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openui-forge-openai

OpenUI generative UI with OpenAI SDK backend. Streaming chat completions with gpt-5.5 (or any current OpenAI-compatible model).

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Price unconfirmed★ 22 GitHub starsRegistry updated · Sep 13, 2026agent-skill

Overview

OpenUI generative UI with OpenAI SDK backend. Streaming chat completions with gpt-5.5 (or any current OpenAI-compatible model).

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OpenUI Forge — OpenAI

Build generative UI apps with OpenUI + OpenAI SDK. One backend, one adapter, streaming out of the box.

Activation Triggers

  • "openui openai", "openui gpt", "openui chatgpt"
  • "generative ui openai", "openai streaming ui"

Prerequisites

  • Node.js >= 22 (24 LTS recommended), React >= 18.3.1 (19+ recommended)
  • OPENAI_API_KEY environment variable set
  • Optional: OPENAI_BASE_URL to route via an OpenAI-compatible provider (Gemini, OpenRouter, xAI, DeepSeek, etc.) without code changes. OPENAI_BASE_URL is the correct env var; the legacy OPENAI_API_BASE was removed in openai v6. See Provider Routing below.
  • Optional: OPENAI_MODEL to pin a specific model (defaults to gpt-5.5)
  • Next.js project (App Router recommended)

Provider Routing

This is the OpenAI-compatible variant: the same OpenAI client and chat.completions.create code talks to any provider below by setting OPENAI_BASE_URL (and OPENAI_MODEL). No code changes. OPENAI_BASE_URL is the correct env var; the old OPENAI_API_BASE was removed in openai v6.

ProviderOPENAI_BASE_URLExample OPENAI_MODEL
Geminihttps://generativelanguage.googleapis.com/v1beta/openai/gemini-3.5-flash
OpenRouterhttps://openrouter.ai/api/v1anthropic/claude-opus-4.7
xAI (Grok)https://api.x.ai/v1grok-4.3
DeepSeekhttps://api.deepseek.comdeepseek-v4-pro
Groqhttps://api.groq.com/openai/v1llama-3.3-70b-versatile
Mistralhttps://api.mistral.ai/v1mistral-large-latest
Togetherhttps://api.together.ai/v1openai/gpt-oss-20b
Fireworkshttps://api.fireworks.ai/inference/v1accounts/fireworks/models/glm-5
Ollama (local)http://localhost:11434/v1/llama3.3 (any placeholder API key)
LM Studio (local)http://localhost:1234/v1loaded model id (any placeholder API key)

Model ids drift; check each provider's current catalog. Base-url routing covers chat completions only, not full OpenAI API parity.

Azure OpenAI is not a generic drop-in. Use OPENAI_BASE_URL=https://YOUR-RESOURCE.openai.azure.com/openai/v1/, set OPENAI_MODEL to your deployment name (not a catalog id like gpt-5.5), and prefer the AzureOpenAI client. The legacy data-plane path also needs an ?api-version= query param.

Quick Start

  1. Install dependencies:
npm install @openuidev/react-ui @openuidev/react-headless @openuidev/react-lang lucide-react zod openai
  1. Add the CSS import to app/layout.tsx:
import "@openuidev/react-ui/components.css";
  1. Create the API route (Step 4 below)
  2. Create the frontend page (Step 5 below)
  3. Run npm run dev and test

Full Code

Backend: app/api/chat/route.ts
import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import OpenAI from "openai";

const client = new 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."],
  });

  const response = await client.chat.completions.create({
    model: process.env.OPENAI_MODEL ?? "gpt-5.5",
    stream: true,
    messages: [{ role: "system", content: systemPrompt }, ...messages],
  });

  // response.toReadableStream() produces NDJSON (one JSON object per line, no SSE `data:` prefix).
  // Pair with openAIReadableStreamAdapter() on the frontend.
  return new Response(response.toReadableStream(), {
    headers: { "Content-Type": "application/x-ndjson" },
  });
}
Frontend: app/chat/page.tsx
"use client";
import { FullScreen } from "@openuidev/react-ui";
import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import {
  openAIReadableStreamAdapter,
  openAIMessageFormat,
} from "@openuidev/react-headless";

export default function ChatPage() {
  return (
    <FullScreen
      componentLibrary={openuiChatLibrary}
      streamProtocol={openAIReadableStreamAdapter()}
      messageFormat={openAIMessageFormat}
      apiUrl="/api/chat"
    />
  );
}

Component Creation

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

export const MyCard = defineComponent({
  name: "MyCard",
  description: "A card displaying a title and body text",
  props: z.object({
    title: z.string().describe("The card heading"),
    body: z.string().describe("The card body content"),
  }),
  component: ({ props }) => (
    <div style={{ border: "1px solid #ddd", borderRadius: 8, padding: 16 }}>
      <h3>{props.title}</h3>
      <p>{props.body}</p>
    </div>
  ),
});

Add to a custom library with createLibrary([MyCard, ...others]) or use the built-in openuiLibrary.

