openui-forge-vercel: Design & UI for AI Agents | OpenAgentSkill

Overview

OpenUI generative UI with Vercel AI SDK. streamText, toUIMessageStreamResponse, and tools support.

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OpenUI Forge — Vercel AI SDK

Build generative UI apps with OpenUI + Vercel AI SDK. Native streaming with streamText and toUIMessageStreamResponse().

Activation Triggers

"openui vercel", "openui vercel ai", "openui ai sdk"
"generative ui vercel", "vercel ai streaming ui"
"useChat openui", "streamText openui"

Prerequisites

Node.js >= 22 (24 LTS recommended), React >= 18.3.1 (19+ recommended)
OPENAI_API_KEY environment variable set
Next.js project (App Router)

Quick Start

Install dependencies:

npm install @openuidev/react-ui @openuidev/react-lang lucide-react zod ai @ai-sdk/openai @ai-sdk/react

Pin to the AI SDK v6 line: ai@^6, @ai-sdk/openai@^3, @ai-sdk/react@^3. 2. Add the CSS import to app/layout.tsx:

import "@openuidev/react-ui/components.css";

Create the API route and frontend page below
Run npm run dev and test

Full Code

Backend: `app/api/chat/route.ts`

import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import { convertToModelMessages, streamText } from "ai";
import { openai } from "@ai-sdk/openai";

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

  const systemPrompt = openuiChatLibrary.prompt({
    preamble: "You are a helpful assistant that generates interactive UIs.",
    additionalRules: ["Always use Stack as root when combining multiple components."],
  });

  // AI SDK v6: convert the UI message stream into model messages before passing to the model.
  const modelMessages = await convertToModelMessages(messages);

  const result = streamText({
    model: openai(process.env.OPENAI_MODEL ?? "gpt-5.5"),
    system: systemPrompt,
    messages: modelMessages,
  });

  return result.toUIMessageStreamResponse();
}

Backend with Tools: `app/api/chat/route.ts`

import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import { convertToModelMessages, streamText, tool, stepCountIs } from "ai";
import { openai } from "@ai-sdk/openai";
import { z } from "zod";

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

  const systemPrompt = openuiChatLibrary.prompt({
    preamble: "You are a helpful assistant that generates interactive UIs. Use tools to fetch data before rendering.",
  });

  // AI SDK v6: convert the UI message stream into model messages before passing to the model.
  const modelMessages = await convertToModelMessages(messages);

  const result = streamText({
    model: openai(process.env.OPENAI_MODEL ?? "gpt-5.5"),
    system: systemPrompt,
    messages: modelMessages,
    tools: {
      getWeather: tool({
        description: "Get current weather for a city",
        inputSchema: z.object({
          city: z.string().describe("City name"),
        }),
        execute: async ({ city }) => {
          return { city, temp: 22, condition: "sunny" };
        },
      }),
    },
    // AI SDK v6: stopWhen replaces the removed `maxSteps` option.
    stopWhen: stepCountIs(3),
  });

  return result.toUIMessageStreamResponse();
}

Frontend (useChat + Renderer): `app/chat/page.tsx`

Drive the conversation with useChat from @ai-sdk/react, then render each assistant message with a per-message <Renderer> from @openuidev/react-lang. The Renderer takes the assistant text as response, the component library as library (NOT componentLibrary), an isStreaming flag for the in-flight message, and an onAction handler for built-in actions like continuing the conversation.

"use client";
import { useChat } from "@ai-sdk/react";
import { Renderer, BuiltinActionType } from "@openuidev/react-lang";
import type { ActionEvent } from "@openuidev/react-lang";
import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import { useState } from "react";

export default function ChatPage() {
  const [input, setInput] = useState("");
  const { messages, sendMessage, status } = useChat();
  const isLoading = status === "submitted" || status === "streaming";

  const handleSend = (text: string) => {
    const trimmed = text.trim();
    if (!trimmed || isLoading) return;
    setInput("");
    sendMessage({ text: trimmed });
  };

  const handleAction = (event: ActionEvent) => {
    if (event.type === BuiltinActionType.ContinueConversation && event.humanFriendlyMessage) {
      handleSend(event.humanFriendlyMessage);
    }
  };

  return (
    <div>
      {messages.map((message, i) => {
        const isLast = i === messages.length - 1;

        if (message.role === "user") {
          const text = message.parts
            .filter((p): p is { type: "text"; text: string } => p.type === "text")
            .map((p) => p.text)
            .join("");
          return <div key={message.id}>{text}</div>;
        }

