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.
Join subreddit HappyHorseAI for discussion
Try for free ArenaAI
🌊 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
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.
- ✅ 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_filemethod for use in generation tasks. - ✅ Flexible Aspect Ratios: Optimized for
16:9,9:16(TikTok/Reels), and1:1. - ✅ Quality Tiers:
1080p(default) and4koutput support.
pip install happyhorse-1-api# 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.txtCreate a .env file in the root directory and add your MuAPI API key:
MUAPI_API_KEY=your_muapi_api_key_hereUse HappyHorse 1.0 as an MCP (Model Context Protocol) server, allowing AI assistants like Claude Desktop or Cursor to directly invoke HappyHorse generation tools.
- Ensure
MUAPI_API_KEYis set in your environment. - Run the server:
python3 mcp_server.py
- To test with the MCP Inspector:
npx -y @modelcontextprotocol/inspector python3 mcp_server.py
from happyhorse_api import HappyHorseAPI
# Initialize the HappyHorse 1.0 client
api = HappyHorseAPI()
# 1. Generate Video from Text (T2V)
print("Generating AI Video using HappyHorse 1.0...")
submission = api.text_to_video(
prompt="A cinematic aerial shot of a coastal city at golden hour, waves crashing against cliffs, birds flying, 1080p",
aspect_ratio="16:9",
duration=10,
quality="1080p"
)
# 2. Wait for completion
result = api.wait_for_completion(submission['request_id'])
print(f"Success! View your HappyHorse 1.0 video here: {result['outputs'][0]}")HappyHorse 1.0's standout feature: jointly generating video and audio in a single Transformer forward pass.
from happyhorse_api import HappyHorseAPI
api = HappyHorseAPI()
# Generate video + audio together from text
submission = api.text_to_video_with_audio(
prompt="A thunderstorm rolling over a mountain range, lightning flashing, thunder rumbling, rain pattering on leaves",
aspect_ratio="16:9",
duration=10,
quality="1080p"
)
result = api.wait_for_completion(submission['request_id'])
print(f"Video with audio: {result['outputs'][0]}")
# Or use image-to-video with audio
submission = api.image_to_video_with_audio(
prompt="@image1 comes alive — waves crashing, seagulls calling, ocean breeze",
images_list=["https://example.com/beach.jpg"],
aspect_ratio="16:9",
duration=10,
)
result = api.wait_for_completion(submission['request_id'])
print(f"Animated image with audio: {result['outputs'][0]}")Tip: Include explicit sound cues in your prompt (e.g. "crowd cheering", "piano melody", "engine roaring") for richer, more accurate audio generation.
Endpoint: POST https://api.muapi.ai/api/v1/happyhorse-1.0-t2v
curl --location --request POST "https://api.muapi.ai/api/v1/happyhorse-1.0-t2v" \
--header "Content-Type: application/json" \
--header "x-api-key: YOUR_API_KEY" \
--data-raw '{
"prompt": "A majestic eagle soaring over snow-capped mountains at sunrise",
"aspect_ratio": "16:9",
"duration": 10,
"quality": "1080p"
}'Endpoint: POST https://api.muapi.ai/api/v1/happyhorse-1.0-i2v
Reference images with @image1, @image2, etc. in the prompt.
curl --location --request POST "https://api.muapi.ai/api/v1/happyhorse-1.0-i2v" \
--header "Content-Type: application/json" \
--header "x-api-key: YOUR_API_KEY" \
--data-raw '{
"prompt": "@image1 — the clouds drift slowly, light shifts from golden to dusk",
"images_list": ["https://example.com/landscape.jpg"],
"aspect_ratio": "16:9",
"duration": 10,
"quality": "1080p"
}'Endpoint: POST https://api.muapi.ai/api/v1/happyhorse-1.0-t2v-audio
Jointly generate video and synchronized audio in one pass.
curl --location --request POST "https://api.muapi.ai/api/v1/happyhorse-1.0-t2v-audio" \
--header "Content-Type: application/json" \
--header "x-api-key: YOUR_API_KEY" \
--data-raw '{
"prompt": "A busy Tokyo street at night, neon signs, rain, traffic noise, jazz music drifting from a bar",
"aspect_ratio": "16:9",
"duration": 10,
"quality": "1080p"
}'Endpoint: POST https://api.muapi.ai/api/v1/happyhorse-1.0-i2v-audio
Animate images with jointly generated audio.
curl --location --request POST "https://api.muapi.ai/api/v1/happyhorse-1.0-i2v-audio" \
--header "Content-Type: application/json" \
--header "x-api-key: YOUR_API_KEY" \
--data-raw '{
"prompt": "@image1 — waves begin to crash, seagulls cry in the distance, wind howling",
"images_list": ["https://example.com/ocean.jpg"],
"aspect_ratio": "16:9",
"duration": 10,
"quality": "1080p"
}'Endpoint: POST https://api.muapi.ai/api/v1/happyhorse-1.0-extend
curl --location --request POST "https://api.muapi.ai/api/v1/happyhorse-1.0-extend" \
--header "Content-Type: application/json" \
--header "x-api-key: YOUR_API_KEY" \
--data-raw '{
"request_id": "your-completed-request-id",
"prompt": "The eagle lands on a mountain peak, surveying the valley",
"duration": 10,
"quality": "1080p"
}'Endpoint: POST https://api.muapi.ai/api/v1/happyhorse-1.0-video-edit
curl --location --request POST "https://api.muapi.ai/api/v1/happyhorse-1.0-video-edit" \
--header "Content-Type: application/json" \
--header "x-api-key: YOUR_API_KEY" \
--data-raw '{
"prompt": "Change the weather to a dramatic thunderstorm",
"video_urls": ["https://example.com/video.mp4"],
"aspect_ratio": "16:9",
"quality": "1080p"
}'| Method | Parameters | Description |
|---|---|---|
text_to_video |
prompt, aspect_ratio, duration, quality, with_audio |
Generate native 1080p video from text. |
image_to_video |
prompt, images_list, aspect_ratio, duration, quality, with_audio |
Animate images. Reference with @image1, @image2, etc. |
text_to_video_with_audio |
prompt, aspect_ratio, duration, quality |
T2V with jointly generated audio in one pass. |
image_to_video_with_audio |
prompt, images_list, aspect_ratio, duration, quality |
I2V with jointly generated audio in one pass. |
extend_video |
request_id, prompt, duration, quality |
Extend an existing HappyHorse video segment. |
video_edit |
prompt, video_urls, images_list, aspect_ratio, quality |
Edit existing videos with natural language. |
upload_file |
file_path |
Upload a local file (image or video) to MuAPI. |
get_result |
request_id |
Check task status and retrieve outputs. |
wait_for_completion |
request_id, poll_interval, timeout |
Blocking helper — polls until generation completes. |
- API Provider: MuAPI.ai
- Leaderboard: Artificial Analysis Video Arena
This project is licensed under the MIT License - see the LICENSE file for details.
Keywords: HappyHorse 1.0 API, Alibaba HappyHorse, AI Video Generator, Text-to-Video AI, Image-to-Video API, HappyHorse Python SDK, Alibaba Video AI, Audio Video Generation, Integrated Audio Video, MuAPI, Video Generation API, Native 1080p AI Video, AI Video Creation, HappyHorse API Documentation, HappyHorse I2V, HappyHorse T2V, AI Movie Generator, Python Video API, HappyHorse Tutorial, #1 AI Video Model.