diff --git a/invokeai/app/invocations/cogview4_text_encoder.py b/invokeai/app/invocations/cogview4_text_encoder.py index d7361549f7a..c6ef1663cf8 100644 --- a/invokeai/app/invocations/cogview4_text_encoder.py +++ b/invokeai/app/invocations/cogview4_text_encoder.py @@ -10,7 +10,6 @@ CogView4ConditioningInfo, ConditioningFieldData, ) -from invokeai.backend.util.devices import TorchDevice # The CogView4 GLM Text Encoder max sequence length set based on the default in diffusers. COGVIEW4_GLM_MAX_SEQ_LEN = 1024 @@ -37,6 +36,8 @@ class CogView4TextEncoderInvocation(BaseInvocation): @torch.no_grad() def invoke(self, context: InvocationContext) -> CogView4ConditioningOutput: glm_embeds = self._glm_encode(context, max_seq_len=COGVIEW4_GLM_MAX_SEQ_LEN) + # Move embeddings to CPU for storage to save VRAM + glm_embeds = glm_embeds.detach().to("cpu") conditioning_data = ConditioningFieldData(conditionings=[CogView4ConditioningInfo(glm_embeds=glm_embeds)]) conditioning_name = context.conditioning.save(conditioning_data) return CogView4ConditioningOutput.build(conditioning_name) @@ -85,7 +86,7 @@ def _glm_encode(self, context: InvocationContext, max_seq_len: int) -> torch.Ten ) text_input_ids = torch.cat([pad_ids, text_input_ids], dim=1) prompt_embeds = glm_text_encoder( - text_input_ids.to(TorchDevice.choose_torch_device()), output_hidden_states=True + text_input_ids.to(glm_text_encoder.device), output_hidden_states=True ).hidden_states[-2] assert isinstance(prompt_embeds, torch.Tensor) diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py index 3ad05bcc9b9..5ce88145ffd 100644 --- a/invokeai/app/invocations/compel.py +++ b/invokeai/app/invocations/compel.py @@ -103,7 +103,7 @@ def _lora_loader() -> Iterator[Tuple[ModelPatchRaw, float]]: textual_inversion_manager=ti_manager, dtype_for_device_getter=TorchDevice.choose_torch_dtype, truncate_long_prompts=False, - device=TorchDevice.choose_torch_device(), + device=text_encoder.device, # Use the device the model is actually on split_long_text_mode=SplitLongTextMode.SENTENCES, ) @@ -212,7 +212,7 @@ def _lora_loader() -> Iterator[Tuple[ModelPatchRaw, float]]: truncate_long_prompts=False, # TODO: returned_embeddings_type=ReturnedEmbeddingsType.PENULTIMATE_HIDDEN_STATES_NON_NORMALIZED, # TODO: clip skip requires_pooled=get_pooled, - device=TorchDevice.choose_torch_device(), + device=text_encoder.device, # Use the device the model is actually on split_long_text_mode=SplitLongTextMode.SENTENCES, ) diff --git a/invokeai/app/invocations/flux_text_encoder.py b/invokeai/app/invocations/flux_text_encoder.py index c395a0bf22d..56ebbe7fd9d 100644 --- a/invokeai/app/invocations/flux_text_encoder.py +++ b/invokeai/app/invocations/flux_text_encoder.py @@ -58,6 +58,12 @@ def invoke(self, context: InvocationContext) -> FluxConditioningOutput: # scoped. This ensures that the T5 model can be freed and gc'd before loading the CLIP model (if necessary). t5_embeddings = self._t5_encode(context) clip_embeddings = self._clip_encode(context) + + # Move embeddings to CPU for storage to save VRAM + # They will be moved to the appropriate device when used by the denoiser + t5_embeddings = t5_embeddings.detach().to("cpu") + clip_embeddings = clip_embeddings.detach().to("cpu") + conditioning_data = ConditioningFieldData( conditionings=[FLUXConditioningInfo(clip_embeds=clip_embeddings, t5_embeds=t5_embeddings)] ) diff --git a/invokeai/app/invocations/sd3_text_encoder.py b/invokeai/app/invocations/sd3_text_encoder.py index 230fdf0f602..24647c9cfc7 100644 --- a/invokeai/app/invocations/sd3_text_encoder.py +++ b/invokeai/app/invocations/sd3_text_encoder.py @@ -21,7 +21,6 @@ from invokeai.backend.patches.lora_conversions.flux_lora_constants import FLUX_LORA_CLIP_PREFIX from invokeai.backend.patches.model_patch_raw import ModelPatchRaw from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData, SD3ConditioningInfo -from invokeai.backend.util.devices import TorchDevice # The SD3 T5 Max Sequence Length set based on the default in diffusers. SD3_T5_MAX_SEQ_LEN = 256 @@ -69,6 +68,15 @@ def invoke(self, context: InvocationContext) -> SD3ConditioningOutput: if self.t5_encoder is not None: t5_embeddings = self._t5_encode(context, SD3_T5_MAX_SEQ_LEN) + # Move all embeddings to CPU for storage to save VRAM + # They will be moved to the appropriate device when used by the denoiser + clip_l_embeddings = clip_l_embeddings.detach().to("cpu") + clip_l_pooled_embeddings = clip_l_pooled_embeddings.detach().to("cpu") + clip_g_embeddings = clip_g_embeddings.detach().to("cpu") + clip_g_pooled_embeddings = clip_g_pooled_embeddings.detach().to("cpu") + if t5_embeddings is not None: + t5_embeddings = t5_embeddings.detach().to("cpu") + conditioning_data = ConditioningFieldData( conditionings=[ SD3ConditioningInfo( @@ -117,7 +125,7 @@ def _t5_encode(self, context: InvocationContext, max_seq_len: int) -> torch.Tens f" {max_seq_len} tokens: {removed_text}" ) - prompt_embeds = t5_text_encoder(text_input_ids.to(TorchDevice.choose_torch_device()))[0] + prompt_embeds = t5_text_encoder(text_input_ids.to(t5_text_encoder.device))[0] assert isinstance(prompt_embeds, torch.Tensor) return prompt_embeds @@ -180,7 +188,7 @@ def _clip_encode( f" {tokenizer_max_length} tokens: {removed_text}" ) prompt_embeds = clip_text_encoder( - input_ids=text_input_ids.to(TorchDevice.choose_torch_device()), output_hidden_states=True + input_ids=text_input_ids.to(clip_text_encoder.device), output_hidden_states=True ) pooled_prompt_embeds = prompt_embeds[0] prompt_embeds = prompt_embeds.hidden_states[-2] diff --git a/invokeai/app/invocations/z_image_text_encoder.py b/invokeai/app/invocations/z_image_text_encoder.py index cc6e947fba3..06718c4897f 100644 --- a/invokeai/app/invocations/z_image_text_encoder.py +++ b/invokeai/app/invocations/z_image_text_encoder.py @@ -57,6 +57,8 @@ class ZImageTextEncoderInvocation(BaseInvocation): @torch.no_grad() def invoke(self, context: InvocationContext) -> ZImageConditioningOutput: prompt_embeds = self._encode_prompt(context, max_seq_len=Z_IMAGE_MAX_SEQ_LEN) + # Move embeddings to CPU for storage to save VRAM + prompt_embeds = prompt_embeds.detach().to("cpu") conditioning_data = ConditioningFieldData(conditionings=[ZImageConditioningInfo(prompt_embeds=prompt_embeds)]) conditioning_name = context.conditioning.save(conditioning_data) return ZImageConditioningOutput( @@ -69,7 +71,6 @@ def _encode_prompt(self, context: InvocationContext, max_seq_len: int) -> torch. Based on the ZImagePipeline._encode_prompt method from diffusers. """ prompt = self.prompt - device = TorchDevice.choose_torch_device() text_encoder_info = context.models.load(self.qwen3_encoder.text_encoder) tokenizer_info = context.models.load(self.qwen3_encoder.tokenizer) @@ -78,6 +79,9 @@ def _encode_prompt(self, context: InvocationContext, max_seq_len: int) -> torch. (_, text_encoder) = exit_stack.enter_context(text_encoder_info.model_on_device()) (_, tokenizer) = exit_stack.enter_context(tokenizer_info.model_on_device()) + # Use the device that the text_encoder is actually on + device = text_encoder.device + # Apply LoRA models to the text encoder lora_dtype = TorchDevice.choose_bfloat16_safe_dtype(device) exit_stack.enter_context( diff --git a/invokeai/app/services/model_records/model_records_base.py b/invokeai/app/services/model_records/model_records_base.py index 9dd69a00f54..89ae87d121b 100644 --- a/invokeai/app/services/model_records/model_records_base.py +++ b/invokeai/app/services/model_records/model_records_base.py @@ -86,6 +86,7 @@ class ModelRecordChanges(BaseModelExcludeNull): default_settings: Optional[MainModelDefaultSettings | LoraModelDefaultSettings | ControlAdapterDefaultSettings] = ( Field(description="Default settings for this model", default=None) ) + cpu_only: Optional[bool] = Field(description="Whether this model should run on CPU only", default=None) # Checkpoint-specific changes # TODO(MM2): Should we expose these? Feels footgun-y... diff --git a/invokeai/backend/flux/modules/conditioner.py b/invokeai/backend/flux/modules/conditioner.py index ffbbbf20dd7..9deb4429292 100644 --- a/invokeai/backend/flux/modules/conditioner.py +++ b/invokeai/backend/flux/modules/conditioner.py @@ -3,8 +3,6 @@ from torch import Tensor, nn from transformers import PreTrainedModel, PreTrainedTokenizer, PreTrainedTokenizerFast -from invokeai.backend.util.devices import TorchDevice - class HFEncoder(nn.Module): def __init__( @@ -33,8 +31,11 @@ def forward(self, text: list[str]) -> Tensor: return_tensors="pt", ) + # Move inputs to the same device as the model to support cpu_only models + model_device = next(self.hf_module.parameters()).device + outputs = self.hf_module( - input_ids=batch_encoding["input_ids"].to(TorchDevice.choose_torch_device()), + input_ids=batch_encoding["input_ids"].to(model_device), attention_mask=None, output_hidden_states=False, ) diff --git a/invokeai/backend/model_manager/configs/clip_embed.py b/invokeai/backend/model_manager/configs/clip_embed.py index 4bb24a0a637..0a07505612a 100644 --- a/invokeai/backend/model_manager/configs/clip_embed.py +++ b/invokeai/backend/model_manager/configs/clip_embed.py @@ -41,6 +41,7 @@ class CLIPEmbed_Diffusers_Config_Base(Diffusers_Config_Base): base: Literal[BaseModelType.Any] = Field(default=BaseModelType.Any) type: Literal[ModelType.CLIPEmbed] = Field(default=ModelType.CLIPEmbed) format: Literal[ModelFormat.Diffusers] = Field(default=ModelFormat.Diffusers) + cpu_only: bool | None = Field(default=None, description="Whether this model should run on CPU only") @classmethod def from_model_on_disk(cls, mod: ModelOnDisk, override_fields: dict[str, Any]) -> Self: diff --git a/invokeai/backend/model_manager/configs/clip_vision.py b/invokeai/backend/model_manager/configs/clip_vision.py index af5a539bc18..ac7e17e8f29 100644 --- a/invokeai/backend/model_manager/configs/clip_vision.py +++ b/invokeai/backend/model_manager/configs/clip_vision.py @@ -28,6 +28,7 @@ class CLIPVision_Diffusers_Config(Diffusers_Config_Base, Config_Base): base: Literal[BaseModelType.Any] = Field(default=BaseModelType.Any) type: Literal[ModelType.CLIPVision] = Field(default=ModelType.CLIPVision) format: Literal[ModelFormat.Diffusers] = Field(default=ModelFormat.Diffusers) + cpu_only: bool | None = Field(default=None, description="Whether this model should run on CPU only") @classmethod def from_model_on_disk(cls, mod: ModelOnDisk, override_fields: dict[str, Any]) -> Self: diff --git a/invokeai/backend/model_manager/configs/llava_onevision.py b/invokeai/backend/model_manager/configs/llava_onevision.py index c6ceb43ca9d..8f7ec28e398 100644 --- a/invokeai/backend/model_manager/configs/llava_onevision.py +++ b/invokeai/backend/model_manager/configs/llava_onevision.py @@ -25,6 +25,7 @@ class LlavaOnevision_Diffusers_Config(Diffusers_Config_Base, Config_Base): type: Literal[ModelType.LlavaOnevision] = Field(default=ModelType.LlavaOnevision) base: Literal[BaseModelType.Any] = Field(default=BaseModelType.Any) + cpu_only: bool | None = Field(default=None, description="Whether this model should run on CPU only") @classmethod def from_model_on_disk(cls, mod: ModelOnDisk, override_fields: dict[str, Any]) -> Self: diff --git a/invokeai/backend/model_manager/configs/main.py b/invokeai/backend/model_manager/configs/main.py index 39887e1b049..5f3d5106449 100644 --- a/invokeai/backend/model_manager/configs/main.py +++ b/invokeai/backend/model_manager/configs/main.py @@ -48,6 +48,7 @@ class MainModelDefaultSettings(BaseModel): width: int | None = Field(default=None, multiple_of=8, ge=64, description="Default width for this model") height: int | None = Field(default=None, multiple_of=8, ge=64, description="Default height for this model") guidance: float | None = Field(default=None, ge=1, description="Default Guidance for this model") + cpu_only: bool | None = Field(default=None, description="Whether this model should run on CPU only") model_config = ConfigDict(extra="forbid") diff --git a/invokeai/backend/model_manager/configs/qwen3_encoder.py b/invokeai/backend/model_manager/configs/qwen3_encoder.py index 4d78795b7d9..3954d4c139f 100644 --- a/invokeai/backend/model_manager/configs/qwen3_encoder.py +++ b/invokeai/backend/model_manager/configs/qwen3_encoder.py @@ -51,6 +51,7 @@ class Qwen3Encoder_Checkpoint_Config(Checkpoint_Config_Base, Config_Base): base: Literal[BaseModelType.Any] = Field(default=BaseModelType.Any) type: Literal[ModelType.Qwen3Encoder] = Field(default=ModelType.Qwen3Encoder) format: Literal[ModelFormat.Checkpoint] = Field(default=ModelFormat.Checkpoint) + cpu_only: bool | None = Field(default=None, description="Whether this model should run on CPU only") @classmethod def from_model_on_disk(cls, mod: ModelOnDisk, override_fields: dict[str, Any]) -> Self: @@ -87,6 +88,7 @@ class Qwen3Encoder_Qwen3Encoder_Config(Config_Base): base: Literal[BaseModelType.Any] = Field(default=BaseModelType.Any) type: Literal[ModelType.Qwen3Encoder] = Field(default=ModelType.Qwen3Encoder) format: Literal[ModelFormat.Qwen3Encoder] = Field(default=ModelFormat.Qwen3Encoder) + cpu_only: bool | None = Field(default=None, description="Whether this model should run on CPU only") @classmethod def from_model_on_disk(cls, mod: ModelOnDisk, override_fields: dict[str, Any]) -> Self: @@ -130,6 +132,7 @@ class Qwen3Encoder_GGUF_Config(Checkpoint_Config_Base, Config_Base): base: Literal[BaseModelType.Any] = Field(default=BaseModelType.Any) type: Literal[ModelType.Qwen3Encoder] = Field(default=ModelType.Qwen3Encoder) format: Literal[ModelFormat.GGUFQuantized] = Field(default=ModelFormat.GGUFQuantized) + cpu_only: bool | None = Field(default=None, description="Whether this model should run on CPU only") @classmethod def from_model_on_disk(cls, mod: ModelOnDisk, override_fields: dict[str, Any]) -> Self: diff --git a/invokeai/backend/model_manager/configs/siglip.py b/invokeai/backend/model_manager/configs/siglip.py index 62ca9494e27..328aae1737b 100644 --- a/invokeai/backend/model_manager/configs/siglip.py +++ b/invokeai/backend/model_manager/configs/siglip.py @@ -27,6 +27,7 @@ class SigLIP_Diffusers_Config(Diffusers_Config_Base, Config_Base): type: Literal[ModelType.SigLIP] = Field(default=ModelType.SigLIP) format: Literal[ModelFormat.Diffusers] = Field(default=ModelFormat.Diffusers) base: Literal[BaseModelType.Any] = Field(default=BaseModelType.Any) + cpu_only: bool | None = Field(default=None, description="Whether this model should run on CPU only") @classmethod def from_model_on_disk(cls, mod: ModelOnDisk, override_fields: dict[str, Any]) -> Self: diff --git a/invokeai/backend/model_manager/configs/t5_encoder.py b/invokeai/backend/model_manager/configs/t5_encoder.py index ed682e14304..2da417b10a5 100644 --- a/invokeai/backend/model_manager/configs/t5_encoder.py +++ b/invokeai/backend/model_manager/configs/t5_encoder.py @@ -21,6 +21,7 @@ class T5Encoder_T5Encoder_Config(Config_Base): base: Literal[BaseModelType.Any] = Field(default=BaseModelType.Any) type: Literal[ModelType.T5Encoder] = Field(default=ModelType.T5Encoder) format: Literal[ModelFormat.T5Encoder] = Field(default=ModelFormat.T5Encoder) + cpu_only: bool | None = Field(default=None, description="Whether this model should run on CPU only") @classmethod def from_model_on_disk(cls, mod: ModelOnDisk, override_fields: dict[str, Any]) -> Self: @@ -50,6 +51,7 @@ class T5Encoder_BnBLLMint8_Config(Config_Base): base: Literal[BaseModelType.Any] = Field(default=BaseModelType.Any) type: Literal[ModelType.T5Encoder] = Field(default=ModelType.T5Encoder) format: Literal[ModelFormat.BnbQuantizedLlmInt8b] = Field(default=ModelFormat.BnbQuantizedLlmInt8b) + cpu_only: bool | None = Field(default=None, description="Whether this model should run on CPU only") @classmethod def from_model_on_disk(cls, mod: ModelOnDisk, override_fields: dict[str, Any]) -> Self: diff --git a/invokeai/backend/model_manager/load/load_default.py b/invokeai/backend/model_manager/load/load_default.py index 3fb7a574f31..ea699207348 100644 --- a/invokeai/backend/model_manager/load/load_default.py +++ b/invokeai/backend/model_manager/load/load_default.py @@ -5,6 +5,8 @@ from pathlib import Path from typing import Optional +import torch + from invokeai.app.services.config import InvokeAIAppConfig from invokeai.backend.model_manager.configs.base import Diffusers_Config_Base from invokeai.backend.model_manager.configs.factory import AnyModelConfig @@ -66,6 +68,30 @@ def _get_model_path(self, config: AnyModelConfig) -> Path: model_base = self._app_config.models_path return (model_base / config.path).resolve() + def _get_execution_device( + self, config: AnyModelConfig, submodel_type: