v1.3.0

This minor update introduces the TeaCache Version Selector, giving you full control over how timesteps are normalized and cached during generation. We have brought back the highly requested, ultra-fast SDE caching behavior as an optional legacy mode while preserving the mathematically precise mode for strict quality control.

🆕 What's New in v1.3.0:

⚡ TeaCache Version Selector (teacache_version)

You can now choose between two distinct caching behaviors directly in the AnimaTeaCache node:

• v1 (Legacy Fast) (Default):

  • How it works: Restores the legacy step normalizer (fixed at 1000.0) from version 1.2.0.
  • Best for: Instant 1.5×–2.0× speedup out-of-the-box on stochastic/SDE samplers (e.g., er_sde, sde gpu). It triggers highly aggressive caching from the very first steps, bypassing manual fine-tuning.
  • Note: May introduce minor structural changes or artifacts on Euler A.

• v2 (Standard Precise):

  • How it works: Employs mathematically precise, dynamic timestep normalization that adapts seamlessly to any sampler range (sigmas, 1000..0, or 1..0).
  • Best for: Samplers like euler_a and workflows requiring absolute geometric accuracy. It fully protects early structure-forming steps and relies on early_steps_factor and late_steps_factor for fine-tuning.

📦 Codebase Changes:

• Added teacache_version parameter to the Python node definitions and model patching core.
• Updated package versioning to v1.3.0 (__init__.py and UI configs).
• Updated comprehensive documentation in both English and Russian READMEs.