System Prompt Generation

For runtime generation (used in the route above), call library.prompt(). For a static file:

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

Validation Checklist

  • OPENAI_API_KEY is set in .env.local
  • CSS import present in root layout
  • API route returns response.toReadableStream() with application/x-ndjson content type
  • Frontend uses streamProtocol={openAIReadableStreamAdapter()} and openAIMessageFormat
  • componentLibrary={openuiChatLibrary} prop passed to FullScreen
  • React >= 18.3.1 installed (peer accepts ^18.3.1 || ^19.0.0)

Error Patterns

ErrorCauseFix
401 from OpenAIMissing or invalid API keySet OPENAI_API_KEY in .env.local
Stream hangsMissing toReadableStream() callEnsure stream: true and return response.toReadableStream()
Components render as textLibrary not passed to FullScreenAdd componentLibrary={openuiChatLibrary} prop
Blank screenCSS not importedAdd @openuidev/react-ui/components.css to root layout
Nothing renders, no errorWrong prop name (adapter is silently ignored)Rename to streamProtocol and call the adapter as a function: streamProtocol={openAIReadableStreamAdapter()}
Partial render then stopModel finished mid-outputCheck token limits, increase max_tokens if needed
View source ↗
File metadata
name: openui-forge-openai
description: OpenUI generative UI with OpenAI SDK backend. Streaming chat completions with gpt-5.5 (or any current OpenAI-compatible model).
version: 1.2.0
author: OthmanAdi
View original text
---
name: openui-forge-openai
description: OpenUI generative UI with OpenAI SDK backend. Streaming chat completions with gpt-5.5 (or any current OpenAI-compatible model).
version: 1.2.0
author: OthmanAdi
---

# OpenUI Forge — OpenAI

Build generative UI apps with OpenUI + OpenAI SDK. One backend, one adapter, streaming out of the box.

## Activation Triggers

- "openui openai", "openui gpt", "openui chatgpt"
- "generative ui openai", "openai streaming ui"

## Prerequisites

- Node.js >= 22 (24 LTS recommended), React >= 18.3.1 (19+ recommended)
- `OPENAI_API_KEY` environment variable set
- Optional: `OPENAI_BASE_URL` to route via an OpenAI-compatible provider (Gemini, OpenRouter, xAI, DeepSeek, etc.) without code changes. `OPENAI_BASE_URL` is the correct env var; the legacy `OPENAI_API_BASE` was removed in openai v6. See [Provider Routing](#provider-routing) below.
- Optional: `OPENAI_MODEL` to pin a specific model (defaults to `gpt-5.5`)
- Next.js project (App Router recommended)

## Provider Routing

This is the OpenAI-compatible variant: the same `OpenAI` client and `chat.completions.create` code talks to any provider below by setting `OPENAI_BASE_URL` (and `OPENAI_MODEL`). No code changes. `OPENAI_BASE_URL` is the correct env var; the old `OPENAI_API_BASE` was removed in openai v6.

| Provider | `OPENAI_BASE_URL` | Example `OPENAI_MODEL` |
|----------|-------------------|------------------------|
| Gemini | `https://generativelanguage.googleapis.com/v1beta/openai/` | `gemini-3.5-flash` |
| OpenRouter | `https://openrouter.ai/api/v1` | `anthropic/claude-opus-4.7` |
| xAI (Grok) | `https://api.x.ai/v1` | `grok-4.3` |
| DeepSeek | `https://api.deepseek.com` | `deepseek-v4-pro` |
| Groq | `https://api.groq.com/openai/v1` | `llama-3.3-70b-versatile` |
| Mistral | `https://api.mistral.ai/v1` | `mistral-large-latest` |
| Together | `https://api.together.ai/v1` | `openai/gpt-oss-20b` |
| Fireworks | `https://api.fireworks.ai/inference/v1` | `accounts/fireworks/models/glm-5` |
| Ollama (local) | `http://localhost:11434/v1/` | `llama3.3` (any placeholder API key) |
| LM Studio (local) | `http://localhost:1234/v1` | loaded model id (any placeholder API key) |

Model ids drift; check each provider's current catalog. Base-url routing covers chat completions only, not full OpenAI API parity.

> **Azure OpenAI is not a generic drop-in.** Use `OPENAI_BASE_URL=https://YOUR-RESOURCE.openai.azure.com/openai/v1/`, set `OPENAI_MODEL` to your *deployment name* (not a catalog id like `gpt-5.5`), and prefer the `AzureOpenAI` client. The legacy data-plane path also needs an `?api-version=` query param.