        // assistant: render generative UI from the text parts
        const response = message.parts
          .filter((p): p is { type: "text"; text: string } => p.type === "text")
          .map((p) => p.text)
          .join("");

        return (
          <Renderer
            key={message.id}
            response={response}
            library={openuiChatLibrary}
            isStreaming={isLoading && isLast}
            onAction={handleAction}
          />
        );
      })}

      <form
        onSubmit={(e) => {
          e.preventDefault();
          handleSend(input);
        }}
      >
        <input value={input} onChange={(e) => setInput(e.target.value)} />
        <button type="submit" disabled={isLoading}>Send</button>
      </form>
    </div>
  );
}

Component Creation

import { defineComponent } from "@openuidev/react-lang";
import { z } from "zod";

export const WeatherCard = defineComponent({
  name: "WeatherCard",
  description: "Displays weather information for a location",
  props: z.object({
    city: z.string().describe("City name"),
    temp: z.number().describe("Temperature in Celsius"),
    condition: z.enum(["sunny", "cloudy", "rainy", "snowy"]).describe("Weather condition"),
  }),
  component: ({ props }) => (
    <div style={{ padding: 16, borderRadius: 12, background: "#f0f9ff" }}>
      <h3>{props.city}</h3>
      <div style={{ fontSize: 32 }}>{props.temp}C</div>
      <div>{props.condition}</div>
    </div>
  ),
});

System Prompt Generation

npx @openuidev/cli generate ./src/lib/library.ts --out src/generated/system-prompt.txt

Or at runtime via openuiChatLibrary.prompt() as shown in the route.

Validation Checklist

Error Patterns

Error	Cause	Fix
`ai` module not found	Missing Vercel AI SDK	`npm install ai @ai-sdk/openai @ai-sdk/react`
`useChat` is not exported / not found	Importing the hook from `ai`	Import `useChat` from `@ai-sdk/react` and install `@ai-sdk/react@^3`
Empty / mismatched model messages	Passing raw UI `messages` straight to `streamText`	`const modelMessages = await convertToModelMessages(messages)`, then pass `messages: modelMessages`
Type error on `maxSteps`	`maxSteps` removed in AI SDK v6	Import `stepCountIs` from `ai` and use `stopWhen: stepCountIs(3)`
Type error on tool `parameters`	Renamed to `inputSchema` in AI SDK v6	Rename `parameters:` to `inputSchema:` in every `tool({...})` definition
Blank response	Wrong export from `@ai-sdk/openai`	Use `openai("gpt-5.5")` not `new OpenAI()`
Generative UI does not render	`componentLibrary` prop passed to `Renderer`, or rendering `message.content` instead of joined text parts	Use `library={openuiChatLibrary}` and pass the joined `text` parts as `response={...}`

View source ↗

File metadata

name: openui-forge-vercel
description: OpenUI generative UI with Vercel AI SDK. streamText, toUIMessageStreamResponse, and tools support.
version: 1.2.0
author: OthmanAdi

View original text

---
name: openui-forge-vercel
description: OpenUI generative UI with Vercel AI SDK. streamText, toUIMessageStreamResponse, and tools support.
version: 1.2.0
author: OthmanAdi
---

# OpenUI Forge — Vercel AI SDK

Build generative UI apps with OpenUI + Vercel AI SDK. Native streaming with `streamText` and `toUIMessageStreamResponse()`.

