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openui-forge-langchain

OpenUI generative UI with LangChain/LangGraph backend. Supports ChatOpenAI and ChatAnthropic.

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Prix non confirmé★ 22 Stars GitHubRegistre mis à jour · 13 sept. 2026agent-skill

Vue d’ensemble

OpenUI generative UI with LangChain/LangGraph backend. Supports ChatOpenAI and ChatAnthropic.

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Documentation source, pas des instructions pour ce site. Vérifiez les permissions avant d’exécuter des commandes.

OpenUI Forge — LangChain

Build generative UI apps with OpenUI + LangChain. Stream from ChatOpenAI or ChatAnthropic, convert to OpenAI NDJSON.

Activation Triggers

"openui langchain", "openui langgraph", "openui langsmith"
"generative ui langchain", "langchain streaming ui"

Prerequisites

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

Quick Start

Install dependencies (pick one or both LLM providers):

npm install @openuidev/react-ui @openuidev/react-headless @openuidev/react-lang lucide-react zod @langchain/openai @langchain/core
# For Anthropic: npm install @langchain/anthropic

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 (OpenAI): `app/api/chat/route.ts`

import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import { ChatOpenAI } from "@langchain/openai";
import { HumanMessage, SystemMessage, AIMessage } from "@langchain/core/messages";

const model = new ChatOpenAI({ model: process.env.OPENAI_MODEL ?? "gpt-5.5", streaming: true });

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.",
  });

  const lcMessages = [
    new SystemMessage(systemPrompt),
    ...messages.map((m: { role: string; content: string }) =>
      m.role === "user" ? new HumanMessage(m.content) : new AIMessage(m.content)
    ),
  ];

  const stream = await model.stream(lcMessages);
  const encoder = new TextEncoder();
  const id = `chatcmpl-${Date.now()}`;

  const readableStream = new ReadableStream({
    async start(controller) {
      for await (const chunk of stream) {
        const text = typeof chunk.content === "string" ? chunk.content : "";
        if (!text) continue;
        const payload = {
          id,
          object: "chat.completion.chunk",
          choices: [{ index: 0, delta: { content: text }, finish_reason: null }],
        };
        controller.enqueue(encoder.encode(`data: ${JSON.stringify(payload)}\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" },
  });
}

Backend (Anthropic variant): `app/api/chat/route.ts`

Replace the model initialization and import:

import { ChatAnthropic } from "@langchain/anthropic";

const model = new ChatAnthropic({
  model: process.env.ANTHROPIC_MODEL ?? "claude-sonnet-4-6",
  maxTokens: 4096,
  streaming: true,
});

Everything else (message mapping, stream conversion, response) stays identical.

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. (langGraphAdapter is also exported from @openuidev/react-headless if you stream LangGraph events natively rather than converting to OpenAI shape.)

Component Creation

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

export const MetricCard = defineComponent({
  name: "MetricCard",
  description: "Displays a metric with label, value, and optional trend",
  props: z.object({
    label: z.string().describe("Metric name"),
    value: z.number().describe("Current metric value"),
    trend: z.enum(["up", "down", "flat"]).optional().describe("Trend direction"),
  }),
  component: ({ props }) => (
    <div style={{ padding: 16, border: "1px solid #e5e7eb", borderRadius: 8 }}>
      <div style={{ fontSize: 14, color: "#6b7280" }}>{props.label}</div>
      <div style={{ fontSize: 24, fontWeight: 700 }}>{props.value}</div>
      {props.trend && <span>{props.trend === "up" ? "+" : props.trend === "down" ? "-" : "="}</span>}
    </div>
  ),
});

System Prompt Generation

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

Validation Checklist

LLM provider API key is set
@langchain/openai or @langchain/anthropic installed
Messages correctly mapped to LangChain message types
Stream chunks converted to OpenAI-compatible SSE with data: prefix
Final chunk has finish_reason: "stop" and ends with data: [DONE]
Frontend uses streamProtocol={openAIAdapter()} and openAIMessageFormat
CSS import in root layout

