Land the ltx2_two_stage inference preset (PR 6 commit 1/5) that exposes
the public LTX-2 two-stage distilled flow: half-resolution denoise
followed by 2x spatial upsample + stage-2 refine denoise (3 steps with
the official distilled sigma schedule, or 2 steps with the reduced
variant).
Schema:
- new _REFINE_STAGE PresetStageSpec with kind="refinement" and
allowed per-request overrides {num_inference_steps, guidance_scale,
image_crf, video_position_offset_sec}
- new LTX2_TWO_STAGE preset with stage_schemas=(denoise, refine) and
stage_defaults.refine={num_inference_steps: 2, guidance_scale: 1.0}
matching the load_kwargs the internal ltx2-streaming gpu_pool uses
- LTX2_TWO_STAGE registered via ALL_PRESETS -> _register_presets()
Init-time refine wiring (enabled, add_noise, upsampler/LoRA/transformer
paths) flows through generator.pipeline.preset_overrides.refine.* and
generator.pipeline.components.{upsampler_weights, lora_path} in a
follow-up commit — the refine stage's internal implementation
(fastvideo/pipelines/stages/ltx2_refine.py in FastVideo-internal) already
treats those as FastVideoArgs fields; this commit only ships the public
preset surface.
5 new tests under fastvideo/tests/api/test_presets.py::TestLtx2Presets:
registration count (3 presets now), two-stage topology, stage defaults,
valid per-request refine override keys, and unknown-override rejection.
Claude Code only scans ~/.claude/skills/ and .claude/skills/ for
user-invocable skills (no skillsPath / skillsDir config option
exists — https://code.claude.com/docs/en/skills.md). Skills in this
repo live under .agents/skills/ so they travel with the repo and
stay under git.
Add a one-shot idempotent sync script that symlinks each
.agents/skills/<name>/ directory into .claude/skills/<name>. Run
after cloning or after adding/removing a skill:
.agents/scripts/sync-skills.sh
Behavior:
* relative symlinks (../../.agents/skills/<name>) so the link
survives moving the clone
* requires a SKILL.md inside each skill directory to be eligible
* prunes stale symlinks whose source vanished from .agents/skills/
* refuses to clobber a pre-existing .claude/skills/<name>/ that
isn't a symlink (lets the operator keep hand-written skills
alongside managed ones)
* prints a linked / unchanged / pruned / skipped summary
Note: .claude/ is gitignored; the symlinks themselves are not
committed. The script is the source of truth for reconstructing
them.
Wraps the existing fastvideo/tests/modal/ssim_test.py
--sync-generated-to-volume path with a step-by-step SKILL.md and a
thin seed_ssim.sh launcher so new SSIM tests can bootstrap their
HF reference videos without manual Modal wrangling.
Motivation: the new test_ltx2_similarity.py (committed earlier on
this branch) has no HF reference video yet; the next operator needs
a deterministic procedure for generating + uploading the first set.
Generalises beyond LTX-2 — any new family test can reuse verbatim.
LTX-2 was the only model family in fastvideo/pipelines/basic/ without an
SSIM coverage file. Add test_ltx2_similarity.py alongside the other
per-family SSIM tests so the in-flight API refactor and future
LTX-2-specific changes (two-stage refine, gpu_pool upstream, Dynamo
backend) have a golden-quality regression guard.
Parameters:
Default (CI-friendly):
model: FastVideo/LTX2-Distilled-Diffusers (8-step distilled)
resolution: 512x768, num_frames=45, num_inference_steps=4
sp_size=2 on 2 GPUs, FLASH_ATTN backend
ltx2_vae_tiling=True for peak-memory safety
--ssim-full-quality:
falls back to the ltx2_distilled preset defaults
(1024x1536, 121 frames, 8 steps, guidance_scale=1.0)
Uses the shared run_text_to_video_similarity_test helper (same pattern
as Wan/TurboDiffusion), so _build_init_kwargs picks up
ltx2_vae_tiling + related tile sizes automatically.
REQUIRED_GPUS = 2 is declared at module scope so the Modal SSIM
orchestrator (fastvideo/tests/modal/ssim_test.py) schedules it
correctly on the L40S:8 runner. LTX2_DISTILLED_MODEL_TO_PARAMS is
named so the orchestrator can split by model id (one subprocess per
entry) for future multi-model LTX-2 coverage.
Threshold min_acceptable_ssim=0.93 matches Wan T2V.
Reference videos are not in the repo. After this lands on main, run
the test once on an L40S and upload via
`python fastvideo/tests/ssim/reference_videos_cli.py upload --quality-tier all`
to seed FastVideo/ssim-reference-videos. Subsequent runs (including
regression guards for in-flight refactor PRs) auto-download the
references before the test executes.
## Summary
Follow-up to #1187. Two small changes:
1. **Merge Protections expanded** — adds `#approved-reviews-by>=1` and `check-success~=pre-commit` to `merge_protections` so the Mergify check shows a unified requirements checklist on every PR (title format + approval + pre-commit), instead of only showing the title format.
2. **Buildkite pipeline comment fix** — updates the outdated Full Suite section comment from "Triggered by adding the 'ready' label via GitHub Actions → Buildkite API" to reflect the new Merge Queue trigger path.
SolitaryThinker