Optional[SubModelType] = None + ) -> Optional[torch.device]: + """Determine the execution device for a model based on its configuration. + + CPU-only execution is only applied to text encoder submodels to save VRAM while keeping + the denoiser on GPU for performance. Conditioning tensors are moved to GPU after encoding. + + Returns: + torch.device("cpu") if the model should run on CPU only, None otherwise (use cache default). + """ + # Check if this is a text encoder submodel of a main model with cpu_only setting + if hasattr(config, "default_settings") and config.default_settings is not None: + if hasattr(config.default_settings, "cpu_only") and config.default_settings.cpu_only is True: + # Only apply CPU execution to text encoder submodels + if submodel_type in [SubModelType.TextEncoder, SubModelType.TextEncoder2, SubModelType.TextEncoder3]: + return torch.device("cpu") + + # Check if this is a standalone text encoder config with cpu_only field (T5Encoder, Qwen3Encoder, etc.) + if hasattr(config, "cpu_only") and config.cpu_only is True: + return torch.device("cpu") + + return None + def _load_and_cache(self, config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> CacheRecord: stats_name = ":".join([config.base, config.type, config.name, (submodel_type or "")]) try: @@ -77,9 +103,13 @@ def _load_and_cache(self, config: AnyModelConfig, submodel_type: Optional[SubMod self._ram_cache.make_room(self.get_size_fs(config, Path(config.path), submodel_type)) loaded_model = self._load_model(config, submodel_type) + # Determine execution device from model config, considering submodel type + execution_device = self._get_execution_device(config, submodel_type) + self._ram_cache.put( get_model_cache_key(config.key, submodel_type), model=loaded_model, + execution_device=execution_device, ) return self._ram_cache.get(key=get_model_cache_key(config.key, submodel_type), stats_name=stats_name) diff --git a/invokeai/backend/model_manager/load/model_cache/cached_model/cached_model_only_full_load.py b/invokeai/backend/model_manager/load/model_cache/cached_model/cached_model_only_full_load.py index e9cf889daad..bb04edef9b5 100644 --- a/invokeai/backend/model_manager/load/model_cache/cached_model/cached_model_only_full_load.py +++ b/invokeai/backend/model_manager/load/model_cache/cached_model/cached_model_only_full_load.py @@ -60,6 +60,11 @@ def is_in_vram(self) -> bool: """Return true if the model is currently in VRAM.""" return self._is_in_vram + @property + def compute_device(self) -> torch.device: + """Return the compute device for this model.""" + return self._compute_device + def full_load_to_vram(self) -> int: """Load all weights into VRAM (if supported by the model). Returns: diff --git a/invokeai/backend/model_manager/load/model_cache/cached_model/cached_model_with_partial_load.py b/invokeai/backend/model_manager/load/model_cache/cached_model/cached_model_with_partial_load.py index 004943c0174..f80b017ba7b 100644 --- a/invokeai/backend/model_manager/load/model_cache/cached_model/cached_model_with_partial_load.py +++ b/invokeai/backend/model_manager/load/model_cache/cached_model/cached_model_with_partial_load.py @@ -136,6 +136,11 @@ def cur_vram_bytes(self) -> int: ) return self._cur_vram_bytes + @property + def compute_device(self) -> torch.device: + """Return the compute device for this model.""" + return self._compute_device + def full_load_to_vram(self) -> int: """Load all weights into VRAM.""" return self.partial_load_to_vram(self.total_bytes()) diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache.py b/invokeai/backend/model_manager/load/model_cache/model_cache.py index fc48217e787..022439331c0 100644 --- a/invokeai/backend/model_manager/load/model_cache/model_cache.py +++ b/invokeai/backend/model_manager/load/model_cache/model_cache.py @@ -316,8 +316,15 @@ def shutdown(self) -> None: @synchronized @record_activity - def put(self, key: str, model: AnyModel) -> None: - """Add a model to the cache.""" + def put(self, key: str, model: AnyModel, execution_device: Optional[torch.device] = None) -> None: + """Add a model to the cache. + + Args: + key: Cache key for the model + model: The model to cache + execution_device: Optional device to use for this specific model. If None, uses the cache's default + execution_device. Use torch.device("cpu") to force a model to run on CPU. + """ if key in self._cached_models: self._logger.debug( f"Attempted to add model {key} ({model.__class__.__name__}), but it already exists in the cache. No action necessary." @@ -331,20 +338,23 @@ def put(self, key: str, model: AnyModel) -> None: if isinstance(model, torch.nn.Module): apply_custom_layers_to_model(model) + # Use the provided execution device, or fall back to the cache's default + effective_execution_device = execution_device if execution_device is not None else self._execution_device + # Partial loading only makes sense on CUDA. # - When running on CPU, there is no 'loading' to do. # - When running on MPS, memory is shared with the CPU, so the default OS memory management already handles this # well. - running_with_cuda = self._execution_device.type == "cuda" + running_with_cuda = effective_execution_device.type == "cuda" # Wrap model. if isinstance(model, torch.nn.Module) and running_with_cuda and self._enable_partial_loading: wrapped_model = CachedModelWithPartialLoad( - model, self._execution_device, keep_ram_copy=self._keep_ram_copy_of_weights + model, effective_execution_device, keep_ram_copy=self._keep_ram_copy_of_weights ) else: wrapped_model = CachedModelOnlyFullLoad( - model, self._execution_device, size, keep_ram_copy=self._keep_ram_copy_of_weights + model, effective_execution_device, size, keep_ram_copy=self._keep_ram_copy_of_weights ) cache_record = CacheRecord(key=key, cached_model=wrapped_model) @@ -428,8 +438,11 @@ def lock(self, cache_entry: CacheRecord, working_mem_bytes: Optional[int]) -> No f"Locking model {cache_entry.key} (Type: {cache_entry.cached_model.model.__class__.__name__})" ) - if self._execution_device.type == "cpu": - # Models don't need to be loaded into VRAM if we're running on CPU. + # Check if the model's specific compute_device is CPU, not just the cache's default execution_device + model_compute_device = cache_entry.cached_model.compute_device + if model_compute_device.type == "cpu": + # Models configured for CPU execution don't need to be loaded into VRAM + self._logger.debug(f"Model {cache_entry.key} is configured for CPU execution, skipping VRAM load") return try: @@ -511,9 +524,11 @@ def _load_locked_model(self, cache_entry: CacheRecord, working_mem_bytes: Option model_cur_vram_bytes = cache_entry.cached_model.cur_vram_bytes() vram_available = self._get_vram_available(working_mem_bytes) loaded_percent = model_cur_vram_bytes / model_total_bytes if model_total_bytes > 0 else 0 + # Use the model's actual compute_device for logging, not the cache's default + model_device = cache_entry.cached_model.compute_device self._logger.info( f"Loaded model '{cache_entry.key}' ({cache_entry.cached_model.model.__class__.__name__}) onto " - f"{self._execution_device.type} device in {(time.time() - start_time):.2f}s. " + f"{model_device.type} device in {(time.time() - start_time):.2f}s. " f"Total model size: {model_total_bytes / MB:.2f}MB, " f"VRAM: {model_cur_vram_bytes / MB:.2f}MB ({loaded_percent:.1%})" ) diff --git a/invokeai/frontend/web/openapi.json b/invokeai/frontend/web/openapi.json index 1be662f85e8..9157ee22fdd 100644 --- a/invokeai/frontend/web/openapi.json +++ b/invokeai/frontend/web/openapi.json @@ -235,6 +235,9 @@ { "$ref": "#/components/schemas/Main_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/Main_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/Main_BnBNF4_FLUX_Config" }, @@ -274,6 +277,9 @@ { "$ref": "#/components/schemas/ControlNet_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/ControlNet_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/ControlNet_Diffusers_SD1_Config" }, @@ -334,6 +340,12 @@ { "$ref": "#/components/schemas/Qwen3Encoder_Qwen3Encoder_Config" }, + { + "$ref": "#/components/schemas/Qwen3Encoder_Checkpoint_Config" + }, + { + "$ref": "#/components/schemas/Qwen3Encoder_GGUF_Config" + }, { "$ref": "#/components/schemas/TI_File_SD1_Config" }, @@ -484,6 +496,9 @@ { "$ref": "#/components/schemas/Main_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/Main_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/Main_BnBNF4_FLUX_Config" }, @@ -523,6 +538,9 @@ { "$ref": "#/components/schemas/ControlNet_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/ControlNet_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/ControlNet_Diffusers_SD1_Config" }, @@ -583,6 +601,12 @@ { "$ref": "#/components/schemas/Qwen3Encoder_Qwen3Encoder_Config" }, + { + "$ref": "#/components/schemas/Qwen3Encoder_Checkpoint_Config" + }, + { + "$ref": "#/components/schemas/Qwen3Encoder_GGUF_Config" + }, { "$ref": "#/components/schemas/TI_File_SD1_Config" }, @@ -778,6 +802,9 @@ { "$ref": "#/components/schemas/Main_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/Main_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/Main_BnBNF4_FLUX_Config" }, @@ -817,6 +844,9 @@ { "$ref": "#/components/schemas/ControlNet_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/ControlNet_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/ControlNet_Diffusers_SD1_Config" }, @@ -877,6 +907,12 @@ { "$ref": "#/components/schemas/Qwen3Encoder_Qwen3Encoder_Config" }, + { + "$ref": "#/components/schemas/Qwen3Encoder_Checkpoint_Config" + }, + { + "$ref": "#/components/schemas/Qwen3Encoder_GGUF_Config" + }, { "$ref": "#/components/schemas/TI_File_SD1_Config" }, @@ -1091,6 +1127,9 @@ { "$ref": "#/components/schemas/Main_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/Main_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/Main_BnBNF4_FLUX_Config" }, @@ -1130,6 +1169,9 @@ { "$ref": "#/components/schemas/ControlNet_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/ControlNet_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/ControlNet_Diffusers_SD1_Config" }, @@ -1190,6 +1232,12 @@ { "$ref": "#/components/schemas/Qwen3Encoder_Qwen3Encoder_Config" }, + { + "$ref": "#/components/schemas/Qwen3Encoder_Checkpoint_Config" + }, + { + "$ref": "#/components/schemas/Qwen3Encoder_GGUF_Config" + }, { "$ref": "#/components/schemas/TI_File_SD1_Config" }, @@ -1530,6 +1578,47 @@ } } }, + "/api/v2/models/i/bulk_delete": { + "post": { + "tags": ["model_manager"], + "summary": "Bulk Delete Models", + "description": "Delete multiple model records from database.\n\nThe configuration records will be removed. The corresponding weights files will be\ndeleted as well if they reside within the InvokeAI \"models\" directory.\nReturns a list of successfully deleted keys and failed deletions with error messages.", + "operationId": "bulk_delete_models", + "requestBody": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/BulkDeleteModelsRequest", + "description": "List of model keys to delete" + } + } + }, + "required": true + }, + "responses": { + "200": { + "description": "Models deleted (possibly with some failures)", + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/BulkDeleteModelsResponse" + } + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + } + } + } + } + }, "/api/v2/models/install": { "post": { "tags": ["model_manager"], @@ -1879,6 +1968,9 @@ { "$ref": "#/components/schemas/Main_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/Main_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/Main_BnBNF4_FLUX_Config" }, @@ -1918,6 +2010,9 @@ { "$ref": "#/components/schemas/ControlNet_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/ControlNet_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/ControlNet_Diffusers_SD1_Config" }, @@ -1978,6 +2073,12 @@ { "$ref": "#/components/schemas/Qwen3Encoder_Qwen3Encoder_Config" }, + { + "$ref": "#/components/schemas/Qwen3Encoder_Checkpoint_Config" + }, + { + "$ref": "#/components/schemas/Qwen3Encoder_GGUF_Config" + }, { "$ref": "#/components/schemas/TI_File_SD1_Config" }, @@ -6157,6 +6258,63 @@ } } }, + "/api/v1/workflows/tags": { + "get": { + "tags": ["workflows"], + "summary": "Get All Tags", + "description": "Gets all unique tags from workflows", + "operationId": "get_all_tags", + "parameters": [ + { + "name": "categories", + "in": "query", + "required": false, + "schema": { + "anyOf": [ + { + "type": "array", + "items": { + "$ref": "#/components/schemas/WorkflowCategory" + } + }, + { + "type": "null" + } + ], + "description": "The categories to include", + "title": "Categories" + }, + "description": "The categories to include" + } + ], + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": { + "type": "array", + "items": { + "type": "string" + }, + "title": "Response Get All Tags" + } + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + } + } + } + } + }, "/api/v1/workflows/counts_by_tag": { "get": { "tags": ["workflows"], @@ -7030,6 +7188,9 @@ { "$ref": "#/components/schemas/Main_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/Main_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/Main_BnBNF4_FLUX_Config" }, @@ -7069,6 +7230,9 @@ { "$ref": "#/components/schemas/ControlNet_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/ControlNet_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/ControlNet_Diffusers_SD1_Config" }, @@ -7129,6 +7293,12 @@ { "$ref": "#/components/schemas/Qwen3Encoder_Qwen3Encoder_Config" }, + { + "$ref": "#/components/schemas/Qwen3Encoder_Checkpoint_Config" + }, + { + "$ref": "#/components/schemas/Qwen3Encoder_GGUF_Config" + }, { "$ref": "#/components/schemas/TI_File_SD1_Config" }, @@ -8933,6 +9103,47 @@ "title": "BoundingBoxOutput", "type": "object" }, + "BulkDeleteModelsRequest": { + "properties": { + "keys": { + "items": { + "type": "string" + }, + "type": "array", + "title": "Keys", + "description": "List of model keys to delete" + } + }, + "type": "object", + "required": ["keys"], + "title": "BulkDeleteModelsRequest", + "description": "Request body for bulk model deletion." + }, + "BulkDeleteModelsResponse": { + "properties": { + "deleted": { + "items": { + "type": "string" + }, + "type": "array", + "title": "Deleted", + "description": "List of successfully deleted model keys" + }, + "failed": { + "items": { + "additionalProperties": true, + "type": "object" + }, + "type": "array", + "title": "Failed", + "description": "List of failed deletions with error messages" + } + }, + "type": "object", + "required": ["deleted", "failed"], + "title": "BulkDeleteModelsResponse", + "description": "Response body for bulk model deletion." + }, "BulkDownloadCompleteEvent": { "description": "Event model for bulk_download_complete", "properties": { @@ -9116,6 +9327,18 @@ "title": "Type", "default": "clip_embed" }, + "cpu_only": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ], + "title": "Cpu Only", + "description": "Whether this model should run on CPU only" + }, "variant": { "type": "string", "const": "gigantic", @@ -9139,6 +9362,7 @@ "repo_variant", "base", "type", + "cpu_only", "variant" ], "title": "CLIPEmbed_Diffusers_G_Config" @@ -9237,6 +9461,18 @@ "title": "Type", "default": "clip_embed" }, + "cpu_only": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ], + "title": "Cpu Only", + "description": "Whether this model should run on CPU only" + }, "variant": { "type": "string", "const": "large", @@ -9260,6 +9496,7 @@ "repo_variant", "base", "type", + "cpu_only", "variant" ], "title": "CLIPEmbed_Diffusers_L_Config" @@ -9514,6 +9751,18 @@ "const": "clip_vision", "title": "Type", "default": "clip_vision" + }, + "cpu_only": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ], + "title": "Cpu Only", + "description": "Whether this model should run on CPU only" } }, "type": "object", @@ -9531,7 +9780,8 @@ "format", "repo_variant", "base", - "type" + "type", + "cpu_only" ], "title": "CLIPVision_Diffusers_Config", "description": "Model config for CLIPVision." @@ -13119,6 +13369,140 @@ ], "title": "ControlNet_Checkpoint_SDXL_Config" }, + "ControlNet_Checkpoint_ZImage_Config": { + "properties": { + "key": { + "type": "string", + "title": "Key", + "description": "A unique key for this model." + }, + "hash": { + "type": "string", + "title": "Hash", + "description": "The hash of the model file(s)." + }, + "path": { + "type": "string", + "title": "Path", + "description": "Path to the model on the filesystem. Relative paths are relative to the Invoke root directory." + }, + "file_size": { + "type": "integer", + "title": "File Size", + "description": "The size of the model in bytes." + }, + "name": { + "type": "string", + "title": "Name", + "description": "Name of the model." + }, + "description": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Description", + "description": "Model description" + }, + "source": { + "type": "string", + "title": "Source", + "description": "The original source of the model (path, URL or repo_id)." + }, + "source_type": { + "$ref": "#/components/schemas/ModelSourceType", + "description": "The type of source" + }, + "source_api_response": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Source Api Response", + "description": "The original API response from the source, as stringified JSON." + }, + "cover_image": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Cover Image", + "description": "Url for image to preview model" + }, + "config_path": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Config Path", + "description": "Path to the config for this model, if any." + }, + "type": { + "type": "string", + "const": "controlnet", + "title": "Type", + "default": "controlnet" + }, + "format": { + "type": "string", + "const": "checkpoint", + "title": "Format", + "default": "checkpoint" + }, + "base": { + "type": "string", + "const": "z-image", + "title": "Base", + "default": "z-image" + }, + "default_settings": { + "anyOf": [ + { + "$ref": "#/components/schemas/ControlAdapterDefaultSettings" + }, + { + "type": "null" + } + ] + } + }, + "type": "object", + "required": [ + "key", + "hash", + "path", + "file_size", + "name", + "description", + "source", + "source_type", + "source_api_response", + "cover_image", + "config_path", + "type", + "format", + "base", + "default_settings" + ], + "title": "ControlNet_Checkpoint_ZImage_Config", + "description": "Model config for Z-Image Control adapter models (Safetensors checkpoint).