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openui-forge-anthropic

OpenUI generative UI with Anthropic Claude SDK backend. Stream conversion to OpenAI NDJSON format.

Quelle prüfen Auf GitHub ansehen

Preis unbestätigt★ 22 GitHub-StarsVerzeichnis aktualisiert · 13. Sept. 2026agent-skill

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OpenUI generative UI with Anthropic Claude SDK backend. Stream conversion to OpenAI NDJSON format.

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OpenUI Forge — Anthropic

Build generative UI apps with OpenUI + Anthropic Claude. Converts Anthropic streaming events to OpenAI-compatible NDJSON.

Activation Triggers

"openui anthropic", "openui claude", "openui sonnet"
"generative ui claude", "claude streaming ui"

Prerequisites

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

Quick Start

Install dependencies:

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

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`

The backend streams from Anthropic and converts each event into OpenAI-compatible SSE chunks that openAIAdapter() expects (data: {json}\n\n lines, terminated by data: [DONE]).

import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic();

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."],
  });

  // ANTHROPIC_MODEL alternatives: claude-opus-4-8, claude-haiku-4-5, claude-fable-5
  const stream = client.messages.stream({
    model: process.env.ANTHROPIC_MODEL ?? "claude-sonnet-4-6",
    max_tokens: 4096,
    system: systemPrompt,
    messages,
  });

  const encoder = new TextEncoder();
  const readableStream = new ReadableStream({
    async start(controller) {
      const id = `chatcmpl-${Date.now()}`;
      for await (const event of stream) {
        if (
          event.type === "content_block_delta" &&
          event.delta.type === "text_delta"
        ) {
          const chunk = {
            id,
            object: "chat.completion.chunk",
            choices: [
              {
                index: 0,
                delta: { content: event.delta.text },
                finish_reason: null,
              },
            ],
          };
          controller.enqueue(
            encoder.encode(`data: ${JSON.stringify(chunk)}\n\n`)
          );
        }
      }
      const done = {
        id,
        object: "chat.completion.chunk",
        choices: [{ index: 0, delta: {}, finish_reason: "stop" }],
      };
      controller.enqueue(encoder.encode(`data: ${JSON.stringify(done)}\n\n`));
      controller.enqueue(encoder.encode("data: [DONE]\n\n"));
      controller.close();
    },
  });

  return new Response(readableStream, {
    headers: { "Content-Type": "text/event-stream" },
  });
}

Frontend: `app/chat/page.tsx`

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

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

The backend emits SSE (data: {json}\n\n). Pair it with openAIAdapter() on the frontend — openAIReadableStreamAdapter() is for NDJSON (no data: prefix) and will silently produce no output here.

Component Creation

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

export const StatusCard = defineComponent({
  name: "StatusCard",
  description: "Displays a status with label and color indicator",
  props: z.object({
    label: z.string().describe("Status label text"),
    status: z.enum(["ok", "warning", "error"]).describe("Current status level"),
  }),
  component: ({ props }) => {
    const colors = { ok: "#22c55e", warning: "#eab308", error: "#ef4444" };
    return (
      <div style={{ display: "flex", alignItems: "center", gap: 8 }}>
        <span style={{ width: 10, height: 10, borderRadius: "50%", background: colors[props.status] }} />
        <span>{props.label}</span>
      </div>
    );
  },
});

System Prompt Generation

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

Or at runtime: openuiChatLibrary.prompt({ preamble: "...", additionalRules: [...] }).

Validation Checklist

ANTHROPIC_API_KEY is set in .env.local
CSS import present in root layout
Backend converts Anthropic content_block_delta events to OpenAI-compatible SSE chunks
Final chunk has finish_reason: "stop" and ends with data: [DONE]
Frontend uses streamProtocol={openAIAdapter()} and openAIMessageFormat
componentLibrary={openuiChatLibrary} prop passed to FullScreen

Error Patterns

Error	Cause	Fix
401 from Anthropic	Missing or invalid API key	Set `ANTHROPIC_API_KEY` in `.env.local`
Stream hangs	Missing `[DONE]` sentinel or `controller.close()`	Ensure final chunk and `[DONE]` are sent
Garbled output	Not wrapping in `data: ...` SSE format	Each chunk must be `data: {json}\n\n`
Components render as text	Library not passed to FullScreen	Add `componentLibrary={openuiChatLibrary}` prop
Nothing renders, no error	Used `openAIReadableStreamAdapter()` (NDJSON) on SSE stream, or `adapter=` prop (silently ignored)	Use `streamProtocol={openAIAdapter()}`
`max_tokens` required	Anthropic API requires explicit max_tokens	Always set `max_tokens` (e.g., 4096)

Quelle ansehen ↗

Dateimetadaten

name: openui-forge-anthropic
description: OpenUI generative UI with Anthropic Claude SDK backend. Stream conversion to OpenAI NDJSON format.
version: 1.2.0
author: OthmanAdi

Originaltext anzeigen

---
name: openui-forge-anthropic
description: OpenUI generative UI with Anthropic Claude SDK backend. Stream conversion to OpenAI NDJSON format.
version: 1.2.0
author: OthmanAdi
---

# OpenUI Forge — Anthropic

Build generative UI apps with OpenUI + Anthropic Claude. Converts Anthropic streaming events to OpenAI-compatible NDJSON.

