ltx2-vidgen

ltx2-vidgen-skill

A Claude Code skill that owns your AI video pipeline — drop a photo in Claude Code → get a video. It deploys your own optimized LTX-2.3 (22B) backend to your Modal serverless GPU and drives it: text-to-video, image-to-video, keyframe interpolation, video-to-video, and IC-LoRA (canny/depth/pose) control, with synced audio — a few cents a clip, your GPU, no per-clip API meter, no rate limit.

Side-by-side image-to-video — two stills brought to life (slow push-in + wind-blown hair). LTX-2.3 (22B) on RTX PRO 6000 (Blackwell, 96 GB, bf16). ▶ full-quality mp4

What this is

A Claude Code skill that owns the whole loop — it deploys your own LTX-2.3 (22B) video backend to your Modal account on first run, then drives it from Claude Code: drop a photo (or a prompt), ask for a video, get the .mp4. You never leave Claude Code; the GPU is yours; there's no SaaS in the middle.

• Modes: text-to-video, image-to-video, keyframe interpolation, video-to-video (retake/restyle), and IC-LoRA canny/depth/pose control — with synced audio.
• Batch: --variations N (one prompt, N takes) and --prompts-file (many prompts) in one warm container.
• Formats: reel / TikTok / Shorts (9:16), YouTube (16:9), square — native, no cropping.
• Optimized: resident pipeline + caches + torch.compile → ~1.96× faster, output bit-identical, bf16 throughout. Clips up to ~10 s; any resolution with sides ÷32.

Install

1. Install the skill (Claude Code, or any agent that reads SKILL.md):

npx skills add patraxo/ltx2-vidgen-skill        # or: cp -R skills/ltx2-video ~/.claude/skills/
pip install modal && modal token new            # Modal SDK + your account (free — $30/mo credits)

…or as a Claude Code plugin marketplace:

/plugin marketplace add patraxo/ltx2-vidgen-skill
/plugin install ltx2-vidgen@ltx2-vidgen-skill

2. Deploy your backend once — into your Modal account (downloads the LTX-2.3 weights + Gemma text encoder; public components only, no HuggingFace token):

git clone https://github.com/patraxo/ltx2-vidgen-skill && cd ltx2-vidgen-skill && ./deploy.sh

That's it. Now in Claude Code, drop a photo (or just describe a scene) and ask:

• "turn this photo into a video, subtle natural motion" — image → i2v
• "interpolate between these two frames" — two images → keyframe
• "restyle the middle of this clip" — a video → v2v
• "generate a neon city street, vertical reel" — prompt only → t2v
• "follow the edges of this clip" — a control render → IC-LoRA control

The skill validates the input, confirms cost (offers a cheap smoke first), calls your deployed app via modal.Cls.from_name (no endpoint, no auth, no secrets), and saves the .mp4 + a preview frame to ./video_out/. First clip cold-starts ~90 s; warm ~31 s.

PYTHONPATH=. uv run modal run deploy/ltx2_model.py::smoke_real --image-path pic.jpg   # i2v
PYTHONPATH=. uv run modal run deploy/ltx2_model.py::run_modes                          # t2v + i2v + keyframe
PYTHONPATH=. uv run modal run deploy/ltx2_model.py::run_retake                         # v2v
PYTHONPATH=. uv run modal run deploy/ltx2_model.py::kf_real --image-a a.jpg --image-b b.jpg
PYTHONPATH=. uv run modal run tests/ship_verify.py                                     # full verify

Modes

All four are exercised by run_modes / run_retake / kf_real and verified working (frame-inspected). The opt stack applies across every mode.

Performance

Runs on Modal serverless NVIDIA RTX PRO 6000 (Blackwell, 96 GB), bf16, billed per-second at $0.000842/s (~$3.03/hr) — so cost ≈ latency: