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name: inference description: "Operate MAGI-1 source-code inference for text-to-video, image-to-video, and video-to-video generation." metadata: disco-role: operating disable-model-invocation: true license: Apache 2.0

MAGI-1 inference

Use this sub-skill when a task needs MAGI-1 source-code inference for text-to-video (t2v), image-to-video (i2v), or video-to-video / continuation (v2v) and the agent must choose configs, edit inference JSON safely, build commands, or troubleshoot CUDA/distributed/checkpoint failures.

Do not use this sub-skill for ComfyUI node installation or graph editing; route those tasks to the ComfyUI sub-skill. Prompt enhancement with Dify is only a root-level auxiliary topic and is not covered here beyond prompt text passed into inference.

Start here

1. Read references/cli-and-api.md to choose the CLI or MagiPipeline API route and assemble t2v, i2v, or v2v arguments.
2. Read references/configuration.md before editing any MAGI JSON config or switching between 4.5B, 24B, base, distill, and fp8-quant variants.
3. Use scripts/magi_config_check.py to validate config shape, required fields, CFG rules, process-count expectations, and optional checkpoint path existence without loading models.
4. Use scripts/magi_command_builder.py to print a safe source-code command and recommended environment variables without executing inference.
5. If inference fails or hangs, read references/troubleshooting.md before changing kernels, checkpoints, distributed settings, or media inputs.

Hard constraints

• Meaningful MAGI inference is CUDA-backed. Use a runtime stack compatible with the repository requirements, including CUDA-enabled PyTorch plus MAGI's attention/media dependencies, then run the bundled preflight checks in the user's environment. Dependency import success proves only preflight readiness, not checkpoint-backed generation.
• Full generation is not a smoke test unless valid MAGI DiT, T5, VAE, and special-token assets are available at the paths referenced by the config and environment.
• engine_config.pp_size * engine_config.cp_size must equal the launched distributed world size. Single-process commands require config values of 1 * 1; multi-GPU configs should use torchrun.
• Keep source-code commands rooted at a MAGI source checkout or installed package tree with inference/ importable. This skill provides operating guidance and bundled helpers; it does not include model weights.

Evidence distilled

This sub-skill distills the inference CLI, API, config schema, example configs, example launch scripts, video/prompt processing, checkpoint loading, and distributed initialization from the MAGI repository evidence paths named in the references. Source paths are recorded as provenance only; all runtime links in this sub-skill point to generated skill files.