## Activation Triggers

- "openui vercel", "openui vercel ai", "openui ai sdk"
- "generative ui vercel", "vercel ai streaming ui"
- "useChat openui", "streamText openui"

## Prerequisites

- Node.js >= 22 (24 LTS recommended), React >= 18.3.1 (19+ recommended)
- `OPENAI_API_KEY` environment variable set
- Next.js project (App Router)

## Quick Start

1. Install dependencies:
```bash
npm install @openuidev/react-ui @openuidev/react-lang lucide-react zod ai @ai-sdk/openai @ai-sdk/react
```
Pin to the AI SDK v6 line: `ai@^6`, `@ai-sdk/openai@^3`, `@ai-sdk/react@^3`.
2. Add the CSS import to `app/layout.tsx`:
```tsx
import "@openuidev/react-ui/components.css";
```
3. Create the API route and frontend page below
4. Run `npm run dev` and test

## Full Code

### Backend: `app/api/chat/route.ts`

```typescript
import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import { convertToModelMessages, streamText } from "ai";
import { openai } from "@ai-sdk/openai";

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

  const systemPrompt = openuiChatLibrary.prompt({
    preamble: "You are a helpful assistant that generates interactive UIs.",
    additionalRules: ["Always use Stack as root when combining multiple components."],
  });

  // AI SDK v6: convert the UI message stream into model messages before passing to the model.
  const modelMessages = await convertToModelMessages(messages);

  const result = streamText({
    model: openai(process.env.OPENAI_MODEL ?? "gpt-5.5"),
    system: systemPrompt,
    messages: modelMessages,
  });

  return result.toUIMessageStreamResponse();
}
```

### Backend with Tools: `app/api/chat/route.ts`

```typescript
import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import { convertToModelMessages, streamText, tool, stepCountIs } from "ai";
import { openai } from "@ai-sdk/openai";
import { z } from "zod";

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

  const systemPrompt = openuiChatLibrary.prompt({
    preamble: "You are a helpful assistant that generates interactive UIs. Use tools to fetch data before rendering.",
  });

  // AI SDK v6: convert the UI message stream into model messages before passing to the model.
  const modelMessages = await convertToModelMessages(messages);

  const result = streamText({
    model: openai(process.env.OPENAI_MODEL ?? "gpt-5.5"),
    system: systemPrompt,
    messages: modelMessages,
    tools: {
      getWeather: tool({
        description: "Get current weather for a city",
        inputSchema: z.object({
          city: z.string().describe("City name"),
        }),
        execute: async ({ city }) => {
          return { city, temp: 22, condition: "sunny" };
        },
      }),
    },
    // AI SDK v6: stopWhen replaces the removed `maxSteps` option.
    stopWhen: stepCountIs(3),
  });

  return result.toUIMessageStreamResponse();
}
```

### Frontend (useChat + Renderer): `app/chat/page.tsx`

Drive the conversation with `useChat` from `@ai-sdk/react`, then render each assistant message with a per-message `<Renderer>` from `@openuidev/react-lang`. The Renderer takes the assistant text as `response`, the component library as `library` (NOT `componentLibrary`), an `isStreaming` flag for the in-flight message, and an `onAction` handler for built-in actions like continuing the conversation.

```tsx
"use client";
import { useChat } from "@ai-sdk/react";
import { Renderer, BuiltinActionType } from "@openuidev/react-lang";
import type { ActionEvent } from "@openuidev/react-lang";
import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import { useState } from "react";

export default function ChatPage() {
  const [input, setInput] = useState("");
  const { messages, sendMessage, status } = useChat();
  const isLoading = status === "submitted" || status === "streaming";

  const handleSend = (text: string) => {
    const trimmed = text.trim();
    if (!trimmed || isLoading) return;
    setInput("");
    sendMessage({ text: trimmed });
  };

  const handleAction = (event: ActionEvent) => {
    if (event.type === BuiltinActionType.ContinueConversation && event.humanFriendlyMessage) {
      handleSend(event.humanFriendlyMessage);
    }
  };

  return (
    <div>
      {messages.map((message, i) => {
        const isLast = i === messages.length - 1;

        if (message.role === "user") {
          const text = message.parts
            .filter((p): p is { type: "text"; text: string } => p.type === "text")
            .map((p) => p.text)
            .join("");
          return <div key={message.id}>{text}</div>;
        }

        // assistant: render generative UI from the text parts
        const response = message.parts
          .filter((p): p is { type: "text"; text: string } => p.type === "text")
          .map((p) => p.text)
          .join("");

        return (
          <Renderer
            key={message.id}
            response={response}
            library={openuiChatLibrary}
            isStreaming={isLoading && isLast}
            onAction={handleAction}
          />
        );
      })}

      <form
        onSubmit={(e) => {
          e.preventDefault();
          handleSend(input);
        }}
      >
        <input value={input} onChange={(e) => setInput(e.target.value)} />
        <button type="submit" disabled={isLoading}>Send</button>
      </form>
    </div>
  );
}
```