\n\nZ-Image Control models are standalone adapters containing only the control layers\n(control_layers, control_all_x_embedder, control_noise_refiner) that extend\nthe base Z-Image transformer with spatial conditioning capabilities.\n\nSupports: Canny, HED, Depth, Pose, MLSD.\nRecommended control_context_scale: 0.65-0.80." + }, "ControlNet_Diffusers_FLUX_Config": { "properties": { "key": { @@ -14083,6 +14467,22 @@ "orig_default": null, "orig_required": false }, + "qwen3_encoder": { + "anyOf": [ + { + "$ref": "#/components/schemas/ModelIdentifierField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The Qwen3 text encoder model used for Z-Image inference", + "field_kind": "input", + "input": "any", + "orig_default": null, + "orig_required": false + }, "hrf_enabled": { "anyOf": [ { @@ -14298,7 +14698,7 @@ "tags": ["metadata"], "title": "Core Metadata", "type": "object", - "version": "2.0.0", + "version": "2.1.0", "output": { "$ref": "#/components/schemas/MetadataOutput" } @@ -18830,6 +19230,22 @@ "title": "Num Steps", "type": "integer" }, + "scheduler": { + "default": "euler", + "description": "Scheduler (sampler) for the denoising process. 'euler' is fast and standard. 'heun' is 2nd-order (better quality, 2x slower). 'lcm' is optimized for few steps.", + "enum": ["euler", "heun", "lcm"], + "field_kind": "input", + "input": "any", + "orig_default": "euler", + "orig_required": false, + "title": "Scheduler", + "type": "string", + "ui_choice_labels": { + "euler": "Euler", + "heun": "Heun (2nd order)", + "lcm": "LCM" + } + }, "guidance": { "default": 4.0, "description": "The guidance strength. Higher values adhere more strictly to the prompt, and will produce less diverse images. FLUX dev only, ignored for schnell.", @@ -18947,7 +19363,7 @@ "tags": ["image", "flux"], "title": "FLUX Denoise", "type": "object", - "version": "4.1.0", + "version": "4.2.0", "output": { "$ref": "#/components/schemas/LatentsOutput" } @@ -19254,6 +19670,22 @@ "title": "Num Steps", "type": "integer" }, + "scheduler": { + "default": "euler", + "description": "Scheduler (sampler) for the denoising process. 'euler' is fast and standard. 'heun' is 2nd-order (better quality, 2x slower). 'lcm' is optimized for few steps.", + "enum": ["euler", "heun", "lcm"], + "field_kind": "input", + "input": "any", + "orig_default": "euler", + "orig_required": false, + "title": "Scheduler", + "type": "string", + "ui_choice_labels": { + "euler": "Euler", + "heun": "Heun (2nd order)", + "lcm": "LCM" + } + }, "guidance": { "default": 4.0, "description": "The guidance strength. Higher values adhere more strictly to the prompt, and will produce less diverse images. FLUX dev only, ignored for schnell.", @@ -21478,6 +21910,9 @@ { "$ref": "#/components/schemas/NormalMapInvocation" }, + { + "$ref": "#/components/schemas/PBRMapsInvocation" + }, { "$ref": "#/components/schemas/PairTileImageInvocation" }, @@ -21487,6 +21922,9 @@ { "$ref": "#/components/schemas/PiDiNetEdgeDetectionInvocation" }, + { + "$ref": "#/components/schemas/PromptTemplateInvocation" + }, { "$ref": "#/components/schemas/PromptsFromFileInvocation" }, @@ -21616,9 +22054,15 @@ { "$ref": "#/components/schemas/VAELoaderInvocation" }, + { + "$ref": "#/components/schemas/ZImageControlInvocation" + }, { "$ref": "#/components/schemas/ZImageDenoiseInvocation" }, + { + "$ref": "#/components/schemas/ZImageDenoiseMetaInvocation" + }, { "$ref": "#/components/schemas/ZImageImageToLatentsInvocation" }, @@ -21634,6 +22078,9 @@ { "$ref": "#/components/schemas/ZImageModelLoaderInvocation" }, + { + "$ref": "#/components/schemas/ZImageSeedVarianceEnhancerInvocation" + }, { "$ref": "#/components/schemas/ZImageTextEncoderInvocation" } @@ -21864,9 +22311,15 @@ { "$ref": "#/components/schemas/NoiseOutput" }, + { + "$ref": "#/components/schemas/PBRMapsOutput" + }, { "$ref": "#/components/schemas/PairTileImageOutput" }, + { + "$ref": "#/components/schemas/PromptTemplateOutput" + }, { "$ref": "#/components/schemas/SD3ConditioningOutput" }, @@ -21918,6 +22371,9 @@ { "$ref": "#/components/schemas/ZImageConditioningOutput" }, + { + "$ref": "#/components/schemas/ZImageControlOutput" + }, { "$ref": "#/components/schemas/ZImageLoRALoaderOutput" }, @@ -22252,7 +22708,7 @@ "type": "object", "required": ["repo_id"], "title": "HFModelSource", - "description": "A HuggingFace repo_id with optional variant, sub-folder and access token.\nNote that the variant option, if not provided to the constructor, will default to fp16, which is\nwhat people (almost) always want." + "description": "A HuggingFace repo_id with optional variant, sub-folder(s) and access token.\nNote that the variant option, if not provided to the constructor, will default to fp16, which is\nwhat people (almost) always want.\n\nThe subfolder can be a single path or multiple paths joined by '+' (e.g., \"text_encoder+tokenizer\").\nWhen multiple subfolders are specified, all of them will be downloaded and combined into the model directory." }, "HFTokenStatus": { "type": "string", @@ -28390,6 +28846,9 @@ { "$ref": "#/components/schemas/NormalMapInvocation" }, + { + "$ref": "#/components/schemas/PBRMapsInvocation" + }, { "$ref": "#/components/schemas/PairTileImageInvocation" }, @@ -28399,6 +28858,9 @@ { "$ref": "#/components/schemas/PiDiNetEdgeDetectionInvocation" }, + { + "$ref": "#/components/schemas/PromptTemplateInvocation" + }, { "$ref": "#/components/schemas/PromptsFromFileInvocation" }, @@ -28528,9 +28990,15 @@ { "$ref": "#/components/schemas/VAELoaderInvocation" }, + { + "$ref": "#/components/schemas/ZImageControlInvocation" + }, { "$ref": "#/components/schemas/ZImageDenoiseInvocation" }, + { + "$ref": "#/components/schemas/ZImageDenoiseMetaInvocation" + }, { "$ref": "#/components/schemas/ZImageImageToLatentsInvocation" }, @@ -28546,6 +29014,9 @@ { "$ref": "#/components/schemas/ZImageModelLoaderInvocation" }, + { + "$ref": "#/components/schemas/ZImageSeedVarianceEnhancerInvocation" + }, { "$ref": "#/components/schemas/ZImageTextEncoderInvocation" } @@ -28734,9 +29205,15 @@ { "$ref": "#/components/schemas/NoiseOutput" }, + { + "$ref": "#/components/schemas/PBRMapsOutput" + }, { "$ref": "#/components/schemas/PairTileImageOutput" }, + { + "$ref": "#/components/schemas/PromptTemplateOutput" + }, { "$ref": "#/components/schemas/SD3ConditioningOutput" }, @@ -28788,6 +29265,9 @@ { "$ref": "#/components/schemas/ZImageConditioningOutput" }, + { + "$ref": "#/components/schemas/ZImageControlOutput" + }, { "$ref": "#/components/schemas/ZImageLoRALoaderOutput" }, @@ -29365,6 +29845,9 @@ { "$ref": "#/components/schemas/NormalMapInvocation" }, + { + "$ref": "#/components/schemas/PBRMapsInvocation" + }, { "$ref": "#/components/schemas/PairTileImageInvocation" }, @@ -29374,6 +29857,9 @@ { "$ref": "#/components/schemas/PiDiNetEdgeDetectionInvocation" }, + { + "$ref": "#/components/schemas/PromptTemplateInvocation" + }, { "$ref": "#/components/schemas/PromptsFromFileInvocation" }, @@ -29503,9 +29989,15 @@ { "$ref": "#/components/schemas/VAELoaderInvocation" }, + { + "$ref": "#/components/schemas/ZImageControlInvocation" + }, { "$ref": "#/components/schemas/ZImageDenoiseInvocation" }, + { + "$ref": "#/components/schemas/ZImageDenoiseMetaInvocation" + }, { "$ref": "#/components/schemas/ZImageImageToLatentsInvocation" }, @@ -29521,6 +30013,9 @@ { "$ref": "#/components/schemas/ZImageModelLoaderInvocation" }, + { + "$ref": "#/components/schemas/ZImageSeedVarianceEnhancerInvocation" + }, { "$ref": "#/components/schemas/ZImageTextEncoderInvocation" } @@ -30069,12 +30564,18 @@ "paste_image_into_bounding_box": { "$ref": "#/components/schemas/ImageOutput" }, + "pbr_maps": { + "$ref": "#/components/schemas/PBRMapsOutput" + }, "pidi_edge_detection": { "$ref": "#/components/schemas/ImageOutput" }, "prompt_from_file": { "$ref": "#/components/schemas/StringCollectionOutput" }, + "prompt_template": { + "$ref": "#/components/schemas/PromptTemplateOutput" + }, "rand_float": { "$ref": "#/components/schemas/FloatOutput" }, @@ -30201,9 +30702,15 @@ "vae_loader": { "$ref": "#/components/schemas/VAEOutput" }, + "z_image_control": { + "$ref": "#/components/schemas/ZImageControlOutput" + }, "z_image_denoise": { "$ref": "#/components/schemas/LatentsOutput" }, + "z_image_denoise_meta": { + "$ref": "#/components/schemas/LatentsMetaOutput" + }, "z_image_i2l": { "$ref": "#/components/schemas/LatentsOutput" }, @@ -30219,229 +30726,237 @@ "z_image_model_loader": { "$ref": "#/components/schemas/ZImageModelLoaderOutput" }, + "z_image_seed_variance_enhancer": { + "$ref": "#/components/schemas/ZImageConditioningOutput" + }, "z_image_text_encoder": { "$ref": "#/components/schemas/ZImageConditioningOutput" } }, "required": [ - "rand_int", - "metadata_to_bool_collection", - "z_image_i2l", - "lora_loader", - "img_lerp", - "lblend", - "blank_image", - "integer_collection", - "z_image_denoise", - "create_denoise_mask", - "denoise_latents_meta", - "img_channel_multiply", - "sdxl_refiner_compel_prompt", + "image_collection", + "infill_rgba", + "cv_inpaint", + "cogview4_i2l", + "face_identifier", + "img_ilerp", + "flux_redux", + "seamless", + "invokeai_img_blend", "show_image", - "float_to_int", - "img_hue_adjust", - "sdxl_compel_prompt", - "get_image_mask_bounding_box", - "metadata_to_lora_collection", - "denoise_latents", - "img_channel_offset", - "string_generator", - "img_conv", - "range_of_size", - "cogview4_denoise", + "infill_cv2", + "z_image_seed_variance_enhancer", + "z_image_model_loader", + "invokeai_img_val_thresholds", + "scheduler", "float", - "metadata_to_integer", + "dw_openpose_detection", + "lora_selector", + "segment_anything", + "sub", + "spandrel_image_to_image_autoscale", + "ip_adapter", + "model_identifier", + "integer", + "create_gradient_mask", + "img_pad_crop", + "color", + "z_image_denoise", + "flux_lora_collection_loader", + "heuristic_resize", + "prompt_from_file", + "grounding_dino", + "latents_collection", + "noise", + "sd3_l2i", + "compel", + "pair_tile_image", + "string_split_neg", + "ideal_size", + "rectangle_mask", "t2i_adapter", - "invokeai_ealightness", - "float_batch", - "metadata_item", - "img_ilerp", - "face_mask_detection", - "tile_to_properties", - "conditioning", - "freeu", - "flux_kontext", - "mlsd_detection", - "sdxl_lora_collection_loader", - "invokeai_img_blend", "img_blur", - "ideal_size", - "range", - "metadata_to_t2i_adapters", - "l2i", - "metadata_to_vae", - "lora_collection_loader", - "canvas_paste_back", - "img_paste", - "lresize", - "random_range", - "metadata_to_integer_collection", "tensor_mask_to_image", - "alpha_mask_to_tensor", - "invokeai_img_hue_adjust_plus", - "string_split_neg", - "flux_fill", - "sd3_denoise", - "flux_controlnet", + "metadata_to_float", + "metadata_from_image", "invokeai_img_dilate_erode", - "canvas_v2_mask_and_crop", - "lineart_edge_detection", - "merge_metadata", + "metadata_to_sdlx_loras", "string_batch", - "mask_combine", - "color", - "float_range", - "crop_latents", - "spandrel_image_to_image", - "metadata_to_float", + "calculate_image_tiles_min_overlap", + "cogview4_text_encoder", "mul", - "infill_tile", - "cv_inpaint", - "calculate_image_tiles", - "img_nsfw", - "image_generator", - "flux_lora_collection_loader", + "img_crop", "string_join", - "seamless", - "sd3_i2l", - "flux_control_lora_loader", - "paste_image_into_bounding_box", - "clip_skip", - "conditioning_collection", - "flux_ip_adapter", - "metadata_to_ip_adapters", - "esrgan", - "invokeai_img_val_thresholds", - "face_identifier", - "metadata", - "cogview4_model_loader", - "sub", - "metadata_to_controlnets", + "metadata_to_integer", + "z_image_denoise_meta", + "tile_to_properties", + "string", + "float_generator", "z_image_text_encoder", + "mask_from_id", "string_join_three", - "unsharp_mask", - "grounding_dino", - "metadata_to_bool", - "apply_tensor_mask_to_image", - "flux_denoise_meta", - "iterate", - "image_batch", - "metadata_from_image", - "integer_math", - "metadata_to_string_collection", - "expand_mask_with_fade", - "integer_generator", - "sd3_l2i", - "boolean_collection", - "round_float", - "infill_rgba", - "z_image_l2i", - "vae_loader", - "controlnet", - "tiled_multi_diffusion_denoise_latents", - "string_split", - "cogview4_i2l", - "image_mask_to_tensor", - "heuristic_resize", - "img_watermark", - "scheduler", - "img_crop", - "sdxl_refiner_model_loader", - "segment_anything", - "color_map", + "float_math", "boolean", - "hed_edge_detection", - "rectangle_mask", - "infill_lama", - "main_model_loader", - "save_image", - "calculate_image_tiles_even_split", + "img_watermark", + "create_denoise_mask", + "invokeai_img_hue_adjust_plus", + "i2l", + "metadata_to_loras", + "cogview4_l2i", + "lora_loader", + "img_chan", + "dynamic_prompt", + "metadata_to_bool", "image", - "flux_redux", - "noise", - "llava_onevision_vllm", + "normal_map", + "flux_text_encoder", + "pidi_edge_detection", + "unsharp_mask", + "flux_lora_loader", + "infill_lama", "invokeai_img_enhance", - "model_identifier", - "img_resize", + "integer_generator", + "string_replace", + "flux_vae_decode", + "z_image_control", + "tiled_multi_diffusion_denoise_latents", "integer_batch", "img_noise", - "cogview4_text_encoder", - "latents_collection", - "metadata_to_loras", - "dynamic_prompt", - "metadata_item_linked", - "z_image_lora_loader", - "merge_tiles_to_image", - "img_chan", - "float_generator", - "compel", - "string", + "metadata_to_sdxl_model", + "sdxl_refiner_model_loader", + "image_generator", + "image_batch", + "conditioning_collection", + "metadata_to_string_collection", + "metadata_to_model", + "metadata_to_vae", + "apply_mask_to_image", + "flux_model_loader", + "metadata_to_ip_adapters", + "z_image_l2i", + "freeu", + "clip_skip", + "sdxl_compel_prompt", + "flux_denoise_meta", + "boolean_collection", "add", - "canny_edge_detection", - "string_collection", - "flux_denoise", - "sd3_text_encoder", - "metadata_to_scheduler", - "mask_edge", - "img_scale", - "flux_vae_decode", - "latents", - "flux_lora_loader", - "float_math", - "div", - "pidi_edge_detection", - "image_panel_layout", - "lscale", + "canvas_v2_mask_and_crop", + "get_image_mask_bounding_box", + "img_nsfw", + "sdxl_model_loader", + "mediapipe_face_detection", + "metadata_item_linked", + "img_resize", "infill_patchmatch", - "face_off", - "sdxl_lora_loader", - "i2l", - "crop_image_to_bounding_box", - "core_metadata", - "calculate_image_tiles_min_overlap", - "image_collection", - "metadata_to_model", - "infill_cv2", + "paste_image_into_bounding_box", + "esrgan", + "metadata_to_float_collection", + "random_range", + "iterate", + "latents", + "flux_ip_adapter", + "float_collection", + "integer_collection", + "color_map", "z_image_lora_collection_loader", - "mask_from_id", - "tomask", - "cogview4_l2i", - "metadata_to_sdlx_loras", - "integer", - "normal_map", + "metadata_field_extractor", + "calculate_image_tiles_even_split", + "face_mask_detection