diff --git a/README.md b/README.md index bd1b3d7bf1f..0fcc86426cc 100644 --- a/README.md +++ b/README.md @@ -75,6 +75,7 @@ Invoke features an organized gallery system for easily storing, accessing, and r - Anima - Qwen Image - Qwen Image Edit +- Ideogram 4 - Nano Banana (API Only) - GPT Image (API Only) - Wan (API Only) diff --git a/docs/src/content/docs/concepts/models.mdx b/docs/src/content/docs/concepts/models.mdx index 3ebdf27c788..ada15da80e8 100644 --- a/docs/src/content/docs/concepts/models.mdx +++ b/docs/src/content/docs/concepts/models.mdx @@ -51,6 +51,44 @@ In this situation, you may need to provide some additional information to identi [set up in the config file]: ../../configuration/invokeai-yaml +## Ideogram 4 + +Ideogram 4 is an open-weight text-to-image model with a distinctive **structured JSON prompt**: instead of a single sentence, the model is trained to read an overall scene description plus a list of regions, each with a bounding box and its own text. Invoke assembles this JSON for you. + +### Installing Ideogram 4 + +The weights are gated on HuggingFace under a **non-commercial license**. Open the model page, accept the terms, and make sure your HuggingFace token is [set up in the config file] before installing. Two builds are available: + +- [`ideogram-ai/ideogram-4-nf4`](https://huggingface.co/ideogram-ai/ideogram-4-nf4) — nf4 quantized, **CUDA only**, fits in 24 GB VRAM. Recommended for NVIDIA GPUs. +- [`ideogram-ai/ideogram-4-fp8`](https://huggingface.co/ideogram-ai/ideogram-4-fp8) — fp8 quantized, runs on **any device**, with higher memory use. + +Paste either repo ID into the Model Manager's HuggingFace / URL field to install. + +### Prompting Ideogram 4 + +When an Ideogram 4 model is selected, Invoke builds the structured JSON prompt automatically: + +- The **positive prompt** becomes the overall scene description. +- Each enabled **Regional Guidance** layer on the Canvas contributes one element: its drawn box becomes the region's bounding box and its prompt becomes that region's description. Draw a box where you want something and describe it there. +- To drive the model directly, paste a **raw JSON** object into the prompt box — anything starting with `{` is passed through unchanged. + +The exact JSON that was encoded is stored in the image metadata as **Structured Caption**, and can be recalled straight back into the prompt box from the metadata viewer. + +:::note[No negative prompt] +Ideogram 4 does not use a negative prompt — it has a dedicated unconditional branch instead, so the negative prompt box has no effect. +::: + +### Generation settings + +- **Sampler Preset** — the primary quality/speed control. `Quality (48 steps)`, `Default (20 steps)`, and `Turbo (12 steps)` each bundle a step count, a guidance schedule, and the schedule shift. +- **Advanced** overrides (all optional, leave on *Auto* to use the preset's values): **Steps**, **Guidance Scale**, **Schedule Shift (mu)**, and a **Color Palette** that biases the generated colors. + +:::caution[Built-in safety filter] +Ideogram 4 ships with a **content safety filter baked into the released model weights**. When it triggers, the model outputs a placeholder image reading *"Image blocked by safety filter"* instead of your image. This is the model's own filter — it is **not** Invoke's NSFW checker (it fires even with the NSFW checker off) and cannot be disabled from Invoke. + +The filter is known to **false-positive on completely benign prompts**, and the quantized builds can trigger it more readily. Invoke always sends the model a structured JSON prompt, which tends to trip the filter less than plain text; if you hit it, rephrasing or adjusting the prompt usually clears it. +::: + ## Editing model metadata Every model has an editable **Source URL** field alongside its name and description. Use it to record where a model came from — for example a Civitai or HuggingFace page — independent of how it was originally installed. The URL is editable from the model's **Edit** view and appears as a clickable link in the model header once set. Models without a URL simply hide the field. diff --git a/invokeai/app/api/dependencies.py b/invokeai/app/api/dependencies.py index 3092f5ab71a..82899822a40 100644 --- a/invokeai/app/api/dependencies.py +++ b/invokeai/app/api/dependencies.py @@ -60,6 +60,7 @@ CogView4ConditioningInfo, ConditioningFieldData, FLUXConditioningInfo, + Ideogram4ConditioningInfo, QwenImageConditioningInfo, SD3ConditioningInfo, SDXLConditioningInfo, @@ -152,6 +153,7 @@ def initialize( SD3ConditioningInfo, CogView4ConditioningInfo, ZImageConditioningInfo, + Ideogram4ConditioningInfo, QwenImageConditioningInfo, AnimaConditioningInfo, ], diff --git a/invokeai/app/invocations/fields.py b/invokeai/app/invocations/fields.py index 4418c86371a..4a1e3b797d8 100644 --- a/invokeai/app/invocations/fields.py +++ b/invokeai/app/invocations/fields.py @@ -344,6 +344,12 @@ class ZImageConditioningField(BaseModel): ) +class Ideogram4ConditioningField(BaseModel): + """An Ideogram 4 conditioning tensor primitive value""" + + conditioning_name: str = Field(description="The name of conditioning tensor") + + class QwenImageConditioningField(BaseModel): """A Qwen Image Edit conditioning tensor primitive value""" diff --git a/invokeai/app/invocations/ideogram4_caption.py b/invokeai/app/invocations/ideogram4_caption.py new file mode 100644 index 00000000000..f4e858d0363 --- /dev/null +++ b/invokeai/app/invocations/ideogram4_caption.py @@ -0,0 +1,91 @@ +from typing import Annotated, Optional + +from pydantic import BaseModel, Field, field_validator + +from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation +from invokeai.app.invocations.fields import InputField, UIComponent +from invokeai.app.invocations.primitives import StringOutput +from invokeai.app.services.shared.invocation_context import InvocationContext +from invokeai.backend.ideogram4.caption import build_ideogram4_caption + +_IDEOGRAM4_COORD_MAX = 1000 + +# Exactly four normalized coordinates [y_min, x_min, y_max, x_max], each in 0..1000. Modeled as a +# constrained type so the generated OpenAPI schema advertises minItems/maxItems and per-item +# minimum/maximum — clients get the contract from the schema, not only from runtime validation. +Ideogram4Bbox = Annotated[ + list[Annotated[int, Field(ge=0, le=_IDEOGRAM4_COORD_MAX)]], + Field(min_length=4, max_length=4), +] + + +class Ideogram4Region(BaseModel): + """A single region of an Ideogram 4 structured caption (description + optional bounding box).""" + + prompt: str = Field(description="The region's description (becomes the element's `desc`).") + bbox: Optional[Ideogram4Bbox] = Field( + default=None, + description="Normalized bounding box [y_min, x_min, y_max, x_max] (0–1000), or null for a region " + "with no drawn content.", + ) + + @field_validator("bbox") + @classmethod + def _validate_bbox(cls, v: Optional[list[int]]) -> Optional[list[int]]: + """Enforce the ordering the constrained type can't express: y_min <= y_max and x_min <= x_max. + + Length (exactly 4) and range (0..1000) are enforced by the Ideogram4Bbox type. The caption + builder forwards the bbox verbatim into the structured JSON, so an inverted box would emit a + malformed prompt the model may misapply — reject it here. + """ + if v is None: + return v + y_min, x_min, y_max, x_max = v + if y_min > y_max or x_min > x_max: + raise ValueError( + f"bbox must satisfy y_min <= y_max and x_min <= x_max, got [y_min={y_min}, x_min={x_min}, " + f"y_max={y_max}, x_max={x_max}]" + ) + return v + + +@invocation( + "ideogram4_caption_builder", + title="Caption Builder - Ideogram 4", + tags=["prompt", "ideogram4"], + category="conditioning", + version="1.0.0", + classification=Classification.Prototype, +) +class Ideogram4CaptionBuilderInvocation(BaseInvocation): + """Assembles the Ideogram 4 structured JSON caption at generation time. + + The caption is built here (not in the graph builder) so the batch-injectable global `prompt` — which + dynamic prompts and prompt batching vary — is folded into the encoded caption. The regions and color + palette are fixed per generation and supplied as inputs. If the prompt is already a JSON object it is + passed through verbatim; otherwise it is always wrapped in the structured JSON schema (never bare + plain text — Ideogram's safety filter false-positives far more on plain text). + """ + + prompt: str = InputField( + default="", + description="The global prompt (becomes `high_level_description`, or is used verbatim if it is " + "already a JSON caption).", + ui_component=UIComponent.Textarea, + ) + regions: list[Ideogram4Region] = InputField( + default=[], + description="Regional descriptions and bounding boxes assembled from Canvas Regional Guidance layers.", + ) + color_palette: list[str] = InputField( + default=[], + description="Optional color palette as hex colors (#RRGGBB).", + ) + + def invoke(self, context: InvocationContext) -> StringOutput: + caption = build_ideogram4_caption( + self.prompt, + [(region.prompt, region.bbox) for region in self.regions], + self.color_palette, + ) + return StringOutput(value=caption) diff --git a/invokeai/app/invocations/ideogram4_denoise.py b/invokeai/app/invocations/ideogram4_denoise.py new file mode 100644 index 00000000000..f9bc9ea855d --- /dev/null +++ b/invokeai/app/invocations/ideogram4_denoise.py @@ -0,0 +1,179 @@ +from typing import Literal, Optional + +import torch + +from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation +from invokeai.app.invocations.fields import ( + FieldDescriptions, + Ideogram4ConditioningField, + Input, + InputField, +) +from invokeai.app.invocations.model import TransformerField +from invokeai.app.invocations.primitives import LatentsOutput +from invokeai.app.services.shared.invocation_context import InvocationContext +from invokeai.app.util.step_callback import ( + FLUX2_LATENT_RGB_BIAS, + FLUX2_LATENT_RGB_FACTORS, + sample_to_lowres_estimated_image, +) +from invokeai.backend.ideogram4 import run_ideogram4_denoise +from invokeai.backend.ideogram4.latent_norm import get_latent_norm +from invokeai.backend.ideogram4.sampler_configs import PRESETS +from invokeai.backend.ideogram4.sampling_utils import unpatchify_and_denormalize +from invokeai.backend.ideogram4.transformer_pair import Ideogram4TransformerPair +from invokeai.backend.stable_diffusion.diffusion.conditioning_data import Ideogram4ConditioningInfo +from invokeai.backend.util.devices import TorchDevice + +# Named sampler presets bundle step count, guidance schedule (with polish tail), and the +# logit-normal schedule mean/std. V4_QUALITY_48 is the reference default. +IDEOGRAM4_SAMPLER_PRESETS = Literal["V4_QUALITY_48", "V4_DEFAULT_20", "V4_TURBO_12"] + + +def _effective_guidance_schedule( + base_schedule: tuple[float, ...], preset_num_steps: int, num_steps: int, guidance_scale: Optional[float] +) -> tuple[float, ...]: + """Build the per-step guidance schedule for the (possibly overridden) step count. + + The preset schedule is ``(polish_gw,)*N_polish + (main_gw,)*N_main`` in loop-index order + (index 0 = the final/polish step). A ``guidance_scale`` override replaces the main weight while + the preset's polish tail is preserved; a changed step count rescales the polish tail + proportionally (always keeping at least one polish and one main step). + + ``num_steps`` must be >= 2 (enforced by the invocation's ``steps`` field) so both a polish and a + main step always exist — otherwise a single step would be all-polish and silently drop the + ``guidance_scale`` override. + """ + polish_gw = base_schedule[0] + main_gw = float(guidance_scale) if guidance_scale is not None else float(base_schedule[-1]) + if num_steps == preset_num_steps and guidance_scale is None: + return base_schedule + n_polish_base = sum(1 for gw in base_schedule if gw == base_schedule[0]) + # Cap the polish tail at num_steps - 1 so at least one main step always remains and the + # guidance_scale override is never silently dropped. + polish_count = max(1, min(round(n_polish_base * num_steps / preset_num_steps), num_steps - 1)) + main_count = num_steps - polish_count + return (polish_gw,) * polish_count + (main_gw,) * main_count + + +@invocation( + "ideogram4_denoise", + title="Denoise - Ideogram 4", + tags=["image", "ideogram4"], + category="latents", + version="1.0.0", + classification=Classification.Prototype, +) +class Ideogram4DenoiseInvocation(BaseInvocation): + """Runs the Ideogram 4 dual-branch flow-matching denoising loop (text-to-image).""" + + transformer: TransformerField = InputField( + description=FieldDescriptions.transformer, input=Input.Connection, title="Transformer" + ) + positive_conditioning: Ideogram4ConditioningField = InputField( + description=FieldDescriptions.positive_cond, input=Input.Connection + ) + sampler_preset: IDEOGRAM4_SAMPLER_PRESETS = InputField( + default="V4_QUALITY_48", + description="Sampler preset (steps + guidance schedule + schedule mean/std).", + title="Sampler Preset", + ) + width: int = InputField(default=1024, multiple_of=16, description="Width of the generated image.") + height: int = InputField(default=1024, multiple_of=16, description="Height of the generated image.") + seed: int = InputField(default=0, description="Randomness seed for reproducibility.") + # Optional advanced overrides of the sampler preset. None = use the preset's value. + steps: Optional[int] = InputField( + default=None, + ge=2, + le=100, + description="Override the preset's step count (minimum 2, so a polish and a main step both " + "exist). Leave empty to use the preset.", + ) + guidance_scale: Optional[float] = InputField( + default=None, + ge=1.0, + le=20.0, + description="Override the main guidance weight (the preset's polish tail is preserved). " + "Empty = use the preset.", + ) + mu: Optional[float] = InputField( + default=None, + ge=-4.0, + le=4.0, + description="Override the logit-normal schedule mean (resolution-adjusted internally). Empty = use the preset.", + ) + + @torch.no_grad() + def invoke(self, context: InvocationContext) -> LatentsOutput: + device = TorchDevice.choose_torch_device() + preset = PRESETS[self.sampler_preset] + + # Apply optional advanced overrides on top of the preset. + num_steps = self.steps if self.steps is not None else preset.num_steps + mu = self.mu if self.mu is not None else preset.mu + guidance_schedule = _effective_guidance_schedule( + preset.guidance_schedule, preset.num_steps, num_steps, self.guidance_scale + ) + + # Load conditioning (the stacked Qwen3-VL features). + cond_data = context.conditioning.load(self.positive_conditioning.conditioning_name) + assert len(cond_data.conditionings) == 1 + info = cond_data.conditionings[0] + assert isinstance(info, Ideogram4ConditioningInfo) + llm_features = info.prompt_embeds.to(device=device, dtype=torch.float32) + + # Progress-preview setup: Ideogram uses a FLUX.2-style 32-channel VAE, so the FLUX.2 + # latent->RGB factors give a usable (approximate) low-res preview of the forming image at each + # step, without a full VAE decode. Denormalization params come from get_latent_norm (no VAE). + latent_shift, latent_scale = get_latent_norm() + rgb_factors = torch.tensor(FLUX2_LATENT_RGB_FACTORS, dtype=torch.float32) + rgb_bias = torch.tensor(FLUX2_LATENT_RGB_BIAS, dtype=torch.float32) + + def step_callback(step: int, total: int, packed_latents: torch.Tensor) -> None: + preview = None + try: + # packed_latents: (1, LATENT_DIM, grid_h, grid_w) -> VAE latent (1, 32, H/8, W/8). + vae_latent = unpatchify_and_denormalize( + packed_latents.float(), + latent_shift.to(packed_latents.device), + latent_scale.to(packed_latents.device), + ) + preview = sample_to_lowres_estimated_image( + samples=vae_latent, + latent_rgb_factors=rgb_factors.to(vae_latent.device), + latent_rgb_bias=rgb_bias.to(vae_latent.device), + ) + except Exception: + # A preview must never break generation — fall back to a plain progress signal. + preview = None + if preview is not None: + context.util.signal_progress( + "Running Ideogram 4 denoising", + step / total, + preview, + (preview.width * 8, preview.height * 