Trending-skills openmaic-classroom
OpenMAIC — Open Multi-Agent Interactive Classroom platform for generating immersive AI-powered learning experiences with slides, quizzes, simulations, and multi-agent discussions.
git clone https://github.com/Aradotso/trending-skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/Aradotso/trending-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/openmaic-classroom" ~/.claude/skills/aradotso-trending-skills-openmaic-classroom && rm -rf "$T"
skills/openmaic-classroom/SKILL.mdOpenMAIC — Multi-Agent Interactive Classroom
Skill by ara.so — Daily 2026 Skills collection.
OpenMAIC (Open Multi-Agent Interactive Classroom) is a Next.js 16 / React 19 / TypeScript platform that converts any topic or document into a full interactive lesson. A multi-agent pipeline (LangGraph 1.1) generates slides, quizzes, HTML simulations, and project-based learning activities delivered by AI teachers and AI classmates with voice (TTS) and whiteboard support.
Project Stack
| Layer | Technology |
|---|---|
| Framework | Next.js 16 (App Router) |
| UI | React 19, Tailwind CSS 4 |
| Agent orchestration | LangGraph 1.1 |
| Language | TypeScript 5 |
| Package manager | pnpm >= 10 |
| Runtime | Node.js >= 20 |
Installation
git clone https://github.com/THU-MAIC/OpenMAIC.git cd OpenMAIC pnpm install
Environment Configuration
cp .env.example .env.local
Edit
.env.local — at minimum one LLM provider key is required:
# LLM Providers (configure at least one) OPENAI_API_KEY=$OPENAI_API_KEY ANTHROPIC_API_KEY=$ANTHROPIC_API_KEY GOOGLE_API_KEY=$GOOGLE_API_KEY # Recommended default model (Gemini 3 Flash = best speed/quality balance) DEFAULT_MODEL=google:gemini-3-flash-preview # Optional: MinerU for advanced PDF/table/formula parsing PDF_MINERU_BASE_URL=https://mineru.net PDF_MINERU_API_KEY=$MINERU_API_KEY # Optional: access code for hosted mode ACCESS_CODE=$OPENMAIC_ACCESS_CODE
Provider Config via YAML (alternative to env vars)
Create
server-providers.yml in the project root:
providers: openai: apiKey: $OPENAI_API_KEY anthropic: apiKey: $ANTHROPIC_API_KEY google: apiKey: $GOOGLE_API_KEY deepseek: apiKey: $DEEPSEEK_API_KEY # Any OpenAI-compatible endpoint custom: baseURL: https://your-proxy.example.com/v1 apiKey: $CUSTOM_API_KEY
Running the App
# Development pnpm dev # → http://localhost:3000 # Production build pnpm build && pnpm start # Type checking pnpm tsc --noEmit # Linting pnpm lint
Docker Deployment
cp .env.example .env.local # Edit .env.local with your API keys docker compose up --build # → http://localhost:3000
Vercel Deployment
# Fork the repo, then import at https://vercel.com/new # Set env vars in Vercel dashboard: # OPENAI_API_KEY or ANTHROPIC_API_KEY or GOOGLE_API_KEY # DEFAULT_MODEL (optional, e.g. google:gemini-3-flash-preview)
One-click deploy button is available in the README; it pre-fills env var descriptions automatically.
Lesson Generation Pipeline
OpenMAIC uses a two-stage pipeline:
| Stage | Description |
|---|---|
| Outline | AI analyzes topic/document and produces a structured lesson outline |
| Scenes | Each outline item is expanded into a typed scene: , , , or |
Scene Types
| Type | Description |
|---|---|
| AI teacher lectures with TTS narration, spotlight, laser pointer |
| Single/multiple choice or short-answer with AI grading |
| HTML-based simulation (physics, flowcharts, etc.) |
| Project-Based Learning — choose a role, collaborate with agents |
API Usage — Generating a Classroom
REST: Start Generation Job
// POST /api/generate const response = await fetch('/api/generate', { method: 'POST', headers: { 'Content-Type': 'application/json' }, body: JSON.stringify({ topic: 'Quantum Entanglement', // Optional: attach document content document: markdownString, // Optional: model override model: 'google:gemini-3-flash-preview', }), }); const { jobId } = await response.json();
REST: Poll Job Status
// GET /api/generate/status?jobId=<jobId> const poll = async (jobId: string) => { while (true) { const res = await fetch(`/api/generate/status?jobId=${jobId}`); const data = await res.json(); if (data.status === 'completed') { console.log('Classroom URL:', data.classroomUrl); break; } if (data.status === 'failed') { throw new Error(data.error); } // status === 'pending' | 'running' await new Promise(r => setTimeout(r, 3000)); } };
REST: Export Slides
// GET /api/export/pptx?classroomId=<id> const exportPptx = async (classroomId: string) => { const res = await fetch(`/api/export/pptx?classroomId=${classroomId}`); const blob = await res.blob(); const url = URL.createObjectURL(blob); // trigger download const a = document.createElement('a'); a.href = url; a.download = 'lesson.pptx'; a.click(); }; // GET /api/export/html?classroomId=<id> const exportHtml = async (classroomId: string) => { const res = await fetch(`/api/export/html?classroomId=${classroomId}`); const html = await res.text(); return html; };
OpenClaw Integration
OpenMAIC ships a skill for OpenClaw, enabling classroom generation from Feishu, Slack, Discord, Telegram, etc.
