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name: align-anything description: "Operate the Align-Anything multimodal alignment package, including training, serving, remote reward models, and satellite projects." metadata: disco-role: operating disable-model-invocation: true license: Apache 2.0

Align-Anything Repo Skill

Use this root skill when a task involves the Align-Anything package: multimodal instruction tuning, preference/reward/cost alignment, PPO with remote reward models, text/image/audio/video/omni serving, or the repository's satellite project workflows.

Route first

• Training, configs, datasets, launchers, and alignment algorithms → sub-skills/training-and-alignment/
• Model loading, text/multimodal/omni CLIs, media inputs, and inference smoke checks → sub-skills/multimodal-serving/
• Remote reward server/client, reward functions, math verifier, and PPO remote-RM wiring → sub-skills/remote-reward-models/
• Satellite projects such as Any-to-Text, Janus, InterMT, language feedback, Chameleon-style text-image-to-text-image, or Eval-Anything → sub-skills/project-workflows/

Read references/overview.md for the package map, references/installation-and-environment.md before running code, and references/troubleshooting.md for cross-cutting failures.

Fast operating sequence

1. Classify the user request by workflow and backend. CUDA/GPU is usually required for real training, model loading, vLLM, and multimodal generation; CPU imports are only partial evidence.

2. Run the bundled environment check before attempting package operations in a new runtime:

   python scripts/check_align_anything_environment.py --json
   

3. Load the most specific sub-skill and its bundled references/scripts.

4. Prefer bundled script templates over source-repository shell snippets. The source scripts were distilled into this skill's scripts/ trees; avoid relying on a particular checkout layout.

5. Do not run long training, benchmark downloads, remote-code models, or project scripts until model/data paths, credentials, output directories, GPU memory, and network expectations are explicit.

Core facts

• Package import name: align_anything
• Package version observed during construction: 0.0.1.dev0
• Primary runtime: Python package with PyTorch, Transformers, DeepSpeed, datasets, Gradio, media dependencies, and optional vLLM/Janus/project-specific extras.
• Confirmed construction commit: see references/repo-provenance.md.
• Router metadata for managed repo-skill import is in references/repo-routing-metadata.json.

Avoid this skill when

• The task is about a different alignment package or a generic RLHF concept with no Align-Anything artifact.
• The user only needs to import/export DisCo skills, not operate the repository.
• A required backend or model/data asset is unavailable and the user has not accepted a narrowed or planning-only scope.

Handoff checklist

When handing a plan to execution, include:

• Selected sub-skill and workflow.
• Package/runtime readiness check result.
• Required backend, model weights, processor/tokenizer, dataset files, reward endpoint, output directory, and optional extras.
• Whether source checkout access is necessary for the current task; the skill itself is self-contained, but some bundled helper scripts can inspect a user-provided Align-Anything checkout when the user asks to inventory local project files.
• Known gaps or optional dependencies from references/troubleshooting.md and the chosen sub-skill's troubleshooting reference.