", + "mlsd_detection", + "invokeai_ealightness", "lineart_anime_edge_detection", + "range_of_size", + "flux_kontext_image_prep", + "controlnet", + "bounding_box", "content_shuffle", - "string_replace", - "img_mul", - "flux_text_encoder", - "sdxl_model_loader", - "prompt_from_file", + "float_to_int", + "lscale", + "denoise_latents", + "mask_edge", + "rand_int", + "string_generator", + "cogview4_model_loader", + "cogview4_denoise", + "image_panel_layout", + "float_batch", "invert_tensor_mask", - "rand_float", - "flux_vae_encode", - "ip_adapter", - "lora_selector", - "spandrel_image_to_image_autoscale", + "blank_image", + "metadata_item", + "vae_loader", + "core_metadata", + "sd3_text_encoder", + "sdxl_refiner_compel_prompt", + "main_model_loader", + "metadata_to_scheduler", + "flux_denoise", + "range", "sd3_model_loader", - "bounding_box", - "metadata_to_string", - "dw_openpose_detection", + "img_paste", + "integer_math", + "prompt_template", + "string_split", + "mask_combine", + "calculate_image_tiles", + "z_image_i2l", + "crop_latents", + "flux_control_lora_loader", + "tomask", + "img_scale", "collect", - "create_gradient_mask", - "flux_kontext_image_prep", - "apply_mask_to_image", - "pair_tile_image", - "z_image_model_loader", - "flux_model_loader", - "metadata_to_sdxl_model", - "metadata_to_float_collection", - "color_correct", - "metadata_field_extractor", - "float_collection", - "mediapipe_face_detection", - "depth_anything_depth_estimation", + "sd3_denoise", + "metadata_to_string", + "z_image_lora_loader", + "conditioning", + "image_mask_to_tensor", + "img_channel_multiply", + "metadata_to_t2i_adapters", + "merge_tiles_to_image", + "spandrel_image_to_image", + "img_conv", + "alpha_mask_to_tensor", + "metadata_to_bool_collection", + "div", + "img_mul", + "llava_onevision_vllm", + "crop_image_to_bounding_box", + "string_collection", "invokeai_img_composite", - "img_pad_crop" + "face_off", + "sd3_i2l", + "img_hue_adjust", + "metadata", + "denoise_latents_meta", + "round_float", + "save_image", + "merge_metadata", + "metadata_to_controlnets", + "flux_controlnet", + "canvas_paste_back", + "sdxl_lora_loader", + "flux_kontext", + "img_channel_offset", + "depth_anything_depth_estimation", + "expand_mask_with_fade", + "hed_edge_detection", + "apply_tensor_mask_to_image", + "rand_float", + "flux_fill", + "img_lerp", + "metadata_to_integer_collection", + "infill_tile", + "sdxl_lora_collection_loader", + "lineart_edge_detection", + "color_correct", + "lblend", + "float_range", + "canny_edge_detection", + "flux_vae_encode", + "l2i", + "metadata_to_lora_collection", + "pbr_maps", + "lresize", + "lora_collection_loader" ] }, "InvocationProgressEvent": { @@ -30996,6 +31511,9 @@ { "$ref": "#/components/schemas/NormalMapInvocation" }, + { + "$ref": "#/components/schemas/PBRMapsInvocation" + }, { "$ref": "#/components/schemas/PairTileImageInvocation" }, @@ -31005,6 +31523,9 @@ { "$ref": "#/components/schemas/PiDiNetEdgeDetectionInvocation" }, + { + "$ref": "#/components/schemas/PromptTemplateInvocation" + }, { "$ref": "#/components/schemas/PromptsFromFileInvocation" }, @@ -31134,9 +31655,15 @@ { "$ref": "#/components/schemas/VAELoaderInvocation" }, + { + "$ref": "#/components/schemas/ZImageControlInvocation" + }, { "$ref": "#/components/schemas/ZImageDenoiseInvocation" }, + { + "$ref": "#/components/schemas/ZImageDenoiseMetaInvocation" + }, { "$ref": "#/components/schemas/ZImageImageToLatentsInvocation" }, @@ -31152,6 +31679,9 @@ { "$ref": "#/components/schemas/ZImageModelLoaderInvocation" }, + { + "$ref": "#/components/schemas/ZImageSeedVarianceEnhancerInvocation" + }, { "$ref": "#/components/schemas/ZImageTextEncoderInvocation" } @@ -31765,6 +32295,9 @@ { "$ref": "#/components/schemas/NormalMapInvocation" }, + { + "$ref": "#/components/schemas/PBRMapsInvocation" + }, { "$ref": "#/components/schemas/PairTileImageInvocation" }, @@ -31774,6 +32307,9 @@ { "$ref": "#/components/schemas/PiDiNetEdgeDetectionInvocation" }, + { + "$ref": "#/components/schemas/PromptTemplateInvocation" + }, { "$ref": "#/components/schemas/PromptsFromFileInvocation" }, @@ -31903,9 +32439,15 @@ { "$ref": "#/components/schemas/VAELoaderInvocation" }, + { + "$ref": "#/components/schemas/ZImageControlInvocation" + }, { "$ref": "#/components/schemas/ZImageDenoiseInvocation" }, + { + "$ref": "#/components/schemas/ZImageDenoiseMetaInvocation" + }, { "$ref": "#/components/schemas/ZImageImageToLatentsInvocation" }, @@ -31921,6 +32463,9 @@ { "$ref": "#/components/schemas/ZImageModelLoaderInvocation" }, + { + "$ref": "#/components/schemas/ZImageSeedVarianceEnhancerInvocation" + }, { "$ref": "#/components/schemas/ZImageTextEncoderInvocation" } @@ -32063,14 +32608,14 @@ "format": "path", "title": "Convert Cache Dir", "description": "Path to the converted models cache directory (DEPRECATED, but do not delete because it is needed for migration from previous versions).", - "default": "models\\.convert_cache" + "default": "models/.convert_cache" }, "download_cache_dir": { "type": "string", "format": "path", "title": "Download Cache Dir", "description": "Path to the directory that contains dynamically downloaded models.", - "default": "models\\.download_cache" + "default": "models/.download_cache" }, "legacy_conf_dir": { "type": "string", @@ -32219,6 +32764,13 @@ "description": "If True, a memory snapshot will be captured before and after every model cache operation, and the result will be logged (at debug level). There is a time cost to capturing the memory snapshots, so it is recommended to only enable this feature if you are actively inspecting the model cache's behaviour.", "default": false }, + "model_cache_keep_alive_min": { + "type": "number", + "minimum": 0.0, + "title": "Model Cache Keep Alive Min", + "description": "How long to keep models in cache after last use, in minutes. A value of 0 (the default) means models are kept in cache indefinitely. If no model generations occur within the timeout period, the model cache is cleared using the same logic as the 'Clear Model Cache' button.", + "default": 0 + }, "device_working_mem_gb": { "type": "number", "title": "Device Working Mem Gb", @@ -32437,7 +32989,7 @@ "additionalProperties": false, "type": "object", "title": "InvokeAIAppConfig", - "description": "Invoke's global app configuration.\n\nTypically, you won't need to interact with this class directly. Instead, use the `get_config` function from `invokeai.app.services.config` to get a singleton config object.\n\nAttributes:\n host: IP address to bind to. Use `0.0.0.0` to serve to your local network.\n port: Port to bind to.\n allow_origins: Allowed CORS origins.\n allow_credentials: Allow CORS credentials.\n allow_methods: Methods allowed for CORS.\n allow_headers: Headers allowed for CORS.\n ssl_certfile: SSL certificate file for HTTPS. See https://www.uvicorn.org/settings/#https.\n ssl_keyfile: SSL key file for HTTPS. See https://www.uvicorn.org/settings/#https.\n log_tokenization: Enable logging of parsed prompt tokens.\n patchmatch: Enable patchmatch inpaint code.\n models_dir: Path to the models directory.\n convert_cache_dir: Path to the converted models cache directory (DEPRECATED, but do not delete because it is needed for migration from previous versions).\n download_cache_dir: Path to the directory that contains dynamically downloaded models.\n legacy_conf_dir: Path to directory of legacy checkpoint config files.\n db_dir: Path to InvokeAI databases directory.\n outputs_dir: Path to directory for outputs.\n custom_nodes_dir: Path to directory for custom nodes.\n style_presets_dir: Path to directory for style presets.\n workflow_thumbnails_dir: Path to directory for workflow thumbnails.\n log_handlers: Log handler. Valid options are \"console\", \"file=\", \"syslog=path|address:host:port\", \"http=\".\n log_format: Log format. Use \"plain\" for text-only, \"color\" for colorized output, \"legacy\" for 2.3-style logging and \"syslog\" for syslog-style.
Valid values: `plain`, `color`, `syslog`, `legacy`\n log_level: Emit logging messages at this level or higher.
Valid values: `debug`, `info`, `warning`, `error`, `critical`\n log_sql: Log SQL queries. `log_level` must be `debug` for this to do anything. Extremely verbose.\n log_level_network: Log level for network-related messages. 'info' and 'debug' are very verbose.
Valid values: `debug`, `info`, `warning`, `error`, `critical`\n use_memory_db: Use in-memory database. Useful for development.\n dev_reload: Automatically reload when Python sources are changed. Does not reload node definitions.\n profile_graphs: Enable graph profiling using `cProfile`.\n profile_prefix: An optional prefix for profile output files.\n profiles_dir: Path to profiles output directory.\n max_cache_ram_gb: The maximum amount of CPU RAM to use for model caching in GB. If unset, the limit will be configured based on the available RAM. In most cases, it is recommended to leave this unset.\n max_cache_vram_gb: The amount of VRAM to use for model caching in GB. If unset, the limit will be configured based on the available VRAM and the device_working_mem_gb. In most cases, it is recommended to leave this unset.\n log_memory_usage: If True, a memory snapshot will be captured before and after every model cache operation, and the result will be logged (at debug level). There is a time cost to capturing the memory snapshots, so it is recommended to only enable this feature if you are actively inspecting the model cache's behaviour.\n device_working_mem_gb: The amount of working memory to keep available on the compute device (in GB). Has no effect if running on CPU. If you are experiencing OOM errors, try increasing this value.\n enable_partial_loading: Enable partial loading of models. This enables models to run with reduced VRAM requirements (at the cost of slower speed) by streaming the model from RAM to VRAM as its used. In some edge cases, partial loading can cause models to run more slowly if they were previously being fully loaded into VRAM.\n keep_ram_copy_of_weights: Whether to keep a full RAM copy of a model's weights when the model is loaded in VRAM. Keeping a RAM copy increases average RAM usage, but speeds up model switching and LoRA patching (assuming there is sufficient RAM). Set this to False if RAM pressure is consistently high.\n ram: DEPRECATED: This setting is no longer used. It has been replaced by `max_cache_ram_gb`, but most users will not need to use this config since automatic cache size limits should work well in most cases. This config setting will be removed once the new model cache behavior is stable.\n vram: DEPRECATED: This setting is no longer used. It has been replaced by `max_cache_vram_gb`, but most users will not need to use this config since automatic cache size limits should work well in most cases. This config setting will be removed once the new model cache behavior is stable.\n lazy_offload: DEPRECATED: This setting is no longer used. Lazy-offloading is enabled by default. This config setting will be removed once the new model cache behavior is stable.\n pytorch_cuda_alloc_conf: Configure the Torch CUDA memory allocator. This will impact peak reserved VRAM usage and performance. Setting to \"backend:cudaMallocAsync\" works well on many systems. The optimal configuration is highly dependent on the system configuration (device type, VRAM, CUDA driver version, etc.), so must be tuned experimentally.\n device: Preferred execution device. `auto` will choose the device depending on the hardware platform and the installed torch capabilities.
Valid values: `auto`, `cpu`, `cuda`, `mps`, `cuda:N` (where N is a device number)\n precision: Floating point precision. `float16` will consume half the memory of `float32` but produce slightly lower-quality images. The `auto` setting will guess the proper precision based on your video card and operating system.
Valid values: `auto`, `float16`, `bfloat16`, `float32`\n sequential_guidance: Whether to calculate guidance in serial instead of in parallel, lowering memory requirements.\n attention_type: Attention type.
Valid values: `auto`, `normal`, `xformers`, `sliced`, `torch-sdp`\n attention_slice_size: Slice size, valid when attention_type==\"sliced\".
Valid values: `auto`, `balanced`, `max`, `1`, `2`, `3`, `4`, `5`, `6`, `7`, `8`\n force_tiled_decode: Whether to enable tiled VAE decode (reduces memory consumption with some performance penalty).\n pil_compress_level: The compress_level setting of PIL.Image.save(), used for PNG encoding. All settings are lossless. 0 = no compression, 1 = fastest with slightly larger filesize, 9 = slowest with smallest filesize. 1 is typically the best setting.\n max_queue_size: Maximum number of items in the session queue.\n clear_queue_on_startup: Empties session queue on startup.\n allow_nodes: List of nodes to allow. Omit to allow all.\n deny_nodes: List of nodes to deny. Omit to deny none.\n node_cache_size: How many cached nodes to keep in memory.\n hashing_algorithm: Model hashing algorthim for model installs. 'blake3_multi' is best for SSDs. 'blake3_single' is best for spinning disk HDDs. 'random' disables hashing, instead assigning a UUID to models. Useful when using a memory db to reduce model installation time, or if you don't care about storing stable hashes for models. Alternatively, any other hashlib algorithm is accepted, though these are not nearly as performant as blake3.
Valid values: `blake3_multi`, `blake3_single`, `random`, `md5`, `sha1`, `sha224`, `sha256`, `sha384`, `sha512`, `blake2b`, `blake2s`, `sha3_224`, `sha3_256`, `sha3_384`, `sha3_512`, `shake_128`, `shake_256`\n remote_api_tokens: List of regular expression and token pairs used when downloading models from URLs. The download URL is tested against the regex, and if it matches, the token is provided in as a Bearer token.\n scan_models_on_startup: Scan the models directory on startup, registering orphaned models. This is typically only used in conjunction with `use_memory_db` for testing purposes.\n unsafe_disable_picklescan: UNSAFE. Disable the picklescan security check during model installation. Recommended only for development and testing purposes. This will allow arbitrary code execution during model installation, so should never be used in production.\n allow_unknown_models: Allow installation of models that we are unable to identify. If enabled, models will be marked as `unknown` in the database, and will not have any metadata associated with them. If disabled, unknown models will be rejected during installation." + "description": "Invoke's global app configuration.\n\nTypically, you won't need to interact with this class directly. Instead, use the `get_config` function from `invokeai.app.services.config` to get a singleton config object.\n\nAttributes:\n host: IP address to bind to. Use `0.0.0.0` to serve to your local network.\n port: Port to bind to.\n allow_origins: Allowed CORS origins.\n allow_credentials: Allow CORS credentials.\n allow_methods: Methods allowed for CORS.\n allow_headers: Headers allowed for CORS.\n ssl_certfile: SSL certificate file for HTTPS. See https://www.uvicorn.org/settings/#https.\n ssl_keyfile: SSL key file for HTTPS. See https://www.uvicorn.org/settings/#https.\n log_tokenization: Enable logging of parsed prompt tokens.\n patchmatch: Enable patchmatch inpaint code.\n models_dir: Path to the models directory.\n convert_cache_dir: Path to the converted models cache directory (DEPRECATED, but do not delete because it is needed for migration from previous versions).\n download_cache_dir: Path to the directory that contains dynamically downloaded models.\n legacy_conf_dir: Path to directory of legacy checkpoint config files.\n db_dir: Path to InvokeAI databases directory.\n outputs_dir: Path to directory for outputs.\n custom_nodes_dir: Path to directory for custom nodes.\n style_presets_dir: Path to directory for style presets.\n workflow_thumbnails_dir: Path to directory for workflow thumbnails.\n log_handlers: Log handler. Valid options are \"console\", \"file=\", \"syslog=path|address:host:port\", \"http=\".\n log_format: Log format. Use \"plain\" for text-only, \"color\" for colorized output, \"legacy\" for 2.3-style logging and \"syslog\" for syslog-style.
Valid values: `plain`, `color`, `syslog`, `legacy`\n log_level: Emit logging messages at this level or higher.
Valid values: `debug`, `info`, `warning`, `error`, `critical`\n log_sql: Log SQL queries. `log_level` must be `debug` for this to do anything. Extremely verbose.\n log_level_network: Log level for network-related messages. 'info' and 'debug' are very verbose.