## Component Creation

```tsx
import { defineComponent } from "@openuidev/react-lang";
import { z } from "zod";

export const WeatherCard = defineComponent({
  name: "WeatherCard",
  description: "Displays weather information for a location",
  props: z.object({
    city: z.string().describe("City name"),
    temp: z.number().describe("Temperature in Celsius"),
    condition: z.enum(["sunny", "cloudy", "rainy", "snowy"]).describe("Weather condition"),
  }),
  component: ({ props }) => (
    <div style={{ padding: 16, borderRadius: 12, background: "#f0f9ff" }}>
      <h3>{props.city}</h3>
      <div style={{ fontSize: 32 }}>{props.temp}C</div>
      <div>{props.condition}</div>
    </div>
  ),
});
```

## System Prompt Generation

```bash
npx @openuidev/cli generate ./src/lib/library.ts --out src/generated/system-prompt.txt
```

Or at runtime via `openuiChatLibrary.prompt()` as shown in the route.

## Validation Checklist

- [ ] `OPENAI_API_KEY` is set in `.env.local`
- [ ] `ai`, `@ai-sdk/openai`, and `@ai-sdk/react` packages installed (v6 line: `ai@^6`, `@ai-sdk/openai@^3`, `@ai-sdk/react@^3`)
- [ ] Route converts UI messages with `convertToModelMessages(messages)` and passes `messages: modelMessages` to `streamText`
- [ ] Route uses `streamText` and returns `result.toUIMessageStreamResponse()`
- [ ] Frontend drives the chat with `useChat` from `@ai-sdk/react` (`messages`, `sendMessage`, `status`)
- [ ] Each assistant message is rendered with `<Renderer response={...} library={openuiChatLibrary} isStreaming={...} onAction={...} />` from `@openuidev/react-lang`
- [ ] Renderer prop is `library={openuiChatLibrary}` (NOT `componentLibrary`)
- [ ] CSS import in root layout
- [ ] If using tools: `stopWhen: stepCountIs(n)` is set (AI SDK v6 replacement for the removed `maxSteps`), tool results feed back to model
- [ ] Tools declared with `inputSchema:` (v6 rename of `parameters:`)

## Error Patterns

| Error | Cause | Fix |
|-------|-------|-----|
| `ai` module not found | Missing Vercel AI SDK | `npm install ai @ai-sdk/openai @ai-sdk/react` |
| `useChat` is not exported / not found | Importing the hook from `ai` | Import `useChat` from `@ai-sdk/react` and install `@ai-sdk/react@^3` |
| Empty / mismatched model messages | Passing raw UI `messages` straight to `streamText` | `const modelMessages = await convertToModelMessages(messages)`, then pass `messages: modelMessages` |
| Type error on `maxSteps` | `maxSteps` removed in AI SDK v6 | Import `stepCountIs` from `ai` and use `stopWhen: stepCountIs(3)` |
| Type error on tool `parameters` | Renamed to `inputSchema` in AI SDK v6 | Rename `parameters:` to `inputSchema:` in every `tool({...})` definition |
| Blank response | Wrong export from `@ai-sdk/openai` | Use `openai("gpt-5.5")` not `new OpenAI()` |
| Generative UI does not render | `componentLibrary` prop passed to `Renderer`, or rendering `message.content` instead of joined text parts | Use `library={openuiChatLibrary}` and pass the joined `text` parts as `response={...}` |