Error Patterns

Error	Cause	Fix
Empty chunks in stream	LangChain AIMessageChunk content may be empty	Skip chunks where `text` is empty
Type error on messages	Wrong LangChain message class	Map `user` to `HumanMessage`, `assistant` to `AIMessage`
Module not found	Missing LangChain provider package	Install `@langchain/openai` or `@langchain/anthropic`
Stream hangs	Missing `[DONE]` sentinel	Always send final stop chunk and `[DONE]`
CORS error	Cross-origin frontend	Add CORS headers if frontend/backend are split

Voir la source ↗

Métadonnées du fichier

name: openui-forge-langchain
description: OpenUI generative UI with LangChain/LangGraph backend. Supports ChatOpenAI and ChatAnthropic.
version: 1.2.0
author: OthmanAdi

Voir le texte original

---
name: openui-forge-langchain
description: OpenUI generative UI with LangChain/LangGraph backend. Supports ChatOpenAI and ChatAnthropic.
version: 1.2.0
author: OthmanAdi
---

# OpenUI Forge — LangChain

Build generative UI apps with OpenUI + LangChain. Stream from ChatOpenAI or ChatAnthropic, convert to OpenAI NDJSON.

## Activation Triggers

- "openui langchain", "openui langgraph", "openui langsmith"
- "generative ui langchain", "langchain streaming ui"

## Prerequisites

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

## Quick Start

1. Install dependencies (pick one or both LLM providers):
```bash
npm install @openuidev/react-ui @openuidev/react-headless @openuidev/react-lang lucide-react zod @langchain/openai @langchain/core
# For Anthropic: npm install @langchain/anthropic
```
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 (OpenAI): `app/api/chat/route.ts`

```typescript
import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import { ChatOpenAI } from "@langchain/openai";
import { HumanMessage, SystemMessage, AIMessage } from "@langchain/core/messages";

const model = new ChatOpenAI({ model: process.env.OPENAI_MODEL ?? "gpt-5.5", streaming: true });

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.",
  });

  const lcMessages = [
    new SystemMessage(systemPrompt),
    ...messages.map((m: { role: string; content: string }) =>
      m.role === "user" ? new HumanMessage(m.content) : new AIMessage(m.content)
    ),
  ];

  const stream = await model.stream(lcMessages);
  const encoder = new TextEncoder();
  const id = `chatcmpl-${Date.now()}`;

  const readableStream = new ReadableStream({
    async start(controller) {
      for await (const chunk of stream) {
        const text = typeof chunk.content === "string" ? chunk.content : "";
        if (!text) continue;
        const payload = {
          id,
          object: "chat.completion.chunk",
          choices: [{ index: 0, delta: { content: text }, finish_reason: null }],
        };
        controller.enqueue(encoder.encode(`data: ${JSON.stringify(payload)}\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" },
  });
}
```

### Backend (Anthropic variant): `app/api/chat/route.ts`

Replace the model initialization and import:

```typescript
import { ChatAnthropic } from "@langchain/anthropic";

const model = new ChatAnthropic({
  model: process.env.ANTHROPIC_MODEL ?? "claude-sonnet-4-6",
  maxTokens: 4096,
  streaming: true,
});
```

Everything else (message mapping, stream conversion, response) stays identical.

### 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. (`langGraphAdapter` is also exported from `@openuidev/react-headless` if you stream LangGraph events natively rather than converting to OpenAI shape.)

