Tio Magic Animation Toolkit

Tio Magic Animation Toolkit is designed to simplify the use of open and closed-source video AI models for animation. The Animation Toolkit empowers animators, developers, and AI enthusiasts to easily generate animated videos without the pain of complex technical setup, local hardware limitations, and haphazard documentation.

This toolkit leverages Modal for cloud computing and runs various open/closed-source video generation models.

Supported Features

Image to Video

Prompt: Woman smiling at the camera, waving her right hand as if she was saying hi and greeting someone.

Interpolate

Prompt: An anime-style young man in a blue t-shirt starts in a standing position. He lifts his right hand and waves to the camera.

Interpolate Wan 2.1 Vace 14b — Wan 2.1 Vace 14b

Pose Guidance

Prompt: Anime-style cartoon animation of a man waving, empty white background. Skin tone, shading, lighting should be the same as the reference image.

Pose Guidance Wan 2.1 Vace 14b — Wan 2.1 Vace 14b

Text to Video

Prompt: A playful cartoon-style penguin with a round belly and flappy wings waddles up to a pair of green sunglasses lying on the ground. The penguin leans forward, carefully picks up the sunglasses with its flipper, and smoothly lifts them up to its face. It tilts its head with a confident smile as the green sunglasses rest perfectly on its beak. The animation is smooth and expressive, with exaggerated, bouncy cartoon motion.

T2V Wan 2.1 PhantomX (LoRA) — Wan 2.1 PhantomX (LoRA)

Supported Providers and Models

Image to Video

Interpolate

Pose Guidance

Wan 2.1 Vace 14b

Text to Video

Local

Image to Video

Interpolate

Luma AI Ray 2

Disclaimer

TL;DR: We don’t make the videos - the AI models do. We just make it easier to use them.

TioMagic Animation is an interface toolkit that sits between you and various video generation AI models. Think of it as a universal remote control for AI video models.

What we do:

✅ Provide a simple Python API to access multiple video models
✅ Handle the complexity of deploying models on Modal/cloud infrastructure
✅ Eliminate the need for expensive local GPUs
✅ Manage job queuing, status tracking, and result retrieval
✅ Abstract away provider-specific implementation details

What we don’t do:

❌ Create or train the AI models
❌ Modify or enhance model outputs
❌ Own any rights to the generated content
❌ Control what the models can or cannot generate

Important Notes:

All generated content comes directly from the underlying models (e.g., Wan2.1-VACE, CogVideoX)
You must comply with each model’s individual license terms
Model availability and capabilities depend on the model creators, not us