## Activation Triggers

- "openui anthropic", "openui claude", "openui sonnet"
- "generative ui claude", "claude streaming ui"

## Prerequisites

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

## Quick Start

1. Install dependencies:
```bash
npm install @openuidev/react-ui @openuidev/react-headless @openuidev/react-lang lucide-react zod @anthropic-ai/sdk
```
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`

The backend streams from Anthropic and converts each event into OpenAI-compatible SSE chunks that `openAIAdapter()` expects (`data: {json}\n\n` lines, terminated by `data: [DONE]`).

```typescript
import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic();

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."],
  });

  // ANTHROPIC_MODEL alternatives: claude-opus-4-8, claude-haiku-4-5, claude-fable-5
  const stream = client.messages.stream({
    model: process.env.ANTHROPIC_MODEL ?? "claude-sonnet-4-6",
    max_tokens: 4096,
    system: systemPrompt,
    messages,
  });

  const encoder = new TextEncoder();
  const readableStream = new ReadableStream({
    async start(controller) {
      const id = `chatcmpl-${Date.now()}`;
      for await (const event of stream) {
        if (
          event.type === "content_block_delta" &&
          event.delta.type === "text_delta"
        ) {
          const chunk = {
            id,
            object: "chat.completion.chunk",
            choices: [
              {
                index: 0,
                delta: { content: event.delta.text },
                finish_reason: null,
              },
            ],
          };
          controller.enqueue(
            encoder.encode(`data: ${JSON.stringify(chunk)}\n\n`)
          );
        }
      }
      const done = {
        id,
        object: "chat.completion.chunk",
        choices: [{ index: 0, delta: {}, finish_reason: "stop" }],
      };
      controller.enqueue(encoder.encode(`data: ${JSON.stringify(done)}\n\n`));
      controller.enqueue(encoder.encode("data: [DONE]\n\n"));
      controller.close();
    },
  });

  return new Response(readableStream, {
    headers: { "Content-Type": "text/event-stream" },
  });
}
```

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

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

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

> The backend emits SSE (`data: {json}\n\n`). Pair it with `openAIAdapter()` on the frontend — `openAIReadableStreamAdapter()` is for NDJSON (no `data:` prefix) and will silently produce no output here.