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Review before install: Avoid automatic install

License: MIT

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AI review approval is missing
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Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 22 GitHub stars
Stars/forks activity: 22 stars, 0 forks; issue activity unavailable in current metadata
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Permission surface: secrets or environment access, shell or command execution

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Source repository: OthmanAdi/openui-forge
License: MIT
Version: 1.2.0
Last GitHub push: Aug 3, 2026
Registry updated: Sep 13, 2026
Instruction path: .agents/skills/openui-forge-vercel/SKILL.md @ 977180d4d3e9

Version reported in registry metadata; check source releases before relying on it.

Quality

49/100

Needs review

Trust

56/100

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      "install_attempts": 0,
      "install_success_rate": null,
      "risk_blocked": 0,
      "setup_required": 0,
      "avg_output_quality": null,
      "production_outcomes": 0,
      "last_outcome_at": null,
      "label": "No agent outcome data yet"
    },
    "auto_install": {
      "allowed": false,
      "sandbox_required": true,
      "reason": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
    },
    "best_for": [
      "design-creative",
      "agent-skill"
    ],
    "known_risks": [
      "AI review approval is missing",
      "Financial research output is not financial advice; require human review before any live investment decision.",
      "Low GitHub adoption signal",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "GitHub adoption: 22 GitHub stars",
      "Stars/forks activity: 22 stars, 0 forks; issue activity unavailable in current metadata",
      "Dependency/runtime risk: command execution surface, credential or environment access"
    ]
  },
  "agent_proven": {
    "version": "agent-proven-v1",
    "score": 0,
    "tier": "unproven",
    "label": "Needs first agent run",
    "summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
    "metrics": {
      "totalOutcomes": 0,
      "successfulOutcomes": 0,
      "failedOutcomes": 0,
      "installAttempts": 0,
      "installSuccessRate": null,
      "successRate": null,
      "recentSuccessRate": null,
      "recentFailureRate": null,
      "riskBlocked": 0,
      "setupRequired": 0,
      "notRelevant": 0,
      "avgOutputQuality": null,
      "avgTimeToUsefulMs": null,
      "productionOutcomes": 0,
      "humanReviewRequired": 0,
      "uniqueAgents": 0,
      "lastOutcomeAt": null
    },
    "signals": [],
    "penalties": [
      "No real agent outcome evidence yet"
    ]
  },
  "audit": {
    "score": 67,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "Financial research output is not financial advice; require human review before any live investment decision",
      "Low GitHub adoption signal",
      "AI review approval is missing",
      "Financial research output is not financial advice; require human review before any live investment decision.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 49,
    "label": "Needs review"
  },
  "supply": {
    "track": "Design and creative production",
    "scenario": "Design and creative",
    "maintenance": "2mo since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "Low GitHub adoption signal",
    "No OpenAgentSkill engagement data yet",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "Financial research output is not financial advice; require human review before any live investment decision"
  ],
  "agent_contract": {
    "task_input": "Use openui-forge-vercel in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 64/100 Manual review",
      "Audit: 67/100 Needs review",
      "Safety: 27/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "othmanadi-openui-forge-vercel (openui-forge-vercel)",
      "install_command": "npx skills add OthmanAdi/openui-forge --skill openui-forge-vercel",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "othmanadi-openui-forge-vercel",
      "task": "Use openui-forge-vercel in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/othmanadi-openui-forge-vercel",
    "api": "https://www.openagentskill.com/api/agent/skills/othmanadi-openui-forge-vercel",
    "audit": "https://www.openagentskill.com/skills/othmanadi-openui-forge-vercel/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=othmanadi-openui-forge-vercel&task=Use%20openui-forge-vercel%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20openui-forge-vercel%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20openui-forge-vercel%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/othmanadi-openui-forge-vercel/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/othmanadi-openui-forge-vercel"
  }
}

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Creator: OthmanAdi
Source: OthmanAdi/openui-forge
Indexed by: OpenAgentSkill community index

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