Add Model Prep

Goal

Prepare external assets and the shared parity-test environment for a FastVideo model port. Stop before writing conversion scripts, model components, pipeline code, registry entries, or executable parity tests.

Ask First

Ask once, then proceed if the HF token is already exported:

Before prep: (1) official reference repo or Diffusers pipeline URL, (2) HF repo
id or local weights path and whether it has a root model_index.json, (3) target
model_family, (4) workload types, (5) which token env var is exported:
HF_TOKEN, HUGGINGFACE_HUB_TOKEN, or HF_API_KEY, (6) may I stage clone and
weights under the FastVideo repo root, and (7) may I install official reference
dependencies into the current FastVideo conda/env for parity tests?

Useful optional inputs: pipeline_class, reference_dir, hf_revision, official_revision, reuse_hints, download_scope.

Rules

• Follow ../add-model/shared/common_rules.md for token/auth safety, state files, escape hatches, and skip/pass semantics.
• Run from the FastVideo repo root.
• Use repo-relative defaults: <ReferenceDir>/, official_weights/<model_family>/, converted_weights/<model_family>/.
• Install official reference deps into the current FastVideo environment, not a new venv/conda env, so parity tests run both implementations with one shared numeric stack.
• If the reference is a Diffusers class/package instead of a cloneable repo, record import path and version instead of cloning.
• Prep may create only the local-test README and PORT_STATUS.md skeletons; executable .py parity tests belong to ../add-model-02-parity/SKILL.md.

Escape Hatches

Follow ../add-model/shared/common_rules.md. Prep-specific ask cases include overwriting an existing clone or weight directory, installing untrusted/private deps, choosing between incompatible official references, large downloads outside the agreed scope, or missing gated-repo auth setup by env var name.

Workflow

1. Verify the repo:

git rev-parse --show-toplevel

Expected markers: fastvideo/, scripts/checkpoint_conversion/, scripts/huggingface/download_hf.py, fastvideo/registry.py.

2. Inspect HF or local weight layout:

python ".agents/skills/add-model-01-prep/scripts/inspect_hf_layout.py" \
    "Org/Model" \
    --revision "<revision>" \
    --json

For a local path, replace Org/Model with /path/to/weights. Record source_layout, needs_conversion, model_index_class, and components_seen.

3. Download HF weights if needed:

python ".agents/skills/add-model-01-prep/scripts/download_hf_weights.py" \
    "Org/Model" \
    "official_weights/<model_family>" \
    --revision "<revision>"

For selected files, repeat --file-name. For partial snapshots, repeat --allow-pattern or --ignore-pattern. If the user provided a local path, record it instead of copying large weights by default.

4. Clone the official reference repo if applicable:

python ".agents/skills/add-model-01-prep/scripts/clone_reference_repo.py" \
    "<official_repo_url>" \
    "<ReferenceDir>" \
    --branch "<tag-or-branch>" \
    --commit "<commit-sha>" \
    --update-gitignore

Omit --branch, --commit, or --update-gitignore when not needed. The helper refuses to overwrite existing paths and prints remote/HEAD instead.

5. Keep prep assets ignored. Ensure .gitignore includes relevant entries:

/<ReferenceDir>/
/official_weights/
/converted_weights/

6. Follow the official repo's setup instructions in the current environment. Inspect dependency files and README install docs before installing anything:

• README*, install docs, or model-card instructions.
• requirements*.txt, pyproject.toml, setup.py, environment.yml.

Use the current FastVideo conda/env. Do not create a new env even if upstream docs recommend one; translate the needed install commands into the active env. Prefer editable/no-deps first so the official source is importable without changing shared pins:

uv pip install --no-deps -e ./<ReferenceDir>

Then install only missing official deps needed for parity imports. Stop before installing requirements that would change FastVideo's core stack. If upstream requires private/non-PyPI deps, record that parity needs a local stub helper rather than pretending setup is complete.

7. Create the model-family local test skeleton and top-level port state file:

mkdir -p tests/local_tests/<model_family>
cp ".agents/skills/add-model-01-prep/templates/local_tests_readme.md" \
    tests/local_tests/<model_family>/README.md
cp ".agents/skills/add-model-01-prep/templates/port_status.md" \
    tests/local_tests/<model_family>/PORT_STATUS.md

Edit every placeholder in the README and PORT_STATUS.md. The README gives later review agents enough information to reproduce the shared environment and run/review parity work:

• official code URL or import path, local clone path, and commit/version;
• HF URL or local weight path, revision, access notes, and token env var name only;
• commands already run and any blocked official dependency installs;
• shared-env install commands to re-run without changing core pins;
• expected local parity test paths and pytest commands;
• private-dependency stubs or known setup gaps;
• PR/review notes explaining which parity tests are required before handoff.

Do not include raw tokens, absolute cache paths that are not repo-reproducible, or large generated outputs. If prep is blocked before imports work, still create the README with official_env_status=blocked and the exact blocker.

PORT_STATUS.md must follow ../add-model/contracts/port_state.md. Record open questions and prep issues immediately, using stable IDs such as Q001 and I001. Keep resolved questions/issues in the table with a resolution instead of deleting them.

Handoff

End with the canonical prep handoff contract from ../add-model/contracts/prep_handoff.md and update the shared state files before handoff.

Helper Scripts

• scripts/inspect_hf_layout.py: classify HF/local layout.
• scripts/download_hf_weights.py: download HF snapshot or selected files.
• scripts/clone_reference_repo.py: clone reference repo safely.