Valid values: `debug`, `info`, `warning`, `error`, `critical`\n use_memory_db: Use in-memory database. Useful for development.\n dev_reload: Automatically reload when Python sources are changed. Does not reload node definitions.\n profile_graphs: Enable graph profiling using `cProfile`.\n profile_prefix: An optional prefix for profile output files.\n profiles_dir: Path to profiles output directory.\n max_cache_ram_gb: The maximum amount of CPU RAM to use for model caching in GB. If unset, the limit will be configured based on the available RAM. In most cases, it is recommended to leave this unset.\n max_cache_vram_gb: The amount of VRAM to use for model caching in GB. If unset, the limit will be configured based on the available VRAM and the device_working_mem_gb. In most cases, it is recommended to leave this unset.\n log_memory_usage: If True, a memory snapshot will be captured before and after every model cache operation, and the result will be logged (at debug level). There is a time cost to capturing the memory snapshots, so it is recommended to only enable this feature if you are actively inspecting the model cache's behaviour.\n model_cache_keep_alive_min: How long to keep models in cache after last use, in minutes. A value of 0 (the default) means models are kept in cache indefinitely. If no model generations occur within the timeout period, the model cache is cleared using the same logic as the 'Clear Model Cache' button.\n device_working_mem_gb: The amount of working memory to keep available on the compute device (in GB). Has no effect if running on CPU. If you are experiencing OOM errors, try increasing this value.\n enable_partial_loading: Enable partial loading of models. This enables models to run with reduced VRAM requirements (at the cost of slower speed) by streaming the model from RAM to VRAM as its used. In some edge cases, partial loading can cause models to run more slowly if they were previously being fully loaded into VRAM.\n keep_ram_copy_of_weights: Whether to keep a full RAM copy of a model's weights when the model is loaded in VRAM. Keeping a RAM copy increases average RAM usage, but speeds up model switching and LoRA patching (assuming there is sufficient RAM). Set this to False if RAM pressure is consistently high.\n ram: DEPRECATED: This setting is no longer used. It has been replaced by `max_cache_ram_gb`, but most users will not need to use this config since automatic cache size limits should work well in most cases. This config setting will be removed once the new model cache behavior is stable.\n vram: DEPRECATED: This setting is no longer used. It has been replaced by `max_cache_vram_gb`, but most users will not need to use this config since automatic cache size limits should work well in most cases. This config setting will be removed once the new model cache behavior is stable.\n lazy_offload: DEPRECATED: This setting is no longer used. Lazy-offloading is enabled by default. This config setting will be removed once the new model cache behavior is stable.\n pytorch_cuda_alloc_conf: Configure the Torch CUDA memory allocator. This will impact peak reserved VRAM usage and performance. Setting to \"backend:cudaMallocAsync\" works well on many systems. The optimal configuration is highly dependent on the system configuration (device type, VRAM, CUDA driver version, etc.), so must be tuned experimentally.\n device: Preferred execution device. `auto` will choose the device depending on the hardware platform and the installed torch capabilities.
Valid values: `auto`, `cpu`, `cuda`, `mps`, `cuda:N` (where N is a device number)\n precision: Floating point precision. `float16` will consume half the memory of `float32` but produce slightly lower-quality images. The `auto` setting will guess the proper precision based on your video card and operating system.
Valid values: `auto`, `float16`, `bfloat16`, `float32`\n sequential_guidance: Whether to calculate guidance in serial instead of in parallel, lowering memory requirements.\n attention_type: Attention type.
Valid values: `auto`, `normal`, `xformers`, `sliced`, `torch-sdp`\n attention_slice_size: Slice size, valid when attention_type==\"sliced\".
Valid values: `auto`, `balanced`, `max`, `1`, `2`, `3`, `4`, `5`, `6`, `7`, `8`\n force_tiled_decode: Whether to enable tiled VAE decode (reduces memory consumption with some performance penalty).\n pil_compress_level: The compress_level setting of PIL.Image.save(), used for PNG encoding. All settings are lossless. 0 = no compression, 1 = fastest with slightly larger filesize, 9 = slowest with smallest filesize. 1 is typically the best setting.\n max_queue_size: Maximum number of items in the session queue.\n clear_queue_on_startup: Empties session queue on startup.\n allow_nodes: List of nodes to allow. Omit to allow all.\n deny_nodes: List of nodes to deny. Omit to deny none.\n node_cache_size: How many cached nodes to keep in memory.\n hashing_algorithm: Model hashing algorthim for model installs. 'blake3_multi' is best for SSDs. 'blake3_single' is best for spinning disk HDDs. 'random' disables hashing, instead assigning a UUID to models. Useful when using a memory db to reduce model installation time, or if you don't care about storing stable hashes for models. Alternatively, any other hashlib algorithm is accepted, though these are not nearly as performant as blake3.
Valid values: `blake3_multi`, `blake3_single`, `random`, `md5`, `sha1`, `sha224`, `sha256`, `sha384`, `sha512`, `blake2b`, `blake2s`, `sha3_224`, `sha3_256`, `sha3_384`, `sha3_512`, `shake_128`, `shake_256`\n remote_api_tokens: List of regular expression and token pairs used when downloading models from URLs. The download URL is tested against the regex, and if it matches, the token is provided in as a Bearer token.\n scan_models_on_startup: Scan the models directory on startup, registering orphaned models. This is typically only used in conjunction with `use_memory_db` for testing purposes.\n unsafe_disable_picklescan: UNSAFE. Disable the picklescan security check during model installation. Recommended only for development and testing purposes. This will allow arbitrary code execution during model installation, so should never be used in production.\n allow_unknown_models: Allow installation of models that we are unable to identify. If enabled, models will be marked as `unknown` in the database, and will not have any metadata associated with them. If disabled, unknown models will be rejected during installation." }, "InvokeAIAppConfigWithSetFields": { "properties": { @@ -34551,6 +35103,18 @@ "const": "any", "title": "Base", "default": "any" + }, + "cpu_only": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ], + "title": "Cpu Only", + "description": "Whether this model should run on CPU only" } }, "type": "object", @@ -34568,7 +35132,8 @@ "format", "repo_variant", "type", - "base" + "base", + "cpu_only" ], "title": "LlavaOnevision_Diffusers_Config", "description": "Model config for Llava Onevision models." @@ -37060,6 +37625,18 @@ ], "title": "Guidance", "description": "Default Guidance for this model" + }, + "cpu_only": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ], + "title": "Cpu Only", + "description": "Whether this model should run on CPU only" } }, "additionalProperties": false, @@ -38079,6 +38656,158 @@ ], "title": "Main_Checkpoint_SDXL_Config" }, + "Main_Checkpoint_ZImage_Config": { + "properties": { + "key": { + "type": "string", + "title": "Key", + "description": "A unique key for this model." + }, + "hash": { + "type": "string", + "title": "Hash", + "description": "The hash of the model file(s)." + }, + "path": { + "type": "string", + "title": "Path", + "description": "Path to the model on the filesystem. Relative paths are relative to the Invoke root directory." + }, + "file_size": { + "type": "integer", + "title": "File Size", + "description": "The size of the model in bytes." + }, + "name": { + "type": "string", + "title": "Name", + "description": "Name of the model." + }, + "description": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Description", + "description": "Model description" + }, + "source": { + "type": "string", + "title": "Source", + "description": "The original source of the model (path, URL or repo_id)." + }, + "source_type": { + "$ref": "#/components/schemas/ModelSourceType", + "description": "The type of source" + }, + "source_api_response": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Source Api Response", + "description": "The original API response from the source, as stringified JSON." + }, + "cover_image": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Cover Image", + "description": "Url for image to preview model" + }, + "type": { + "type": "string", + "const": "main", + "title": "Type", + "default": "main" + }, + "trigger_phrases": { + "anyOf": [ + { + "items": { + "type": "string" + }, + "type": "array", + "uniqueItems": true + }, + { + "type": "null" + } + ], + "title": "Trigger Phrases", + "description": "Set of trigger phrases for this model" + }, + "default_settings": { + "anyOf": [ + { + "$ref": "#/components/schemas/MainModelDefaultSettings" + }, + { + "type": "null" + } + ], + "description": "Default settings for this model" + }, + "config_path": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Config Path", + "description": "Path to the config for this model, if any." + }, + "base": { + "type": "string", + "const": "z-image", + "title": "Base", + "default": "z-image" + }, + "format": { + "type": "string", + "const": "checkpoint", + "title": "Format", + "default": "checkpoint" + } + }, + "type": "object", + "required": [ + "key", + "hash", + "path", + "file_size", + "name", + "description", + "source", + "source_type", + "source_api_response", + "cover_image", + "type", + "trigger_phrases", + "default_settings", + "config_path", + "base", + "format" + ], + "title": "Main_Checkpoint_ZImage_Config", + "description": "Model config for Z-Image single-file checkpoint models (safetensors, etc)." + }, "Main_Diffusers_CogView4_Config": { "properties": { "key": { @@ -43219,6 +43948,9 @@ { "$ref": "#/components/schemas/Main_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/Main_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/Main_BnBNF4_FLUX_Config" }, @@ -43258,6 +43990,9 @@ { "$ref": "#/components/schemas/ControlNet_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/ControlNet_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/ControlNet_Diffusers_SD1_Config" }, @@ -43318,6 +44053,12 @@ { "$ref": "#/components/schemas/Qwen3Encoder_Qwen3Encoder_Config" }, + { + "$ref": "#/components/schemas/Qwen3Encoder_Checkpoint_Config" + }, + { + "$ref": "#/components/schemas/Qwen3Encoder_GGUF_Config" + }, { "$ref": "#/components/schemas/TI_File_SD1_Config" }, @@ -43703,6 +44444,9 @@ { "$ref": "#/components/schemas/Main_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/Main_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/Main_BnBNF4_FLUX_Config" }, @@ -43742,6 +44486,9 @@ { "$ref": "#/components/schemas/ControlNet_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/ControlNet_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/ControlNet_Diffusers_SD1_Config" }, @@ -43802,6 +44549,12 @@ { "$ref": "#/components/schemas/Qwen3Encoder_Qwen3Encoder_Config" }, + { + "$ref": "#/components/schemas/Qwen3Encoder_Checkpoint_Config" + }, + { + "$ref": "#/components/schemas/Qwen3Encoder_GGUF_Config" + }, { "$ref": "#/components/schemas/TI_File_SD1_Config" }, @@ -44080,6 +44833,9 @@ { "$ref": "#/components/schemas/Main_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/Main_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/Main_BnBNF4_FLUX_Config" }, @@ -44119,6 +44875,9 @@ { "$ref": "#/components/schemas/ControlNet_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/ControlNet_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/ControlNet_Diffusers_SD1_Config" }, @@ -44179,6 +44938,12 @@ { "$ref": "#/components/schemas/Qwen3Encoder_Qwen3Encoder_Config" }, + { + "$ref": "#/components/schemas/Qwen3Encoder_Checkpoint_Config" + }, + { + "$ref": "#/components/schemas/Qwen3Encoder_GGUF_Config" + }, { "$ref": "#/components/schemas/TI_File_SD1_Config" }, @@ -44315,6 +45080,9 @@ { "$ref": "#/components/schemas/Main_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/Main_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/Main_BnBNF4_FLUX_Config" }, @@ -44354,6 +45122,9 @@ { "$ref": "#/components/schemas/ControlNet_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/ControlNet_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/ControlNet_Diffusers_SD1_Config" }, @@ -44414,6 +45185,12 @@ { "$ref": "#/components/schemas/Qwen3Encoder_Qwen3Encoder_Config" }, + { + "$ref": "#/components/schemas/Qwen3Encoder_Checkpoint_Config" + }, + { + "$ref": "#/components/schemas/Qwen3Encoder_GGUF_Config" + }, { "$ref": "#/components/schemas/TI_File_SD1_Config" }, @@ -44717,6 +45494,18 @@ "title": "Default Settings", "description": "Default settings for this model" }, + "cpu_only": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ], + "title": "Cpu Only", + "description": "Whether this model should run on CPU only" + }, "variant": { "anyOf": [ { @@ -44916,6 +45705,9 @@ { "$ref": "#/components/schemas/Main_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/Main_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/Main_BnBNF4_FLUX_Config" }, @@ -44955,6 +45747,9 @@ { "$ref": "#/components/schemas/ControlNet_Checkpoint_FLUX_Config" }, + { + "$ref": "#/components/schemas/ControlNet_Checkpoint_ZImage_Config" + }, { "$ref": "#/components/schemas/ControlNet_Diffusers_SD1_Config" }, @@ -45015,6 +45810,12 @@ { "$ref": "#/components/schemas/Qwen3Encoder_Qwen3Encoder_Config" }, + { + "$ref": "#/components/schemas/Qwen3Encoder_Checkpoint_Config" + }, + { + "$ref": "#/components/schemas/Qwen3Encoder_GGUF_Config" + }, { "$ref": "#/components/schemas/TI_File_SD1_Config" }, @@ -45522,6 +46323,158 @@ "title": "OutputFieldJSONSchemaExtra", "type": "object" }, + "PBRMapsInvocation": { + "category": "image", + "class": "invocation", + "classification": "stable", + "description": "Generate Normal, Displacement and Roughness Map from a given image", + "node_pack": "invokeai", + "properties": { + "board": { + "anyOf": [ + { + "$ref": "#/components/schemas/BoardField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The board to save the image to", + "field_kind": "internal", + "input": "direct", + "orig_required": false, + "ui_hidden": false + }, + "metadata": { + "anyOf": [ + { + "$ref": "#/components/schemas/MetadataField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Optional metadata to be saved with the image", + "field_kind": "internal", + "input": "connection", + "orig_required": false, + "ui_hidden": false + }, + "id": { + "description": "The id of this instance of an invocation. Must be unique among all instances of invocations.", + "field_kind": "node_attribute", + "title": "Id", + "type": "string" + }, + "is_intermediate": { + "default": false, + "description": "Whether or not this is an intermediate invocation.", + "field_kind": "node_attribute", + "input": "direct", + "orig_required": true, + "title": "Is Intermediate", + "type": "boolean", + "ui_hidden": false, + "ui_type": "IsIntermediate" + }, + "use_cache": { + "default": true, + "description": "Whether or not to use the cache", + "field_kind": "node_attribute", + "title": "Use Cache", + "type": "boolean" + }, + "image": { + "anyOf": [ + { + "$ref": "#/components/schemas/ImageField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Input image", + "field_kind": "input", + "input": "any", + "orig_required": true + }, + "tile_size": { + "default": 512, + "description": "Tile size", + "field_kind": "input", + "input": "any", + "orig_default": 512, + "orig_required": false, + "title": "Tile Size", + "type": "integer" + }, + "border_mode": { + "default": "none", + "description": "Border mode to apply to eliminate any artifacts or seams", + "enum": ["none", "seamless", "mirror", "replicate"], + "field_kind": "input", + "input": "any", + "orig_default": "none", + "orig_required": false, + "title": "Border Mode", + "type": "string" + }, + "type": { + "const": "pbr_maps", + "default": "pbr_maps", + "field_kind": "node_attribute", + "title": "type", + "type": "string" + } + }, + "required": ["type", "id"], + "tags": ["image", "material"], + "title": "PBR Maps", + "type": "object", + "version": "1.0.0", + "output": { + "$ref": "#/components/schemas/PBRMapsOutput" + } + }, + "PBRMapsOutput": { + "class": "output", + "properties": { + "normal_map": { + "$ref": "#/components/schemas/ImageField", + "default": null, + "description": "The generated normal map", + "field_kind": "output", + "ui_hidden": false + }, + "roughness_map": { + "$ref": "#/components/schemas/ImageField", + "default": null, + "description": "The generated roughness map", + "field_kind": "output", + "ui_hidden": false + }, + "displacement_map": { + "$ref": "#/components/schemas/ImageField", + "default": null, + "description": "The generated displacement map", + "field_kind": "output", + "ui_hidden": false + }, + "type": { + "const": "pbr_maps-output", + "default": "pbr_maps-output", + "field_kind": "node_attribute", + "title": "type", + "type": "string" + } + }, + "required": ["output_meta", "normal_map", "roughness_map", "displacement_map", "type", "type"], + "title": "PBRMapsOutput", + "type": "object" + }, "PaginatedResults_WorkflowRecordListItemWithThumbnailDTO_": { "properties": { "page": { @@ -45944,6 +46897,121 @@ "title": "ProgressImage", "type": "object" }, + "PromptTemplateInvocation": { + "category": "prompt", + "class": "invocation", + "classification": "stable", + "description": "Applies a Style Preset template to positive and negative prompts.