THU-MAIC/OpenMAICPublic

Get an immersive, multi-agent learning experience in just one click

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Live Demo · Quick Start · Lemonade · FunASR · Features · Use Cases · OpenClaw

• 2026-07-21 — v0.3.1 released! One-click MP4 video export; server-backed runtime storage with a Postgres reference server; direct slide manipulation in the editor (drag, resize, rotate, multi-select); smarter "Edit with AI" (validated JSON Patch edits, multi-session history); expanded Document Parsing (multi-format upload, audio/video extraction, AliDocMind, MinerU); new providers (Azure OpenAI, SearXNG, ComfyUI) and the GPT-5.6 model family; action-level playback navigation; SSRF hardening. See changelog.
• 2026-06-28 — v0.3.0 released! Project-Based Learning (PBL) v2 with classroom UI; "Edit with AI" Pro-mode editor agent; the @openmaic/* SDK family (DSL/renderer/importer) published to npm; optional per-stage model routing; new models (GLM-5.2, Kimi K2.7 Code, Qwen3.7 Plus/Max); a vocational-learning task engine; Korean (ko-KR) locale; and relicensing from AGPL-3.0 to MIT. See changelog.
• 2026-06-02 — v0.2.2 released! MAIC Editor (v0) Pro Mode for editing generated slides; editable outline before generation; offline-ready classroom export; new search providers (Brave/Baidu/Bocha/MiniMax) and Azure STT; new models (Claude Opus 4.8, MiniMax M3, Gemini 3.5 Flash); Traditional Chinese (zh-TW) and Brazilian Portuguese (pt-BR) locales. See changelog.
• 2026-04-26 — v0.2.1 released! Integrated VoxCPM2 TTS with voice cloning and on-the-fly auto-generated voices; added per-model thinking config; added end-of-course completion page with persistent quiz state; added latest released models including DeepSeek-V4 / GPT-5.5 / GPT-Image-2 / Xiaomi MiMo / Hy3. See changelog.
• 2026-04-20 — v0.2.0 released! Deep Interactive Mode — 3D visualization, simulations, games, mind maps, and online programming for hands-on learning. See features for details.
• 2026-04-14 — v0.1.1 released! Automatic language inference, ACCESS_CODE authentication, classroom ZIP export/import, custom TTS/ASR providers, Ollama support, and more. See changelog.
• 2026-03-26 — v0.1.0 released! Discussion TTS, immersive mode, keyboard shortcuts, whiteboard enhancements, new providers, and more. See changelog.

OpenMAIC (Open Multi-Agent Interactive Classroom) is an open-source AI platform that turns any topic or document into a rich, interactive classroom experience. Powered by multi-agent orchestration, it generates slides, quizzes, interactive simulations, and project-based learning activities — all delivered by AI teachers and AI classmates who can speak, draw on a whiteboard, and engage in real-time discussions with you. With built-in OpenClaw integration, you can generate classrooms directly from messaging apps like Feishu, Slack, or Telegram.

• One-click lesson generation — Describe a topic or attach your materials; the AI builds a full lesson in minutes
• Multi-agent classroom — AI teachers and peers lecture, discuss, and interact with you in real time
• Rich scene types — Slides, quizzes, interactive HTML simulations, and project-based learning (PBL)
• Whiteboard & TTS — Agents draw diagrams, write formulas, and explain out loud
• Export anywhere — Download editable .pptx slides or interactive .html pages
• OpenClaw integration — Generate classrooms from Feishu, Slack, Telegram, and 20+ messaging apps via your AI assistant

• Node.js >= 20
• pnpm >= 10

git clone https://github.com/THU-MAIC/OpenMAIC.git
cd OpenMAIC
pnpm install

cp .env.example .env.local

Fill in at least one LLM provider key:

OPENAI_API_KEY=sk-...
AZURE_OPENAI_API_KEY=...
AZURE_OPENAI_BASE_URL=https://YOUR-RESOURCE.openai.azure.com/openai
AZURE_OPENAI_MODELS=YOUR-DEPLOYMENT-NAME
ANTHROPIC_API_KEY=sk-ant-...
GOOGLE_API_KEY=...
GROK_API_KEY=xai-...
OPENROUTER_API_KEY=sk-or-...
TENCENT_API_KEY=sk-...
XIAOMI_API_KEY=...
# Or configure Amazon Bedrock with AWS credentials and BEDROCK_REGION.

