HappyHorse 1.0 API: Python Wrapper for Alibaba's #1 AI Video Generator

The most comprehensive Python wrapper for the HappyHorse 1.0 API (developed by Alibaba's Taotian Group), delivered via muapi.ai. Generate cinematic, native 1080p AI videos with integrated audio from text prompts and static images — currently ranked #1 on the Artificial Analysis Video Arena.

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🌊 Also explore these top AI video models:

• 🎬 Seedance 2.0 API — ByteDance's cinematic 2K model with character sheets, omni-reference & video edit
• 🎥 Veo 4 API — Google DeepMind's native 4K model with audio, character consistency & camera controls

🚀 Why Use HappyHorse 1.0 API?

HappyHorse 1.0 is Alibaba's state-of-the-art AI video generation model, built by the Future Life Lab team at Taotian Group. It debuted anonymously on April 7, 2026, instantly claiming the top spot in both Text-to-Video and Image-to-Video categories on the Artificial Analysis leaderboard.

• #1 Ranked: 1333 Elo in T2V, 1392 Elo in I2V — surpassing every competitor on the Artificial Analysis leaderboard.
• Native 1080p HD: Full HD output without upscaling, powered by a 15B-parameter 40-layer Transformer architecture.
• Integrated Audio-Video: Jointly generates video and audio in a single forward pass — no separate audio pipeline needed.
• Blazing Fast: ~10 seconds average generation time, one of the fastest available models.
• Developer-First: Simple Python SDK via MuAPI infrastructure.

🌟 Key Features of HappyHorse 1.0 API

• ✅ HappyHorse 1.0 Text-to-Video (T2V): Transform descriptive prompts into stunning native 1080p HD video clips.
• ✅ HappyHorse 1.0 Image-to-Video (I2V): Animate static images with precise motion control using images_list.
• ✅ Integrated Audio-Video Generation: Generate synchronized audio and video jointly in one Transformer pass — include sound cues like "rain pattering" or "crowd cheering" directly in your prompt.
• ✅ Video Extension: Seamlessly extend existing clips while maintaining consistent style and motion.
• ✅ Video Edit: Edit existing videos using natural language prompts and reference images.
• ✅ File Upload: Upload local images and videos directly via the upload_file method for use in generation tasks.
• ✅ Flexible Aspect Ratios: Optimized for 16:9, 9:16 (TikTok/Reels), and 1:1.
• ✅ Quality Tiers: 1080p (default) and 4k output support.

🛠 Installation

Via Pip (Recommended)

pip install happyhorse-1-api

From Source

# Clone the HappyHorse 1.0 API repository
git clone https://github.com/Anil-matcha/HappyHorse-1.0-API.git
cd HappyHorse-1.0-API

# Install required dependencies
pip install -r requirements.txt

Configuration

Create a .env file in the root directory and add your MuAPI API key:

MUAPI_API_KEY=your_muapi_api_key_here

🤖 HappyHorse 1.0 MCP Server

Use HappyHorse 1.0 as an MCP (Model Context Protocol) server, allowing AI assistants like Claude Desktop or Cursor to directly invoke HappyHorse generation tools.

Running the MCP Server

1. Ensure MUAPI_API_KEY is set in your environment.
2. Run the server:

   python3 mcp_server.py
   

3. To test

... View full README on GitHub