\n\nSelect a Style Preset and provide positive/negative prompts. The node replaces\n{prompt} placeholders in the template with your input prompts.", + "node_pack": "invokeai", + "properties": { + "id": { + "description": "The id of this instance of an invocation. Must be unique among all instances of invocations.", + "field_kind": "node_attribute", + "title": "Id", + "type": "string" + }, + "is_intermediate": { + "default": false, + "description": "Whether or not this is an intermediate invocation.", + "field_kind": "node_attribute", + "input": "direct", + "orig_required": true, + "title": "Is Intermediate", + "type": "boolean", + "ui_hidden": false, + "ui_type": "IsIntermediate" + }, + "use_cache": { + "default": true, + "description": "Whether or not to use the cache", + "field_kind": "node_attribute", + "title": "Use Cache", + "type": "boolean" + }, + "style_preset": { + "anyOf": [ + { + "$ref": "#/components/schemas/StylePresetField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The Style Preset to use as a template", + "field_kind": "input", + "input": "any", + "orig_required": true + }, + "positive_prompt": { + "default": "", + "description": "The positive prompt to insert into the template's {prompt} placeholder", + "field_kind": "input", + "input": "any", + "orig_default": "", + "orig_required": false, + "title": "Positive Prompt", + "type": "string", + "ui_component": "textarea" + }, + "negative_prompt": { + "default": "", + "description": "The negative prompt to insert into the template's {prompt} placeholder", + "field_kind": "input", + "input": "any", + "orig_default": "", + "orig_required": false, + "title": "Negative Prompt", + "type": "string", + "ui_component": "textarea" + }, + "type": { + "const": "prompt_template", + "default": "prompt_template", + "field_kind": "node_attribute", + "title": "type", + "type": "string" + } + }, + "required": ["type", "id"], + "tags": ["prompt", "template", "style", "preset"], + "title": "Prompt Template", + "type": "object", + "version": "1.0.0", + "output": { + "$ref": "#/components/schemas/PromptTemplateOutput" + } + }, + "PromptTemplateOutput": { + "class": "output", + "description": "Output for the Prompt Template node", + "properties": { + "positive_prompt": { + "description": "The positive prompt with the template applied", + "field_kind": "output", + "title": "Positive Prompt", + "type": "string", + "ui_hidden": false + }, + "negative_prompt": { + "description": "The negative prompt with the template applied", + "field_kind": "output", + "title": "Negative Prompt", + "type": "string", + "ui_hidden": false + }, + "type": { + "const": "prompt_template_output", + "default": "prompt_template_output", + "field_kind": "node_attribute", + "title": "type", + "type": "string" + } + }, + "required": ["output_meta", "positive_prompt", "negative_prompt", "type", "type"], + "title": "PromptTemplateOutput", + "type": "object" + }, "PromptsFromFileInvocation": { "category": "prompt", "class": "invocation", @@ -46313,6 +47381,278 @@ "title": "Qwen3EncoderField", "type": "object" }, + "Qwen3Encoder_Checkpoint_Config": { + "properties": { + "key": { + "type": "string", + "title": "Key", + "description": "A unique key for this model." + }, + "hash": { + "type": "string", + "title": "Hash", + "description": "The hash of the model file(s)." + }, + "path": { + "type": "string", + "title": "Path", + "description": "Path to the model on the filesystem. Relative paths are relative to the Invoke root directory." + }, + "file_size": { + "type": "integer", + "title": "File Size", + "description": "The size of the model in bytes." + }, + "name": { + "type": "string", + "title": "Name", + "description": "Name of the model." + }, + "description": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Description", + "description": "Model description" + }, + "source": { + "type": "string", + "title": "Source", + "description": "The original source of the model (path, URL or repo_id)." + }, + "source_type": { + "$ref": "#/components/schemas/ModelSourceType", + "description": "The type of source" + }, + "source_api_response": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Source Api Response", + "description": "The original API response from the source, as stringified JSON." + }, + "cover_image": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Cover Image", + "description": "Url for image to preview model" + }, + "config_path": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Config Path", + "description": "Path to the config for this model, if any." + }, + "base": { + "type": "string", + "const": "any", + "title": "Base", + "default": "any" + }, + "type": { + "type": "string", + "const": "qwen3_encoder", + "title": "Type", + "default": "qwen3_encoder" + }, + "format": { + "type": "string", + "const": "checkpoint", + "title": "Format", + "default": "checkpoint" + }, + "cpu_only": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ], + "title": "Cpu Only", + "description": "Whether this model should run on CPU only" + } + }, + "type": "object", + "required": [ + "key", + "hash", + "path", + "file_size", + "name", + "description", + "source", + "source_type", + "source_api_response", + "cover_image", + "config_path", + "base", + "type", + "format", + "cpu_only" + ], + "title": "Qwen3Encoder_Checkpoint_Config", + "description": "Configuration for single-file Qwen3 Encoder models (safetensors)." + }, + "Qwen3Encoder_GGUF_Config": { + "properties": { + "key": { + "type": "string", + "title": "Key", + "description": "A unique key for this model." + }, + "hash": { + "type": "string", + "title": "Hash", + "description": "The hash of the model file(s)." + }, + "path": { + "type": "string", + "title": "Path", + "description": "Path to the model on the filesystem. Relative paths are relative to the Invoke root directory." + }, + "file_size": { + "type": "integer", + "title": "File Size", + "description": "The size of the model in bytes." + }, + "name": { + "type": "string", + "title": "Name", + "description": "Name of the model." + }, + "description": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Description", + "description": "Model description" + }, + "source": { + "type": "string", + "title": "Source", + "description": "The original source of the model (path, URL or repo_id)." + }, + "source_type": { + "$ref": "#/components/schemas/ModelSourceType", + "description": "The type of source" + }, + "source_api_response": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Source Api Response", + "description": "The original API response from the source, as stringified JSON." + }, + "cover_image": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Cover Image", + "description": "Url for image to preview model" + }, + "config_path": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Config Path", + "description": "Path to the config for this model, if any." + }, + "base": { + "type": "string", + "const": "any", + "title": "Base", + "default": "any" + }, + "type": { + "type": "string", + "const": "qwen3_encoder", + "title": "Type", + "default": "qwen3_encoder" + }, + "format": { + "type": "string", + "const": "gguf_quantized", + "title": "Format", + "default": "gguf_quantized" + }, + "cpu_only": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ], + "title": "Cpu Only", + "description": "Whether this model should run on CPU only" + } + }, + "type": "object", + "required": [ + "key", + "hash", + "path", + "file_size", + "name", + "description", + "source", + "source_type", + "source_api_response", + "cover_image", + "config_path", + "base", + "type", + "format", + "cpu_only" + ], + "title": "Qwen3Encoder_GGUF_Config", + "description": "Configuration for GGUF-quantized Qwen3 Encoder models." + }, "Qwen3Encoder_Qwen3Encoder_Config": { "properties": { "key": { @@ -46402,6 +47742,18 @@ "const": "qwen3_encoder", "title": "Format", "default": "qwen3_encoder" + }, + "cpu_only": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ], + "title": "Cpu Only", + "description": "Whether this model should run on CPU only" } }, "type": "object", @@ -46418,7 +47770,8 @@ "cover_image", "base", "type", - "format" + "format", + "cpu_only" ], "title": "Qwen3Encoder_Qwen3Encoder_Config", "description": "Configuration for Qwen3 Encoder models in a diffusers-like format.\n\nThe model weights are expected to be in a folder called text_encoder inside the model directory,\ncompatible with Qwen2VLForConditionalGeneration or similar architectures used by Z-Image." @@ -50105,6 +51458,18 @@ "const": "any", "title": "Base", "default": "any" + }, + "cpu_only": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ], + "title": "Cpu Only", + "description": "Whether this model should run on CPU only" } }, "type": "object", @@ -50122,7 +51487,8 @@ "format", "repo_variant", "type", - "base" + "base", + "cpu_only" ], "title": "SigLIP_Diffusers_Config", "description": "Model config for SigLIP." @@ -51440,6 +52806,19 @@ "$ref": "#/components/schemas/StringPosNegOutput" } }, + "StylePresetField": { + "description": "A style preset primitive field", + "properties": { + "style_preset_id": { + "description": "The id of the style preset", + "title": "Style Preset Id", + "type": "string" + } + }, + "required": ["style_preset_id"], + "title": "StylePresetField", + "type": "object" + }, "StylePresetRecordWithImage": { "properties": { "name": { @@ -51948,162 +53327,308 @@ "title": "Cover Image", "description": "Url for image to preview model" }, - "format": { - "type": "string", - "const": "diffusers", - "title": "Format", - "default": "diffusers" - }, - "repo_variant": { - "$ref": "#/components/schemas/ModelRepoVariant", - "default": "" - }, - "type": { - "type": "string", - "const": "t2i_adapter", - "title": "Type", - "default": "t2i_adapter" - }, - "default_settings": { - "anyOf": [ - { - "$ref": "#/components/schemas/ControlAdapterDefaultSettings" - }, - { - "type": "null" - } - ] - }, + "format": { + "type": "string", + "const": "diffusers", + "title": "Format", + "default": "diffusers" + }, + "repo_variant": { + "$ref": "#/components/schemas/ModelRepoVariant", + "default": "" + }, + "type": { + "type": "string", + "const": "t2i_adapter", + "title": "Type", + "default": "t2i_adapter" + }, + "default_settings": { + "anyOf": [ + { + "$ref": "#/components/schemas/ControlAdapterDefaultSettings" + }, + { + "type": "null" + } + ] + }, + "base": { + "type": "string", + "const": "sd-1", + "title": "Base", + "default": "sd-1" + } + }, + "type": "object", + "required": [ + "key", + "hash", + "path", + "file_size", + "name", + "description", + "source", + "source_type", + "source_api_response", + "cover_image", + "format", + "repo_variant", + "type", + "default_settings", + "base" + ], + "title": "T2IAdapter_Diffusers_SD1_Config" + }, + "T2IAdapter_Diffusers_SDXL_Config": { + "properties": { + "key": { + "type": "string", + "title": "Key", + "description": "A unique key for this model." + }, + "hash": { + "type": "string", + "title": "Hash", + "description": "The hash of the model file(s)." + }, + "path": { + "type": "string", + "title": "Path", + "description": "Path to the model on the filesystem. Relative paths are relative to the Invoke root directory." + }, + "file_size": { + "type": "integer", + "title": "File Size", + "description": "The size of the model in bytes." + }, + "name": { + "type": "string", + "title": "Name", + "description": "Name of the model." + }, + "description": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Description", + "description": "Model description" + }, + "source": { + "type": "string", + "title": "Source", + "description": "The original source of the model (path, URL or repo_id)." + }, + "source_type": { + "$ref": "#/components/schemas/ModelSourceType", + "description": "The type of source" + }, + "source_api_response": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Source Api Response", + "description": "The original API response from the source, as stringified JSON." + }, + "cover_image": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Cover Image", + "description": "Url for image to preview model" + }, + "format": { + "type": "string", + "const": "diffusers", + "title": "Format", + "default": "diffusers" + }, + "repo_variant": { + "$ref": "#/components/schemas/ModelRepoVariant", + "default": "" + }, + "type": { + "type": "string", + "const": "t2i_adapter", + "title": "Type", + "default": "t2i_adapter" + }, + "default_settings": { + "anyOf": [ + { + "$ref": "#/components/schemas/ControlAdapterDefaultSettings" + }, + { + "type": "null" + } + ] + }, + "base": { + "type": "string", + "const": "sdxl", + "title": "Base", + "default": "sdxl" + } + }, + "type": "object", + "required": [ + "key", + "hash", + "path", + "file_size", + "name", + "description", + "source", + "source_type", + "source_api_response", + "cover_image", + "format", + "repo_variant", + "type", + "default_settings", + "base" + ], + "title": "T2IAdapter_Diffusers_SDXL_Config" + }, + "T5EncoderField": { + "properties": { + "tokenizer": { + "$ref": "#/components/schemas/ModelIdentifierField", + "description": "Info to load tokenizer submodel" + }, + "text_encoder": { + "$ref": "#/components/schemas/ModelIdentifierField", + "description": "Info to load text_encoder submodel" + }, + "loras": { + "description": "LoRAs to apply on model loading", + "items": { + "$ref": "#/components/schemas/LoRAField" + }, + "title": "Loras", + "type": "array" + } + }, + "required": ["tokenizer", "text_encoder", "loras"], + "title": "T5EncoderField", + "type": "object" + }, + "T5Encoder_BnBLLMint8_Config": { + "properties": { + "key": { + "type": "string", + "title": "Key", + "description": "A unique key for this model." + }, + "hash": { + "type": "string", + "title": "Hash", + "description": "The hash of the model file(s)." + }, + "path": { + "type": "string", + "title": "Path", + "description": "Path to the model on the filesystem. Relative paths are relative to the Invoke root directory." + }, + "file_size": { + "type": "integer", + "title": "File Size", + "description": "The size of the model in bytes." + }, + "name": { + "type": "string", + "title": "Name", + "description": "Name of the model." + }, + "description": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Description", + "description": "Model description" + }, + "source": { + "type": "string", + "title": "Source", + "description": "The original source of the model (path, URL or repo_id)." + }, + "source_type": { + "$ref": "#/components/schemas/ModelSourceType", + "description": "The type of source" + }, + "source_api_response": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Source Api Response", + "description": "The original API response from the source, as stringified JSON." + }, + "cover_image": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Cover Image", + "description": "Url for image to preview model" + }, "base": { "type": "string", - "const": "sd-1", + "const": "any", "title": "Base", - "default": "sd-1" - } - }, - "type": "object", - "required": [ - "key", - "hash", - "path", - "file_size", - "name", - "description", - "source", - "source_type", - "source_api_response", - "cover_image", - "format", - "repo_variant", - "type", - "default_settings", - "base" - ], - "title": "T2IAdapter_Diffusers_SD1_Config" - }, - "T2IAdapter_Diffusers_SDXL_Config": { - "properties": { - "key": { - "type": "string", - "title": "Key", - "description": "A unique key for this model." - }, - "hash": { - "type": "string", - "title": "Hash", - "description": "The hash of the model file(s)." - }, - "path": { - "type": "string", - "title": "Path", - "description": "Path to the model on the filesystem. Relative paths are relative to the Invoke root directory." - }, - "file_size": { - "type": "integer", - "title": "File Size", - "description": "The size of the model in bytes." - }, - "name": { - "type": "string", - "title": "Name", - "description": "Name of the model." - }, - "description": { - "anyOf": [ - { - "type": "string" - }, - { - "type": "null" - } - ], - "title": "Description", - "description": "Model description" + "default": "any" }, - "source": { + "type": { "type": "string", - "title": "Source", - "description": "The original source of the model (path, URL or repo_id)." - }, - "source_type": { - "$ref": "#/components/schemas/ModelSourceType", - "description": "The type of source" - }, - "source_api_response": { - "anyOf": [ - { - "type": "string" - }, - { - "type": "null" - } - ], - "title": "Source Api Response", - "description": "The original API response from the source, as stringified JSON." - }, - "cover_image": { - "anyOf": [ - { - "type": "string" - }, - { - "type": "null" - } - ], - "title": "Cover Image", - "description": "Url for image to preview model" + "const": "t5_encoder", + "title": "Type", + "default": "t5_encoder" }, "format": { "type": "string", - "const": "diffusers", + "const": "bnb_quantized_int8b", "title": "Format", - "default": "diffusers" - }, - "repo_variant": { - "$ref": "#/components/schemas/ModelRepoVariant", - "default": "" - }, - "type": { - "type": "string", - "const": "t2i_adapter", - "title": "Type", - "default": "t2i_adapter" + "default": "bnb_quantized_int8b" }, - "default_settings": { + "cpu_only": { "anyOf": [ { - "$ref": "#/components/schemas/ControlAdapterDefaultSettings" + "type": "boolean" }, { "type": "null" } - ] - }, - "base": { - "type": "string", - "const": "sdxl", - "title": "Base", - "default": "sdxl" + ], + "title": "Cpu Only", + "description": "Whether this model should run on CPU only" } }, "type": "object", @@ -52118,38 +53643,15 @@ "source_type", "source_api_response", "cover_image", - "format", - "repo_variant", + "base", "type", - "default_settings", - "base" + "format", + "cpu_only" ], - "title": "T2IAdapter_Diffusers_SDXL_Config" - }, - "T5EncoderField": { - "properties": { - "tokenizer": { - "$ref": "#/components/schemas/ModelIdentifierField", - "description": "Info to load tokenizer submodel" - }, - "text_encoder": { - "$ref": "#/components/schemas/ModelIdentifierField", - "description": "Info to load text_encoder submodel" - }, - "loras": { - "description": "LoRAs to apply on model loading", - "items": { - "$ref": "#/components/schemas/LoRAField" - }, - "title": "Loras", - "type": "array" - } - }, - "required": ["tokenizer", "text_encoder", "loras"], - "title": "T5EncoderField", - "type": "object" + "title": "T5Encoder_BnBLLMint8_Config", + "description": "Configuration for T5 Encoder models quantized by bitsandbytes' LLM.int8." }, - "T5Encoder_BnBLLMint8_Config": { + "T5Encoder_T5Encoder_Config": { "properties": { "key": { "type": "string", @@ -52235,119 +53737,21 @@ }, "format": { "type": "string", - "const": "bnb_quantized_int8b", + "const": "t5_encoder", "title": "Format", - "default": "bnb_quantized_int8b" - } - }, - "type": "object", - "required": [ - "key", - "hash", - "path", - "file_size", - "name", - "description", - "source", - "source_type", - "source_api_response", - "cover_image", - "base", - "type", - "format" - ], - "title": "T5Encoder_BnBLLMint8_Config", - "description": "Configuration for T5 Encoder models quantized by bitsandbytes' LLM.int8." - }, - "T5Encoder_T5Encoder_Config": { - "properties": { - "key": { - "type": "string", - "title": "Key", - "description": "A unique key for this model." - }, - "hash": { - "type": "string", - "title": "Hash", - "description": "The