align-anything

# 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: ```bash 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.