8), + ) + else: + context.util.signal_progress("Running Ideogram 4 denoising", step / total) + + transformer_info = context.models.load(self.transformer.transformer) + with transformer_info.model_on_device() as (_, transformers): + assert isinstance(transformers, Ideogram4TransformerPair) + packed = run_ideogram4_denoise( + conditional_transformer=transformers.conditional, + unconditional_transformer=transformers.unconditional, + llm_features=llm_features, + height=self.height, + width=self.width, + num_steps=num_steps, + mu=mu, + std=preset.std, + guidance_schedule=guidance_schedule, + seed=self.seed, + device=device, + step_callback=step_callback, + ) + + packed = packed.detach().to("cpu") + name = context.tensors.save(tensor=packed) + return LatentsOutput.build(latents_name=name, latents=packed, seed=None) diff --git a/invokeai/app/invocations/ideogram4_latents_to_image.py b/invokeai/app/invocations/ideogram4_latents_to_image.py new file mode 100644 index 00000000000..085f2c48e7a --- /dev/null +++ b/invokeai/app/invocations/ideogram4_latents_to_image.py @@ -0,0 +1,62 @@ +import torch +from einops import rearrange +from PIL import Image + +from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation +from invokeai.app.invocations.fields import ( + FieldDescriptions, + Input, + InputField, + LatentsField, + WithBoard, + WithMetadata, +) +from invokeai.app.invocations.model import VAEField +from invokeai.app.invocations.primitives import ImageOutput +from invokeai.app.services.shared.invocation_context import InvocationContext +from invokeai.backend.ideogram4.autoencoder import AutoEncoder +from invokeai.backend.ideogram4.latent_norm import get_latent_norm +from invokeai.backend.ideogram4.sampling_utils import unpatchify_and_denormalize +from invokeai.backend.util.devices import TorchDevice + + +@invocation( + "ideogram4_l2i", + title="Latents to Image - Ideogram 4", + tags=["latents", "image", "vae", "l2i", "ideogram4"], + category="latents", + version="1.0.0", + classification=Classification.Prototype, +) +class Ideogram4LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard): + """Decodes Ideogram 4 packed latents to an image with the FLUX.2-style VAE.""" + + latents: LatentsField = InputField(description=FieldDescriptions.latents, input=Input.Connection) + vae: VAEField = InputField(description=FieldDescriptions.vae, input=Input.Connection) + + @torch.no_grad() + def invoke(self, context: InvocationContext) -> ImageOutput: + # Packed latents from denoise: (1, 128, grid_h, grid_w). + latents = context.tensors.load(self.latents.latents_name) + device = TorchDevice.choose_torch_device() + + vae_info = context.models.load(self.vae.vae) + latent_shift, latent_scale = get_latent_norm() + + with vae_info.model_on_device() as (_, vae): + assert isinstance(vae, AutoEncoder), f"Expected Ideogram 4 AutoEncoder, got {type(vae).__name__}." + context.util.signal_progress("Running VAE") + vae_dtype = next(vae.parameters()).dtype + + # Denormalize + unpatchify to a standard (1, 32, H/8, W/8) latent. + z = unpatchify_and_denormalize(latents.float().to(device), latent_shift.to(device), latent_scale.to(device)) + TorchDevice.empty_cache() + decoded = vae.decoder(z.to(vae_dtype)) + + img = decoded.float().clamp(-1.0, 1.0) + img = rearrange(img[0], "c h w -> h w c") + img_pil = Image.fromarray((127.5 * (img + 1.0)).byte().cpu().numpy()) + + TorchDevice.empty_cache() + image_dto = context.images.save(image=img_pil) + return ImageOutput.build(image_dto) diff --git a/invokeai/app/invocations/ideogram4_model_loader.py b/invokeai/app/invocations/ideogram4_model_loader.py new file mode 100644 index 00000000000..45927214080 --- /dev/null +++ b/invokeai/app/invocations/ideogram4_model_loader.py @@ -0,0 +1,64 @@ +from invokeai.app.invocations.baseinvocation import ( + BaseInvocation, + BaseInvocationOutput, + Classification, + invocation, + invocation_output, +) +from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField +from invokeai.app.invocations.model import ( + ModelIdentifierField, + Qwen3EncoderField, + TransformerField, + VAEField, +) +from invokeai.app.services.shared.invocation_context import InvocationContext +from invokeai.backend.model_manager.taxonomy import BaseModelType, ModelType, SubModelType + + +@invocation_output("ideogram4_model_loader_output") +class Ideogram4ModelLoaderOutput(BaseInvocationOutput): + """Ideogram 4 model loader output.""" + + transformer: TransformerField = OutputField(description=FieldDescriptions.transformer, title="Transformer") + qwen3_encoder: Qwen3EncoderField = OutputField( + description=FieldDescriptions.qwen3_encoder, title="Qwen3-VL Encoder" + ) + vae: VAEField = OutputField(description=FieldDescriptions.vae, title="VAE") + + +@invocation( + "ideogram4_model_loader", + title="Main Model - Ideogram 4", + tags=["model", "ideogram4"], + category="model", + version="1.0.0", + classification=Classification.Prototype, +) +class Ideogram4ModelLoaderInvocation(BaseInvocation): + """Loads an Ideogram 4 model, outputting its submodels. + + Ideogram 4 is distributed as a single bundled diffusers folder, so the transformer + (both branches), the Qwen3-VL text encoder + tokenizer, and the VAE are all loaded + from the one selected model. + """ + + model: ModelIdentifierField = InputField( + description="The Ideogram 4 model to load.", + input=Input.Direct, + ui_model_base=BaseModelType.Ideogram4, + ui_model_type=ModelType.Main, + title="Model", + ) + + def invoke(self, context: InvocationContext) -> Ideogram4ModelLoaderOutput: + transformer = self.model.model_copy(update={"submodel_type": SubModelType.Transformer}) + text_encoder = self.model.model_copy(update={"submodel_type": SubModelType.TextEncoder}) + tokenizer = self.model.model_copy(update={"submodel_type": SubModelType.Tokenizer}) + vae = self.model.model_copy(update={"submodel_type": SubModelType.VAE}) + + return Ideogram4ModelLoaderOutput( + transformer=TransformerField(transformer=transformer, loras=[]), + qwen3_encoder=Qwen3EncoderField(tokenizer=tokenizer, text_encoder=text_encoder), + vae=VAEField(vae=vae), + ) diff --git a/invokeai/app/invocations/ideogram4_text_encoder.py b/invokeai/app/invocations/ideogram4_text_encoder.py new file mode 100644 index 00000000000..ca2a809f1bb --- /dev/null +++ b/invokeai/app/invocations/ideogram4_text_encoder.py @@ -0,0 +1,60 @@ +from contextlib import ExitStack + +import torch + +from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation +from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, UIComponent +from invokeai.app.invocations.model import Qwen3EncoderField +from invokeai.app.invocations.primitives import Ideogram4ConditioningOutput +from invokeai.app.services.shared.invocation_context import InvocationContext +from invokeai.backend.ideogram4.text_encoding import encode_qwen3vl_prompt +from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ( + ConditioningFieldData, + Ideogram4ConditioningInfo, +) + + +@invocation( + "ideogram4_text_encoder", + title="Prompt - Ideogram 4", + tags=["prompt", "conditioning", "ideogram4"], + category="conditioning", + version="1.0.0", + classification=Classification.Prototype, +) +class Ideogram4TextEncoderInvocation(BaseInvocation): + """Encodes a prompt for Ideogram 4 using the Qwen3-VL encoder. + + The prompt is normally a structured JSON caption (see the Ideogram 4 prompting guide); + plain text also works but yields lower-quality results. + """ + + prompt: str = InputField( + description="The prompt to encode. A structured JSON caption is recommended.", + ui_component=UIComponent.Textarea, + ) + qwen3_encoder: Qwen3EncoderField = InputField( + title="Qwen3-VL Encoder", + description=FieldDescriptions.qwen3_encoder, + input=Input.Connection, + ) + + @torch.no_grad() + def invoke(self, context: InvocationContext) -> Ideogram4ConditioningOutput: + text_encoder_info = context.models.load(self.qwen3_encoder.text_encoder) + tokenizer_info = context.models.load(self.qwen3_encoder.tokenizer) + + with ExitStack() as exit_stack: + (_, text_encoder) = exit_stack.enter_context(text_encoder_info.model_on_device()) + (_, tokenizer) = exit_stack.enter_context(tokenizer_info.model_on_device()) + + context.util.signal_progress("Running Qwen3-VL text encoder") + prompt_embeds = encode_qwen3vl_prompt(self.prompt, tokenizer, text_encoder) + + # Move to CPU for storage to save VRAM. + prompt_embeds = prompt_embeds.detach().to("cpu") + conditioning_data = ConditioningFieldData( + conditionings=[Ideogram4ConditioningInfo(prompt_embeds=prompt_embeds)] + ) + conditioning_name = context.conditioning.save(conditioning_data) + return Ideogram4ConditioningOutput.build(conditioning_name) diff --git a/invokeai/app/invocations/metadata.py b/invokeai/app/invocations/metadata.py index da24d8802bb..a2baea7f81b 100644 --- a/invokeai/app/invocations/metadata.py +++ b/invokeai/app/invocations/metadata.py @@ -166,6 +166,7 @@ def invoke(self, context: InvocationContext) -> MetadataOutput: "z_image_img2img", "z_image_inpaint", "z_image_outpaint", + "ideogram4_txt2img", "qwen_image_txt2img", "qwen_image_img2img", "qwen_image_inpaint", @@ -237,6 +238,13 @@ class CoreMetadataInvocation(BaseInvocation): default=None, description="The Qwen3 text encoder model used for Z-Image inference", ) + # Ideogram 4 assembles its structured JSON caption at generation time (ideogram4_caption_builder), + # so this is a declared field rather than a static extra: the graph wires the builder's output to it + # via an edge, capturing the exact caption encoded for each (possibly batched) image. + ideogram4_caption: Optional[str] = InputField( + default=None, + description="The structured JSON caption encoded for Ideogram 4 inference", + ) # High resolution fix metadata. hrf_enabled: Optional[bool] = InputField( diff --git a/invokeai/app/invocations/primitives.py b/invokeai/app/invocations/primitives.py index 6249de0cd8e..7b580b21d4d 100644 --- a/invokeai/app/invocations/primitives.py +++ b/invokeai/app/invocations/primitives.py @@ -20,6 +20,7 @@ DenoiseMaskField, FieldDescriptions, FluxConditioningField, + Ideogram4ConditioningField, ImageField, Input, InputField, @@ -488,6 +489,17 @@ def build(cls, conditioning_name: str) -> "ZImageConditioningOutput": return cls(conditioning=ZImageConditioningField(conditioning_name=conditioning_name)) +@invocation_output("ideogram4_conditioning_output") +class Ideogram4ConditioningOutput(BaseInvocationOutput): + """Base class for nodes that output an Ideogram 4 text conditioning tensor.""" + + conditioning: Ideogram4ConditioningField = OutputField(description=FieldDescriptions.cond) + + @classmethod + def build(cls, conditioning_name: str) -> "Ideogram4ConditioningOutput": + return cls(conditioning=Ideogram4ConditioningField(conditioning_name=conditioning_name)) + + @invocation_output("qwen_image_conditioning_output") class QwenImageConditioningOutput(BaseInvocationOutput): """Base class for nodes that output a Qwen Image Edit conditioning tensor.""" diff --git a/invokeai/backend/ideogram4/NOTICE.md b/invokeai/backend/ideogram4/NOTICE.md new file mode 100644 index 00000000000..fa3907d6895 --- /dev/null +++ b/invokeai/backend/ideogram4/NOTICE.md @@ -0,0 +1,24 @@ +# Ideogram 4 vendored inference code + +The following modules in this package are adapted from the Ideogram 4 reference +implementation at https://github.com/ideogram-oss/ideogram4 (the `ideogram4` +Python package), which is licensed under the Apache License, Version 2.0: + +- `modeling_ideogram4.py` +- `autoencoder.py` +- `latent_norm.py` +- `scheduler.py` +- `sampler_configs.py` +- `constants.py` +- `quantized_loading.py` + +Copyright © Ideogram, Inc. Licensed under the Apache License, Version 2.0; a copy +is available at http://www.apache.org/licenses/LICENSE-2.0. + +Modifications by the InvokeAI project: intra-package import paths were rewritten +to `invokeai.backend.ideogram4.*`. The remaining modules in this package +(`conditioning.py`, `sampling_utils.py`, `denoise.py`, etc.) are original InvokeAI +code that wraps the vendored model for use in InvokeAI invocations. + +The Ideogram 4 model **weights** are NOT covered by this Apache license; they are +distributed under the separate "Ideogram Non-Commercial Model Agreement". diff --git a/invokeai/backend/ideogram4/__init__.py b/invokeai/backend/ideogram4/__init__.py new file mode 100644 index 00000000000..bd2331e669f --- /dev/null +++ b/invokeai/backend/ideogram4/__init__.py @@ -0,0 +1,43 @@ +"""Ideogram 4 backend. + +The model modules (``modeling_ideogram4``, ``autoencoder``, ``latent_norm``, +``scheduler``, ``sampler_configs``, ``constants``, ``quantized_loading``) are +adapted from the Apache-2.0 Ideogram 4 reference implementation +(https://github.com/ideogram-oss/ideogram4). See ``NOTICE.md``. The remaining +modules wrap that model for InvokeAI invocations. + +``quantized_loading`` is intentionally not re-exported here so that importing this +package does not eagerly import ``bitsandbytes``; import it directly where needed. +""" + +from invokeai.backend.ideogram4.denoise import run_ideogram4_denoise +from invokeai.backend.ideogram4.modeling_ideogram4 import Ideogram4Config, Ideogram4Transformer +from invokeai.backend.ideogram4.sampler_configs import PRESETS +from invokeai.backend.ideogram4.sampling_utils import ( + AE_SCALE_FACTOR, + LATENT_DIM, + PATCH_SIZE, + PIXELS_PER_IMAGE_TOKEN, + build_denoise_inputs, + pack_latents_to_grid, + unpatchify_and_denormalize, + validate_dimensions, +) +from invokeai.backend.ideogram4.text_encoding import MAX_TEXT_TOKENS, encode_qwen3vl_prompt + +__all__ = [ + "Ideogram4Config", + "Ideogram4Transformer", + "PRESETS", + "run_ideogram4_denoise", + "encode_qwen3vl_prompt", + "MAX_TEXT_TOKENS", + "build_denoise_inputs", + "pack_latents_to_grid", + "unpatchify_and_denormalize", + "validate_dimensions", + "AE_SCALE_FACTOR", + "LATENT_DIM", + "PATCH_SIZE", + "PIXELS_PER_IMAGE_TOKEN", +] diff --git a/invokeai/backend/ideogram4/autoencoder.py b/invokeai/backend/ideogram4/autoencoder.py new file mode 100644 index 00000000000..c1f64e98961 --- /dev/null +++ b/invokeai/backend/ideogram4/autoencoder.py @@ -0,0 +1,384 @@ +"""Flux2 KL autoencoder.""" + +from __future__ import annotations + +import math +import re +from dataclasses import dataclass, field + +import torch +from einops import rearrange +from torch import Tensor, nn + + +@dataclass +class AutoEncoderParams: + resolution: int = 256 + in_channels: int = 3 + ch: int = 128 + out_ch: int = 3 + ch_mult: list[int] = field(default_factory=lambda: [1, 2, 4, 4]) + num_res_blocks: int = 2 + z_channels: int = 32 + + +def swish(x: Tensor) -> Tensor: + return x * torch.sigmoid(x) + + +class AttnBlock(nn.Module): + def __init__(self, in_channels: int): + super().__init__() + self.in_channels = in_channels + + self.norm = nn.GroupNorm(num_groups=32, num_channels=in_channels, eps=1e-6, affine=True) + + self.q = nn.Conv2d(in_channels, in_channels, kernel_size=1) + self.k = nn.Conv2d(in_channels, in_channels, kernel_size=1) + self.v = nn.Conv2d(in_channels, in_channels, kernel_size=1) + self.proj_out = nn.Conv2d(in_channels, in_channels, kernel_size=1) + + def attention(self, h_: Tensor) -> Tensor: + h_ = self.norm(h_) + q = self.q(h_) + k = self.k(h_) + v = self.v(h_) + + b, c, h, w = q.shape + q = rearrange(q, "b c h w -> b 1 (h w) c").contiguous() + k = rearrange(k, "b c h w -> b 1 (h w) c").contiguous() + v = rearrange(v, "b c h w -> b 1 (h w) c").contiguous() + h_ = nn.functional.scaled_dot_product_attention(q, k, v) + + return rearrange(h_, "b 1 (h w) c -> b c h w", h=h, w=w, c=c, b=b) + + def forward(self, x: Tensor) -> Tensor: + return x + self.proj_out(self.attention(x)) + + +class ResnetBlock(nn.Module): + def __init__(self, in_channels: int, out_channels: int): + super().