hash of the model file(s)." - }, - "path": { - "type": "string", - "title": "Path", - "description": "Path to the model on the filesystem. Relative paths are relative to the Invoke root directory." - }, - "file_size": { - "type": "integer", - "title": "File Size", - "description": "The size of the model in bytes." - }, - "name": { - "type": "string", - "title": "Name", - "description": "Name of the model." - }, - "description": { - "anyOf": [ - { - "type": "string" - }, - { - "type": "null" - } - ], - "title": "Description", - "description": "Model description" - }, - "source": { - "type": "string", - "title": "Source", - "description": "The original source of the model (path, URL or repo_id)." - }, - "source_type": { - "$ref": "#/components/schemas/ModelSourceType", - "description": "The type of source" - }, - "source_api_response": { - "anyOf": [ - { - "type": "string" - }, - { - "type": "null" - } - ], - "title": "Source Api Response", - "description": "The original API response from the source, as stringified JSON." + "default": "t5_encoder" }, - "cover_image": { + "cpu_only": { "anyOf": [ { - "type": "string" + "type": "boolean" }, { "type": "null" } ], - "title": "Cover Image", - "description": "Url for image to preview model" - }, - "base": { - "type": "string", - "const": "any", - "title": "Base", - "default": "any" - }, - "type": { - "type": "string", - "const": "t5_encoder", - "title": "Type", - "default": "t5_encoder" - }, - "format": { - "type": "string", - "const": "t5_encoder", - "title": "Format", - "default": "t5_encoder" + "title": "Cpu Only", + "description": "Whether this model should run on CPU only" } }, "type": "object", @@ -52364,7 +53768,8 @@ "cover_image", "base", "type", - "format" + "format", + "cpu_only" ], "title": "T5Encoder_T5Encoder_Config", "description": "Configuration for T5 Encoder models in a bespoke, diffusers-like format. The model weights are expected to be in\na folder called text_encoder_2 inside the model directory, with a config file named model.safetensors.index.json." @@ -55470,45 +56875,193 @@ "title": "ZImageConditioningOutput", "type": "object" }, - "ZImageDenoiseInvocation": { - "category": "image", + "ZImageControlField": { + "description": "A Z-Image control conditioning field for spatial control (Canny, HED, Depth, Pose, MLSD).", + "properties": { + "image_name": { + "description": "The name of the preprocessed control image", + "title": "Image Name", + "type": "string" + }, + "control_model": { + "$ref": "#/components/schemas/ModelIdentifierField", + "description": "The Z-Image ControlNet adapter model" + }, + "control_context_scale": { + "default": 0.75, + "description": "The strength of the control signal. Recommended range: 0.65-0.80.", + "maximum": 2.0, + "minimum": 0.0, + "title": "Control Context Scale", + "type": "number" + }, + "begin_step_percent": { + "default": 0.0, + "description": "When the control is first applied (% of total steps)", + "maximum": 1.0, + "minimum": 0.0, + "title": "Begin Step Percent", + "type": "number" + }, + "end_step_percent": { + "default": 1.0, + "description": "When the control is last applied (% of total steps)", + "maximum": 1.0, + "minimum": 0.0, + "title": "End Step Percent", + "type": "number" + } + }, + "required": ["image_name", "control_model"], + "title": "ZImageControlField", + "type": "object" + }, + "ZImageControlInvocation": { + "category": "control", "class": "invocation", "classification": "prototype", - "description": "Run the denoising process with a Z-Image model.\n\nSupports regional prompting by connecting multiple conditioning inputs with masks.", + "description": "Configure Z-Image ControlNet for spatial conditioning.\n\nTakes a preprocessed control image (e.g., Canny edges, depth map, pose)\nand a Z-Image ControlNet adapter model to enable spatial control.\n\nSupports 5 control modes: Canny, HED, Depth, Pose, MLSD.\nRecommended control_context_scale: 0.65-0.80.", "node_pack": "invokeai", "properties": { - "board": { + "id": { + "description": "The id of this instance of an invocation. Must be unique among all instances of invocations.", + "field_kind": "node_attribute", + "title": "Id", + "type": "string" + }, + "is_intermediate": { + "default": false, + "description": "Whether or not this is an intermediate invocation.", + "field_kind": "node_attribute", + "input": "direct", + "orig_required": true, + "title": "Is Intermediate", + "type": "boolean", + "ui_hidden": false, + "ui_type": "IsIntermediate" + }, + "use_cache": { + "default": true, + "description": "Whether or not to use the cache", + "field_kind": "node_attribute", + "title": "Use Cache", + "type": "boolean" + }, + "image": { "anyOf": [ { - "$ref": "#/components/schemas/BoardField" + "$ref": "#/components/schemas/ImageField" }, { "type": "null" } ], "default": null, - "description": "The board to save the image to", - "field_kind": "internal", - "input": "direct", - "orig_required": false, - "ui_hidden": false + "description": "The preprocessed control image (Canny, HED, Depth, Pose, or MLSD)", + "field_kind": "input", + "input": "any", + "orig_required": true }, - "metadata": { + "control_model": { "anyOf": [ { - "$ref": "#/components/schemas/MetadataField" + "$ref": "#/components/schemas/ModelIdentifierField" }, { "type": "null" } ], "default": null, - "description": "Optional metadata to be saved with the image", - "field_kind": "internal", - "input": "connection", + "description": "ControlNet model to load", + "field_kind": "input", + "input": "any", + "orig_required": true, + "title": "Control Model", + "ui_model_base": ["z-image"], + "ui_model_type": ["controlnet"] + }, + "control_context_scale": { + "default": 0.75, + "description": "Strength of the control signal. Recommended range: 0.65-0.80.", + "field_kind": "input", + "input": "any", + "maximum": 2.0, + "minimum": 0.0, + "orig_default": 0.75, "orig_required": false, + "title": "Control Scale", + "type": "number" + }, + "begin_step_percent": { + "default": 0.0, + "description": "When the control is first applied (% of total steps)", + "field_kind": "input", + "input": "any", + "maximum": 1.0, + "minimum": 0.0, + "orig_default": 0.0, + "orig_required": false, + "title": "Begin Step Percent", + "type": "number" + }, + "end_step_percent": { + "default": 1.0, + "description": "When the control is last applied (% of total steps)", + "field_kind": "input", + "input": "any", + "maximum": 1.0, + "minimum": 0.0, + "orig_default": 1.0, + "orig_required": false, + "title": "End Step Percent", + "type": "number" + }, + "type": { + "const": "z_image_control", + "default": "z_image_control", + "field_kind": "node_attribute", + "title": "type", + "type": "string" + } + }, + "required": ["type", "id"], + "tags": ["image", "z-image", "control", "controlnet"], + "title": "Z-Image ControlNet", + "type": "object", + "version": "1.1.0", + "output": { + "$ref": "#/components/schemas/ZImageControlOutput" + } + }, + "ZImageControlOutput": { + "class": "output", + "description": "Z-Image Control output containing control configuration.", + "properties": { + "control": { + "$ref": "#/components/schemas/ZImageControlField", + "description": "Z-Image control conditioning", + "field_kind": "output", "ui_hidden": false }, + "type": { + "const": "z_image_control_output", + "default": "z_image_control_output", + "field_kind": "node_attribute", + "title": "type", + "type": "string" + } + }, + "required": ["output_meta", "control", "type", "type"], + "title": "ZImageControlOutput", + "type": "object" + }, + "ZImageDenoiseInvocation": { + "category": "image", + "class": "invocation", + "classification": "prototype", + "description": "Run the denoising process with a Z-Image model.\n\nSupports regional prompting by connecting multiple conditioning inputs with masks.", + "node_pack": "invokeai", + "properties": { "id": { "description": "The id of this instance of an invocation. Must be unique among all instances of invocations.", "field_kind": "node_attribute", @@ -55589,6 +57142,16 @@ "title": "Denoising End", "type": "number" }, + "add_noise": { + "default": true, + "description": "Add noise based on denoising start.", + "field_kind": "input", + "input": "any", + "orig_default": true, + "orig_required": false, + "title": "Add Noise", + "type": "boolean" + }, "transformer": { "anyOf": [ { @@ -55651,12 +57214,12 @@ "title": "Negative Conditioning" }, "guidance_scale": { - "default": 0.0, - "description": "Guidance scale for classifier-free guidance. Use 0.0 for Z-Image-Turbo.", + "default": 1.0, + "description": "Guidance scale for classifier-free guidance. 1.0 = no CFG (recommended for Z-Image-Turbo). Values > 1.0 amplify guidance.", "field_kind": "input", "input": "any", - "minimum": 0.0, - "orig_default": 0.0, + "minimum": 1.0, + "orig_default": 1.0, "orig_required": false, "title": "Guidance Scale", "type": "number" @@ -55704,6 +57267,54 @@ "title": "Seed", "type": "integer" }, + "control": { + "anyOf": [ + { + "$ref": "#/components/schemas/ZImageControlField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Z-Image control conditioning for spatial control (Canny, HED, Depth, Pose, MLSD).", + "field_kind": "input", + "input": "connection", + "orig_default": null, + "orig_required": false + }, + "vae": { + "anyOf": [ + { + "$ref": "#/components/schemas/VAEField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "VAE Required for control conditioning.", + "field_kind": "input", + "input": "connection", + "orig_default": null, + "orig_required": false + }, + "scheduler": { + "default": "euler", + "description": "Scheduler (sampler) for the denoising process. Euler is the default and recommended for Z-Image-Turbo. Heun is 2nd-order (better quality, 2x slower). LCM is optimized for few steps.", + "enum": ["euler", "heun", "lcm"], + "field_kind": "input", + "input": "any", + "orig_default": "euler", + "orig_required": false, + "title": "Scheduler", + "type": "string", + "ui_choice_labels": { + "euler": "Euler", + "heun": "Heun (2nd order)", + "lcm": "LCM" + } + }, "type": { "const": "z_image_denoise", "default": "z_image_denoise", @@ -55716,11 +57327,304 @@ "tags": ["image", "z-image"], "title": "Denoise - Z-Image", "type": "object", - "version": "1.2.0", + "version": "1.4.0", "output": { "$ref": "#/components/schemas/LatentsOutput" } }, + "ZImageDenoiseMetaInvocation": { + "category": "latents", + "class": "invocation", + "classification": "stable", + "description": "Run denoising process with a Z-Image transformer model + metadata.", + "node_pack": "invokeai", + "properties": { + "metadata": { + "anyOf": [ + { + "$ref": "#/components/schemas/MetadataField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Optional metadata to be saved with the image", + "field_kind": "internal", + "input": "connection", + "orig_required": false, + "ui_hidden": false + }, + "id": { + "description": "The id of this instance of an invocation. Must be unique among all instances of invocations.", + "field_kind": "node_attribute", + "title": "Id", + "type": "string" + }, + "is_intermediate": { + "default": false, + "description": "Whether or not this is an intermediate invocation.", + "field_kind": "node_attribute", + "input": "direct", + "orig_required": true, + "title": "Is Intermediate", + "type": "boolean", + "ui_hidden": false, + "ui_type": "IsIntermediate" + }, + "use_cache": { + "default": true, + "description": "Whether or not to use the cache", + "field_kind": "node_attribute", + "title": "Use Cache", + "type": "boolean" + }, + "latents": { + "anyOf": [ + { + "$ref": "#/components/schemas/LatentsField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Latents tensor", + "field_kind": "input", + "input": "connection", + "orig_default": null, + "orig_required": false + }, + "denoise_mask": { + "anyOf": [ + { + "$ref": "#/components/schemas/DenoiseMaskField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "A mask of the region to apply the denoising process to. Values of 0.0 represent the regions to be fully denoised, and 1.0 represent the regions to be preserved.", + "field_kind": "input", + "input": "connection", + "orig_default": null, + "orig_required": false + }, + "denoising_start": { + "default": 0.0, + "description": "When to start denoising, expressed a percentage of total steps", + "field_kind": "input", + "input": "any", + "maximum": 1, + "minimum": 0, + "orig_default": 0.0, + "orig_required": false, + "title": "Denoising Start", + "type": "number" + }, + "denoising_end": { + "default": 1.0, + "description": "When to stop denoising, expressed a percentage of total steps", + "field_kind": "input", + "input": "any", + "maximum": 1, + "minimum": 0, + "orig_default": 1.0, + "orig_required": false, + "title": "Denoising End", + "type": "number" + }, + "add_noise": { + "default": true, + "description": "Add noise based on denoising start.", + "field_kind": "input", + "input": "any", + "orig_default": true, + "orig_required": false, + "title": "Add Noise", + "type": "boolean" + }, + "transformer": { + "anyOf": [ + { + "$ref": "#/components/schemas/TransformerField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Z-Image model (Transformer) to load", + "field_kind": "input", + "input": "connection", + "orig_required": true, + "title": "Transformer" + }, + "positive_conditioning": { + "anyOf": [ + { + "$ref": "#/components/schemas/ZImageConditioningField" + }, + { + "items": { + "$ref": "#/components/schemas/ZImageConditioningField" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Positive conditioning tensor", + "field_kind": "input", + "input": "connection", + "orig_required": true, + "title": "Positive Conditioning" + }, + "negative_conditioning": { + "anyOf": [ + { + "$ref": "#/components/schemas/ZImageConditioningField" + }, + { + "items": { + "$ref": "#/components/schemas/ZImageConditioningField" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Negative conditioning tensor", + "field_kind": "input", + "input": "connection", + "orig_default": null, + "orig_required": false, + "title": "Negative Conditioning" + }, + "guidance_scale": { + "default": 1.0, + "description": "Guidance scale for classifier-free guidance. 1.0 = no CFG (recommended for Z-Image-Turbo). Values > 1.0 amplify guidance.", + "field_kind": "input", + "input": "any", + "minimum": 1.0, + "orig_default": 1.0, + "orig_required": false, + "title": "Guidance Scale", + "type": "number" + }, + "width": { + "default": 1024, + "description": "Width of the generated image.", + "field_kind": "input", + "input": "any", + "multipleOf": 16, + "orig_default": 1024, + "orig_required": false, + "title": "Width", + "type": "integer" + }, + "height": { + "default": 1024, + "description": "Height of the generated image.", + "field_kind": "input", + "input": "any", + "multipleOf": 16, + "orig_default": 1024, + "orig_required": false, + "title": "Height", + "type": "integer" + }, + "steps": { + "default": 8, + "description": "Number of denoising steps. 8 recommended for Z-Image-Turbo.", + "exclusiveMinimum": 0, + "field_kind": "input", + "input": "any", + "orig_default": 8, + "orig_required": false, + "title": "Steps", + "type": "integer" + }, + "seed": { + "default": 0, + "description": "Randomness seed for reproducibility.", + "field_kind": "input", + "input": "any", + "orig_default": 0, + "orig_required": false, + "title": "Seed", + "type": "integer" + }, + "control": { + "anyOf": [ + { + "$ref": "#/components/schemas/ZImageControlField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Z-Image control conditioning for spatial control (Canny, HED, Depth, Pose, MLSD).", + "field_kind": "input", + "input": "connection", + "orig_default": null, + "orig_required": false + }, + "vae": { + "anyOf": [ + { + "$ref": "#/components/schemas/VAEField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "VAE Required for control conditioning.", + "field_kind": "input", + "input": "connection", + "orig_default": null, + "orig_required": false + }, + "scheduler": { + "default": "euler", + "description": "Scheduler (sampler) for the denoising process. Euler is the default and recommended for Z-Image-Turbo. Heun is 2nd-order (better quality, 2x slower). LCM is optimized for few steps.", + "enum": ["euler", "heun", "lcm"], + "field_kind": "input", + "input": "any", + "orig_default": "euler", + "orig_required": false, + "title": "Scheduler", + "type": "string", + "ui_choice_labels": { + "euler": "Euler", + "heun": "Heun (2nd order)", + "lcm": "LCM" + } + }, + "type": { + "const": "z_image_denoise_meta", + "default": "z_image_denoise_meta", + "field_kind": "node_attribute", + "title": "type", + "type": "string" + } + }, + "required": ["type", "id"], + "tags": ["z-image", "latents", "denoise", "txt2img", "t2i", "t2l", "img2img", "i2i", "l2l"], + "title": "Denoise - Z-Image + Metadata", + "type": "object", + "version": "1.0.0", + "output": { + "$ref": "#/components/schemas/LatentsMetaOutput" + } + }, "ZImageImageToLatentsInvocation": { "category": "image", "class": "invocation", @@ -56354,6 +58258,105 @@ "title": "ZImageModelLoaderOutput", "type": "object" }, + "ZImageSeedVarianceEnhancerInvocation": { + "category": "conditioning", + "class": "invocation", + "classification": "prototype", + "description": "Adds seed-based noise to Z-Image conditioning to increase variance between seeds.\n\nZ-Image-Turbo can produce relatively similar images with different seeds,\nmaking it harder to explore variations of a prompt. This node implements\nreproducible, seed-based noise injection into text embeddings to increase\nvisual variation while maintaining reproducibility.