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name: interactive-serving description: "Operate TurboDiffusion's interactive T2V/I2V terminal server with safe launch validation, TUI commands, and runtime parameter handling." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

TurboDiffusion interactive serving

Use this sub-skill when the task is to launch or troubleshoot TurboDiffusion's interactive terminal server for repeated text-to-video (T2V) or image-to-video (I2V) generations while keeping loaded model objects alive across prompts.

Route here for

• Choosing an installed CLI vs Python-module TUI launch command.
• Validating T2V --dit_path vs I2V --high_noise_model_path and --low_noise_model_path before opening the TUI.
• Explaining the TUI prompt flow, slash commands, output path prompts, and I2V image path prompts.
• Adjusting runtime parameters with /set without restarting the server.
• Diagnosing source-layout import errors, missing mode-specific model paths, invalid resolution/aspect ratio selections, /set validation errors, and interactive cancellation.

Route elsewhere

• One-shot, non-interactive T2V/I2V scripts, prompt files, and direct --save_path generation: use the sibling video-inference sub-skill.
• CUDA extension builds, turbo_diffusion_ops, SageSLA/SpargeAttn installation, quantized-linear backend failures, or FastNorm/custom-op checks: use the sibling acceleration-backends sub-skill.
• Checkpoint conversion, training, model merging, or quantized checkpoint export: use the sibling training-and-checkpoints sub-skill.

Runtime files

• TUI server guide: launch flow, model residency behavior, slash commands, prompt/image/output handling, and runtime-adjustable parameters.
• CLI reference: public launch methods, argument tables, mode-specific requirements, defaults, and resolution/aspect-ratio validation.
• Troubleshooting: failure matrix for import quirks, missing model paths, invalid CLI values, /set errors, cancellation, and backend-routed problems.
• Command renderer: safe dry-run helper that renders, but never executes, a T2V or I2V TUI launch command.

Quick operating pattern

1. Decide whether the user needs the installed turbodiffusion-serve entry point or python -m turbodiffusion.serve.
2. Use the command renderer or the tables in CLI reference to build a mode-correct launch.
3. For source-layout installs, prepend a public PYTHONPATH entry that exposes TurboDiffusion's top-level imaginaire, rcm, and inference helper modules; a common source checkout uses PYTHONPATH=turbodiffusion.
4. Once the TUI starts, keep it running for multiple prompts so VAE/model objects remain loaded instead of paying startup cost per generation.
5. Use Troubleshooting before changing backend packages or rerouting to another sub-skill.