__init__() + self.in_channels = in_channels + out_channels = in_channels if out_channels is None else out_channels + self.out_channels = out_channels + + self.norm1 = nn.GroupNorm(num_groups=32, num_channels=in_channels, eps=1e-6, affine=True) + self.conv1 = nn.Conv2d(in_channels, out_channels, kernel_size=3, stride=1, padding=1) + self.norm2 = nn.GroupNorm(num_groups=32, num_channels=out_channels, eps=1e-6, affine=True) + self.conv2 = nn.Conv2d(out_channels, out_channels, kernel_size=3, stride=1, padding=1) + if self.in_channels != self.out_channels: + self.nin_shortcut = nn.Conv2d(in_channels, out_channels, kernel_size=1, stride=1, padding=0) + + def forward(self, x): + h = x + h = self.norm1(h) + h = swish(h) + h = self.conv1(h) + + h = self.norm2(h) + h = swish(h) + h = self.conv2(h) + + if self.in_channels != self.out_channels: + x = self.nin_shortcut(x) + + return x + h + + +class Downsample(nn.Module): + def __init__(self, in_channels: int): + super().__init__() + # no asymmetric padding in torch conv, must do it ourselves + self.conv = nn.Conv2d(in_channels, in_channels, kernel_size=3, stride=2, padding=0) + + def forward(self, x: Tensor): + pad = (0, 1, 0, 1) + x = nn.functional.pad(x, pad, mode="constant", value=0) + x = self.conv(x) + return x + + +class Upsample(nn.Module): + def __init__(self, in_channels: int): + super().__init__() + self.conv = nn.Conv2d(in_channels, in_channels, kernel_size=3, stride=1, padding=1) + + def forward(self, x: Tensor): + x = nn.functional.interpolate(x, scale_factor=2.0, mode="nearest") + x = self.conv(x) + return x + + +class Encoder(nn.Module): + def __init__( + self, + resolution: int, + in_channels: int, + ch: int, + ch_mult: list[int], + num_res_blocks: int, + z_channels: int, + ): + super().__init__() + self.quant_conv = torch.nn.Conv2d(2 * z_channels, 2 * z_channels, 1) + self.ch = ch + self.num_resolutions = len(ch_mult) + self.num_res_blocks = num_res_blocks + self.resolution = resolution + self.in_channels = in_channels + # downsampling + self.conv_in = nn.Conv2d(in_channels, self.ch, kernel_size=3, stride=1, padding=1) + + curr_res = resolution + in_ch_mult = (1,) + tuple(ch_mult) + self.in_ch_mult = in_ch_mult + self.down = nn.ModuleList() + block_in = self.ch + for i_level in range(self.num_resolutions): + block = nn.ModuleList() + attn = nn.ModuleList() + block_in = ch * in_ch_mult[i_level] + block_out = ch * ch_mult[i_level] + for _ in range(self.num_res_blocks): + block.append(ResnetBlock(in_channels=block_in, out_channels=block_out)) + block_in = block_out + down = nn.Module() + down.block = block + down.attn = attn + if i_level != self.num_resolutions - 1: + down.downsample = Downsample(block_in) + curr_res = curr_res // 2 + self.down.append(down) + + # middle + self.mid = nn.Module() + self.mid.block_1 = ResnetBlock(in_channels=block_in, out_channels=block_in) + self.mid.attn_1 = AttnBlock(block_in) + self.mid.block_2 = ResnetBlock(in_channels=block_in, out_channels=block_in) + + # end + self.norm_out = nn.GroupNorm(num_groups=32, num_channels=block_in, eps=1e-6, affine=True) + self.conv_out = nn.Conv2d(block_in, 2 * z_channels, kernel_size=3, stride=1, padding=1) + + def forward(self, x: Tensor) -> Tensor: + # downsampling + hs = [self.conv_in(x)] + for i_level in range(self.num_resolutions): + for i_block in range(self.num_res_blocks): + h = self.down[i_level].block[i_block](hs[-1]) # type: ignore[index, operator] + if len(self.down[i_level].attn) > 0: # type: ignore[arg-type] + h = self.down[i_level].attn[i_block](h) # type: ignore[index, operator] + hs.append(h) + if i_level != self.num_resolutions - 1: + hs.append(self.down[i_level].downsample(hs[-1])) # type: ignore[operator] + + # middle + h = hs[-1] + h = self.mid.block_1(h) # type: ignore[operator] + h = self.mid.attn_1(h) # type: ignore[operator] + h = self.mid.block_2(h) # type: ignore[operator] + # end + h = self.norm_out(h) + h = swish(h) + h = self.conv_out(h) + h = self.quant_conv(h) + return h + + +class Decoder(nn.Module): + def __init__( + self, + ch: int, + out_ch: int, + ch_mult: list[int], + num_res_blocks: int, + in_channels: int, + resolution: int, + z_channels: int, + ): + super().__init__() + self.post_quant_conv = torch.nn.Conv2d(z_channels, z_channels, 1) + self.ch = ch + self.num_resolutions = len(ch_mult) + self.num_res_blocks = num_res_blocks + self.resolution = resolution + self.in_channels = in_channels + self.ffactor = 2 ** (self.num_resolutions - 1) + + # compute in_ch_mult, block_in and curr_res at lowest res + block_in = ch * ch_mult[self.num_resolutions - 1] + curr_res = resolution // 2 ** (self.num_resolutions - 1) + self.z_shape = (1, z_channels, curr_res, curr_res) + + # z to block_in + self.conv_in = nn.Conv2d(z_channels, block_in, kernel_size=3, stride=1, padding=1) + + # middle + self.mid = nn.Module() + self.mid.block_1 = ResnetBlock(in_channels=block_in, out_channels=block_in) + self.mid.attn_1 = AttnBlock(block_in) + self.mid.block_2 = ResnetBlock(in_channels=block_in, out_channels=block_in) + + # upsampling + self.up = nn.ModuleList() + for i_level in reversed(range(self.num_resolutions)): + block = nn.ModuleList() + attn = nn.ModuleList() + block_out = ch * ch_mult[i_level] + for _ in range(self.num_res_blocks + 1): + block.append(ResnetBlock(in_channels=block_in, out_channels=block_out)) + block_in = block_out + up = nn.Module() + up.block = block + up.attn = attn + if i_level != 0: + up.upsample = Upsample(block_in) + curr_res = curr_res * 2 + self.up.insert(0, up) # prepend to get consistent order + + # end + self.norm_out = nn.GroupNorm(num_groups=32, num_channels=block_in, eps=1e-6, affine=True) + self.conv_out = nn.Conv2d(block_in, out_ch, kernel_size=3, stride=1, padding=1) + + def forward(self, z: Tensor) -> Tensor: + z = self.post_quant_conv(z) + + # get dtype for proper tracing + upscale_dtype = next(self.up.parameters()).dtype + + # z to block_in + h = self.conv_in(z) + + # middle + h = self.mid.block_1(h) # type: ignore[operator] + h = self.mid.attn_1(h) # type: ignore[operator] + h = self.mid.block_2(h) # type: ignore[operator] + + # cast to proper dtype + h = h.to(upscale_dtype) + # upsampling + for i_level in reversed(range(self.num_resolutions)): + for i_block in range(self.num_res_blocks + 1): + h = self.up[i_level].block[i_block](h) # type: ignore[index, operator] + if len(self.up[i_level].attn) > 0: # type: ignore[arg-type] + h = self.up[i_level].attn[i_block](h) # type: ignore[index, operator] + if i_level != 0: + h = self.up[i_level].upsample(h) # type: ignore[operator] + + # end + h = self.norm_out(h) + h = swish(h) + h = self.conv_out(h) + return h + + +class AutoEncoder(nn.Module): + def __init__(self, params: AutoEncoderParams): + super().__init__() + self.params = params + self.encoder = Encoder( + resolution=params.resolution, + in_channels=params.in_channels, + ch=params.ch, + ch_mult=params.ch_mult, + num_res_blocks=params.num_res_blocks, + z_channels=params.z_channels, + ) + self.decoder = Decoder( + resolution=params.resolution, + in_channels=params.in_channels, + ch=params.ch, + out_ch=params.out_ch, + ch_mult=params.ch_mult, + num_res_blocks=params.num_res_blocks, + z_channels=params.z_channels, + ) + + self.bn_eps = 1e-4 + self.bn_momentum = 0.1 + self.ps = [2, 2] + self.bn = torch.nn.BatchNorm2d( + math.prod(self.ps) * params.z_channels, + eps=self.bn_eps, + momentum=self.bn_momentum, + affine=False, + track_running_stats=True, + ) + + +_NUM_RESOLUTIONS = 4 + + +def convert_diffusers_state_dict(src: dict[str, Tensor]) -> dict[str, Tensor]: + out: dict[str, Tensor] = {} + attn_substrings = (".mid.attn_1.",) + for src_key, tensor in src.items(): + dst_key = _rewrite_diffusers_key(src_key) + if dst_key is None: + raise KeyError(f"Unrecognized diffusers VAE state-dict key: {src_key}") + if any(s in dst_key for s in attn_substrings) and dst_key.endswith(".weight") and tensor.ndim == 2: + tensor = tensor.unsqueeze(-1).unsqueeze(-1) + out[dst_key] = tensor + return out + + +def _rewrite_diffusers_key(key: str) -> str | None: + if key.startswith("bn."): + return key + + if key.startswith("quant_conv."): + return key.replace("quant_conv.", "encoder.quant_conv.", 1) + if key.startswith("post_quant_conv."): + return key.replace("post_quant_conv.", "decoder.post_quant_conv.", 1) + + if key == "encoder.conv_norm_out.weight": + return "encoder.norm_out.weight" + if key == "encoder.conv_norm_out.bias": + return "encoder.norm_out.bias" + if key == "decoder.conv_norm_out.weight": + return "decoder.norm_out.weight" + if key == "decoder.conv_norm_out.bias": + return "decoder.norm_out.bias" + + m = re.match(r"^(encoder|decoder)\.mid_block\.resnets\.(\d+)\.(.+)$", key) + if m: + side, idx, rest = m.group(1), int(m.group(2)), m.group(3) + rest = rest.replace("conv_shortcut", "nin_shortcut") + return f"{side}.mid.block_{idx + 1}.{rest}" + m = re.match(r"^(encoder|decoder)\.mid_block\.attentions\.0\.(.+)$", key) + if m: + side, rest = m.group(1), m.group(2) + rest = ( + rest.replace("group_norm.", "norm.") + .replace("to_q.", "q.") + .replace("to_k.", "k.") + .replace("to_v.", "v.") + .replace("to_out.0.", "proj_out.") + ) + return f"{side}.mid.attn_1.{rest}" + + m = re.match(r"^encoder\.down_blocks\.(\d+)\.resnets\.(\d+)\.(.+)$", key) + if m: + level, res_idx, rest = m.group(1), m.group(2), m.group(3) + rest = rest.replace("conv_shortcut", "nin_shortcut") + return f"encoder.down.{level}.block.{res_idx}.{rest}" + m = re.match(r"^encoder\.down_blocks\.(\d+)\.downsamplers\.0\.conv\.(.+)$", key) + if m: + return f"encoder.down.{m.group(1)}.downsample.conv.{m.group(2)}" + + m = re.match(r"^decoder\.up_blocks\.(\d+)\.resnets\.(\d+)\.(.+)$", key) + if m: + diffusers_idx = int(m.group(1)) + res_idx = m.group(2) + rest = m.group(3).replace("conv_shortcut", "nin_shortcut") + return f"decoder.up.{_NUM_RESOLUTIONS - 1 - diffusers_idx}.block.{res_idx}.{rest}" + m = re.match(r"^decoder\.up_blocks\.(\d+)\.upsamplers\.0\.conv\.(.+)$", key) + if m: + diffusers_idx = int(m.group(1)) + return f"decoder.up.{_NUM_RESOLUTIONS - 1 - diffusers_idx}.upsample.conv.{m.group(2)}" + + if key.startswith(("encoder.conv_in.", "encoder.conv_out.", "decoder.conv_in.", "decoder.conv_out.")): + return key + + return None diff --git a/invokeai/backend/ideogram4/caption.py b/invokeai/backend/ideogram4/caption.py new file mode 100644 index 00000000000..a8c1582498d --- /dev/null +++ b/invokeai/backend/ideogram4/caption.py @@ -0,0 +1,92 @@ +"""Runtime assembly of Ideogram 4's structured JSON caption. + +This is the Python port of the frontend ``buildIdeogram4Caption`` (buildIdeogram4Prompt.ts). It runs +at generation time (inside the ``ideogram4_caption_builder`` node) rather than at graph-build time, so +that dynamic-prompt expansions and prompt batching — which vary the *global* prompt — are reflected in +the encoded caption. The regions (description + bbox) and color palette are fixed per generation and +are passed in as node inputs. + +Schema notes (must match the reference the model was trained on): + - bbox is ``[y_min, x_min, y_max, x_max]``, normalized to 0–1000, origin top-left. The graph builder + computes it from canvas coordinates; here it is passed through verbatim. + - Key order matters: ``high_level_description``, (``style_description``), ``compositional_deconstruction``; + ``obj`` elements use ``type``, ``bbox``, ``desc``. Python dicts preserve insertion order. + - Serialized with compact separators and non-ASCII preserved (matches JS ``JSON.stringify`` and the + reference's ``ensure_ascii=False``). +""" + +import json +import re +from typing import Optional + +_HEX_COLOR_RE = re.compile(r"#[0-9A-F]{6}") + +# Centered, deliberately sub-full-frame bbox ([y_min, x_min, y_max, x_max], 0–1000) for the element we +# auto-synthesize when the user drew no regions. Empirically, Ideogram 4's built-in safety filter blocks +# "degenerate" captions — an empty ``elements`` list, or a single *full-frame* [0,0,1000,1000] element +# whose desc merely repeats ``high_level_description``. A partial bbox (or a distinct desc) avoids the +# block; since a no-region prompt only gives us one description, we make the default element partial. +_DEFAULT_SCENE_BBOX = (100, 100, 900, 900) + + +def build_ideogram4_caption( + global_prompt: str, + regions: list[tuple[str, Optional[list[int]]]], + color_palette: list[str], +) -> str: + """Assemble the Ideogram 4 prompt from a global prompt, regions, and an optional color palette. + + - Raw-JSON passthrough: if the trimmed global prompt already starts with ``{`` it is returned + verbatim (the user controls the JSON; regions/palette are ignored). + - Otherwise a structured JSON caption is always built — regions become ``obj`` elements and a + palette becomes ``style_description.color_palette``. A prompt with neither still becomes a + minimal caption (just ``high_level_description``), never bare plain text: Ideogram is trained on + the JSON schema and its safety filter false-positives far more on plain text. + + ``regions`` is a list of ``(description, bbox)`` where bbox is ``[y_min, x_min, y_max, x_max]`` or + None. Regions with a blank description are dropped. + """ + trimmed = global_prompt.strip() + + # The user pasted a structured caption (or any JSON object) — use it verbatim. + if trimmed.startswith("{"): + return global_prompt + + elements: list[dict] = [] + for description, bbox in regions: + if not description.strip(): + continue + if bbox is not None: + elements.append({"type": "obj", "bbox": bbox, "desc": description}) + else: + elements.append({"type": "obj", "desc": description}) + + # No usable regions: synthesize one default element describing the whole scene from the prompt, with + # a partial (non-full-frame) bbox. An empty `elements` list — or a full-frame element repeating the + # prompt — trips Ideogram's safety filter (verified empirically); a partial default box avoids it. + if not elements: + elements = [{"type": "obj", "bbox": list(_DEFAULT_SCENE_BBOX), "desc": trimmed}] + + # Normalize the palette to uppercase #RRGGBB (the schema's required hex form); drop invalid entries. + # Mirror the JS order: uppercase first, then validate. + palette = [c.upper() for c in color_palette if _HEX_COLOR_RE.fullmatch(c.upper())] + + # Always emit a structured caption (never bare plain text): Ideogram 4 is trained on the JSON schema + # and its built-in safety filter false-positives far more often on plain-text prompts than on + # structured JSON. A prompt with no regions/palette becomes a minimal caption carrying just the + # high_level_description (with an empty compositional_deconstruction). Raw-JSON pastes still pass + # through verbatim above. + compositional_deconstruction = {"background": "", "elements": elements} + if palette: + caption = { + "high_level_description": trimmed, + "style_description": {"color_palette": palette}, + "compositional_deconstruction": compositional_deconstruction, + } + else: + caption = { + "high_level_description": trimmed, + "compositional_deconstruction": compositional_deconstruction, + } + + return json.dumps(caption, separators=(",", ":"), ensure_ascii=False) diff --git a/invokeai/backend/ideogram4/constants.py b/invokeai/backend/ideogram4/constants.py new file mode 100644 index 00000000000..442929f2692 --- /dev/null +++ b/invokeai/backend/ideogram4/constants.py @@ -0,0 +1,11 @@ +SEQUENCE_PADDING_INDICATOR = -1 + +OUTPUT_IMAGE_INDICATOR = 2 +LLM_TOKEN_INDICATOR = 3 + +# Image grid coordinates start at this offset so they never collide with text token indices +# (text positions start at 0 and never exceed max_text_tokens, which is well below this). +IMAGE_POSITION_OFFSET = 65536 + +# Layers of Qwen3-VL whose hidden states are concatenated and fed to the transformer. +QWEN3_VL_ACTIVATION_LAYERS = (0, 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, 35) diff --git a/invokeai/backend/ideogram4/denoise.py b/invokeai/backend/ideogram4/denoise.py new file mode 100644 index 00000000000..2f985595711 --- /dev/null +++ b/invokeai/backend/ideogram4/denoise.py @@ -0,0 +1,126 @@ +"""Ideogram 4 denoising loop. + +Ports ``Ideogram4Pipeline.