* feat: add Anima model support
* schema
* image to image
* regional guidance
* loras
* last fixes
* tests
* fix attributions
* fix attributions
* refactor to use diffusers reference
* fix an additional lora type
* some adjustments to follow flux 2 paper implementation
* use t5 from model manager instead of downloading
* make lora identification more reliable
* fix: resolve lint errors in anima module
Remove unused variable, fix import ordering, inline dict() call,
and address minor lint issues across anima-related files.
* Chore Ruff format again
* fix regional guidance error
* fix(anima): validate unexpected keys after strict=False checkpoint loading
Capture the load_state_dict result and raise RuntimeError on unexpected
keys (indicating a corrupted or incompatible checkpoint), while logging
a warning for missing keys (expected for inv_freq buffers regenerated
at runtime).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(anima): make model loader submodel fields required instead of Optional
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(anima): add Classification.Prototype to LoRA loaders, fix exception types
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(anima): fix replace-all in key conversion, warn on DoRA+LoKR, unify grouping functions
- Use key.replace(old, new, 1) in _convert_kohya_unet_key and _convert_kohya_te_key to avoid replacing multiple occurrences
- Upgrade DoRA+LoKR dora_scale strip from logger.debug to logger.warning since it represents data loss
- Replace _group_kohya_keys and _group_by_layer with a single _group_keys_by_layer function parameterized by extra_suffixes, with _KOHYA_KNOWN_SUFFIXES and _PEFT_EXTRA_SUFFIXES constants
- Add test_empty_state_dict_returns_empty_model to verify empty input produces a model with no layers
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(anima): add safety cap for Qwen3 sequence length to prevent OOM
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(anima): add denoising range validation, fix closure capture, add edge case tests
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(anima): add T5 to metadata, fix dead code, decouple scheduler type guard
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(anima): update VAE field description for required field
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore: regenerate frontend types after upstream merge
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore: ruff format anima_denoise.py
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(anima): add T5 encoder metadata recall handler
The T5 encoder was added to generation metadata but had no recall
handler, so it wasn't restored when recalling from metadata.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore(frontend): add regression test for buildAnimaGraph
Add tests for CFG gating (negative conditioning omitted when cfgScale <= 1)
and basic graph structure (model loader, text encoder, denoise nodes).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* only show 0.6b for anima
* dont show 0.6b for other models
* schema
* Anima preview 3
* fix ci
---------
Co-authored-by: Your Name <you@example.com>
Co-authored-by: kappacommit <samwolfe40@gmail.com>
Co-authored-by: Alexander Eichhorn <alex@eichhorn.dev>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>
Add comprehensive support for Z-Image-Turbo (S3-DiT) models including:
Backend:
- New BaseModelType.ZImage in taxonomy
- Z-Image model config classes (ZImageTransformerConfig, Qwen3TextEncoderConfig)
- Model loader for Z-Image transformer and Qwen3 text encoder
- Z-Image conditioning data structures
- Step callback support for Z-Image with FLUX latent RGB factors
Invocations:
- z_image_model_loader: Load Z-Image transformer and Qwen3 encoder
- z_image_text_encoder: Encode prompts using Qwen3 with chat template
- z_image_denoise: Flow matching denoising with time-shifted sigmas
- z_image_image_to_latents: Encode images to 16-channel latents
- z_image_latents_to_image: Decode latents using FLUX VAE
Frontend:
- Z-Image graph builder for text-to-image generation
- Model picker and validation updates for z-image base type
- CFG scale now allows 0 (required for Z-Image-Turbo)
- Clip skip disabled for Z-Image (uses Qwen3, not CLIP)
- Optimal dimension settings for Z-Image (1024x1024)
Technical details:
- Uses Qwen3 text encoder (not CLIP/T5)
- 16 latent channels with FLUX-compatible VAE
- Flow matching scheduler with dynamic time shift
- 8 inference steps recommended for Turbo variant
- bfloat16 inference dtype
In `ObjectSerializerDisk`, we use `torch.load` to load serialized objects from disk. With torch 2.6.0, torch defaults to `weights_only=True`. As a result, torch will raise when attempting to deserialize anything with an unrecognized class.
For example, our `ConditioningFieldData` class is untrusted. When we load conditioning from disk, we will get a runtime error.
Torch provides a method to add trusted classes to an allowlist. This change adds an arg to `ObjectSerializerDisk` to add a list of safe globals to the allowlist and uses it for both `ObjectSerializerDisk` instances.
Note: My first attempt inferred the class from the generic type arg that `ObjectSerializerDisk` accepts, and added that to the allowlist. Unfortunately, this doesn't work.
For example, `ConditioningFieldData` has a `conditionings` attribute that may be one some other untrusted classes representing model-specific conditioning data. So, even if we allowlist `ConditioningFieldData`, loading will fail when torch deserializes the `conditionings` attribute.