You can also configure providers via server-providers.yml:

providers:
  openai:
    apiKey: sk-...
  azure:
    apiKey: ...
    baseUrl: https://YOUR-RESOURCE.openai.azure.com/openai
    models:
      - YOUR-DEPLOYMENT-NAME
  anthropic:
    apiKey: sk-ant-...
  bedrock:
    models:
      - us.anthropic.claude-sonnet-5
      - us.anthropic.claude-opus-4-8

Supported providers: OpenAI, Azure OpenAI, Anthropic, Amazon Bedrock, Google Gemini, DeepSeek, Qwen, Kimi, MiniMax, Grok (xAI), OpenRouter, Doubao, Tencent Hunyuan/TokenHub, Xiaomi MiMo, GLM (Zhipu), Ollama (local), Lemonade (local LLM / image / TTS / ASR), FunASR (local ASR), and any OpenAI-compatible API.

Amazon Bedrock quick example:

BEDROCK_REGION=us-east-1
BEDROCK_MODELS=us.anthropic.claude-sonnet-5,us.anthropic.claude-opus-4-8
DEFAULT_MODEL=bedrock:us.anthropic.claude-sonnet-5

Bedrock uses AWS environment credentials or the AWS SDK credential provider chain. For temporary credentials, set AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, and AWS_SESSION_TOKEN, or use an AWS profile / role available to the runtime.

OpenMAIC supports Lemonade as a local, OpenAI-compatible provider for LLMs, image generation, TTS, and ASR. No API key is required.

Run Lemonade locally, then point OpenMAIC to it:

LEMONADE_BASE_URL=http://localhost:13305/v1
TTS_LEMONADE_BASE_URL=http://localhost:13305/v1
ASR_LEMONADE_BASE_URL=http://localhost:13305/v1
IMAGE_LEMONADE_BASE_URL=http://localhost:13305/v1

OpenMAIC can transcribe locally through FunASR's OpenAI-compatible server. The built-in provider supports SenseVoiceSmall, Paraformer, and Fun-ASR-Nano and requires no API key.

python -m pip install torch torchaudio
python -m pip install "funasr==1.4.0" fastapi uvicorn python-multipart
# Add vLLM for Fun-ASR-Nano on NVIDIA GPUs
python -m pip install vllm
funasr-server --device cuda --model fun-asr-nano

Point OpenMAIC at the server:

ASR_FUNASR_BASE_URL=http://localhost:8000/v1

Use funasr-server --device cpu --model sensevoice for a CPU-only setup. See the FunASR deployment guide for production options.

OpenAI quick example:

OPENAI_API_KEY=sk-...
DEFAULT_MODEL=openai:gpt-5.5

MiniMax quick examples:

MINIMAX_API_KEY=...
MINIMAX_BASE_URL=https://api.minimaxi.com/anthropic/v1
DEFAULT_MODEL=minimax:MiniMax-M2.7-highspeed

TTS_MINIMAX_API_KEY=...
TTS_MINIMAX_BASE_URL=https://api.minimaxi.com

IMAGE_MINIMAX_API_KEY=...
IMAGE_MINIMAX_BASE_URL=https://api.minimaxi.com

IMAGE_OPENAI_API_KEY=...
IMAGE_OPENAI_BASE_URL=https://api.openai.com/v1

VIDEO_MINIMAX_API_KEY=...
VIDEO_MINIMAX_BASE_URL=https://api.minimaxi.com

Xiaomi MiMo Token Plan quick example:

MIMO_API_KEY=tp-...
MIMO_BASE_URL=https://token-plan-cn.xiaomimimo.com/v1
DEFAULT_MODEL=xiaomi:mimo-v2.5-pro

Use https://token-plan-sgp.xiaomimimo.com/v1 or https://token-plan-ams.xiaomimimo.com/v1 for the Singapore or Europe Token Plan clusters.

GLM (Zhipu) quick examples:

# China (default)
GLM_API_KEY=...
GLM_BASE_URL=https://open.bigmodel.cn/api/paas/v4

# International (z.ai)
GLM_API_KEY=...
GLM_BASE_URL=https://api.z.ai/api/paas/v4

DEFAULT_MODEL=glm:glm-5.1

Recommended model: Gemini 3 Flash — best balance of quality and speed. For highest quality (at slower speed), try Gemini 3.1 Pro.

If you want OpenMAIC server APIs to use Gemini by default, also set DEFAULT_MODEL=google:gemini-3-flash-preview.

If you want to use MiniMax as the default server model, set DEFAULT_MODEL=minimax:MiniMax-M2.7-highspeed.

pnpm dev

Open http://localhost:3000 and start learning!

pnpm build && pnpm start

To protect your deployment with a site-level password, set ACCESS_CODE in .env.local:

ACCESS_CODE=your-secret-code

When set, visitors see a password prompt before accessing the app. All API routes are also protected. If not set, the app works as before.

Or manually:

1. Fork this repository
2. Import into Vercel
3. Set environment variables (at minimum one LLM API key)
4. Deploy

cp .env.example .env.local
# Edit .env.local with your API keys, then:
docker compose up --build

The server-persistence profile runs exactly two containers: the OpenMAIC app and PostgreSQL. The persistence HTTP server is embedded in the app at /api/persistence; there is no standalone persistence service.

cp .env.example .env.local
printf '\nDATABASE_URL=postgres://openmaic:openmaic-dev@postgres:5432/openmaic\nPERSISTENCE_DEV_TOKEN=openmaic-local-dev\n' >> .env.local
NEXT_PUBLIC_PERSISTENCE=1 NEXT_PUBLIC_PERSISTENCE_TOKEN=openmaic-local-dev docker compose --profile server-persistence up --build

Add your provider API keys to .env.local as usual. Runtime sessions and course documents become server-backed; device-scoped KV data (including the anonymous device learner key and playback position) remains in the browser. Existing browser course data is copied into the configured server store lazily, one course at a time when it is first accessed, using the same verified migration path as browser persistence.

NEXT_PUBLIC_PERSISTENCE is a build-time switch compiled into the browser bundle. A build with it enabled must be deployed with a working runtime DATABASE_URL and PERSISTENCE_DEV_TOKEN, while NEXT_PUBLIC_PERSISTENCE_TOKEN must match that server token at build time. Otherwise the browser selects HTTP persistence but the embedded endpoint returns configuration/authentication/initialization errors; the home page shows a persistence-unavailable toast and keeps the prior course list instead of misleadingly displaying an empty library.

PERSISTENCE_DEV_TOKEN and NEXT_PUBLIC_PERSISTENCE_TOKEN are not a secret in any meaningful sense: the NEXT_PUBLIC_ token is compiled into the public JavaScript bundle, fully visible to every visitor, and therefore provides no confidentiality and no user isolation whatsoever — anyone who can load the page can extract it and read or write every learner partition and all documents by choosing an x-learner-key. Its only purpose is to keep unrelated network scanners out of an endpoint on a trusted network. This is suitable only for localhost or trusted-network, single-user deployments. Before production, replace lib/persistence/server-auth.ts with real session verification that derives the learner partition from server-controlled identity, and change the document/merge/admin authorization policies as appropriate.

PERSISTENCE_POSTGRES_PASSWORD initializes the PostgreSQL role only when the data directory is empty; changing it later does not rotate an existing openmaic-postgres volume. For a disposable local database, run docker compose --profile server-persistence down -v, set the new password and matching DATABASE_URL, then start the profile again. To preserve data, connect as an administrator and run ALTER ROLE openmaic WITH PASSWORD 'new-password';, then update DATABASE_URL.