__call__``'s sampling loop, decoupled from model loading +and text encoding. Runs the Euler flow-matching loop with dual-branch asymmetric +CFG: the conditional transformer over the packed ``[text][image]`` sequence and the +unconditional transformer over image-only tokens with zeroed conditioning. +""" + +from __future__ import annotations + +from typing import Callable, Optional, Sequence + +import torch + +from invokeai.backend.ideogram4.modeling_ideogram4 import Ideogram4Transformer +from invokeai.backend.ideogram4.sampling_utils import ( + LATENT_DIM, + build_denoise_inputs, + pack_latents_to_grid, +) +from invokeai.backend.ideogram4.scheduler import get_schedule_for_resolution, make_step_intervals + +# Called after each completed step with (step_index, total_steps, packed_latents), where +# packed_latents is the current estimate in packed grid form ``(1, LATENT_DIM, grid_h, grid_w)`` — +# ready for a preview (unpatchify + VAE decode / RGB approximation) without re-deriving the grid. +StepCallback = Callable[[int, int, torch.Tensor], None] + + +@torch.no_grad() +def run_ideogram4_denoise( + *, + conditional_transformer: Ideogram4Transformer, + unconditional_transformer: Ideogram4Transformer, + llm_features: torch.Tensor, + height: int, + width: int, + num_steps: int, + mu: float, + std: float, + guidance_schedule: Optional[Sequence[float]] = None, + guidance_scale: float = 7.0, + seed: Optional[int] = None, + device: torch.device, + step_callback: Optional[StepCallback] = None, +) -> torch.Tensor: + """Sample latents for a single image. + + Args: + conditional_transformer / unconditional_transformer: the two DiT branches. + llm_features: ``(num_text_tokens, 53248)`` text conditioning on ``device``. + guidance_schedule: per-step guidance weights in loop-INDEX order (index 0 is + the last/polish step), length ``num_steps``. Falls back to a constant + ``guidance_scale`` when ``None``. + + Returns: + Packed latents ``(1, LATENT_DIM, grid_h, grid_w)``. + """ + num_text_tokens = int(llm_features.shape[0]) + llm_dim = int(llm_features.shape[-1]) + + inputs = build_denoise_inputs(num_text_tokens, height, width, device) + num_image_tokens = inputs["num_image_tokens"] + grid_h, grid_w = inputs["grid_h"], inputs["grid_w"] + + schedule = get_schedule_for_resolution((height, width), known_mean=mu, std=std) + step_intervals = make_step_intervals(num_steps).to(device) + + if guidance_schedule is not None: + gw_per_step = torch.as_tensor(guidance_schedule, dtype=torch.float32, device=device) + if gw_per_step.shape != (num_steps,): + raise ValueError(f"guidance_schedule must have length {num_steps}, got {tuple(gw_per_step.shape)}") + else: + gw_per_step = torch.full((num_steps,), float(guidance_scale), dtype=torch.float32, device=device) + + # Conditional branch: text features followed by zeros for the image tokens. + llm_features_full = torch.zeros( + 1, num_text_tokens + num_image_tokens, llm_dim, dtype=llm_features.dtype, device=device + ) + llm_features_full[0, :num_text_tokens] = llm_features.to(device) + + # Unconditional (negative) branch is image-only with zeroed conditioning. + neg_position_ids = inputs["position_ids"][:, num_text_tokens:] + neg_segment_ids = inputs["segment_ids"][:, num_text_tokens:] + neg_indicator = inputs["indicator"][:, num_text_tokens:] + neg_llm_features = torch.zeros(1, num_image_tokens, llm_dim, dtype=llm_features.dtype, device=device) + + generator = torch.Generator(device=device) + if seed is not None: + generator.manual_seed(seed) + z = torch.randn(1, num_image_tokens, LATENT_DIM, dtype=torch.float32, device=device, generator=generator) + text_z_padding = torch.zeros(1, num_text_tokens, LATENT_DIM, dtype=torch.float32, device=device) + + for i in range(num_steps - 1, -1, -1): + t_val = float(schedule(step_intervals[i + 1].unsqueeze(0)).item()) + s_val = float(schedule(step_intervals[i].unsqueeze(0)).item()) + t = torch.full((1,), t_val, dtype=torch.float32, device=device) + + pos_z = torch.cat([text_z_padding, z], dim=1) + pos_out = conditional_transformer( + llm_features=llm_features_full, + x=pos_z, + t=t, + position_ids=inputs["position_ids"], + segment_ids=inputs["segment_ids"], + indicator=inputs["indicator"], + ) + pos_v = pos_out[:, num_text_tokens:] + + neg_v = unconditional_transformer( + llm_features=neg_llm_features, + x=z, + t=t, + position_ids=neg_position_ids, + segment_ids=neg_segment_ids, + indicator=neg_indicator, + ) + + gw_i = gw_per_step[i] + v = gw_i * pos_v + (1.0 - gw_i) * neg_v + z = z + v * (s_val - t_val) + + if step_callback is not None: + # Hand the callback the current estimate in packed grid form so it can render a preview. + step_callback(num_steps - i, num_steps, pack_latents_to_grid(z, grid_h, grid_w)) + + return pack_latents_to_grid(z, grid_h, grid_w) diff --git a/invokeai/backend/ideogram4/latent_norm.py b/invokeai/backend/ideogram4/latent_norm.py new file mode 100644 index 00000000000..225c4ed5049 --- /dev/null +++ b/invokeai/backend/ideogram4/latent_norm.py @@ -0,0 +1,272 @@ +from __future__ import annotations + +import torch + +LATENT_SHIFT: tuple[float, ...] = ( + 0.01984364, + 0.10149707, + 0.29689495, + 0.27188619, + -0.21445648, + -0.15979549, + 0.05021099, + -0.15083604, + -0.15360136, + -0.20131799, + 0.01922352, + 0.0622626, + 0.10140969, + -0.06739428, + 0.3758261, + -0.233712, + 0.35164491, + -0.02590912, + -0.0271935, + -0.10833897, + -0.1476848, + -0.01130957, + -0.2298372, + 0.23526423, + -0.10893522, + 0.11957631, + 0.04047799, + 0.3134589, + -0.17225064, + -0.18646109, + -0.34691978, + -0.03571246, + 0.02583857, + 0.10190072, + 0.28402294, + 0.26952152, + -0.21634675, + -0.17938656, + 0.04358909, + -0.15007621, + -0.1548502, + -0.18971131, + 0.02710861, + 0.05609494, + 0.10697846, + -0.06854968, + 0.38167698, + -0.24269937, + 0.35705471, + -0.03063305, + -0.02946109, + -0.11244286, + -0.14336038, + -0.01362137, + -0.21863696, + 0.23228983, + -0.11739769, + 0.11693044, + 0.02563311, + 0.31356594, + -0.17420591, + -0.19006285, + -0.34905377, + -0.04025005, + 0.01924137, + 0.07652984, + 0.2995608, + 0.2628057, + -0.22011674, + -0.12715361, + 0.04879879, + -0.14075719, + -0.15935895, + -0.2123584, + 0.01974813, + 0.05523547, + 0.10011992, + -0.06428964, + 0.37781868, + -0.21491644, + 0.34254215, + -0.03153528, + -0.0310082, + -0.10761415, + -0.14730405, + -0.02475182, + -0.2285588, + 0.2515081, + -0.10445128, + 0.12446, + 0.07062869, + 0.30880162, + -0.18016875, + -0.18869164, + -0.34533499, + -0.0129177, + 0.02578168, + 0.07993659, + 0.28642181, + 0.26038408, + -0.22459419, + -0.14820155, + 0.04059549, + -0.14043529, + -0.16111187, + -0.2020305, + 0.02602069, + 0.04852717, + 0.10432153, + -0.06309942, + 0.38402443, + -0.22397003, + 0.34814481, + -0.03774432, + -0.03381438, + -0.11245691, + -0.14128767, + -0.02853208, + -0.21752016, + 0.24872463, + -0.11399775, + 0.1222687, + 0.05620835, + 0.309178, + -0.18065738, + -0.19401479, + -0.34495114, + -0.01760592, +) + +LATENT_SCALE: tuple[float, ...] = ( + 1.63933691, + 1.70204478, + 1.73642566, + 1.90004803, + 1.6675316, + 1.69059584, + 1.56853198, + 1.62314944, + 1.89106626, + 1.58086668, + 1.60822129, + 1.60962993, + 1.63322129, + 1.56074359, + 1.73419528, + 1.7919265, + 1.64040632, + 1.66802808, + 1.60390303, + 1.75480492, + 1.63187587, + 1.64334594, + 1.61722884, + 1.60146046, + 1.63459219, + 1.55291476, + 1.68771497, + 1.68415657, + 1.78966054, + 1.66631641, + 1.65626686, + 1.65976433, + 1.63487607, + 1.69513249, + 1.72933756, + 1.91310663, + 1.67035057, + 1.72286863, + 1.56719251, + 1.61934825, + 1.88628859, + 1.56911539, + 1.59455129, + 1.60829869, + 1.62470611, + 1.56052853, + 1.73677003, + 1.77563606, + 1.63732541, + 1.66370527, + 1.59508952, + 1.75153949, + 1.63029275, + 1.64517667, + 1.61659342, + 1.59722044, + 1.64103121, + 1.5408531, + 1.68610394, + 1.67772755, + 1.78998563, + 1.66621713, + 1.65458955, + 1.66041308, + 1.64710857, + 1.68163503, + 1.74000294, + 1.92784786, + 1.67411194, + 1.67395548, + 1.57406532, + 1.62199356, + 1.87618195, + 1.5584375, + 1.57438785, + 1.61711053, + 1.63094305, + 1.55644029, + 1.73124302, + 1.80666627, + 1.6463621, + 1.65932006, + 1.60816188, + 1.75682671, + 1.64695873, + 1.63121722, + 1.61380832, + 1.60478651, + 1.63396035, + 1.53505068, + 1.65534289, + 1.67132281, + 1.80317197, + 1.6767314, + 1.65700938, + 1.68426259, + 1.65339716, + 1.67540638, + 1.73298504, + 1.94067348, + 1.67893609, + 1.70635117, + 1.5730906, + 1.61928553, + 1.87148809, + 1.56244866, + 1.56697152, + 1.61584394, + 1.62759496, + 1.55480378, + 1.73484107, + 1.79055143, + 1.64688773, + 1.66121492, + 1.60135887, + 1.75254572, + 1.64798332, + 1.62989921, + 1.61381592, + 1.60792883, + 1.63939668, + 1.53075757, + 1.65371318, + 1.66801185, + 1.80029087, + 1.67591476, + 1.65655173, + 1.68533454, +) + + +def get_latent_norm() -> tuple[torch.Tensor, torch.Tensor]: + shift = torch.tensor(LATENT_SHIFT, dtype=torch.float32) + scale = torch.tensor(LATENT_SCALE, dtype=torch.float32) + assert shift.shape == (128,) and scale.shape == (128,) + return shift, scale diff --git a/invokeai/backend/ideogram4/modeling_ideogram4.py b/invokeai/backend/ideogram4/modeling_ideogram4.py new file mode 100644 index 00000000000..6ab11c659c6 --- /dev/null +++ b/invokeai/backend/ideogram4/modeling_ideogram4.py @@ -0,0 +1,367 @@ +"""Ideogram4 transformer backbone. + +The transformer consumes Qwen3-VL embeddings and flow-matching noise tokens to +produce velocity predictions on image latents. +""" + +from __future__ import annotations + +import math +from dataclasses import dataclass + +import torch +import torch.nn as nn +import torch.nn.functional as F + +from invokeai.backend.ideogram4.constants import ( + LLM_TOKEN_INDICATOR, + OUTPUT_IMAGE_INDICATOR, + QWEN3_VL_ACTIVATION_LAYERS, +) + + +@dataclass +class Ideogram4Config: + emb_dim: int = 4608 + num_layers: int = 34 + num_heads: int = 18 + intermediate_size: int = 12288 + adanln_dim: int = 512 + + # Latent dimension after patchification: ae_channels (32) * patch_size**2 (4) = 128. + in_channels: int = 128 + + # Hidden size of Qwen3-VL-8B-Instruct multiplied by the number of layers we extract + # Qwen3-VL hidden size = 4096 + llm_features_dim: int = 4096 * len(QWEN3_VL_ACTIVATION_LAYERS) + + rope_theta: int = 5_000_000 + mrope_section: tuple[int, ...] = (24, 20, 20) + + norm_eps: float = 1e-5 + + +def _rotate_half(x: torch.Tensor) -> torch.Tensor: + half = x.shape[-1] // 2 + x1 = x[..., :half] + x2 = x[..., half:] + return torch.cat((-x2, x1), dim=-1) + + +def _apply_rotary_pos_emb( + q: torch.Tensor, + k: torch.Tensor, + cos: torch.Tensor, + sin: torch.Tensor, +) -> tuple[torch.Tensor, torch.Tensor]: + # q, k: (B, num_heads, L, head_dim); cos/sin: (B, L, head_dim). + cos = cos.unsqueeze(1) + sin = sin.unsqueeze(1) + q_embed = (q * cos) + (_rotate_half(q) * sin) + k_embed = (k * cos) + (_rotate_half(k) * sin) + return q_embed, k_embed + + +class Ideogram4MRoPE(nn.Module): + inv_freq: torch.Tensor + + def __init__( + self, + head_dim: int, + base: int, + mrope_section: tuple[int, ...], + ) -> None: + super().__init__() + inv_freq = 1.0 / (base ** (torch.arange(0, head_dim, 2, dtype=torch.float32) / head_dim)) + self.register_buffer("inv_freq", inv_freq, persistent=False) + self.mrope_section = tuple(mrope_section) + self.head_dim = head_dim + + @torch.no_grad() + def forward(self, position_ids: torch.Tensor) -> tuple[torch.Tensor, torch.Tensor]: + # position_ids: (B, L, 3) of int. + assert position_ids.ndim == 3 and position_ids.shape[-1] == 3 + batch_size, seq_len, _ = position_ids.shape + + # (3, B, inv_freq_size, L) + pos = position_ids.permute(2, 0, 1).to(dtype=torch.float32) # type: ignore[arg-type] + inv_freq = self.inv_freq.to(dtype=torch.float32)[None, None, :, None].expand(3, batch_size, -1, 1) # type: ignore[index] + freqs = inv_freq @ pos.unsqueeze(2) + freqs = freqs.transpose(2, 3) # (3, B, L, inv_freq_size) + + # interleaved mrope: pull H freqs into idx 1 mod 3, W freqs into idx 2 mod 3. + freqs_t = freqs[0].clone() + for axis, offset in ((1, 1), (2, 2)): + length = self.mrope_section[axis] * 3 + idx = torch.arange(offset, length, 3, device=freqs_t.device) + freqs_t[..., idx] = freqs[axis][..., idx] + + emb = torch.cat((freqs_t, freqs_t), dim=-1) + return emb.cos(), emb.sin() + + +class Ideogram4RMSNorm(nn.Module): + def __init__(self, dim: int, eps: float = 1e-6) -> None: + super().__init__() + self.weight = nn.Parameter(torch.ones(dim)) + self.eps = eps + + def forward(self, x: torch.Tensor) -> torch.Tensor: + return F.rms_norm(x, self.weight.shape, self.weight, self.eps) + + +class Ideogram4Attention(nn.Module): + def __init__(self, hidden_size: int, num_heads: int, eps: float = 1e-5) -> None: + super().__init__() + assert hidden_size % num_heads == 0 + self.hidden_size = hidden_size + self.num_heads = num_heads + self.head_dim = hidden_size // num_heads + + self.qkv = nn.Linear(hidden_size, hidden_size * 3, bias=False) + self.norm_q = Ideogram4RMSNorm(self.head_dim, eps=eps) + self.norm_k = Ideogram4RMSNorm(self.head_dim, eps=eps) + self.o = nn.Linear(hidden_size, hidden_size, bias=False) + + def forward( + self, + x: torch.Tensor, + segment_ids: torch.Tensor, + cos: torch.Tensor, + sin: torch.Tensor, + ) -> torch.Tensor: + batch_size, seq_len, _ = x.shape + + qkv = self.qkv(x) + qkv = qkv.view(batch_size, seq_len, 3, self.num_heads, self.head_dim) + q, k, v = qkv.unbind(dim=2) + + q = self.norm_q(q) + k = self.norm_k(k) + + # SDPA expects (B, num_heads, L, head_dim). + q = q.transpose(1, 2) + k = k.transpose(1, 2) + v = v.transpose(1, 2) + + q, k = _apply_rotary_pos_emb(q, k, cos, sin) + + # Block-diagonal mask from segment ids: (B, 1, L, L), True = attend. + attn_mask = (segment_ids.unsqueeze(2) == segment_ids.unsqueeze(1)).unsqueeze(1) + + out = F.scaled_dot_product_attention(q, k, v, attn_mask=attn_mask) + out = out.transpose(1, 2).reshape(batch_size, seq_len, self.hidden_size) + return self.o(out) + + +class Ideogram4MLP(nn.Module): + def __init__(self, dim: int, hidden_dim: int) -> None: + super().__init__() + self.w1 = nn.Linear(dim, hidden_dim, bias=False) + self.w2 = nn.Linear(hidden_dim, dim, bias=False) + self.w3 = nn.Linear(dim, hidden_dim, bias=False) + + def forward(self, x: torch.Tensor) -> torch.Tensor: + return self.w2(F.silu(self.w1(x)) * self.w3(x)) + + +class Ideogram4TransformerBlock(nn.Module): + def __init__( + self, + hidden_size: int, + intermediate_size: int, + num_heads: int, + norm_eps: float, + adanln_dim: int, + ) -> None: + super().__init__() + self.attention = Ideogram4Attention(hidden_size, num_heads, eps=1e-5) + self.feed_forward = Ideogram4MLP(hidden_size, intermediate_size) + + self.attention_norm1 = Ideogram4RMSNorm(hidden_size, eps=norm_eps) + self.ffn_norm1 = Ideogram4RMSNorm(hidden_size, eps=norm_eps) + self.attention_norm2 = Ideogram4RMSNorm(hidden_size, eps=norm_eps) + self.ffn_norm2 = Ideogram4RMSNorm(hidden_size, eps=norm_eps) + + self.adaln_modulation = nn.Linear(adanln_dim, 4 * hidden_size, bias=True) + + def forward( + self, + x: torch.Tensor, + segment_ids: torch.Tensor, + cos: torch.Tensor, + sin: torch.Tensor, + adaln_input: torch.Tensor, + ) -> torch.Tensor: + mod = self.adaln_modulation(adaln_input) + scale_msa, gate_msa, scale_mlp, gate_mlp = mod.chunk(4, dim=-1) + gate_msa = torch.tanh(gate_msa) + gate_mlp = torch.tanh(gate_mlp) + scale_msa = 1.0 + scale_msa + scale_mlp = 1.0 + scale_mlp + + attn_out = self.attention( + self.attention_norm1(x) * scale_msa, + segment_ids=segment_ids, + cos=cos, + sin=sin, + ) + x = x + gate_msa * self.attention_norm2(attn_out) + x = x + gate_mlp * self.ffn_norm2(self.feed_forward(self.ffn_norm1(x) * scale_mlp)) + return x + + +def _sinusoidal_embedding(t: torch.Tensor, dim: int, scale: float = 1e4) -> torch.Tensor: + t = t.to(torch.float32) + half = dim // 2 + freq = math.log(scale) / (half - 1) + freq = torch.exp(torch.arange(half, dtype=torch.float32, device=t.device) * -freq) # type: ignore[assignment] + emb = t.unsqueeze(-1) * freq + emb = torch.cat([torch.sin(emb), torch.cos(emb)], dim=-1) + if dim % 2 == 1: + emb = F.pad(emb, (0, 1)) + return emb + + +class Ideogram4EmbedScalar(nn.Module): + def __init__(self, dim: int, input_range: tuple[float, float]) -> None: + super().