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name: inference description: "Run LatentSync single-pair, small-batch, Gradio, and deployment-aware inference workflows safely." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Inference

Use this sub-skill when you need LatentSync to synthesize lip-synced video from an input video and an input audio file, or when you need to launch the local demo UI.

Do not use this sub-skill for training, raw preprocessing pipeline stages, or SyncNet/FVD scoring.

What this sub-skill owns

• Single-pair generation through the repo-maintained scripts.inference module.
• A safer replacement for the demo shell command with explicit repository root, config, checkpoint, input, output, temp, seed, and DeepCache controls.
• Small-batch generation for file-list or pair-list inputs when outputs are only being produced.
• Gradio demo launch with explicit share and browser behavior instead of implicit public sharing.
• Reference-only notes for Cog/Replicate deployment entry points.

Route here when the request is about

• Running the demo assets or a user-supplied video/audio pair.
• Choosing between the 256 and 512 U-Net inference configs.
• Enabling or disabling DeepCache during generation.
• Launching, smoke-checking, or adapting the Gradio app.
• Understanding Cog/Replicate inference behavior before adapting it elsewhere.

Do not route here when the request is about

• Selecting training stages, launching U-Net/SyncNet training, or editing train configs. Use the training sub-skill when available.
• Processing raw datasets into face-aligned training clips. Use the data-preparation sub-skill.
• Scoring generated outputs with SyncNet confidence, SyncNet accuracy, or FVD. Use ../evaluation/SKILL.md when outputs are being evaluated.
• Downloading remote weights or running network-only deployment helpers as local inference.

Start here

1. Read references/workflows.md for single-pair, batch, and UI launch flows.
2. Read references/api-reference.md for prompt-safe CLI, function, pipeline, and config notes.
3. Read references/troubleshooting.md before long GPU runs or when a preflight check fails.
4. Use scripts/run_inference.py for CLI and small-batch generation.
5. Use scripts/launch_gradio.py for local UI launch or Gradio import smoke tests.
6. Read references/deployment.md only when adapting Cog/Replicate behavior.

Runtime rules

• Always pass --repo-root to helper scripts so imports, configs, checkpoints, masks, and assets resolve from the intended LatentSync runtime tree.
• Prefer configs/unet/stage2_512.yaml for the released v1.6 checkpoint and configs/unet/stage2.yaml for a v1.5 or 256-resolution checkpoint.
• Treat missing checkpoints/latentsync_unet.pt, missing Whisper weights, missing ffmpeg, and unavailable CUDA as preflight blockers.
• Keep temp directories isolated; the underlying pipeline deletes and recreates its temp_dir.
• Use the evaluation sub-skill only after batch outputs need scores.