Compose cannot attach depends_on to openmaic only when this optional profile is active without also affecting the default deployment. Startup therefore relies on the embedded route's retry-on-next-request behavior while PostgreSQL becomes healthy.

The embedded endpoint implements the package's RuntimeStore HTTP contract and DocumentStore HTTP contract. Leave NEXT_PUBLIC_PERSISTENCE unset to retain the existing browser-only behavior.

The "Export Video" menu builds a self-contained Hyperframes project entirely in the browser. Turning that into an MP4 needs Chromium + FFmpeg on Node 22, so it runs in an isolated render-service container rather than the app.

It's opt-in. Start it with the video-export compose profile:

docker compose --profile video-export up --build

The app auto-detects the service via RENDER_SERVICE_URL (preset in docker-compose.yml) and enables one-click MP4 rendering. Without the profile — or when RENDER_SERVICE_URL is unset — export degrades to downloading the project ZIP for local CLI rendering. See render-service/README.md for standalone setup and tuning (RENDER_MAX_CONCURRENCY, etc.).

MinerU provides enhanced parsing for complex tables, formulas, and OCR. You can use the MinerU official API or self-host your own instance.

Set PDF_MINERU_BASE_URL (and PDF_MINERU_API_KEY if needed) in .env.local.

VoxCPM2 is an open-source TTS model from OpenBMB with voice cloning. OpenMAIC ships an adapter; run VoxCPM on your own hardware and OpenMAIC will talk to it.

1. Run a VoxCPM backend. Three deployment styles, all behind the same OpenMAIC adapter. You toggle which one in Settings.

See the VoxCPM repo for backend setup.

2. Point OpenMAIC at it. Open Settings → Text-to-Speech → VoxCPM2, pick the backend, and paste your Base URL. The Request URL preview confirms OpenMAIC will hit the right endpoint.

Or pre-configure it via env var (no API key required):

TTS_VOXCPM_BASE_URL=http://localhost:8000/v1

3. Manage voices. Three voice modes, all under Settings → Text-to-Speech → VoxCPM2 → VoxCPM Voices.

• Auto Voice (default): OpenMAIC generates a voice prompt from each agent's persona at synthesis time. No setup required.
• Prompt voice: describe the voice in natural language, e.g. "warm female teacher voice, calm and encouraging, mid-pitch".
• Clone voice: upload a short reference audio clip or record one in the browser. The clip is stored in IndexedDB and sent to your VoxCPM backend on each synthesis.

Passive listening? ❌ Hands-on exploration! ✅

As Einstein said: "Play is the highest form of research."

While Standard Mode focuses on quickly generating classroom content, Deep Interactive Mode goes further — creating interactive, explorable, hands-on learning experiences. Students don't just watch knowledge; they adjust experiments, observe simulations, and actively explore how things work.

🌐 3D Visualization Three-dimensional visual representations that make abstract structures more intuitive.	⚙️ Simulation Process simulations and experimental environments for observing dynamic changes and outcomes.
🎮 Game Knowledge-based mini-games that reinforce understanding and memory through interactive challenges.	🧭 Mind Map Structured knowledge organization to help learners build an overall conceptual framework.
💻 Online Programming In-browser coding and instant execution for learning by writing, testing, and iterating.

The AI teacher can actively operate the UI to guide students — highlighting key areas, setting conditions, providing hints, and directing attention at the right moments.

All generated interactive UI is fully responsive — desktop, tablet, or mobile.

Desktop	Mobile
iPad

If you are looking for a version with richer functionality, stronger interactivity, and deeper optimization for high-quality educational UI production, please visit MAIC-UI.

Describe what you want to learn or attach reference materials. OpenMAIC's two-stage pipeline handles the rest:

🎓 Slides AI teachers deliver lectures with voice narration, spotlight effects, and laser pointer animations — just like a real classroom.	🧪 Quiz Interactive quizzes (single / multiple choice, short answer) with real-time AI grading and feedback.
🔬 Interactive Simulation HTML-based interactive experiments for visual, hands-on learning — physics simulators, flowcharts, and more.	🏗️ Project-Based Learning (PBL) Choose a role and collaborate with AI agents on structured projects with milestones and deliverables.