__init__() + self.dim = dim + self.range_min, self.range_max = input_range + assert self.range_max > self.range_min + self.mlp_in = nn.Linear(dim, dim, bias=True) + self.mlp_out = nn.Linear(dim, dim, bias=True) + + def forward(self, x: torch.Tensor) -> torch.Tensor: + # x is shape (..., 1) or (...,) holding a scalar per token. + x = x.to(torch.float32) + scaled = 1e4 * (x - self.range_min) / (self.range_max - self.range_min) + emb = _sinusoidal_embedding(scaled, self.dim) + emb = emb.to(getattr(self.mlp_in, "compute_dtype", None) or self.mlp_in.weight.dtype) + emb = F.silu(self.mlp_in(emb)) + return self.mlp_out(emb) + + +class Ideogram4FinalLayer(nn.Module): + def __init__(self, hidden_size: int, out_channels: int, adanln_dim: int) -> None: + super().__init__() + self.norm_final = nn.LayerNorm(hidden_size, eps=1e-6, elementwise_affine=False) + self.linear = nn.Linear(hidden_size, out_channels, bias=True) + self.adaln_modulation = nn.Linear(adanln_dim, hidden_size, bias=True) + + def forward(self, x: torch.Tensor, c: torch.Tensor) -> torch.Tensor: + scale = 1.0 + self.adaln_modulation(F.silu(c)) + return self.linear(self.norm_final(x) * scale) + + +class Ideogram4Transformer(nn.Module): + """Ideogram 4 flow-matching transformer.""" + + def __init__(self, config: Ideogram4Config) -> None: + super().__init__() + self.config = config + + head_dim = config.emb_dim // config.num_heads + + self.input_proj = nn.Linear(config.in_channels, config.emb_dim, bias=True) + self.llm_cond_norm = Ideogram4RMSNorm(config.llm_features_dim, eps=1e-6) + self.llm_cond_proj = nn.Linear(config.llm_features_dim, config.emb_dim, bias=True) + self.t_embedding = Ideogram4EmbedScalar(config.emb_dim, input_range=(0.0, 1.0)) + self.adaln_proj = nn.Linear(config.emb_dim, config.adanln_dim, bias=True) + + self.embed_image_indicator = nn.Embedding(2, config.emb_dim) + + self.rotary_emb = Ideogram4MRoPE( + head_dim=head_dim, + base=config.rope_theta, + mrope_section=config.mrope_section, + ) + + self.layers = nn.ModuleList( + [ + Ideogram4TransformerBlock( + hidden_size=config.emb_dim, + intermediate_size=config.intermediate_size, + num_heads=config.num_heads, + norm_eps=config.norm_eps, + adanln_dim=config.adanln_dim, + ) + for _ in range(config.num_layers) + ] + ) + + self.final_layer = Ideogram4FinalLayer( + hidden_size=config.emb_dim, + out_channels=config.in_channels, + adanln_dim=config.adanln_dim, + ) + + @property + def device(self) -> torch.device: + return next(self.parameters()).device + + def forward( + self, + *, + llm_features: torch.Tensor, + x: torch.Tensor, + t: torch.Tensor, + position_ids: torch.Tensor, + segment_ids: torch.Tensor, + indicator: torch.Tensor, + ) -> torch.Tensor: + """Velocity prediction. + + Args: + llm_features: (B, L, llm_features_dim) Qwen3-VL conditioning features. + x: (B, L, in_channels) noise tokens. + t: (B,) or (B, L) flow-matching time in [0, 1]. + position_ids: (B, L, 3) (t, h, w) positions for MRoPE. + segment_ids: (B, L) sample id within a packed batch. + indicator: (B, L) per-token role: LLM_TOKEN_INDICATOR or OUTPUT_IMAGE_INDICATOR. + + Returns: + (B, L, in_channels) velocity prediction in float32. Only the positions + with ``indicator == OUTPUT_IMAGE_INDICATOR`` are meaningful. + """ + batch_size, seq_len, in_channels = x.shape + assert in_channels == self.config.in_channels + + param_dtype = getattr(self.input_proj, "compute_dtype", None) or self.input_proj.weight.dtype + x = x.to(param_dtype) + t = t.to(param_dtype) + llm_features = llm_features.to(param_dtype) + + indicator = indicator.to(torch.long) + llm_token_mask = (indicator == LLM_TOKEN_INDICATOR).to(x.dtype).unsqueeze(-1) + output_image_mask = (indicator == OUTPUT_IMAGE_INDICATOR).to(x.dtype).unsqueeze(-1) + + llm_features = llm_features * llm_token_mask + x = x * output_image_mask + + x = self.input_proj(x) * output_image_mask + + # Keep shape (B, 1, ...) when t is per-sample so downstream adaln_modulation + # projections don't pay for L identical copies. + t_cond = self.t_embedding(t) + if t.dim() == 1: + t_cond = t_cond.unsqueeze(1) + adaln_input = F.silu(self.adaln_proj(t_cond)) + + llm_features = self.llm_cond_norm(llm_features) + llm_features = self.llm_cond_proj(llm_features) * llm_token_mask + + h = x + llm_features + + image_indicator_embedding = self.embed_image_indicator((indicator == OUTPUT_IMAGE_INDICATOR).to(torch.long)) + h = h + image_indicator_embedding + + cos, sin = self.rotary_emb(position_ids) + cos = cos.to(h.dtype) + sin = sin.to(h.dtype) + + for layer in self.layers: + h = layer(h, segment_ids=segment_ids, cos=cos, sin=sin, adaln_input=adaln_input) + + out = self.final_layer(h, c=adaln_input) + return out.to(torch.float32) diff --git a/invokeai/backend/ideogram4/quantized_loading.py b/invokeai/backend/ideogram4/quantized_loading.py new file mode 100644 index 00000000000..1b710293bde --- /dev/null +++ b/invokeai/backend/ideogram4/quantized_loading.py @@ -0,0 +1,282 @@ +from __future__ import annotations + +import warnings +from typing import TYPE_CHECKING + +import torch +import torch.nn as nn +import torch.nn.functional as F + +if TYPE_CHECKING: + pass + +_BNB_SIBLING_SUFFIXES = ( + ".absmax", + ".quant_map", + ".nested_absmax", + ".nested_quant_map", +) + +# Largest magnitude representable by the e4m3 float8 format. Per-row weight +# scales map each row's max abs value onto this so we use the full range. +FP8_E4M3_MAX = 448.0 +FP8_WEIGHT_DTYPE = torch.float8_e4m3fn +FP8_SCALE_SUFFIX = ".weight_scale" +# Marker written into the text encoder's config.json so the loader knows to take +# the custom weight-only FP8 path instead of transformers' from_pretrained. +FP8_TEXT_ENCODER_CONFIG_FLAG = "ideogram_fp8_weight_only" + + +def is_bnb4bit_state_dict(state_dict: dict[str, torch.Tensor]) -> bool: + """True if any key looks like a bnb 4-bit quant_state sibling.""" + return any(".quant_state.bitsandbytes__" in k for k in state_dict) + + +def swap_linears_to_bnb4bit( + module: nn.Module, + compute_dtype: torch.dtype, + *, + quant_type: str = "nf4", + compress_statistics: bool = False, +) -> None: + import bitsandbytes as bnb + + for name, child in list(module.named_children()): + if isinstance(child, nn.Linear): + new_linear = bnb.nn.Linear4bit( + child.in_features, + child.out_features, + bias=child.bias is not None, + compute_dtype=compute_dtype, + compress_statistics=compress_statistics, + quant_type=quant_type, + ) + setattr(module, name, new_linear) + else: + swap_linears_to_bnb4bit( + child, + compute_dtype, + quant_type=quant_type, + compress_statistics=compress_statistics, + ) + + +def load_bnb4bit_state_dict( + model: nn.Module, + state_dict: dict[str, torch.Tensor], + device: torch.device, + dtype: torch.dtype, +) -> None: + import bitsandbytes as bnb + + consumed: set[str] = set() + for full_name, tensor in state_dict.items(): + if ".quant_state." in full_name or full_name.endswith(_BNB_SIBLING_SUFFIXES): + continue + parent_path, _, param_name = full_name.rpartition(".") + parent = model.get_submodule(parent_path) if parent_path else model + current = parent._parameters.get(param_name) + if not isinstance(current, bnb.nn.Params4bit): + continue + prefix = full_name + "." + quantized_stats = {k: v for k, v in state_dict.items() if k.startswith(prefix)} + # bnb's from_prequantized pops keys it consumes from the dict, so snapshot + # the names first. + consumed.add(full_name) + consumed.update(quantized_stats.keys()) + parent._parameters[param_name] = bnb.nn.Params4bit.from_prequantized( + data=tensor, + quantized_stats=quantized_stats, + requires_grad=False, + device=device, + ) + + remaining = {k: v for k, v in state_dict.items() if k not in consumed} + for k in list(remaining): + if remaining[k].is_floating_point(): + remaining[k] = remaining[k].to(device=device, dtype=dtype) + else: + remaining[k] = remaining[k].to(device=device) + + missing, unexpected = model.load_state_dict(remaining, strict=False) + # Quantized weights are loaded via from_prequantized above, so they appear in + # `missing` from load_state_dict's perspective — filter those out. + real_missing = [m for m in missing if m not in consumed] + if real_missing: + raise RuntimeError(f"missing keys after quantized load: {real_missing[:10]}") + if unexpected: + raise RuntimeError(f"unexpected keys after quantized load: {unexpected[:10]}") + + for p in model.parameters(): + if isinstance(p, bnb.nn.Params4bit): + continue + if p.is_floating_point() and p.dtype != dtype: + p.data = p.data.to(dtype=dtype) + if p.device != device: + p.data = p.data.to(device=device) + for name, b in list(model.named_buffers()): + if b.is_floating_point() and b.dtype != dtype: + parent_path, _, leaf = name.rpartition(".") + parent = model.get_submodule(parent_path) if parent_path else model + parent.register_buffer( + leaf, + b.to(device=device, dtype=dtype), + persistent=leaf not in parent._non_persistent_buffers_set, + ) + elif b.device != device: + parent_path, _, leaf = name.rpartition(".") + parent = model.get_submodule(parent_path) if parent_path else model + parent.register_buffer( + leaf, + b.to(device=device), + persistent=leaf not in parent._non_persistent_buffers_set, + ) + + +# --------------------------------------------------------------------------- +# Weight-only FP8 (e4m3) +# +# Activations stay in the compute dtype (e.g. bfloat16); only Linear weights are +# stored as float8 with a per-output-channel (per-row) float32 scale. At forward +# time the weight is dequantized back to the compute dtype and a normal bf16 +# matmul runs, so this needs no FP8 tensor-core hardware and works on any device +# that can store float8 (CPU included). The win is ~2x smaller Linear weights. +# --------------------------------------------------------------------------- + + +def quantize_weight_to_fp8( + weight: torch.Tensor, +) -> tuple[torch.Tensor, torch.Tensor]: + """Quantize a 2-D Linear weight to e4m3 float8 with per-row scales. + + Returns ``(weight_fp8, scale)`` where ``weight_fp8`` has shape ``(out, in)`` + in ``float8_e4m3fn`` and ``scale`` has shape ``(out,)`` in float32 such that + ``weight ≈ weight_fp8.to(dtype) * scale[:, None]``. + """ + w = weight.detach().to(torch.float32) + amax = w.abs().amax(dim=1, keepdim=True).clamp(min=1e-12) + scale = amax / FP8_E4M3_MAX + q = (w / scale).clamp(-FP8_E4M3_MAX, FP8_E4M3_MAX).to(FP8_WEIGHT_DTYPE) + return q, scale.squeeze(1).to(torch.float32) + + +def is_fp8_state_dict(state_dict: dict[str, torch.Tensor]) -> bool: + """True if the checkpoint carries weight-only FP8 Linear weights.""" + return any(k.endswith(FP8_SCALE_SUFFIX) for k in state_dict) or any( + v.dtype == FP8_WEIGHT_DTYPE for v in state_dict.values() + ) + + +class Fp8Linear(nn.Module): + """Linear layer holding an e4m3 float8 weight + per-row float32 scale. + + The weight and scale are registered as buffers (not parameters) so they load + via ``load_state_dict`` and are excluded from optimizer/grad machinery. The + dequantized matmul runs in ``compute_dtype``. + """ + + weight: torch.Tensor + weight_scale: torch.Tensor + bias: torch.Tensor | None + + def __init__( + self, + in_features: int, + out_features: int, + bias: bool, + compute_dtype: torch.dtype, + ) -> None: + super().__init__() + self.in_features = in_features + self.out_features = out_features + self.compute_dtype = compute_dtype + self.register_buffer( + "weight", + torch.empty(out_features, in_features, dtype=FP8_WEIGHT_DTYPE), + ) + self.register_buffer("weight_scale", torch.empty(out_features, dtype=torch.float32)) + if bias: + self.register_buffer("bias", torch.empty(out_features, dtype=compute_dtype)) + else: + self.bias = None + + def forward(self, x: torch.Tensor) -> torch.Tensor: + w = self.weight.to(x.dtype) * self.weight_scale.to(x.dtype).unsqueeze(1) + bias = self.bias.to(x.dtype) if self.bias is not None else None + return F.linear(x, w, bias) + + +def swap_linears_to_fp8( + module: nn.Module, + state_dict: dict[str, torch.Tensor], + compute_dtype: torch.dtype, + *, + prefix: str = "", +) -> None: + """Replace each ``nn.Linear`` that has a saved FP8 scale with an ``Fp8Linear``. + + Gating on the presence of ``.weight_scale`` means only layers that were + actually quantized at save time are swapped; everything else loads normally in + the compute dtype. + """ + for name, child in list(module.named_children()): + child_prefix = f"{prefix}{name}" + if isinstance(child, nn.Linear) and f"{child_prefix}{FP8_SCALE_SUFFIX}" in state_dict: + setattr( + module, + name, + Fp8Linear( + child.in_features, + child.out_features, + bias=child.bias is not None, + compute_dtype=compute_dtype, + ), + ) + else: + swap_linears_to_fp8(child, state_dict, compute_dtype, prefix=f"{child_prefix}.") + + +def load_fp8_state_dict( + model: nn.Module, + state_dict: dict[str, torch.Tensor], + device: torch.device, + dtype: torch.dtype, + *, + assign: bool = False, + strict: bool = True, +) -> None: + """Load a weight-only FP8 checkpoint into ``model``. + + ``model`` must already have its FP8 Linear layers swapped in (see + ``swap_linears_to_fp8``). FP8 weights are kept as float8, scales stay float32, + and every other floating tensor is cast to ``dtype``. + + ``assign=True`` replaces the module's tensors with the prepared ones rather than + copying into them. Use it when the model was built with ``from_config`` so the + non-quantized params take the loaded dtype directly and computed non-persistent + buffers (e.g. rotary caches) are left untouched. With ``assign=False`` (default), + the caller must have already put the unquantized params in ``dtype``. + + ``strict=False`` downgrades missing keys to a warning (e.g. tied weights that a + ``transformers`` model resolves itself); unexpected keys always raise. + """ + prepared: dict[str, torch.Tensor] = {} + for k, v in state_dict.items(): + if v.dtype == FP8_WEIGHT_DTYPE: + prepared[k] = v.to(device=device) + elif k.endswith(FP8_SCALE_SUFFIX): + prepared[k] = v.to(device=device, dtype=torch.float32) + elif v.is_floating_point(): + prepared[k] = v.to(device=device, dtype=dtype) + else: + prepared[k] = v.to(device=device) + + missing, unexpected = model.load_state_dict(prepared, strict=False, assign=assign) + if unexpected: + raise RuntimeError(f"unexpected keys after fp8 load: {unexpected[:10]}") + if missing: + if strict: + raise RuntimeError(f"missing keys after fp8 load: {missing[:10]}") + warnings.warn(f"missing keys after fp8 load: {missing[:10]}", stacklevel=2) + + model.to(device) diff --git a/invokeai/backend/ideogram4/sampler_configs.py b/invokeai/backend/ideogram4/sampler_configs.py new file mode 100644 index 00000000000..5aefa31e454 --- /dev/null +++ b/invokeai/backend/ideogram4/sampler_configs.py @@ -0,0 +1,29 @@ +"""Named sampler configurations for Ideogram 4 inference.""" + +from __future__ import annotations + +from invokeai.backend.ideogram4.scheduler import SamplerParameters + +# guidance_schedule is in loop-INDEX order: index 0 is the LAST (polish) step. +# Each preset does the first N_main sampling steps at gw=7, then N_cleanup +# polish steps at gw=3. +PRESETS: dict[str, SamplerParameters] = { + "V4_QUALITY_48": SamplerParameters( + num_steps=48, + guidance_schedule=(3.0,) * 3 + (7.0,) * 45, + mu=0.0, + std=1.5, + ), + "V4_DEFAULT_20": SamplerParameters( + num_steps=20, + guidance_schedule=(3.0,) * 2 + (7.0,) * 18, + mu=0.0, + std=1.75, + ), + "V4_TURBO_12": SamplerParameters( + num_steps=12, + guidance_schedule=(3.0,) * 1 + (7.0,) * 11, + mu=0.5, + std=1.75, + ), +} diff --git a/invokeai/backend/ideogram4/sampling_utils.py b/invokeai/backend/ideogram4/sampling_utils.py new file mode 100644 index 00000000000..54dede15bb3 --- /dev/null +++ b/invokeai/backend/ideogram4/sampling_utils.py @@ -0,0 +1,130 @@ +"""Sampling helpers for Ideogram 4: packed-sequence construction and latent unpacking. + +These wrap the vendored reference model (``modeling_ideogram4`` etc.) for use in +InvokeAI invocations. They mirror the logic of ``Ideogram4Pipeline._build_inputs`` +and ``Ideogram4Pipeline._decode`` from the reference implementation, specialised +to the single-image (batch size 1) case InvokeAI generates, where there is no +left-padding so the packed layout is simply ``[text tokens][image tokens]``. +""" + +from __future__ import annotations + +from typing import TypedDict + +import torch + +from invokeai.backend.ideogram4.constants import ( + IMAGE_POSITION_OFFSET, + LLM_TOKEN_INDICATOR, + OUTPUT_IMAGE_INDICATOR, +) + +# Latent