## Component Creation

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

export const MetricCard = defineComponent({
  name: "MetricCard",
  description: "Displays a metric with label, value, and optional trend",
  props: z.object({
    label: z.string().describe("Metric name"),
    value: z.number().describe("Current metric value"),
    trend: z.enum(["up", "down", "flat"]).optional().describe("Trend direction"),
  }),
  component: ({ props }) => (
    <div style={{ padding: 16, border: "1px solid #e5e7eb", borderRadius: 8 }}>
      <div style={{ fontSize: 14, color: "#6b7280" }}>{props.label}</div>
      <div style={{ fontSize: 24, fontWeight: 700 }}>{props.value}</div>
      {props.trend && <span>{props.trend === "up" ? "+" : props.trend === "down" ? "-" : "="}</span>}
    </div>
  ),
});
```

## System Prompt Generation

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

## Validation Checklist

- [ ] LLM provider API key is set
- [ ] `@langchain/openai` or `@langchain/anthropic` installed
- [ ] Messages correctly mapped to LangChain message types
- [ ] Stream chunks converted to OpenAI-compatible SSE with `data:` prefix
- [ ] Final chunk has `finish_reason: "stop"` and ends with `data: [DONE]`
- [ ] Frontend uses `streamProtocol={openAIAdapter()}` and `openAIMessageFormat`
- [ ] CSS import in root layout

## Error Patterns

| Error | Cause | Fix |
|-------|-------|-----|
| Empty chunks in stream | LangChain AIMessageChunk content may be empty | Skip chunks where `text` is empty |
| Type error on messages | Wrong LangChain message class | Map `user` to `HumanMessage`, `assistant` to `AIMessage` |
| Module not found | Missing LangChain provider package | Install `@langchain/openai` or `@langchain/anthropic` |
| Stream hangs | Missing `[DONE]` sentinel | Always send final stop chunk and `[DONE]` |
| CORS error | Cross-origin frontend | Add CORS headers if frontend/backend are split |

Examiner la source

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Licence: MIT
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Réviser avant installation: Éviter l’installation automatique

Licence: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Low GitHub adoption signal
L’approbation de revue IA est absente
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

Ouvrir l’audit complet

Les outils sont des indications de métadonnées, pas une compatibilité testée. Les prompts sont des suggestions.

Commencer par une petite tâche

1Lisez la source et confirmez entrées, résultats, dépendances et permissions.
2Demandez un plan à l’agent. Approuvez la configuration et les coûts avant un test isolé.
3Vérifiez résultats et fichiers modifiés. Signalez uniquement ce qui a été exécuté et conservez la révision source.

Vérifiez les dépendances, clés API et frais externes dans la source. Un dépôt public ne rend pas tous les services gratuits.

Source et conseils d’utilisation

RépertoriéContrôle statique

Métadonnées et examens sont indicatifs. Popularité, découverte et exécution réussie sont des faits distincts.

Dépôt source: OthmanAdi/openui-forge
Licence: MIT
Version: 1.2.0
Dernier push GitHub: 3 août 2026
Registre mis à jour: 13 sept. 2026
Chemin des instructions: .agents/skills/openui-forge-langchain/SKILL.md @ 977180d4d3e9

Version déclarée dans le registre ; vérifiez les versions de la source.

Qualité

49/100

Revue nécessaire

Confiance

56/100

Do not auto-install

Audit

67/100

Revue nécessaire

Ouvrir l’audit complet Voir le rapport d’évaluation

Dependency or permission surface needs review
Permission surface may require sandboxing
Low GitHub adoption signal
L’approbation de revue IA est absente
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: —
Résultats: —

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    "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",
      "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-langchain 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-langchain (openui-forge-langchain)",
      "install_command": "npx skills add OthmanAdi/openui-forge --skill openui-forge-langchain",
      "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-langchain",
      "task": "Use openui-forge-langchain 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-langchain",
    "api": "https://www.openagentskill.com/api/agent/skills/othmanadi-openui-forge-langchain",
    "audit": "https://www.openagentskill.com/skills/othmanadi-openui-forge-langchain/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=othmanadi-openui-forge-langchain&task=Use%20openui-forge-langchain%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20openui-forge-langchain%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20openui-forge-langchain%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/othmanadi-openui-forge-langchain/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/othmanadi-openui-forge-langchain"
  }
}

Pour le créateur

Source de la fiche

Indexé par Registry

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Cette fiche a été indexée à partir de sources publiques et n’est pas marquée officielle tant qu’une revendication de mainteneur n’est pas approuvée.

Créateur: OthmanAdi
Source: OthmanAdi/openui-forge
Indexé par: Index communautaire OpenAgentSkill

L’attribution renvoie au dépôt public ou au profil du créateur. Les créateurs peuvent revendiquer la fiche pour mettre à jour les signaux de propriété.

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