\n\nThe noise strength is auto-calibrated relative to the embedding's standard\ndeviation, ensuring consistent results across different prompts.", + "node_pack": "invokeai", + "properties": { + "id": { + "description": "The id of this instance of an invocation. Must be unique among all instances of invocations.", + "field_kind": "node_attribute", + "title": "Id", + "type": "string" + }, + "is_intermediate": { + "default": false, + "description": "Whether or not this is an intermediate invocation.", + "field_kind": "node_attribute", + "input": "direct", + "orig_required": true, + "title": "Is Intermediate", + "type": "boolean", + "ui_hidden": false, + "ui_type": "IsIntermediate" + }, + "use_cache": { + "default": true, + "description": "Whether or not to use the cache", + "field_kind": "node_attribute", + "title": "Use Cache", + "type": "boolean" + }, + "conditioning": { + "anyOf": [ + { + "$ref": "#/components/schemas/ZImageConditioningField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Conditioning tensor", + "field_kind": "input", + "input": "connection", + "orig_required": true, + "title": "Conditioning" + }, + "seed": { + "default": 0, + "description": "Seed for reproducible noise generation. Different seeds produce different noise patterns.", + "field_kind": "input", + "input": "any", + "minimum": 0, + "orig_default": 0, + "orig_required": false, + "title": "Seed", + "type": "integer" + }, + "strength": { + "default": 0.1, + "description": "Noise strength as multiplier of embedding std. 0=off, 0.1=subtle, 0.5=strong.", + "field_kind": "input", + "input": "any", + "maximum": 2.0, + "minimum": 0.0, + "orig_default": 0.1, + "orig_required": false, + "title": "Strength", + "type": "number" + }, + "randomize_percent": { + "default": 50.0, + "description": "Percentage of embedding values to add noise to (1-100). Lower values create more selective noise patterns.", + "field_kind": "input", + "input": "any", + "maximum": 100.0, + "minimum": 1.0, + "orig_default": 50.0, + "orig_required": false, + "title": "Randomize Percent", + "type": "number" + }, + "type": { + "const": "z_image_seed_variance_enhancer", + "default": "z_image_seed_variance_enhancer", + "field_kind": "node_attribute", + "title": "type", + "type": "string" + } + }, + "required": ["type", "id"], + "tags": ["conditioning", "z-image", "variance", "seed"], + "title": "Seed Variance Enhancer - Z-Image", + "type": "object", + "version": "1.0.0", + "output": { + "$ref": "#/components/schemas/ZImageConditioningOutput" + } + }, "ZImageTextEncoderInvocation": { "category": "conditioning", "class": "invocation", diff --git a/invokeai/frontend/web/package-lock.json b/invokeai/frontend/web/package-lock.json new file mode 100644 index 00000000000..f387a54f6a5 --- /dev/null +++ b/invokeai/frontend/web/package-lock.json @@ -0,0 +1,13062 @@ +{ + 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"sha512-CHOUy7mu3lbD6o6LJLfllpjkzhHXSBlX8B9+qPddUsIfeF5S/UZ5q0kmCsnRqT1UHFQZchNFDDzMbQsuesHWlw==", + "license": "MIT", + "dependencies": { + "use-sync-external-store": "^1.2.2" + }, + "engines": { + "node": ">=12.7.0" + }, + "peerDependencies": { + "@types/react": ">=16.8", + "immer": ">=9.0.6", + "react": ">=16.8" + }, + "peerDependenciesMeta": { + "@types/react": { + "optional": true + }, + "immer": { + "optional": true + }, + "react": { + "optional": true + } + } + } + } +} diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json index 5bdd7ba08ee..de6a0a39920 100644 --- a/invokeai/frontend/web/public/locales/en.json +++ b/invokeai/frontend/web/public/locales/en.json @@ -906,6 +906,8 @@ "convertToDiffusersHelpText4": "This is a one time process only. It might take around 30s-60s depending on the specifications of your computer.", "convertToDiffusersHelpText5": "Please make sure you have enough disk space. Models generally vary between 2GB-7GB in size.", "convertToDiffusersHelpText6": "Do you wish to convert this model?", + "cpuOnly": "CPU Only", + "runOnCpu": "Run text encoder model on CPU only", "noDefaultSettings": "No default settings configured for this model. Visit the Model Manager to add default settings.", "defaultSettings": "Default Settings", "defaultSettingsSaved": "Default Settings Saved", @@ -1567,8 +1569,6 @@ "problemUnpublishingWorkflow": "Problem Unpublishing Workflow", "problemUnpublishingWorkflowDescription": "There was a problem unpublishing the workflow. Please try again.", "workflowUnpublished": "Workflow Unpublished", - "sentToCanvas": "Sent to Canvas", - "sentToUpscale": "Sent to Upscale", "promptGenerationStarted": "Prompt generation started", "uploadAndPromptGenerationFailed": "Failed to upload image and generate prompt", "promptExpansionFailed": "We ran into an issue. Please try prompt expansion again.", @@ -1997,6 +1997,13 @@ "paragraphs": [ "Enable 'Optimized Image-to-Image' for a more gradual Denoise Strength scale for image-to-image and inpainting transformations with Flux models. This setting improves the ability to control the amount of change applied to an image, but may be turned off if you prefer to use the standard Denoise Strength scale. This setting is still being tuned and is in beta status." ] + }, + "cpuOnly": { + "heading": "CPU Only", + "paragraphs": [ + "When enabled, only the text encoder component will run on CPU instead of GPU.", + "This saves VRAM for the denoiser while only slightly impacting performance. The conditioning outputs are automatically moved to GPU for the denoiser." + ] } }, "workflows": { @@ -2722,7 +2729,6 @@ "selectPreset": "Select Style Preset", "noMatchingPresets": "No matching presets" }, - "ui": { "tabs": { "generate": "Generate", diff --git a/invokeai/frontend/web/src/app/store/nanostores/util.ts b/invokeai/frontend/web/src/app/store/nanostores/util.ts index a5a75ae8e5b..6797996b217 100644 --- a/invokeai/frontend/web/src/app/store/nanostores/util.ts +++ b/invokeai/frontend/web/src/app/store/nanostores/util.ts @@ -5,7 +5,6 @@ import { atom } from 'nanostores'; * A fallback non-writable atom that always returns `false`, used when a nanostores atom is only conditionally available * in a hook or component. * - * @knipignore */ export const $false: ReadableAtom = atom(false); /** diff --git a/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts b/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts index fc045356e0c..5c48c3c9979 100644 --- a/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts +++ b/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts @@ -73,7 +73,8 @@ export type Feature = | 'tileSize' | 'tileOverlap' | 'optimizedDenoising' - | 'fluxDevLicense'; + | 'fluxDevLicense' + | 'cpuOnly'; export type PopoverData = PopoverProps & { image?: string; diff --git a/invokeai/frontend/web/src/features/modelManagerV2/hooks/useEncoderModelSettings.ts b/invokeai/frontend/web/src/features/modelManagerV2/hooks/useEncoderModelSettings.ts new file mode 100644 index 00000000000..b1521f55fce --- /dev/null +++ b/invokeai/frontend/web/src/features/modelManagerV2/hooks/useEncoderModelSettings.ts @@ -0,0 +1,33 @@ +import type { EncoderModelSettingsFormData } from 'features/modelManagerV2/subpanels/ModelPanel/EncoderModelSettings/EncoderModelSettings'; +import { useMemo } from 'react'; +import type { + CLIPEmbedModelConfig, + CLIPVisionModelConfig, + LlavaOnevisionModelConfig, + Qwen3EncoderModelConfig, + SigLIPModelConfig, + T5EncoderModelConfig, +} from 'services/api/types'; + +type EncoderModelConfig = + | CLIPEmbedModelConfig + | T5EncoderModelConfig + | Qwen3EncoderModelConfig + | CLIPVisionModelConfig + | SigLIPModelConfig + | LlavaOnevisionModelConfig; + +export const useEncoderModelSettings = (modelConfig: EncoderModelConfig) => { + const encoderModelSettingsDefaults = useMemo(() => { + const cpuOnly = modelConfig.cpu_only ?? false; + + return { + cpuOnly: { + value: cpuOnly, + isEnabled: cpuOnly, + }, + }; + }, [modelConfig]); + + return encoderModelSettingsDefaults; +}; diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/EncoderModelSettings/EncoderModelSettings.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/EncoderModelSettings/EncoderModelSettings.tsx new file mode 100644 index 00000000000..3284e3b7a17 --- /dev/null +++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/EncoderModelSettings/EncoderModelSettings.tsx @@ -0,0 +1,139 @@ +import { Button, Flex, FormControl, FormLabel, Heading, Switch } from '@invoke-ai/ui-library'; +import { useAppSelector } from 'app/store/storeHooks'; +import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover'; +import { useEncoderModelSettings } from 'features/modelManagerV2/hooks/useEncoderModelSettings'; +import { selectSelectedModelKey } from 'features/modelManagerV2/store/modelManagerV2Slice'; +import { toast } from 'features/toast/toast'; +import type { ChangeEvent } from 'react'; +import { memo, useCallback, useMemo } from 'react'; +import type { Control, SubmitHandler } from 'react-hook-form'; +import { useController, useForm } from 'react-hook-form'; +import { useTranslation } from 'react-i18next'; +import { PiCheckBold } from 'react-icons/pi'; +import { useUpdateModelMutation } from 'services/api/endpoints/models'; +import type { + CLIPEmbedModelConfig, + CLIPVisionModelConfig, + LlavaOnevisionModelConfig, + Qwen3EncoderModelConfig, + SigLIPModelConfig, + T5EncoderModelConfig, +} from 'services/api/types'; + +export type EncoderModelSettingsFormData = { + cpuOnly: FormField; +}; + +type EncoderModelConfig = + | CLIPEmbedModelConfig + | T5EncoderModelConfig + | Qwen3EncoderModelConfig + | CLIPVisionModelConfig + | SigLIPModelConfig + | LlavaOnevisionModelConfig; + +type Props = { + modelConfig: EncoderModelConfig; +}; + +const DefaultCpuOnly = memo((props: { name: 'cpuOnly'; control: Control }) => { + const { field } = useController(props); + const { t } = useTranslation(); + + const onChange = useCallback( + (e: ChangeEvent) => { + const updatedValue = { + ...(field.value as FormField), + value: e.target.checked, + isEnabled: e.target.checked, + }; + field.onChange(updatedValue); + }, + [field] + ); + + const value = useMemo(() => { + return (field.value as FormField).value; + }, [field.value]); + + return ( + + + {t('modelManager.runOnCpu')} + + + + ); +}); + +DefaultCpuOnly.displayName = 'DefaultCpuOnly'; + +export const EncoderModelSettings = memo(({ modelConfig }: Props) => { + const selectedModelKey = useAppSelector(selectSelectedModelKey); + const { t } = useTranslation(); + + const settingsDefaults = useEncoderModelSettings(modelConfig); + const [updateModel, { isLoading: isLoadingUpdateModel }] = useUpdateModelMutation(); + + const { handleSubmit, control, formState, reset } = useForm({ + defaultValues: settingsDefaults, + }); + + const onSubmit = useCallback>( + (data) => { + if (!selectedModelKey) { + return; + } + + const body = { + cpu_only: data.cpuOnly.isEnabled ? data.cpuOnly.value : null, + }; + + updateModel({ + key: selectedModelKey, + body, + }) + .unwrap() + .then((_) => { + toast({ + id: 'ENCODER_SETTINGS_SAVED', + title: t('modelManager.settingsSaved'), + status: 'success', + }); + reset(data); + }) + .catch((error) => { + if (error) { + toast({ + id: 'ENCODER_SETTINGS_SAVE_FAILED', + title: `${error.data.detail} `, + status: 'error', + }); + } + }); + }, + [selectedModelKey, reset, updateModel, t] + ); + + return ( + <> + + {t('modelManager.settings')} + + + + + + ); +}); + +EncoderModelSettings.displayName = 'EncoderModelSettings'; diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx index 20b8fd6c13d..604d3b49a39 100644 --- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx +++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx @@ -1,5 +1,6 @@ import { Box, Divider, Flex, SimpleGrid } from '@invoke-ai/ui-library'; import { ControlAdapterModelDefaultSettings } from 'features/modelManagerV2/subpanels/ModelPanel/ControlAdapterModelDefaultSettings/ControlAdapterModelDefaultSettings'; +import { EncoderModelSettings } from 'features/modelManagerV2/subpanels/ModelPanel/EncoderModelSettings/EncoderModelSettings'; import { LoRAModelDefaultSettings } from 'features/modelManagerV2/subpanels/ModelPanel/LoRAModelDefaultSettings/LoRAModelDefaultSettings'; import { ModelConvertButton } from 'features/modelManagerV2/subpanels/ModelPanel/ModelConvertButton'; import { ModelEditButton } from 'features/modelManagerV2/subpanels/ModelPanel/ModelEditButton'; @@ -8,7 +9,15 @@ import { TriggerPhrases } from 'features/modelManagerV2/subpanels/ModelPanel/Tri import { filesize } from 'filesize'; import { memo, useMemo } from 'react'; import { useTranslation } from 'react-i18next'; -import type { AnyModelConfig } from 'services/api/types'; +import type { + AnyModelConfig, + CLIPEmbedModelConfig, + CLIPVisionModelConfig, + LlavaOnevisionModelConfig, + Qwen3EncoderModelConfig, + SigLIPModelConfig, + T5EncoderModelConfig, +} from 'services/api/types'; import { isExternalModel } from './isExternalModel'; import { MainModelDefaultSettings } from './MainModelDefaultSettings/MainModelDefaultSettings'; @@ -18,6 +27,25 @@ import { ModelReidentifyButton } from './ModelReidentifyButton'; import { ModelUpdatePathButton } from './ModelUpdatePathButton'; import { RelatedModels } from './RelatedModels'; +type EncoderModelConfig = + | CLIPEmbedModelConfig + | T5EncoderModelConfig + | Qwen3EncoderModelConfig + | CLIPVisionModelConfig + | SigLIPModelConfig + | LlavaOnevisionModelConfig; + +const isEncoderModel = (modelConfig: AnyModelConfig): modelConfig is EncoderModelConfig => { + return ( + modelConfig.type === 'clip_embed' || + modelConfig.type === 't5_encoder' || + modelConfig.type === 'qwen3_encoder' || + modelConfig.type === 'clip_vision' || + modelConfig.type === 'siglip' || + modelConfig.type === 'llava_onevision' + ); +}; + type Props = { modelConfig: AnyModelConfig; }; @@ -42,9 +70,13 @@ export const ModelView = memo(({ modelConfig }: Props) => { if (modelConfig.type === 'main' || modelConfig.type === 'lora') { return true; } + // Encoder models + if (isEncoderModel(modelConfig)) { + return true; + } return false; - }, [modelConfig.base, modelConfig.type]); + }, [modelConfig]); return ( @@ -102,6 +134,7 @@ export const ModelView = memo(({ modelConfig }: Props) => { )} {modelConfig.type === 'main' && } + {isEncoderModel(modelConfig) && } )} diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts index 829c5d435cd..9e7a638ac70 100644 --- a/invokeai/frontend/web/src/services/api/schema.ts +++ b/invokeai/frontend/web/src/services/api/schema.ts @@ -3231,6 +3231,11 @@ export type components = { * @constant */ type: "clip_embed"; + /** + * Cpu Only + * @description Whether this model should run on CPU only + */ + cpu_only: boolean | null; /** * Variant * @default gigantic @@ -3307,6 +3312,11 @@ export type components = { * @constant */ type: "clip_embed"; + /** + * Cpu Only + * @description Whether this model should run on CPU only + */ + cpu_only: boolean | null; /** * Variant * @default large @@ -3479,6 +3489,11 @@ export type components = { * @constant */ type: "clip_vision"; + /** + * Cpu Only + * @description Whether this model should run on CPU only + */ + cpu_only: boolean | null; }; /** * CV2 Infill @@ -14519,6 +14534,11 @@ export type components = { * @constant */ base: "any"; + /** + * Cpu Only + * @description Whether this model should run on CPU only + */ + cpu_only: boolean | null; }; /** * Apply LoRA Collection - SD1.5 @@ -15807,6 +15827,11 @@ export type components = { * @description Default Guidance for this model */ guidance?: number | null; + /** + * Cpu Only + * @description Whether this model should run on CPU only + */ + cpu_only?: boolean | null; }; /** * Main Model - SD1.5, SD2 @@ -19346,6 +19371,11 @@ export type components = { * @description Default settings for this model */ default_settings?: components["schemas"]["MainModelDefaultSettings"] | components["schemas"]["LoraModelDefaultSettings"] | components["schemas"]["ControlAdapterDefaultSettings"] | null; + /** + * Cpu Only + * @description Whether this model should run on CPU only + */ + cpu_only?: boolean | null; /** * Variant * @description The variant of the model. @@ -20334,6 +20364,11 @@ export type components = { * @constant */ format: "checkpoint"; + /** + * Cpu Only + * @description Whether this model should run on CPU only + */ + cpu_only: boolean | null; }; /** * Qwen3Encoder_GGUF_Config @@ -20410,6 +20445,11 @@ export type components = { * @constant */ format: "gguf_quantized"; + /** + * Cpu Only + * @description Whether this model should run on CPU only + */ + cpu_only: boolean | null; }; /** * Qwen3Encoder_Qwen3Encoder_Config @@ -20484,6 +20524,11 @@ export type components = { * @constant */ format: "qwen3_encoder"; + /** + * Cpu Only + * @description Whether this model should run on CPU only + */ + cpu_only: boolean | null; }; /** * Random Float @@ -22403,6 +22448,11 @@ export type components = { * @constant */ base: "any"; + /** + * Cpu Only + * @description Whether this model should run on CPU only + */ + cpu_only: boolean | null; }; /** * Image-to-Image (Autoscale) @@ -23594,6 +23644,11 @@ export type components = { * @constant */ format: "bnb_quantized_int8b"; + /** + * Cpu Only + * @description Whether this model should run on CPU only + */ + cpu_only: boolean | null; }; /** * T5Encoder_T5Encoder_Config @@ -23666,6 +23721,11 @@ export type components = { * @constant */ format: "t5_encoder"; + /** + * Cpu Only + * @description Whether this model should run on CPU only + */ + cpu_only: boolean | null; }; /** TBLR */ TBLR: { diff --git a/invokeai/frontend/web/src/services/api/types.ts b/invokeai/frontend/web/src/services/api/types.ts index 7ca815ea86a..48ac01e0ee3 100644 --- a/invokeai/frontend/web/src/services/api/types.ts +++ b/invokeai/frontend/web/src/services/api/types.ts @@ -89,7 +89,7 @@ export type T2IAdapterModelConfig = Extract; export type CLIPGEmbedModelConfig = Extract; export type CLIPEmbedModelConfig = Extract; -type LlavaOnevisionConfig = Extract; +export type LlavaOnevisionModelConfig = Extract; export type T5EncoderModelConfig = Extract; export type T5EncoderBnbQuantizedLlmInt8bModelConfig = Extract< S['AnyModelConfig'], @@ -98,8 +98,8 @@ export type T5EncoderBnbQuantizedLlmInt8bModelConfig = Extract< export type Qwen3EncoderModelConfig = Extract; export type SpandrelImageToImageModelConfig = Extract; export type CheckpointModelConfig = Extract; -type CLIPVisionDiffusersConfig = Extract; -type SigLipModelConfig = Extract; +export type CLIPVisionModelConfig = Extract; +export type SigLIPModelConfig = Extract; export type FLUXReduxModelConfig = Extract; type ApiModelConfig = Extract; type UnknownModelConfig = Extract; @@ -193,11 +193,11 @@ export const isIPAdapterModelConfig = (config: AnyModelConfig): config is IPAdap return config.type === 'ip_adapter'; }; -export const isCLIPVisionModelConfig = (config: AnyModelConfig): config is CLIPVisionDiffusersConfig => { +export const isCLIPVisionModelConfig = (config: AnyModelConfig): config is CLIPVisionModelConfig => { return config.type === 'clip_vision'; }; -export const isLLaVAModelConfig = (config: AnyModelConfig): config is LlavaOnevisionConfig => { +export const isLLaVAModelConfig = (config: AnyModelConfig): config is LlavaOnevisionModelConfig => { return config.type === 'llava_onevision'; }; @@ -265,7 +265,7 @@ export const isSpandrelImageToImageModelConfig = ( return config.type === 'spandrel_image_to_image'; }; -export const isSigLipModelConfig = (config: AnyModelConfig): config is SigLipModelConfig => { +export const isSigLipModelConfig = (config: AnyModelConfig): config is SigLIPModelConfig => { return config.type === 'siglip'; };