patch size (each transformer image token covers a patch_size x patch_size +# block of VAE latents) and the VAE's spatial downscale factor. A single image +# token therefore covers ``PATCH_SIZE * AE_SCALE_FACTOR`` pixels per side. +PATCH_SIZE = 2 +AE_SCALE_FACTOR = 8 +PIXELS_PER_IMAGE_TOKEN = PATCH_SIZE * AE_SCALE_FACTOR # 16 + +# Packed-latent channel count: ae z_channels (32) * patch_size**2 (4) = 128. +LATENT_DIM = 128 + + +class Ideogram4DenoiseInputs(TypedDict): + """The packed-sequence tensors fed to the transformer during denoising.""" + + position_ids: torch.Tensor # (1, L, 3) int64 — (t, h, w) positions for MRoPE + segment_ids: torch.Tensor # (1, L) int64 — sample id within the packed batch + indicator: torch.Tensor # (1, L) int64 — LLM_TOKEN_INDICATOR or OUTPUT_IMAGE_INDICATOR + num_text_tokens: int + num_image_tokens: int + grid_h: int + grid_w: int + + +def validate_dimensions(height: int, width: int) -> None: + """Ensure the requested resolution is compatible with the patch/VAE grid.""" + if height % PIXELS_PER_IMAGE_TOKEN != 0 or width % PIXELS_PER_IMAGE_TOKEN != 0: + raise ValueError(f"height and width must be divisible by {PIXELS_PER_IMAGE_TOKEN}, got {height}x{width}") + + +def build_denoise_inputs( + num_text_tokens: int, + height: int, + width: int, + device: torch.device, +) -> Ideogram4DenoiseInputs: + """Build the packed ``[text][image]`` position/segment/indicator tensors for one image. + + Mirrors ``Ideogram4Pipeline._build_inputs`` for batch size 1 (no padding). + """ + validate_dimensions(height, width) + grid_h = height // PIXELS_PER_IMAGE_TOKEN + grid_w = width // PIXELS_PER_IMAGE_TOKEN + num_image_tokens = grid_h * grid_w + total_seq_len = num_text_tokens + num_image_tokens + + # Image grid positions (t=0, h, w), offset so they never collide with text positions. + h_idx = torch.arange(grid_h).view(-1, 1).expand(grid_h, grid_w).reshape(-1) + w_idx = torch.arange(grid_w).view(1, -1).expand(grid_h, grid_w).reshape(-1) + t_idx = torch.zeros_like(h_idx) + image_pos = torch.stack([t_idx, h_idx, w_idx], dim=1) + IMAGE_POSITION_OFFSET + + position_ids = torch.zeros(1, total_seq_len, 3, dtype=torch.long) + text_pos = torch.arange(num_text_tokens) + text_pos_3d = torch.stack([text_pos, text_pos, text_pos], dim=1) + position_ids[0, :num_text_tokens] = text_pos_3d + position_ids[0, num_text_tokens:] = image_pos + + # Single sample, no padding -> every position belongs to segment 1. + segment_ids = torch.ones(1, total_seq_len, dtype=torch.long) + + indicator = torch.zeros(1, total_seq_len, dtype=torch.long) + indicator[0, :num_text_tokens] = LLM_TOKEN_INDICATOR + indicator[0, num_text_tokens:] = OUTPUT_IMAGE_INDICATOR + + return Ideogram4DenoiseInputs( + position_ids=position_ids.to(device), + segment_ids=segment_ids.to(device), + indicator=indicator.to(device), + num_text_tokens=num_text_tokens, + num_image_tokens=num_image_tokens, + grid_h=grid_h, + grid_w=grid_w, + ) + + +def pack_latents_to_grid(z: torch.Tensor, grid_h: int, grid_w: int) -> torch.Tensor: + """Reshape sampled latents ``(1, grid_h*grid_w, LATENT_DIM)`` to ``(1, LATENT_DIM, grid_h, grid_w)``. + + Stores the packed latent in a channels-first 4-D tensor so the grid dimensions + survive in the latent shape (the L2I node recovers them). + """ + batch_size = z.shape[0] + z = z.reshape(batch_size, grid_h, grid_w, LATENT_DIM) + return z.permute(0, 3, 1, 2).contiguous() + + +def unpatchify_and_denormalize( + packed: torch.Tensor, + latent_shift: torch.Tensor, + latent_scale: torch.Tensor, +) -> torch.Tensor: + """Convert a packed latent ``(1, LATENT_DIM, grid_h, grid_w)`` to a VAE latent ``(1, 32, H/8, W/8)``. + + Applies the per-channel latent denormalization (``z * scale + shift``) in the + packed space, then unpatchifies, exactly as ``Ideogram4Pipeline._decode`` does. + """ + batch_size, channels, grid_h, grid_w = packed.shape + if channels != LATENT_DIM: + raise ValueError(f"expected {LATENT_DIM} packed channels, got {channels}") + + # (B, grid_h, grid_w, LATENT_DIM) + z = packed.permute(0, 2, 3, 1) + z = z * latent_scale.to(z.device, z.dtype) + latent_shift.to(z.device, z.dtype) + + ae_channels = LATENT_DIM // (PATCH_SIZE * PATCH_SIZE) # 32 + z = z.reshape(batch_size, grid_h, grid_w, PATCH_SIZE, PATCH_SIZE, ae_channels) + z = z.permute(0, 5, 1, 3, 2, 4).contiguous() + z = z.reshape(batch_size, ae_channels, grid_h * PATCH_SIZE, grid_w * PATCH_SIZE) + return z diff --git a/invokeai/backend/ideogram4/scheduler.py b/invokeai/backend/ideogram4/scheduler.py new file mode 100644 index 00000000000..1a9d3fab10b --- /dev/null +++ b/invokeai/backend/ideogram4/scheduler.py @@ -0,0 +1,69 @@ +"""Logit-normal schedule and Euler flow-matching sampler.""" + +from __future__ import annotations + +import math +from dataclasses import dataclass + +import torch + + +@dataclass(frozen=True) +class LogitNormalSchedule: + mean: float + std: float = 1.0 + logsnr_min: float = -15.0 + logsnr_max: float = 18.0 + + def __call__(self, t: torch.Tensor) -> torch.Tensor: + t = t.to(torch.float64) + z = torch.special.ndtri(t) + y = self.mean + self.std * z + t_ = torch.special.expit(y) + t_ = 1 - t_ + t_min = 1.0 / (1 + math.exp(0.5 * self.logsnr_max)) + t_max = 1.0 / (1 + math.exp(0.5 * self.logsnr_min)) + return t_.clamp(t_min, t_max).to(torch.float32) + + +def get_schedule_for_resolution( + image_resolution: tuple[int, int], + known_resolution: tuple[int, int] = (512, 512), + known_mean: float = 1.0, + std: float = 1.0, +) -> LogitNormalSchedule: + """Resolution-aware schedule used at eval time.""" + num_pixels = image_resolution[0] * image_resolution[1] + known_pixels = known_resolution[0] * known_resolution[1] + mean = known_mean + 0.5 * math.log(num_pixels / known_pixels) + return LogitNormalSchedule(mean=mean, std=std) + + +def make_step_intervals(num_steps: int) -> torch.Tensor: + """Default linear step schedule used by the v4 eval config.""" + return torch.linspace(0.0, 1.0, num_steps + 1, dtype=torch.float32) + + +@dataclass(frozen=True, kw_only=True) +class SamplerParameters: + """Bundle of sampling hyperparameters for a named preset. + + ``guidance_schedule`` is in LOOP-INDEX order: index 0 is the LAST sampling + step (final polish), index ``num_steps - 1`` is the FIRST sampling step. + ``mu`` and ``std`` are the mean and stddev of the logit-normal noise + schedule passed to ``get_schedule_for_resolution`` (as ``known_mean`` and + ``std`` respectively). + + See ``ideogram4.sampler_configs.PRESETS`` for the named preset registry. + """ + + num_steps: int + guidance_schedule: tuple[float, ...] + mu: float + std: float = 1.0 + + def __post_init__(self) -> None: + if len(self.guidance_schedule) != self.num_steps: + raise ValueError( + f"guidance_schedule has length {len(self.guidance_schedule)}, expected num_steps={self.num_steps}" + ) diff --git a/invokeai/backend/ideogram4/text_encoding.py b/invokeai/backend/ideogram4/text_encoding.py new file mode 100644 index 00000000000..47eb97925cd --- /dev/null +++ b/invokeai/backend/ideogram4/text_encoding.py @@ -0,0 +1,87 @@ +"""Qwen3-VL text encoding for Ideogram 4. + +Ideogram 4 conditions on a concatenation of hidden states taken from 13 specific +layers of the Qwen3-VL language model (see ``QWEN3_VL_ACTIVATION_LAYERS``), giving +a ``(seq_len, 4096 * 13) == (seq_len, 53248)`` feature tensor. + +The reference pipeline runs the encoder over the full packed ``[text][image]`` +sequence, but the text-token hidden states are independent of the image tokens +(attention is causal and gated to LLM-token positions), so we encode the text +tokens only. The denoise node assembles the full packed sequence. +""" + +from __future__ import annotations + +import torch + +from invokeai.backend.ideogram4.constants import QWEN3_VL_ACTIVATION_LAYERS + +# Matches Ideogram4PipelineConfig.max_text_tokens. +MAX_TEXT_TOKENS = 2048 + + +def encode_qwen3vl_prompt( + prompt: str, + tokenizer, + text_encoder, + *, + max_text_tokens: int = MAX_TEXT_TOKENS, +) -> torch.Tensor: + """Encode a single prompt into Ideogram 4 conditioning features. + + Returns a ``(num_text_tokens, 53248)`` float32 tensor (on the encoder's device; + the caller is responsible for moving it to CPU for storage). + """ + # Importing here keeps module import cheap and tolerant of transformers versions + # that lay out the masking utilities differently. + from transformers.masking_utils import create_causal_mask + + device = next(text_encoder.parameters()).device + + # Chat-format and tokenize, matching Ideogram4Pipeline._tokenize. + messages = [{"role": "user", "content": [{"type": "text", "text": prompt}]}] + text = tokenizer.apply_chat_template(messages, add_generation_prompt=True, tokenize=False) + encoded = tokenizer(text, return_tensors="pt", add_special_tokens=False) + token_ids = encoded["input_ids"].to(device) # (1, L) + num_text_tokens = int(token_ids.shape[1]) + if num_text_tokens > max_text_tokens: + raise ValueError(f"prompt has {num_text_tokens} tokens, exceeds max_text_tokens={max_text_tokens}") + + # Text-only sequence: every position is a real LLM token. + attention_mask = torch.ones((1, num_text_tokens), dtype=torch.long, device=device) + pos_2d = torch.arange(num_text_tokens, device=device)[None, :] # (1, L) + + language_model = text_encoder.language_model + inputs_embeds = language_model.embed_tokens(token_ids) + + position_ids_4d = pos_2d[None, ...].expand(4, 1, num_text_tokens) + text_position_ids = position_ids_4d[0] # (1, L) + mrope_position_ids = position_ids_4d[1:] # (3, 1, L) + + causal_mask = create_causal_mask( + config=language_model.config, + inputs_embeds=inputs_embeds, + attention_mask=attention_mask, + past_key_values=None, + position_ids=text_position_ids, + ) + position_embeddings = language_model.rotary_emb(inputs_embeds, mrope_position_ids) + + tap_set = set(QWEN3_VL_ACTIVATION_LAYERS) + captured: dict[int, torch.Tensor] = {} + hidden_states = inputs_embeds + for layer_idx, decoder_layer in enumerate(language_model.layers): + hidden_states = decoder_layer( + hidden_states, + attention_mask=causal_mask, + position_ids=text_position_ids, + past_key_values=None, + position_embeddings=position_embeddings, + ) + if layer_idx in tap_set: + captured[layer_idx] = hidden_states + + selected = [captured[i] for i in QWEN3_VL_ACTIVATION_LAYERS] + stacked = torch.stack(selected, dim=0) # (num_taps, 1, L, H) + stacked = stacked.permute(1, 2, 3, 0).reshape(1, num_text_tokens, -1) # (1, L, H*num_taps) + return stacked[0].to(torch.float32) # (L, 53248) diff --git a/invokeai/backend/ideogram4/transformer_pair.py b/invokeai/backend/ideogram4/transformer_pair.py new file mode 100644 index 00000000000..509149fd61e --- /dev/null +++ b/invokeai/backend/ideogram4/transformer_pair.py @@ -0,0 +1,25 @@ +"""Container holding Ideogram 4's two transformer branches as a single submodel. + +Ideogram 4 uses dual-branch asymmetric CFG with two *separate* weight sets +(``transformer/`` and ``unconditional_transformer/`` on disk). InvokeAI's model +cache keys a cached entity by (model, submodel_type) and there is no +"unconditional transformer" submodel type, so we load both branches into one +``nn.Module`` returned for ``SubModelType.Transformer``. This keeps both branches +co-resident through the denoise loop (each step runs both), which is required for +acceptable performance and is what makes the nf4 build fit in 24 GB. +""" + +from __future__ import annotations + +import torch + +from invokeai.backend.ideogram4.modeling_ideogram4 import Ideogram4Transformer + + +class Ideogram4TransformerPair(torch.nn.Module): + """Holds the conditional and unconditional Ideogram 4 transformers.""" + + def __init__(self, conditional: Ideogram4Transformer, unconditional: Ideogram4Transformer) -> None: + super().__init__() + self.conditional = conditional + self.unconditional = unconditional diff --git a/invokeai/backend/model_manager/configs/factory.py b/invokeai/backend/model_manager/configs/factory.py index 1d2fa7be1f7..6d36b6c8a6f 100644 --- a/invokeai/backend/model_manager/configs/factory.py +++ b/invokeai/backend/model_manager/configs/factory.py @@ -74,6 +74,7 @@ Main_Diffusers_CogView4_Config, Main_Diffusers_Flux2_Config, Main_Diffusers_FLUX_Config, + Main_Diffusers_Ideogram4_Config, Main_Diffusers_QwenImage_Config, Main_Diffusers_SD1_Config, Main_Diffusers_SD2_Config, @@ -180,6 +181,7 @@ Annotated[Main_Diffusers_CogView4_Config, Main_Diffusers_CogView4_Config.get_tag()], Annotated[Main_Diffusers_QwenImage_Config, Main_Diffusers_QwenImage_Config.get_tag()], Annotated[Main_Diffusers_ZImage_Config, Main_Diffusers_ZImage_Config.get_tag()], + Annotated[Main_Diffusers_Ideogram4_Config, Main_Diffusers_Ideogram4_Config.get_tag()], # Main (Pipeline) - checkpoint format # IMPORTANT: FLUX.2 must be checked BEFORE FLUX.1 because FLUX.2 has specific validation # that will reject FLUX.1 models, but FLUX.1 validation may incorrectly match FLUX.2 models diff --git a/invokeai/backend/model_manager/configs/main.py b/invokeai/backend/model_manager/configs/main.py index 10835b389fc..f3dbc1df902 100644 --- a/invokeai/backend/model_manager/configs/main.py +++ b/invokeai/backend/model_manager/configs/main.py @@ -85,6 +85,10 @@ def from_base( return cls(steps=9, cfg_scale=1.0, width=1024, height=1024) case BaseModelType.Anima: return cls(steps=35, cfg_scale=4.5, width=1024, height=1024) + case BaseModelType.Ideogram4: + # Ideogram 4 uses sampler presets (default V4_QUALITY_48 = 48 steps) and a + # dual-branch guidance schedule; these are sensible UI defaults. + return cls(steps=48, cfg_scale=7.0, width=1024, height=1024) case BaseModelType.Flux2: # Different defaults based on variant if variant in (Flux2VariantType.Klein4BBase, Flux2VariantType.Klein9BBase): @@ -1285,6 +1289,37 @@ def _validate_looks_like_gguf_quantized(cls, mod: ModelOnDisk) -> None: raise NotAMatchError("state dict does not look like GGUF quantized") +class Main_Diffusers_Ideogram4_Config(Diffusers_Config_Base, Main_Config_Base, Config_Base): + """Model config for Ideogram 4 diffusers models (nf4 / fp8 quantized). + + The on-disk layout is a diffusers pipeline folder bundling two transformers + (transformer/ + unconditional_transformer/), a Qwen3-VL text_encoder/ + tokenizer/, + and a FLUX.2-style vae/. Quantization (nf4 vs fp8) lives inside the component folders + and is detected by the loader, not here. + """ + + base: Literal[BaseModelType.Ideogram4] = Field(BaseModelType.Ideogram4) + + @classmethod + def from_model_on_disk(cls, mod: ModelOnDisk, override_fields: dict[str, Any]) -> Self: + raise_if_not_dir(mod) + + raise_for_override_fields(cls, override_fields) + + # The Ideogram4Pipeline class name in model_index.json uniquely identifies this base. + raise_for_class_name( + common_config_paths(mod.path), + {"Ideogram4Pipeline"}, + ) + + repo_variant = override_fields.pop("repo_variant", None) or cls._get_repo_variant_or_raise(mod) + + return cls( + **override_fields, + repo_variant=repo_variant, + ) + + class Main_Diffusers_QwenImage_Config(Diffusers_Config_Base, Main_Config_Base, Config_Base): """Model config for Qwen Image diffusers models (both txt2img and edit).""" diff --git a/invokeai/backend/model_manager/load/model_loaders/ideogram4.py b/invokeai/backend/model_manager/load/model_loaders/ideogram4.py new file mode 100644 index 00000000000..3b430dc0b36 --- /dev/null +++ b/invokeai/backend/model_manager/load/model_loaders/ideogram4.py @@ -0,0 +1,230 @@ +"""Model loading for Ideogram 4 in InvokeAI. + +The on-disk model is a diffusers pipeline folder bundling: + - transformer/ (Ideogram4Transformer, nf4 or fp8 quantized) + - unconditional_transformer/ (Ideogram4Transformer, nf4 or fp8 quantized) + - text_encoder/ + tokenizer/ (Qwen3-VL, nf4 or fp8) + - vae/ (FLUX.2-style AutoencoderKL; loaded via the vendored AutoEncoder) + +The transformer is our vendored ``Ideogram4Transformer`` (not a diffusers class), so we +build it explicitly and load the prequantized state dict — mirroring how InvokeAI loads +FLUX nf4. Both transformer branches are returned as a single ``Ideogram4TransformerPair``. +""" + +import itertools +import json +from pathlib import Path +from typing import Optional + +import accelerate +import torch +from safetensors.torch import load_file + +from invokeai.backend.model_manager.configs.factory import AnyModelConfig +from invokeai.backend.model_manager.configs.main import Main_Diffusers_Ideogram4_Config +from invokeai.backend.model_manager.load.load_default import ModelLoader +from invokeai.backend.model_manager.load.model_loader_registry import ModelLoaderRegistry +from invokeai.backend.model_manager.taxonomy import ( + AnyModel, + BaseModelType, + ModelFormat, + ModelType, + SubModelType, +) +from invokeai.backend.util.devices import TorchDevice + + +def _load_local_state_dict(folder: Path, basename: str) -> dict[str, torch.Tensor]: + """Load a (possibly sharded) safetensors checkpoint from a local diffusers component folder.""" + index_path = folder / f"{basename}.safetensors.index.json" + if index_path.exists(): + with open(index_path) as f: + weight_map: dict[str, str] = json.load(f)["weight_map"] + sd: dict[str, torch.Tensor] = {} + for shard in sorted(set(weight_map.values())): + sd.update(load_file(folder / shard)) + return sd + return load_file(folder / f"{basename}.safetensors") + + +def _verify_encoder_fully_materialized(model: torch.nn.Module, *, context: str) -> None: + """Fail if any parameter is still on the meta device after loading the text encoder. + + The encoder is built under ``accelerate.init_empty_weights()`` (every param starts on the meta + device) and then filled from the checkpoint. Missing keys are only acceptable for tied weights, which + ``transformers`` materializes via ``tie_weights()``; any other missing key leaves a meta tensor that + would pass loading but fail later during device movement or encoding. Re-tie, then hard-fail if any + meta tensor remains so a bad/mismatched encoder is rejected at load time instead. + """ + if hasattr(model, "tie_weights"): + model.tie_weights() + meta = [ + name + for name, tensor in itertools.chain(model.named_parameters(), model.named_buffers()) + if getattr(tensor, "is_meta", False) + ] + if meta: + raise RuntimeError( + f"{context}: {len(meta)} parameter(s) remain on the meta device after loading " + f"(missing or mismatched weights): {meta[:10]}" + ) + + +@ModelLoaderRegistry.register(base=BaseModelType.Ideogram4, type=ModelType.Main, format=ModelFormat.Diffusers) +class Ideogram4DiffusersModel(ModelLoader): + """Loads Ideogram 4 main models (nf4 / fp8) bundled in diffusers layout.""" + + def _load_model( + self, + config: AnyModelConfig, + submodel_type: Optional[SubModelType] = None, + ) -> AnyModel: + if not isinstance(config, Main_Diffusers_Ideogram4_Config): + raise ValueError(f"Expected Main_Diffusers_Ideogram4_Config, got {type(config).__name__}.") + if submodel_type is None: + raise Exception("A submodel type must be provided when loading Ideogram 4 main pipelines.") + + model_path = Path(config.path) + + match submodel_type: + case SubModelType.Transformer: + return self._load_transformer_pair(model_path) + case SubModelType.TextEncoder: + return self._load_text_encoder(model_path) + case SubModelType.Tokenizer: + from transformers import AutoTokenizer + + return AutoTokenizer.from_pretrained(model_path / "tokenizer", local_files_only=True) + case SubModelType.VAE: + return self._load_vae(model_path) + + raise ValueError( + f"Unsupported submodel for Ideogram 4: {submodel_type.value if submodel_type else 'None'}. " + "Supported: Transformer, TextEncoder, Tokenizer, VAE." + ) + + def _load_transformer_pair(self, model_path: Path) -> AnyModel: + from invokeai.backend.ideogram4.transformer_pair import Ideogram4TransformerPair + + conditional = self._load_one_transformer(model_path / "transformer") + unconditional = self._load_one_transformer(model_path / "unconditional_transformer") + return Ideogram4TransformerPair(conditional=conditional, unconditional=unconditional) + + def _load_one_transformer(self, folder: Path) -> torch.nn.Module: + from invokeai.backend.ideogram4.modeling_ideogram4 import Ideogram4Config, Ideogram4Transformer + from invokeai.backend.ideogram4.quantized_loading import ( + is_bnb4bit_state_dict, + is_fp8_state_dict, + load_fp8_state_dict, + swap_linears_to_fp8, + ) + from invokeai.backend.quantization.bnb_nf4 import quantize_model_nf4 + + target_device = TorchDevice.choose_torch_device() + compute_dtype = TorchDevice.choose_bfloat16_safe_dtype(target_device) + + sd = _load_local_state_dict(folder, "diffusion_pytorch_model") + self._ram_cache.make_room(sum(t.nelement() * t.element_size() for t in sd.values())) + + if is_bnb4bit_state_dict(sd): + # nf4: build the model with InvokeLinearNF4 layers (compress_statistics=False, matching + # the on-disk single-quant format), then load the prequantized state dict. The model + # stays on CPU/meta until the cache moves it to the GPU. + with accelerate.init_empty_weights(): + model: torch.nn.Module = Ideogram4Transformer(Ideogram4Config()) + model = quantize_model_nf4(model, modules_to_not_convert=set(), compute_dtype=compute_dtype) + model.load_state_dict(sd, strict=True, assign=True) + return model + + if is_fp8_state_dict(sd): + # Weight-only fp8 (e4m3): dequantizes to compute dtype at forward time; runs on any device. + model = Ideogram4Transformer(Ideogram4Config()) + model.to(compute_dtype) + swap_linears_to_fp8(model, sd, compute_dtype=compute_dtype) + load_fp8_state_dict(model, sd, device=torch.device("cpu"), dtype=compute_dtype) + model.eval() + return model + + # Unquantized fallback. + with accelerate.init_empty_weights(): + model = Ideogram4Transformer(Ideogram4Config()) + model.load_state_dict(sd, strict=True, assign=True) + return model.to(compute_dtype) + + def _load_text_encoder(self, model_path: Path) -> AnyModel: + import accelerate + from transformers import AutoConfig, AutoModel + + from invokeai.backend.ideogram4.quantized_loading import ( + FP8_TEXT_ENCODER_CONFIG_FLAG, + load_fp8_state_dict, + swap_linears_to_fp8, + ) + from invokeai.backend.quantization.bnb_nf4 import quantize_model_nf4 + + encoder_path = model_path / "text_encoder" + target_device = TorchDevice.choose_torch_device() + compute_dtype = TorchDevice.choose_bfloat16_safe_dtype(target_device) + + raw_cfg = json.loads((encoder_path / "config.json").read_text(encoding="utf-8")) + + # Build the bare architecture from config, then load the prequantized weights ourselves. We must + # NOT use transformers' native bitsandbytes loading (from_pretrained with a quantization_config) + # because the resulting bnb Linear4bit layers are not compatible with InvokeAI's partial-loading + # model cache. This mirrors how the FLUX T5 bnb encoder is loaded. + cfg = AutoConfig.from_pretrained(encoder_path, local_files_only=True) + # Drop the quantization_config so from_config builds a plain (unquantized) architecture. + if hasattr(cfg, "quantization_config"): + cfg.quantization_config = None + + sd = _load_local_state_dict(encoder_path, "model") + self._ram_cache.make_room(sum(t.nelement() * t.element_size() for t in sd.values())) + + if raw_cfg.get(FP8_TEXT_ENCODER_CONFIG_FLAG, False): + # Weight-only fp8 (e4m3): build the empty architecture, swap the quantized Linears for + # Fp8Linear (gated on a saved per-row scale), then load. Mirrors the transformer fp8 branch; + # runs on any device. strict=False tolerates the tied embed weights transformers resolves + # itself; unexpected keys still raise. assign=True fills the meta params directly. + with accelerate.init_empty_weights(): + model: torch.nn.Module = AutoModel.from_config(cfg) + swap_linears_to_fp8(model, sd, compute_dtype=compute_dtype) + load_fp8_state_dict(model, sd, device=torch.device("cpu"), dtype=compute_dtype, assign=True, strict=False) + _verify_encoder_fully_materialized(model, context="Ideogram 4 fp8 text encoder") + model.eval() + return model + + is_bnb_nf4 = "quantization_config" in raw_cfg and bool(raw_cfg["quantization_config"].get("load_in_4bit")) + + with accelerate.init_empty_weights(): + model = AutoModel.from_config(cfg) + if is_bnb_nf4: + model = quantize_model_nf4(model, modules_to_not_convert=set(), compute_dtype=compute_dtype) + + _, unexpected = model.load_state_dict(sd, strict=False, assign=True) + # Unexpected keys signal a wrong or contaminated checkpoint and must hard-fail. Missing keys are + # acceptable only for tied weights (resolved by _verify_encoder_fully_materialized via + # tie_weights); any genuinely missing non-tied weight is caught there as a leftover meta tensor. + if unexpected: + raise RuntimeError(f"unexpected keys loading Ideogram 4 text encoder: {unexpected[:10]}") + _verify_encoder_fully_materialized(model, context="Ideogram 4 text encoder") + if not is_bnb_nf4: + model = model.to(compute_dtype) + model.eval() + return model + + def _load_vae(self, model_path: Path) -> AnyModel: + from invokeai.backend.ideogram4.autoencoder import ( + AutoEncoder, + AutoEncoderParams, + convert_diffusers_state_dict, + ) + + target_device = TorchDevice.choose_torch_device() + model_dtype = TorchDevice.choose_bfloat16_safe_dtype(target_device) + + sd = load_file(model_path / "vae" / "diffusion_pytorch_model.safetensors") + sd = convert_diffusers_state_dict(sd) + ae = AutoEncoder(AutoEncoderParams()) + ae.load_state_dict(sd) + ae.eval() + return ae.to(model_dtype) diff --git a/invokeai/backend/model_manager/starter_models.py b/invokeai/backend/model_manager/starter_models.py index eb2eff9f633..194c02fd404 100644 --- a/invokeai/backend/model_manager/starter_models.py +++ b/invokeai/backend/model_manager/starter_models.py @@ -1646,6 +1646,30 @@ def _gemini_3_resolution_presets( ) # endregion +# region Ideogram 4 +# Self-contained diffusers pipelines (both transformers + Qwen3-VL text encoder + VAE in one folder), so +# no separate dependencies. Gated, non-commercial license: the license must be accepted on the +# HuggingFace model page and a HuggingFace token configured before the download will succeed — same as +# FLUX.1 dev. +ideogram_4_nf4 = StarterModel( + name="Ideogram 4 (nf4)", + base=BaseModelType.Ideogram4, + source="ideogram-ai/ideogram-4-nf4", + description="Ideogram 4 text-to-image in nf4-quantized Diffusers format (CUDA only). Structured JSON " + "prompting with regional layout control. Non-commercial license — accept it on HuggingFace first. ~16GB", + type=ModelType.Main, +) + +ideogram_4_fp8 = StarterModel( + name="Ideogram 4 (fp8)", + base=BaseModelType.Ideogram4, + source="ideogram-ai/ideogram-4-fp8", + description="Ideogram 4 text-to-image in fp8-quantized Diffusers format (runs on any device, higher " + "memory use). Non-commercial license — accept it on HuggingFace first. ~26GB", + type=ModelType.Main, +) +# endregion + # List of starter models, displayed on the frontend. # The order/sort of this list is not changed by the frontend - set it how you want it here. STARTER_MODELS: list[StarterModel] = [ @@ -1656,6 +1680,8 @@ def _gemini_3_resolution_presets( flux_dev, sd35_medium, sd35_large, + ideogram_4_nf4, + ideogram_4_fp8, cyberrealistic_sd1, rev_animated_sd1, dreamshaper_8_sd1, @@ -1881,6 +1907,11 @@ def _gemini_3_resolution_presets( anima_lllite_sketch, ] +# nf4 is the recommended 24GB CUDA path; the fp8 build is offered separately for non-CUDA / more VRAM. +ideogram_bundle: list[StarterModel] = [ + ideogram_4_nf4, +] + STARTER_BUNDLES: dict[str, StarterModelBundle] = { BaseModelType.StableDiffusion1: StarterModelBundle(name="Stable Diffusion 1.5", models=sd1_bundle), BaseModelType.StableDiffusionXL: StarterModelBundle(name="SDXL", models=sdxl_bundle), @@ -1889,6 +1920,7 @@ def _gemini_3_resolution_presets( BaseModelType.ZImage: StarterModelBundle(name="Z-Image Turbo", models=zimage_bundle), BaseModelType.QwenImage: StarterModelBundle(name="Qwen Image", models=qwen_image_bundle), BaseModelType.Anima: StarterModelBundle(name="Anima", models=anima_bundle), + BaseModelType.Ideogram4: StarterModelBundle(name="Ideogram 4", models=ideogram_bundle), } assert len(STARTER_MODELS) == len({m.source for m in STARTER_MODELS}), "Duplicate starter models" diff --git a/invokeai/backend/model_manager/taxonomy.py b/invokeai/backend/model_manager/taxonomy.py index a2e4e58bdc4..6c91e48edbc 100644 --- a/invokeai/backend/model_manager/taxonomy.py +++ b/invokeai/backend/model_manager/taxonomy.py @@ -52,6 +52,8 @@ class BaseModelType(str, Enum): """Indicates the model is associated with CogView 4 model architecture.""" ZImage = "z-image" """Indicates the model is associated with Z-Image model architecture, including Z-Image-Turbo.""" + Ideogram4 = "ideogram-4" + """Indicates the model is associated with the Ideogram 4 text-to-image model architecture.""" External = "external" """Indicates the model is hosted by an external provider.""" QwenImage = "qwen-image" diff --git a/invokeai/backend/stable_diffusion/diffusion/conditioning_data.py b/invokeai/backend/stable_diffusion/diffusion/conditioning_data.py index 6a9959f1e87..0efec4dcbc0 100644 --- a/invokeai/backend/stable_diffusion/diffusion/conditioning_data.py +++ b/invokeai/backend/stable_diffusion/diffusion/conditioning_data.py @@ -88,6 +88,21 @@ def to(self, device: torch.device | None = None, dtype: torch.dtype | None = Non return self +@dataclass +class Ideogram4ConditioningInfo: + """Ideogram 4 text conditioning from the Qwen3-VL encoder. + + prompt_embeds is the concatenation of hidden states from 13 Qwen3-VL layers. + Shape: (seq_len, 53248) where 53248 = 4096 * 13. + """ + + prompt_embeds: torch.Tensor + + def to(self, device: torch.device | None = None, dtype: torch.dtype | None = None): + self.prompt_embeds = self.prompt_embeds.to(device=device, dtype=dtype) + return self + + @dataclass class QwenImageConditioningInfo: """Qwen Image Edit conditioning information from Qwen2.5-VL encoder.""" @@ -142,6 +157,7 @@ class ConditioningFieldData: | List[SD3ConditioningInfo] | List[CogView4ConditioningInfo] | List[ZImageConditioningInfo] + | List[Ideogram4ConditioningInfo] | List[QwenImageConditioningInfo] | List[AnimaConditioningInfo] ) diff --git a/invokeai/frontend/web/openapi.json b/invokeai/frontend/web/openapi.json index 662279c94d7..a89094dbdb4 100644 --- a/invokeai/frontend/web/openapi.json +++ b/invokeai/frontend/web/openapi.json @@ -819,6 +819,9 @@ { "$ref": "#/components/schemas/Main_Diffusers_ZImage_Config" }, + { + "$ref": "#/components/schemas/Main_Diffusers_Ideogram4_Config" + }, { "$ref": "#/components/schemas/Main_Checkpoint_SD1_Config" }, @@ -1151,6 +1154,9 @@ { "$ref": "#/components/schemas/Main_Diffusers_ZImage_Config" }, + { + "$ref": "#/components/schemas/Main_Diffusers_Ideogram4_Config" + }, { "$ref": "#/components/schemas/Main_Checkpoint_SD1_Config" }, @@ -1483,6 +1489,9 @@ { "$ref": "#/components/schemas/Main_Diffusers_ZImage_Config" }, + { + "$ref": "#/components/schemas/Main_Diffusers_Ideogram4_Config" + }, { "$ref": "#/components/schemas/Main_Checkpoint_SD1_Config" }, @@ -1860,6 +1869,9 @@ { "$ref": "#/components/schemas/Main_Diffusers_ZImage_Config" }, + { + "$ref": "#/components/schemas/Main_Diffusers_Ideogram4_Config" + }, { "$ref": "#/components/schemas/Main_Checkpoint_SD1_Config" }, @@ -2261,6 +2273,9 @@ { "$ref": "#/components/schemas/Main_Diffusers_ZImage_Config" }, + { + "$ref": "#/components/schemas/Main_Diffusers_Ideogram4_Config" + }, { "$ref": "#/components/schemas/Main_Checkpoint_SD1_Config" }, @@ -3492,6 +3507,9 @@ { "$ref": "#/components/schemas/Main_Diffusers_ZImage_Config" }, + { + "$ref": "#/components/schemas/Main_Diffusers_Ideogram4_Config" + }, { "$ref": "#/components/schemas/Main_Checkpoint_SD1_Config" }, @@ -11868,6 +11886,9 @@ { "$ref": "#/components/schemas/Main_Diffusers_ZImage_Config" }, + { + "$ref": "#/components/schemas/Main_Diffusers_Ideogram4_Config" + }, { "$ref": "#/components/schemas/Main_Checkpoint_SD1_Config" }, @@ -12407,6 +12428,7 @@ "flux2", "cogview4", "z-image", + "ideogram-4", "external", "qwen-image", "anima", @@ -19571,6 +19593,7 @@ "z_image_img2img", "z_image_inpaint", "z_image_outpaint", + "ideogram4_txt2img", "qwen_image_txt2img", "qwen_image_img2img", "qwen_image_inpaint", @@ -19977,6 +20000,23 @@ "orig_default": null, "orig_required": false }, + "ideogram4_caption": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The structured JSON caption encoded for Ideogram 4 inference", + "field_kind": "input", + "input": "any", + "orig_default": null, + "orig_required": false, + "title": "Ideogram4 Caption" + }, "hrf_enabled": { "anyOf": [ { @@ -29645,6 +29685,21 @@ { "$ref": "#/components/schemas/IdealSizeInvocation" }, + { + "$ref": "#/components/schemas/Ideogram4CaptionBuilderInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4DenoiseInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4LatentsToImageInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4ModelLoaderInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4TextEncoderInvocation" + }, { "$ref": "#/components/schemas/IfInvocation" }, @@ -30302,6 +30357,12 @@ { "$ref": "#/components/schemas/IdealSizeOutput" }, + { + "$ref": "#/components/schemas/Ideogram4ConditioningOutput" + }, + { + "$ref": "#/components/schemas/Ideogram4ModelLoaderOutput" + }, { "$ref": "#/components/schemas/IfInvocationOutput" }, @@ -32489,11 +32550,11 @@ "title": "IdealSizeOutput", "type": "object" }, - "IfInvocation": { - "category": "math", + "Ideogram4CaptionBuilderInvocation": { + "category": "conditioning", "class": "invocation", - "classification": "stable", - "description": "Selects between two optional inputs based on a boolean condition.", + "classification": "prototype", + "description": "Assembles the Ideogram 4 structured JSON caption at generation time.