openmaic-classroom
多智能体交互教室平台,将任意主题转为完整互动课程,支持多 Agent 管道教学
npx skills add aradotso/trending-skills --skill openmaic-classroomBefore / After 效果对比
1 组手动设计课程结构、编写讲义、制作练习和测验,一门课程需要数周时间
输入主题自动生成完整互动课程,多 Agent 协作教学,学生可立即开始学习
description SKILL.md
openmaic-classroom
OpenMAIC — 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: $CUSTOM_API_KEY
Running the App
# Development
pnpm dev
# → http://localhost:3000
# Production build
pnpm build && pnpm start
# Type checking
pnpm tsc --noEmit
# Linting
pnpm lint
Docker Deployment
cp .env.example .env.local
# Edit .env.local with your API keys
docker compose up --build
# → http://localhost:3000
Vercel Deployment
# Fork the repo, then import at https://vercel.com/new
# Set env vars in Vercel dashboard:
# OPENAI_API_KEY or ANTHROPIC_API_KEY or GOOGLE_API_KEY
# DEFAULT_MODEL (optional, e.g. google:gemini-3-flash-preview)
One-click deploy button is available in the README; it pre-fills env var descriptions automatically.
Lesson Generation Pipeline
OpenMAIC uses a two-stage pipeline:
Stage Description
Outline AI analyzes topic/document and produces a structured lesson outline
Scenes
Each outline item is expanded into a typed scene: slides, quiz, interactive, or pbl
Scene Types
Type Description
slides
AI teacher lectures with TTS narration, spotlight, laser pointer
quiz
Single/multiple choice or short-answer with AI grading
interactive
HTML-based simulation (physics, flowcharts, etc.)
pbl
Project-Based Learning — choose a role, collaborate with agents
API Usage — Generating a Classroom
REST: Start Generation Job
// POST /api/generate
const response = await fetch('/api/generate', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
topic: 'Quantum Entanglement',
// Optional: attach document content
document: markdownString,
// Optional: model override
model: 'google:gemini-3-flash-preview',
}),
});
const { jobId } = await response.json();
REST: Poll Job Status
// GET /api/generate/status?jobId=<jobId>
const poll = async (jobId: string) => {
while (true) {
const res = await fetch(`/api/generate/status?jobId=${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": "$OPENMAIC_ACCESS_CODE",
// Self-hosted mode — local repo + server URL
"repoDir": "/path/to/OpenMAIC",
"url": "http://localhost:3000"
}
}
}
}
}
OpenClaw Skill Lifecycle
Phase What Happens
Clone Detect existing checkout or clone fresh
Startup
Choose pnpm dev, pnpm build && pnpm start, or Docker
Provider Keys
Guide user to edit .env.local
Generation Submit async job, poll, return classroom link
Custom Scene Development Pattern
Scenes are typed React components. To add a new scene type:
// types/scene.ts
export type SceneType = 'slides' | 'quiz' | 'interactive' | 'pbl' | 'custom';
export interface CustomScene {
type: 'custom';
title: string;
content: string;
// your fields
metadata: Record<string, unknown>;
}
// components/scenes/CustomScene.tsx
'use client';
import { type CustomScene } from '@/types/scene';
interface Props {
scene: CustomScene;
onComplete: () => void;
}
export function CustomSceneComponent({ scene, onComplete }: Props) {
return (
<div className="flex flex-col gap-4 p-6">
<h2 className="text-2xl font-bold">{scene.title}</h2>
<div dangerouslySetInnerHTML={{ __html: scene.content }} />
<button
className="mt-4 rounded-lg bg-blue-600 px-6 py-2 text-white"
onClick={onComplete}
>
Continue
</button>
</div>
);
}
Multi-Agent Interaction Modes
Mode Trigger Description
Classroom Discussion Automatic Agents proactively start discussions; user can jump in or get called on
Roundtable Debate Scene config Multiple agent personas debate a topic with whiteboard illustrations
Q&A User asks question AI teacher responds with slides, diagrams, or whiteboard drawings
Whiteboard During any scene Agents draw equations, flowcharts, or concept diagrams in real time
MinerU Advanced Document Parsing
For complex PDFs with tables, formulas, or scanned images:
# Use MinerU hosted API
PDF_MINERU_BASE_URL=https://mineru.net
PDF_MINERU_API_KEY=$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 .pptx
GET /api/export/pptx?classroomId=
Fully editable slides
Interactive .html
GET /api/export/html?classroomId=
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
No LLM provider configured
Set at least one of OPENAI_API_KEY, ANTHROPIC_API_KEY, or GOOGLE_API_KEY in .env.local
Generation hangs at outline stage
Check API key quota; try switching to google:gemini-3-flash-preview 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 PDF_MINERU_BASE_URL in .env.local
Vercel timeout during generation
Increase function timeout in vercel.json; generation is async so the API should return a jobId immediately
Docker build fails
Ensure DOCKER_BUILDKIT=1 and that .env.local exists before running docker compose up --build
OpenClaw skill not found
Run clawhub install openmaic or manually copy skills/openmaic to ~/.openclaw/skills/
pnpm install fails on Node < 20
Upgrade Node.js to >= 20 (nvm use 20)
Port 3000 already in use
Set PORT=3001 in .env.local or run PORT=3001 pnpm dev
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
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