Classroom Discussion — Agents proactively initiate discussions; you can jump in anytime or get called on Roundtable Debate — Multiple agents with different personas discuss a topic, with whiteboard illustrations Q&A Mode — Ask questions freely; the AI teacher responds with slides, diagrams, or whiteboard drawings Whiteboard — AI agents draw on a shared whiteboard in real time — solving equations step by step, sketching flowcharts, or illustrating concepts visually.

OpenMAIC integrates with OpenClaw — a personal AI assistant that connects to messaging platforms you already use (Feishu, Slack, Discord, Telegram, WhatsApp, etc.). With this integration, you can generate and view interactive classrooms directly from your chat app without ever touching a terminal.

Just tell your OpenClaw assistant what you want to learn — it handles everything else:

• Hosted mode — Grab an access code from open.maic.chat, save it in your config, and generate classrooms instantly — no local setup required
• Self-hosted mode — Clone, install dependencies, configure API keys, and start the server — the skill guides you through each step
• Track progress — Poll the async generation job and send you the link when ready

Every step asks for your confirmation first. No black-box automation.

clawhub install openmaic

mkdir -p ~/.openclaw/skills
cp -R /path/to/OpenMAIC/skills/openmaic ~/.openclaw/skills/openmaic

{
  "skills": {
    "entries": {
      "openmaic": {
        "config": {
          // Hosted mode: paste your access code from open.maic.chat
          "accessCode": "sk-xxx",
          // Self-hosted mode: local repo path and URL
          "repoDir": "/path/to/OpenMAIC",
          "url": "http://localhost:3000"
        }
      }
    }
  }
}

Offline / intranet classrooms: When you export a classroom (.maic.zip) or a Resource Pack, OpenMAIC inlines the external assets referenced by interactive scenes (KaTeX, Three.js incl. three/addons, Tailwind CDN, Google Fonts, images) into the exported HTML as data: URIs. The exported course then plays fully offline after import into an air-gapped/intranet instance — no public CDN is contacted at playback time. Assets that can't be fetched at export time (e.g. CORS-restricted image hosts) are reported and left as URLs. Classrooms exported before this feature still reference CDNs and must be re-exported to gain offline support.

• Text-to-Speech — Multiple voice providers with customizable voices
• Speech Recognition — Talk to your AI teacher using your microphone
• Web Search — Agents search the web for up-to-date information during class
• i18n — Interface supports 7 languages: Chinese (Simplified & Traditional), English, Japanese, Russian, Arabic, and Portuguese (Brazil)
• Dark Mode — Easy on the eyes for late-night study sessions

"Teach me Python from scratch in 30 min"	"How to play the board game Avalon"
"Analyze the stock prices of Zhipu and MiniMax"	"Break down the latest DeepSeek paper"

We welcome contributions from the community! Whether it's bug reports, feature ideas, or pull requests — every bit helps.