## Quick Start

1. Install dependencies:
```bash
npm install @openuidev/react-ui @openuidev/react-headless @openuidev/react-lang lucide-react zod openai
```
2. Add the CSS import to `app/layout.tsx`:
```tsx
import "@openuidev/react-ui/components.css";
```
3. Create the API route (Step 4 below)
4. Create the frontend page (Step 5 below)
5. Run `npm run dev` and test

## Full Code

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

```typescript
import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import OpenAI from "openai";

const client = new 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."],
  });

  const response = await client.chat.completions.create({
    model: process.env.OPENAI_MODEL ?? "gpt-5.5",
    stream: true,
    messages: [{ role: "system", content: systemPrompt }, ...messages],
  });

  // response.toReadableStream() produces NDJSON (one JSON object per line, no SSE `data:` prefix).
  // Pair with openAIReadableStreamAdapter() on the frontend.
  return new Response(response.toReadableStream(), {
    headers: { "Content-Type": "application/x-ndjson" },
  });
}
```

### Frontend: `app/chat/page.tsx`

```tsx
"use client";
import { FullScreen } from "@openuidev/react-ui";
import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import {
  openAIReadableStreamAdapter,
  openAIMessageFormat,
} from "@openuidev/react-headless";

export default function ChatPage() {
  return (
    <FullScreen
      componentLibrary={openuiChatLibrary}
      streamProtocol={openAIReadableStreamAdapter()}
      messageFormat={openAIMessageFormat}
      apiUrl="/api/chat"
    />
  );
}
```

## Component Creation

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

export const MyCard = defineComponent({
  name: "MyCard",
  description: "A card displaying a title and body text",
  props: z.object({
    title: z.string().describe("The card heading"),
    body: z.string().describe("The card body content"),
  }),
  component: ({ props }) => (
    <div style={{ border: "1px solid #ddd", borderRadius: 8, padding: 16 }}>
      <h3>{props.title}</h3>
      <p>{props.body}</p>
    </div>
  ),
});
```

Add to a custom library with `createLibrary([MyCard, ...others])` or use the built-in `openuiLibrary`.

## System Prompt Generation

For runtime generation (used in the route above), call `library.prompt()`. For a static file:

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

## Validation Checklist

- [ ] `OPENAI_API_KEY` is set in `.env.local`
- [ ] CSS import present in root layout
- [ ] API route returns `response.toReadableStream()` with `application/x-ndjson` content type
- [ ] Frontend uses `streamProtocol={openAIReadableStreamAdapter()}` and `openAIMessageFormat`
- [ ] `componentLibrary={openuiChatLibrary}` prop passed to `FullScreen`
- [ ] React >= 18.3.1 installed (peer accepts `^18.3.1 || ^19.0.0`)

## Error Patterns

| Error | Cause | Fix |
|-------|-------|-----|
| 401 from OpenAI | Missing or invalid API key | Set `OPENAI_API_KEY` in `.env.local` |
| Stream hangs | Missing `toReadableStream()` call | Ensure `stream: true` and return `response.toReadableStream()` |
| Components render as text | Library not passed to FullScreen | Add `componentLibrary={openuiChatLibrary}` prop |
| Blank screen | CSS not imported | Add `@openuidev/react-ui/components.css` to root layout |
| Nothing renders, no error | Wrong prop name (`adapter` is silently ignored) | Rename to `streamProtocol` and call the adapter as a function: `streamProtocol={openAIReadableStreamAdapter()}` |
| Partial render then stop | Model finished mid-output | Check token limits, increase `max_tokens` if needed |

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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-openai/SKILL.md @ 977180d4d3e9

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  • GitHub adoption: 22 GitHub stars
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      "recent_failure_rate": null,
      "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",
      "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",
      "Permission surface: secrets or environment access, shell or command execution"
    ]
  },
  "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": 65,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "Low GitHub adoption signal",
      "AI review approval is missing",
      "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"
    ]
  },
  "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": "3mo 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",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "AI review approval is missing",
    "Quality score needs review"
  ],
  "agent_contract": {
    "task_input": "Use openui-forge-openai 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: 62/100 Manual review",
      "Audit: 65/100 Needs review",
      "Safety: 21/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "othmanadi-openui-forge-openai (openui-forge-openai)",
      "install_command": "npx skills add OthmanAdi/openui-forge --skill openui-forge-openai",
      "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-openai",
      "task": "Use openui-forge-openai 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-openai",
    "api": "https://www.openagentskill.com/api/agent/skills/othmanadi-openui-forge-openai",
    "audit": "https://www.openagentskill.com/skills/othmanadi-openui-forge-openai/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=othmanadi-openui-forge-openai&task=Use%20openui-forge-openai%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20openui-forge-openai%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20openui-forge-openai%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/othmanadi-openui-forge-openai/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/othmanadi-openui-forge-openai"
  }
}

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