## Component Creation

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

export const StatusCard = defineComponent({
  name: "StatusCard",
  description: "Displays a status with label and color indicator",
  props: z.object({
    label: z.string().describe("Status label text"),
    status: z.enum(["ok", "warning", "error"]).describe("Current status level"),
  }),
  component: ({ props }) => {
    const colors = { ok: "#22c55e", warning: "#eab308", error: "#ef4444" };
    return (
      <div style={{ display: "flex", alignItems: "center", gap: 8 }}>
        <span style={{ width: 10, height: 10, borderRadius: "50%", background: colors[props.status] }} />
        <span>{props.label}</span>
      </div>
    );
  },
});
```

## System Prompt Generation

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

Or at runtime: `openuiChatLibrary.prompt({ preamble: "...", additionalRules: [...] })`.

## Validation Checklist

- [ ] `ANTHROPIC_API_KEY` is set in `.env.local`
- [ ] CSS import present in root layout
- [ ] Backend converts Anthropic `content_block_delta` events to OpenAI-compatible SSE chunks
- [ ] Final chunk has `finish_reason: "stop"` and ends with `data: [DONE]`
- [ ] Frontend uses `streamProtocol={openAIAdapter()}` and `openAIMessageFormat`
- [ ] `componentLibrary={openuiChatLibrary}` prop passed to `FullScreen`

## Error Patterns

| Error | Cause | Fix |
|-------|-------|-----|
| 401 from Anthropic | Missing or invalid API key | Set `ANTHROPIC_API_KEY` in `.env.local` |
| Stream hangs | Missing `[DONE]` sentinel or `controller.close()` | Ensure final chunk and `[DONE]` are sent |
| Garbled output | Not wrapping in `data: ...` SSE format | Each chunk must be `data: {json}\n\n` |
| Components render as text | Library not passed to FullScreen | Add `componentLibrary={openuiChatLibrary}` prop |
| Nothing renders, no error | Used `openAIReadableStreamAdapter()` (NDJSON) on SSE stream, or `adapter=` prop (silently ignored) | Use `streamProtocol={openAIAdapter()}` |
| `max_tokens` required | Anthropic API requires explicit max_tokens | Always set `max_tokens` (e.g., 4096) |

Quelle prüfen

Preis und Betriebskosten

Skill beziehen: Preis unbestätigt
Ausführen: Anforderungen unbestätigt. Agenten-, API- und Dienstkosten an der Quelle prüfen.
Lizenz: MIT
Preis unbestätigt: Der Preis ist noch nicht bestätigt. Vorhandene Quell- und Installationslinks bleiben verfügbar.

Kostenloser Bezug bedeutet nicht kostenlosen Betrieb. Preise sind keine Sicherheitsbewertung. Preisinformation einreichen →

Skill-Quelle erfasst

Ein Anleitungspfad ist erfasst. Das ist kein Ausführungstest und keine Sicherheits- oder Kompatibilitätsgarantie.

Vor Installation prüfen: Automatische Installation vermeiden

Lizenz: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Low GitHub adoption signal
KI-Prüffreigabe fehlt
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
Review status: AI review approval is missing

Vollständiges Audit öffnen

Tools sind Metadatenhinweise, keine getestete Kompatibilität. Prompts sind Vorschläge.

Mit einer kleinen Aufgabe beginnen

1Quelle lesen und Eingaben, Ergebnisse, Abhängigkeiten sowie Berechtigungen prüfen.
2Agent um einen Plan bitten. Einrichtung und Kosten vor einem isolierten Test genehmigen.
3Ergebnisse und geänderte Dateien prüfen. Nur tatsächliche Ausführungen melden und die Quellrevision aufbewahren.

Prüfe Abhängigkeiten, API-Schlüssel und externe Kosten in der Quelle. Öffentliche Repositories bedeuten nicht, dass alle Dienste kostenlos sind.

Quelle und Nutzungshinweise

ErfasstStatisch geprüft

Metadaten und Prüfungen dienen der Orientierung. Beliebtheit, Quellenerfassung und erfolgreiche Ausführung sind verschiedene Fakten.

Quell-Repository: OthmanAdi/openui-forge
Lizenz: MIT
Version: 1.2.0
Letzter GitHub-Push: 3. Aug. 2026
Verzeichnis aktualisiert: 13. Sept. 2026
Anleitungspfad: .agents/skills/openui-forge-anthropic/SKILL.md @ 977180d4d3e9

Version aus den Verzeichnismetadaten; Releases der Quelle prüfen.

Qualität

49/100

Prüfung nötig

Vertrauen

56/100

Do not auto-install

Audit

67/100

Prüfung nötig

Vollständiges Audit öffnen Eval-Bericht ansehen

Dependency or permission surface needs review
Permission surface may require sandboxing
Low GitHub adoption signal
KI-Prüffreigabe fehlt
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
Review status: AI review approval is missing

Verified installs: —
Ergebnisse: —

Kopieren ist keine Installation. Zahlen benötigen eine Erfolgsmeldung und garantieren keine allgemeine Qualität.

Agent-Zugang

Die Registry API stellt Entscheidungs-, Vertrauens-, Audit-, Use-Case- und Installationssignale ohne UI-Scraping bereit.

Installations-API öffnen LLM-Textformat Manifest öffnen Auto-Auflösungsplan

Weitere Details

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    "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",
      "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": "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",
    "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-anthropic 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: 31/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "othmanadi-openui-forge-anthropic (openui-forge-anthropic)",
      "install_command": "npx skills add OthmanAdi/openui-forge --skill openui-forge-anthropic",
      "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-anthropic",
      "task": "Use openui-forge-anthropic 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-anthropic",
    "api": "https://www.openagentskill.com/api/agent/skills/othmanadi-openui-forge-anthropic",
    "audit": "https://www.openagentskill.com/skills/othmanadi-openui-forge-anthropic/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=othmanadi-openui-forge-anthropic&task=Use%20openui-forge-anthropic%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20openui-forge-anthropic%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20openui-forge-anthropic%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/othmanadi-openui-forge-anthropic/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/othmanadi-openui-forge-anthropic"
  }
}

Für Ersteller

Quelle des Eintrags

Registry-indexiert

Beanspruchbar

Dieser Eintrag wurde aus öffentlichen Quellen indexiert und ist erst nach Genehmigung eines Maintainer-Anspruchs offiziell.

Ersteller: OthmanAdi
Quelle: OthmanAdi/openui-forge
Indexiert von: OpenAgentSkill Community-Index

Die Zuordnung verlinkt auf das öffentliche Repository oder Creator-Profil. Creator können den Eintrag beanspruchen, um Eigentümersignale zu aktualisieren.

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