OpenMAIC/
├── app/                        # Next.js App Router
│   ├── api/                    #   Server API routes (~18 endpoints)
│   │   ├── generate/           #     Scene generation pipeline (outlines, content, images, TTS …)
│   │   ├── generate-classroom/ #     Async classroom job submission + polling
│   │   ├── chat/               #     Multi-agent discussion (SSE streaming)
│   │   ├── pbl/                #     Project-Based Learning endpoints
│   │   └── ...                 #     quiz-grade, parse-pdf, web-search, transcription, etc.
│   ├── classroom/[id]/         #   Classroom playback page
│   └── page.tsx                #   Home page (generation input)
│
├── lib/                        # Core business logic
│   ├── generation/             #   Two-stage lesson generation pipeline
│   ├── orchestration/          #   LangGraph multi-agent orchestration (director graph)
│   ├── playback/               #   Playback state machine (idle → playing → live)
│   ├── action/                 #   Action execution engine (speech, whiteboard, effects)
│   ├── ai/                     #   LLM provider abstraction
│   ├── api/                    #   Stage API facade (slide/canvas/scene manipulation)
│   ├── store/                  #   Zustand state stores
│   ├── types/                  #   Centralized TypeScript type definitions
│   ├── audio/                  #   TTS & ASR providers
│   ├── media/                  #   Image & video generation providers
│   ├── export/                 #   PPTX & HTML export
│   ├── hooks/                  #   React custom hooks (55+)
│   ├── i18n/                   #   Internationalization (zh-CN, zh-TW, en-US, ja-JP, ru-RU, ar-SA, pt-BR)
│   └── ...                     #   prosemirror, storage, pdf, web-search, utils
│
├── components/                 # React UI components
│   ├── slide-renderer/         #   Canvas-based slide editor & renderer
│   │   ├── Editor/Canvas/      #     Interactive editing canvas
│   │   └── components/element/ #     Element renderers (text, image, shape, table, chart …)
│   ├── scene-renderers/        #   Quiz, Interactive, PBL scene renderers
│   ├── generation/             #   Lesson generation toolbar & progress
│   ├── chat/                   #   Chat area & session management
│   ├── settings/               #   Settings panel (providers, TTS, ASR, media …)
│   ├── whiteboard/             #   SVG-based whiteboard drawing
│   ├── agent/                  #   Agent avatar, config, info bar
│   ├── ui/                     #   Base UI primitives (shadcn/ui + Radix)
│   └── ...                     #   audio, roundtable, stage, ai-elements
│
├── packages/                   # Workspace packages
│   ├── pptxgenjs/              #   Customized PowerPoint generation
│   └── mathml2omml/            #   MathML → Office Math conversion
│
├── skills/                     # OpenClaw / ClawHub skills
│   └── openmaic/               #   Guided OpenMAIC setup & generation SOP
│       ├── SKILL.md            #   Thin router with confirmation rules
│       └── references/         #   On-demand SOP sections
│
├── configs/                    # Shared constants (shapes, fonts, hotkeys, themes …)
└── public/                     # Static assets (logos, avatars)

• Generation Pipeline (lib/generation/) — Two-stage: outline generation → scene content generation
• Multi-Agent Orchestration (lib/orchestration/) — LangGraph state machine managing agent turns and discussions
• Playback Engine (lib/playback/) — State machine driving classroom playback and live interaction
• Action Engine (lib/action/) — Executes 28+ action types (speech, whiteboard draw/text/shape/chart, spotlight, laser …)

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

This project is licensed under the MIT License, so commercial use is permitted free of charge. For partnership or collaboration inquiries, please contact: thu_maic@mail.tsinghua.edu.cn

If you find OpenMAIC useful in your research, please consider citing:

@Article{JCST-2509-16000,
  title = {From MOOC to MAIC: Reimagine Online Teaching and Learning through LLM-driven Agents},
  journal = {Journal of Computer Science and Technology},
  volume = {},
  number = {},
  pages = {},
  year = {2026},
  issn = {1000-9000(Print) /1860-4749(Online)},
  doi = {10.1007/s11390-025-6000-0},
  url = {https://jcst.ict.ac.cn/en/article/doi/10.1007/s11390-025-6000-0},
  author = {Ji-Fan Yu and Daniel Zhang-Li and Zhe-Yuan Zhang and Yu-Cheng Wang and Hao-Xuan Li and Joy Jia Yin Lim and Zhan-Xin Hao and Shang-Qing Tu and Lu Zhang and Xu-Sheng Dai and Jian-Xiao Jiang and Shen Yang and Fei Qin and Ze-Kun Li and Xin Cong and Bin Xu and Lei Hou and Man-Li Li and Juan-Zi Li and Hui-Qin Liu and Yu Zhang and Zhi-Yuan Liu and Mao-Song Sun}
}

This project is licensed under the MIT License.

The repository bundles workspace packages that are not covered by the root MIT license and keep their own terms:

• packages/mathml2omml — LGPL-3.0-or-later
• packages/pptxgenjs — MIT (third-party)

When redistributing the repository as a whole, the terms of each bundled package above apply to that package's files.