git /tmp/prowler
mkdir -p .claude/skills
cp -r /tmp/prowler/skills/ai-sdk-5 .claude/skills/ai-sdk-5
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ai Sdk 5 in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ai Sdk 5 on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ai Sdk 5 is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Breaking Changes from AI SDK 4

typescript
// ❌ 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

typescript
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)

typescript
// ❌ 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)

typescript
// 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

typescript
// 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

typescript
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)

typescript
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

typescript
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>
)}

Frequently asked questions

What does the Ai Sdk 5 AI skill do?

Vercel AI SDK 5 patterns. Trigger: When building AI features with AI SDK v5 (chat, streaming, tools/function calling, UIMessage parts), including migration from v4.

Why use Ai Sdk 5 on TypingMind?

Because you install it once and use it with any model. Ai Sdk 5 is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ai Sdk 5 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/prowler-cloud/prowler/tree/master/skills/ai-sdk-5. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ai Sdk 5?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ai Sdk 5?

As many as you like. As long as a model supports skills, you can use Ai Sdk 5 with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ai Sdk 5 AI skill free?

Yes. It is published on GitHub by prowler-cloud under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