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HappyHorse by Ace Data Cloud — source CLI

A command-line tool for AI video generation using HappyHorse through the AceDataCloud platform.

Installation status

The HappyHorse MCP package is publicly available at mcp-happyhorse from AceDataCloud/HappyHorseMCP. This CLI is maintained in the Clis source repository; the HappyHorseCli mirror now contains this source and its standard build workflow. A PyPI release named happyhorse-cli is not published as of 2026-10-19. The existing publisher's new-project allowance resumes on 2026-10-20; until the first exact-version receipt, this remains a source installation. Use the existing published MCP if you need a registry-distributed integration.

For the source CLI, use the pinned source below in an isolated Python environment; it is a local source installation, not a PyPI release. 中文安装与密钥指南

The publication checklist records the concrete mirror/package release steps and the temporary publisher-project allowance gate. The repository is already populated; no new account registration is required.

Source installation

python -m pip install "git+https://github.com/AceDataCloud/Clis.git@06c580dbfddd59f9b9bb1c80e86776723fc6cfd3#subdirectory=happyhorse"

API key and free local checks

Register/sign in at Applications, initialize General application if needed, and copy or create an API Key with HappyHorse generation and task-query access. Check expiration, limits, balance and current pricing. Store only the raw token in ACEDATACLOUD_API_TOKEN, never a prompt or commit. A platform account-management token is different.

happyhorse --help
happyhorse models

These are local reference commands. Generation is charged under your current account terms. Save its task ID; use happyhorse task <task-id> or happyhorse wait <task-id> for that same task instead of generating again.

Usage

# Set API token
export ACEDATACLOUD_API_TOKEN=your_token_here

# Generate video from text
happyhorse generate "A horse galloping through a field"

# Generate video from image
happyhorse image-to-video "Animate this scene" --image-url https://example.com/photo.jpg

# Generate video from reference images
happyhorse reference-to-video "Create scene" --image-urls https://example.com/ref.jpg

# Edit a video
happyhorse video-edit "Add dramatic music" --video-url https://example.com/video.mp4

# Check task status
happyhorse task abc123-def456

# Wait for task completion
happyhorse wait abc123 --interval 5

# List available models
happyhorse models

# Show configuration
happyhorse config

Options

generate

Option Default Description
--model happyhorse-1.1-t2v Model to use
--resolution 1080P Video resolution (720P, 1080P)
--ratio 16:9 Aspect ratio (16:9, 9:16, 1:1, 4:3, 3:4)
--duration 5 Duration in seconds
--watermark False Add watermark
--audio-setting auto Audio setting (auto, origin)
--seed None Random seed
--callback-url None Webhook callback URL
--async False Submit asynchronously
--json False Output raw JSON

Models

Model Type
happyhorse-1.0-t2v Text-to-Video
happyhorse-1.1-t2v Text-to-Video (default)
happyhorse-1.0-i2v Image-to-Video
happyhorse-1.1-i2v Image-to-Video
happyhorse-1.0-r2v Reference-to-Video
happyhorse-1.1-r2v Reference-to-Video
happyhorse-1.0-video-edit Video Edit

License

MIT

Metadata

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