metaai-api

Unofficial Python SDK and API server for Meta AI — generate images, chat with Llama, and manage conversations. No API key required, just your browser cookies.

⚠️ Disclaimer: This is an unofficial, reverse-engineered client. It is not affiliated with, endorsed by, or sponsored by Meta. Use at your own risk and in compliance with Meta's Terms of Service. Cookie-based authentication may break at any time as Meta updates their platform.

What's New in v3.0.0

Meta AI migrated from HTTP GraphQL to DGW (Datagram WebSocket) for all chat and image generation. The old HTTP-based methods no longer work — Meta's GraphQL schema changed (removed RewriteOptionsInput, AttachmentInput, MentionInput, sendMessageStream, and more).

This version uses browser automation (via agent-browser) as the primary method, which works for ANY prompt. The browser creates valid DGW messages natively.

Breaking Changes from v2.x

• prompt() now uses browser automation (no more OAuth token extraction)
• generate_image_new() uses browser automation
• Video generation is NOT available on Meta AI (Meta says "I can't generate videos right now")
• upload_image() is not yet supported via browser method
• Cookie-based auth replaces access token for primary methods

What Still Works

• ✅ Image generation (text → image)
• ✅ Chat (text conversation, Instant + Thinking modes)
• ✅ Conversation management (list, new)
• ✅ Media fetching by card ID (HTTP GraphQL)
• ✅ DGW frame replay (advanced WebSocket method)

Features

• 🖼️ Image generation — Create images from text prompts
• 💬 Chat — Text conversation with Meta AI (Instant + Thinking modes)
• 📋 Conversation management — List conversations
• 🔗 Media fetching — Get URLs for already-generated media by card ID
• 🔓 No API key — Uses your browser cookies for authentication
• 🌐 REST API server — Deploy once, call from any language
• 📦 Python SDK — Use as a library in your Python projects

Install

pip install metaai-sdk[api,browser]
agent-browser install  # downloads Chrome for browser automation

Or from source:

git clone https://github.com/mir-ashiq/metaai-api.git
cd metaai-api
pip install -e ".[api,browser]"
agent-browser install

Quick Start

As a Python SDK

from metaai_api import MetaAI

ai = MetaAI(cookies={
    "datr": "your_datr_cookie",
    "ecto_1_sess": "your_ecto_1_sess_cookie",
})

# Generate an image
result = ai.generate_image_new("a watercolor painting of a red panda")
print(result["image_urls"])

# Chat
reply = ai.prompt("What is 2+2?")
print(reply["message"])

# List conversations
convs = ai.list_conversations()
for c in convs:
    print(c["title"])

ai.close()

As an API server

export META_AI_DATR="your_datr_cookie"
export META_AI_ECTO_1_SESS="your_ecto_1_sess_cookie"
export META_AI_API_KEY="your_secret_key"  # optional

python -m metaai_api.api_server

Then call from any language:

curl -X POST http://localhost:8000/image \
  -H "Authorization: Bearer your_secret_key" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "a watercolor painting of a cat"}'

Getting Your Cookies

1. Open https://www.meta.ai/ and log in
2. Press F12 → Application → Cookies → https://www.meta.ai
3. Copy the values of datr and ecto_1_sess

Or set them as environment variables:

export META_AI_DATR="..."
export META_AI_ECTO_1_SESS="..."

See CHANGES_AND_COOKIES.md for details on cookie expiration and the optional access token.

API Reference

Python SDK

REST API Endpoints

How It Works

Meta AI uses a custom WebSocket protocol called DGW (Datagram WebSocket) for image generation and chat. The server validates message integrity, so you can't construct valid messages from scratch in Python.

This SDK uses browser automation (via agent-browser) to drive a real headless Chrome browser:

1. Launches Chrome with your cookies injected
2. Types the prompt into the meta.ai chat input
3. Waits for the image/response to appear
4. Extracts URLs and text from the page

For advanced users, the replay_frame() method allows replaying captured DGW frames via WebSocket (each frame works once).

See GENERATION_API.md for detailed API usage.

Deployment

Docker

export META_AI_DATR="..."
export META_AI_ECTO_1_SESS="..."
export META_AI_API_KEY="..."

docker-compose up -d

Direct

pip install metaai-sdk[api,browser]
agent-browser install
python -m metaai_api.api_server

See QUICK_START.md for a step-by-step guide.

Limitations

• Video generation: NOT available on Meta AI. Meta AI responds: "I can't generate videos right now."
• Cookie expiration: ecto_1_sess expires frequently. Re-extract if requests fail.
• Speed: ~30-40s per image (browser startup + generation).
• Region: Meta AI isn't available in all regions.
• Image upload: Not yet supported via browser method.

Environment Variables

Project Structure

metaai-api/
├── src/metaai_api/
│   ├── __init__.py          # Package exports
│   ├── main.py              # MetaAI class (main entry point)
│   ├── generation.py        # GenerationAPI (image/video generation)
│   ├── client.py            # MetaAIClient (HTTP/WebSocket)
│   ├── browser.py           # BrowserBackend (agent-browser automation)
│   ├── api_server.py        # FastAPI server
│   ├── parser.py            # DGW frame parser
│   ├── exceptions.py        # Error hierarchy
│   ├── utils.py             # Constants and helpers
│   ├── html_scraper.py      # HTML scraping (legacy)
│   ├── image_upload.py      # Image upload (legacy)
│   ├── video_generation.py  # Video generation (legacy)
│   └── video_generation_new.py  # Video generation (legacy)
├── examples/                # Example scripts
├── scripts/                 # Test scripts
├── test/                    # Test suite
├── Dockerfile               # Docker deployment
├── docker-compose.yml       # Docker Compose
├── pyproject.toml           # Package config
└── requirements.txt         # Dependencies

License

MIT

Author

Ashiq Hussain Mir