Install the Skill
# Via ClawHub (recommended) clawhub install openmaic # Manual install mkdir -p ~/.openclaw/skills cp -R /path/to/OpenMAIC/skills/openmaic ~/.openclaw/skills/openmaic
Configure OpenClaw
Edit
~/.openclaw/openclaw.json:
{ "skills": { "entries": { "openmaic": { "config": { // Hosted mode — get access code from https://open.maic.chat/ "accessCode": "$OPENMAIC_ACCESS_CODE", // Self-hosted mode — local repo + server URL "repoDir": "/path/to/OpenMAIC", "url": "http://localhost:3000" } } } } }
OpenClaw Skill Lifecycle
| Phase | What Happens |
|---|---|
| Clone | Detect existing checkout or clone fresh |
| Startup | Choose , , or Docker |
| Provider Keys | Guide user to edit |
| Generation | Submit async job, poll, return classroom link |
Custom Scene Development Pattern
Scenes are typed React components. To add a new scene type:
// types/scene.ts export type SceneType = 'slides' | 'quiz' | 'interactive' | 'pbl' | 'custom'; export interface CustomScene { type: 'custom'; title: string; content: string; // your fields metadata: Record<string, unknown>; }
// components/scenes/CustomScene.tsx 'use client'; import { type CustomScene } from '@/types/scene'; interface Props { scene: CustomScene; onComplete: () => void; } export function CustomSceneComponent({ scene, onComplete }: Props) { return ( <div className="flex flex-col gap-4 p-6"> <h2 className="text-2xl font-bold">{scene.title}</h2> <div dangerouslySetInnerHTML={{ __html: scene.content }} /> <button className="mt-4 rounded-lg bg-blue-600 px-6 py-2 text-white" onClick={onComplete} > Continue </button> </div> ); }
Multi-Agent Interaction Modes
| Mode | Trigger | Description |
|---|---|---|
| Classroom Discussion | Automatic | Agents proactively start discussions; user can jump in or get called on |
| Roundtable Debate | Scene config | Multiple agent personas debate a topic with whiteboard illustrations |
| Q&A | User asks question | AI teacher responds with slides, diagrams, or whiteboard drawings |
| Whiteboard | During any scene | Agents draw equations, flowcharts, or concept diagrams in real time |
MinerU Advanced Document Parsing
For complex PDFs with tables, formulas, or scanned images:
# Use MinerU hosted API PDF_MINERU_BASE_URL=https://mineru.net PDF_MINERU_API_KEY=$MINERU_API_KEY # Or self-hosted MinerU instance (Docker) PDF_MINERU_BASE_URL=http://localhost:8888
Without MinerU, OpenMAIC falls back to standard PDF text extraction.
Supported LLM Providers & Model Strings
// Model string format: "provider:model-name" const models = { // Google (recommended) geminiFlash: 'google:gemini-3-flash-preview', // best speed/quality geminiPro: 'google:gemini-3.1-pro', // highest quality // OpenAI gpt4o: 'openai:gpt-4o', gpt4oMini: 'openai:gpt-4o-mini', // Anthropic claude4Sonnet: 'anthropic:claude-sonnet-4-5', claude4Haiku: 'anthropic:claude-haiku-4-5', // DeepSeek deepseekChat: 'deepseek:deepseek-chat', // OpenAI-compatible (custom base URL) custom: 'custom:your-model-name', };
Export Formats
| Format | Endpoint | Notes |
|---|---|---|
PowerPoint | | Fully editable slides |
Interactive | | Self-contained HTML page |
Common Patterns
Generate a Classroom from a Document String
const generateFromDocument = async (markdownContent: string, topic: string) => { const res = await fetch('/api/generate', { method: 'POST', headers: { 'Content-Type': 'application/json' }, body: JSON.stringify({ topic, document: markdownContent, model: process.env.DEFAULT_MODEL ?? 'google:gemini-3-flash-preview', }), }); const { jobId } = await res.json(); // Poll until done let classroomUrl: string | null = null; while (!classroomUrl) { await new Promise(r => setTimeout(r, 4000)); const status = await fetch(`/api/generate/status?jobId=${jobId}`).then(r => r.json()); if (status.status === 'completed') classroomUrl = status.classroomUrl; if (status.status === 'failed') throw new Error(status.error); } return classroomUrl; };
Check Provider Health
// GET /api/providers const checkProviders = async () => { const res = await fetch('/api/providers'); const { providers } = await res.json(); // providers: Array<{ name: string; available: boolean; models: string[] }> return providers.filter((p: { available: boolean }) => p.available); };
Troubleshooting
| Problem | Solution |
|---|---|
| Set at least one of , , or in |
| Generation hangs at outline stage | Check API key quota; try switching to for higher rate limits |
| TTS not working | TTS requires a browser with Web Speech API support; check browser console for errors |
| PDF parsing produces garbled text | Enable MinerU by setting in |
| Vercel timeout during generation | Increase function timeout in ; generation is async so the API should return a immediately |
| Docker build fails | Ensure and that exists before running |
| OpenClaw skill not found | Run or manually copy to |
fails on Node < 20 | Upgrade Node.js to >= 20 () |
| Port 3000 already in use | Set in or run |
Key File Structure
OpenMAIC/ ├── app/ # Next.js App Router pages & API routes │ ├── api/ │ │ ├── generate/ # POST lesson generation, GET status │ │ ├── export/ # pptx / html export endpoints │ │ └── providers/ # LLM provider health check │ └── classroom/ # Classroom viewer pages ├── components/ │ ├── scenes/ # Slide, Quiz, Interactive, PBL components │ ├── whiteboard/ # Real-time whiteboard rendering │ └── agents/ # Agent avatar & TTS components ├── lib/ │ ├── agents/ # LangGraph agent graph definitions │ ├── providers/ # LLM provider abstractions │ └── generation/ # Outline + scene generation pipeline ├── skills/ │ └── openmaic/ # OpenClaw skill definition ├── server-providers.yml # Optional YAML provider config ├── .env.example # Environment variable template └── docker-compose.yml # Docker deployment config