\n\nThe caption is built here (not in the graph builder) so the batch-injectable global `prompt` \u2014 which\ndynamic prompts and prompt batching vary \u2014 is folded into the encoded caption. The regions and color\npalette are fixed per generation and supplied as inputs. If the prompt is already a JSON object it is\npassed through verbatim; otherwise it is always wrapped in the structured JSON schema (never bare\nplain text \u2014 Ideogram's safety filter false-positives far more on plain text).", "node_pack": "invokeai", "properties": { "id": { @@ -32520,99 +32581,100 @@ "title": "Use Cache", "type": "boolean" }, - "condition": { - "default": false, - "description": "The condition used to select an input", + "prompt": { + "default": "", + "description": "The global prompt (becomes `high_level_description`, or is used verbatim if it is already a JSON caption).", "field_kind": "input", "input": "any", - "orig_default": false, + "orig_default": "", "orig_required": false, - "title": "Condition", - "type": "boolean" + "title": "Prompt", + "type": "string", + "ui_component": "textarea" }, - "true_input": { - "anyOf": [ - {}, - { - "type": "null" - } - ], - "default": null, - "description": "Selected when the condition is true", + "regions": { + "default": [], + "description": "Regional descriptions and bounding boxes assembled from Canvas Regional Guidance layers.", "field_kind": "input", "input": "any", - "orig_default": null, + "items": { + "$ref": "#/components/schemas/Ideogram4Region" + }, + "orig_default": [], "orig_required": false, - "title": "True Input", - "ui_type": "AnyField" + "title": "Regions", + "type": "array" }, - "false_input": { - "anyOf": [ - {}, - { - "type": "null" - } - ], - "default": null, - "description": "Selected when the condition is false", + "color_palette": { + "default": [], + "description": "Optional color palette as hex colors (#RRGGBB).", "field_kind": "input", "input": "any", - "orig_default": null, + "items": { + "type": "string" + }, + "orig_default": [], "orig_required": false, - "title": "False Input", - "ui_type": "AnyField" + "title": "Color Palette", + "type": "array" }, "type": { - "const": "if", - "default": "if", + "const": "ideogram4_caption_builder", + "default": "ideogram4_caption_builder", "field_kind": "node_attribute", "title": "type", "type": "string" } }, "required": ["type", "id"], - "tags": ["logic", "conditional"], - "title": "If", + "tags": ["prompt", "ideogram4"], + "title": "Caption Builder - Ideogram 4", "type": "object", "version": "1.0.0", "output": { - "$ref": "#/components/schemas/IfInvocationOutput" + "$ref": "#/components/schemas/StringOutput" } }, - "IfInvocationOutput": { + "Ideogram4ConditioningField": { + "description": "An Ideogram 4 conditioning tensor primitive value", + "properties": { + "conditioning_name": { + "description": "The name of conditioning tensor", + "title": "Conditioning Name", + "type": "string" + } + }, + "required": ["conditioning_name"], + "title": "Ideogram4ConditioningField", + "type": "object" + }, + "Ideogram4ConditioningOutput": { "class": "output", + "description": "Base class for nodes that output an Ideogram 4 text conditioning tensor.", "properties": { - "value": { - "anyOf": [ - {}, - { - "type": "null" - } - ], - "default": null, - "description": "The selected value", + "conditioning": { + "$ref": "#/components/schemas/Ideogram4ConditioningField", + "description": "Conditioning tensor", "field_kind": "output", - "title": "Output", - "ui_hidden": false, - "ui_type": "AnyField" + "ui_hidden": false }, "type": { - "const": "if_output", - "default": "if_output", + "const": "ideogram4_conditioning_output", + "default": "ideogram4_conditioning_output", "field_kind": "node_attribute", "title": "type", "type": "string" } }, - "required": ["output_meta", "value", "type", "type"], - "title": "IfInvocationOutput", + "required": ["output_meta", "conditioning", "type", "type"], + "title": "Ideogram4ConditioningOutput", "type": "object" }, - "ImageBatchInvocation": { - "category": "batch", + "Ideogram4DenoiseInvocation": { + "category": "latents", "class": "invocation", - "classification": "special", - "description": "Create a batched generation, where the workflow is executed once for each image in the batch.", + "classification": "prototype", + "description": "Runs the Ideogram 4 dual-branch flow-matching denoising loop (text-to-image).", "node_pack": "invokeai", "properties": { "id": { @@ -32639,59 +32701,676 @@ "title": "Use Cache", "type": "boolean" }, - "batch_group_id": { - "default": "None", - "description": "The ID of this batch node's group. If provided, all batch nodes in with the same ID will be 'zipped' before execution, and all nodes' collections must be of the same size.", - "enum": ["None", "Group 1", "Group 2", "Group 3", "Group 4", "Group 5"], + "transformer": { + "anyOf": [ + { + "$ref": "#/components/schemas/TransformerField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Transformer", "field_kind": "input", - "input": "direct", - "orig_default": "None", + "input": "connection", + "orig_required": true, + "title": "Transformer" + }, + "positive_conditioning": { + "anyOf": [ + { + "$ref": "#/components/schemas/Ideogram4ConditioningField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Positive conditioning tensor", + "field_kind": "input", + "input": "connection", + "orig_required": true + }, + "sampler_preset": { + "default": "V4_QUALITY_48", + "description": "Sampler preset (steps + guidance schedule + schedule mean/std).", + "enum": ["V4_QUALITY_48", "V4_DEFAULT_20", "V4_TURBO_12"], + "field_kind": "input", + "input": "any", + "orig_default": "V4_QUALITY_48", "orig_required": false, - "title": "Batch Group", + "title": "Sampler Preset", "type": "string" }, - "images": { + "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" + }, + "seed": { + "default": 0, + "description": "Randomness seed for reproducibility.", + "field_kind": "input", + "input": "any", + "orig_default": 0, + "orig_required": false, + "title": "Seed", + "type": "integer" + }, + "steps": { "anyOf": [ { - "items": { - "$ref": "#/components/schemas/ImageField" - }, - "minItems": 1, - "type": "array" + "maximum": 100, + "minimum": 2, + "type": "integer" }, { "type": "null" } ], "default": null, - "description": "The images to batch over", + "description": "Override the preset's step count (minimum 2, so a polish and a main step both exist). Leave empty to use the preset.", "field_kind": "input", "input": "any", - "orig_required": true, - "title": "Images" + "orig_default": null, + "orig_required": false, + "title": "Steps" + }, + "guidance_scale": { + "anyOf": [ + { + "maximum": 20.0, + "minimum": 1.0, + "type": "number" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Override the main guidance weight (the preset's polish tail is preserved). Empty = use the preset.", + "field_kind": "input", + "input": "any", + "orig_default": null, + "orig_required": false, + "title": "Guidance Scale" + }, + "mu": { + "anyOf": [ + { + "maximum": 4.0, + "minimum": -4.0, + "type": "number" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Override the logit-normal schedule mean (resolution-adjusted internally). Empty = use the preset.", + "field_kind": "input", + "input": "any", + "orig_default": null, + "orig_required": false, + "title": "Mu" }, "type": { - "const": "image_batch", - "default": "image_batch", + "const": "ideogram4_denoise", + "default": "ideogram4_denoise", "field_kind": "node_attribute", "title": "type", "type": "string" } }, "required": ["type", "id"], - "tags": ["primitives", "image", "batch", "special"], - "title": "Image Batch", + "tags": ["image", "ideogram4"], + "title": "Denoise - Ideogram 4", "type": "object", "version": "1.0.0", "output": { - "$ref": "#/components/schemas/ImageOutput" + "$ref": "#/components/schemas/LatentsOutput" } }, - "ImageBlurInvocation": { - "category": "image", + "Ideogram4LatentsToImageInvocation": { + "category": "latents", "class": "invocation", - "classification": "stable", - "description": "Blurs an image", + "classification": "prototype", + "description": "Decodes Ideogram 4 packed latents to an image with the FLUX.2-style VAE.", + "node_pack": "invokeai", + "properties": { + "board": { + "anyOf": [ + { + "$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": [ + { + "$ref": "#/components/schemas/MetadataField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Optional metadata to be saved with the image", + "field_kind": "internal", + "input": "connection", + "orig_required": false, + "ui_hidden": false + }, + "id": { + "description": "The id of this instance of an invocation. Must be unique among all instances of invocations.", + "field_kind": "node_attribute", + "title": "Id", + "type": "string" + }, + "is_intermediate": { + "default": false, + "description": "Whether or not this is an intermediate invocation.", + "field_kind": "node_attribute", + "input": "direct", + "orig_required": true, + "title": "Is Intermediate", + "type": "boolean", + "ui_hidden": false, + "ui_type": "IsIntermediate" + }, + "use_cache": { + "default": true, + "description": "Whether or not to use the cache", + "field_kind": "node_attribute", + "title": "Use Cache", + "type": "boolean" + }, + "latents": { + "anyOf": [ + { + "$ref": "#/components/schemas/LatentsField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Latents tensor", + "field_kind": "input", + "input": "connection", + "orig_required": true + }, + "vae": { + "anyOf": [ + { + "$ref": "#/components/schemas/VAEField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "VAE", + "field_kind": "input", + "input": "connection", + "orig_required": true + }, + "type": { + "const": "ideogram4_l2i", + "default": "ideogram4_l2i", + "field_kind": "node_attribute", + "title": "type", + "type": "string" + } + }, + "required": ["type", "id"], + "tags": ["latents", "image", "vae", "l2i", "ideogram4"], + "title": "Latents to Image - Ideogram 4", + "type": "object", + "version": "1.0.0", + "output": { + "$ref": "#/components/schemas/ImageOutput" + } + }, + "Ideogram4ModelLoaderInvocation": { + "category": "model", + "class": "invocation", + "classification": "prototype", + "description": "Loads an Ideogram 4 model, outputting its submodels.\n\nIdeogram 4 is distributed as a single bundled diffusers folder, so the transformer\n(both branches), the Qwen3-VL text encoder + tokenizer, and the VAE are all loaded\nfrom the one selected model.", + "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" + }, + "model": { + "$ref": "#/components/schemas/ModelIdentifierField", + "description": "The Ideogram 4 model to load.", + "field_kind": "input", + "input": "direct", + "orig_required": true, + "title": "Model", + "ui_model_base": ["ideogram-4"], + "ui_model_type": ["main"] + }, + "type": { + "const": "ideogram4_model_loader", + "default": "ideogram4_model_loader", + "field_kind": "node_attribute", + "title": "type", + "type": "string" + } + }, + "required": ["model", "type", "id"], + "tags": ["model", "ideogram4"], + "title": "Main Model - Ideogram 4", + "type": "object", + "version": "1.0.0", + "output": { + "$ref": "#/components/schemas/Ideogram4ModelLoaderOutput" + } + }, + "Ideogram4ModelLoaderOutput": { + "class": "output", + "description": "Ideogram 4 model loader output.", + "properties": { + "transformer": { + "$ref": "#/components/schemas/TransformerField", + "description": "Transformer", + "field_kind": "output", + "title": "Transformer", + "ui_hidden": false + }, + "qwen3_encoder": { + "$ref": "#/components/schemas/Qwen3EncoderField", + "description": "Qwen3 tokenizer and text encoder", + "field_kind": "output", + "title": "Qwen3-VL Encoder", + "ui_hidden": false + }, + "vae": { + "$ref": "#/components/schemas/VAEField", + "description": "VAE", + "field_kind": "output", + "title": "VAE", + "ui_hidden": false + }, + "type": { + "const": "ideogram4_model_loader_output", + "default": "ideogram4_model_loader_output", + "field_kind": "node_attribute", + "title": "type", + "type": "string" + } + }, + "required": ["output_meta", "transformer", "qwen3_encoder", "vae", "type", "type"], + "title": "Ideogram4ModelLoaderOutput", + "type": "object" + }, + "Ideogram4Region": { + "description": "A single region of an Ideogram 4 structured caption (description + optional bounding box).", + "properties": { + "prompt": { + "description": "The region's description (becomes the element's `desc`).", + "title": "Prompt", + "type": "string" + }, + "bbox": { + "anyOf": [ + { + "items": { + "maximum": 1000, + "minimum": 0, + "type": "integer" + }, + "maxItems": 4, + "minItems": 4, + "type": "array" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Normalized bounding box [y_min, x_min, y_max, x_max] (0\u20131000), or null for a region with no drawn content.", + "title": "Bbox" + } + }, + "required": ["prompt"], + "title": "Ideogram4Region", + "type": "object" + }, + "Ideogram4TextEncoderInvocation": { + "category": "conditioning", + "class": "invocation", + "classification": "prototype", + "description": "Encodes a prompt for Ideogram 4 using the Qwen3-VL encoder.\n\nThe prompt is normally a structured JSON caption (see the Ideogram 4 prompting guide);\nplain text also works but yields lower-quality results.", + "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" + }, + "prompt": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The prompt to encode. A structured JSON caption is recommended.", + "field_kind": "input", + "input": "any", + "orig_required": true, + "title": "Prompt", + "ui_component": "textarea" + }, + "qwen3_encoder": { + "anyOf": [ + { + "$ref": "#/components/schemas/Qwen3EncoderField" + }, + { + "type": "null" + } + ], + "default": null, + "description": "Qwen3 tokenizer and text encoder", + "field_kind": "input", + "input": "connection", + "orig_required": true, + "title": "Qwen3-VL Encoder" + }, + "type": { + "const": "ideogram4_text_encoder", + "default": "ideogram4_text_encoder", + "field_kind": "node_attribute", + "title": "type", + "type": "string" + } + }, + "required": ["type", "id"], + "tags": ["prompt", "conditioning", "ideogram4"], + "title": "Prompt - Ideogram 4", + "type": "object", + "version": "1.0.0", + "output": { + "$ref": "#/components/schemas/Ideogram4ConditioningOutput" + } + }, + "IfInvocation": { + "category": "math", + "class": "invocation", + "classification": "stable", + "description": "Selects between two optional inputs based on a boolean condition.", + "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" + }, + "condition": { + "default": false, + "description": "The condition used to select an input", + "field_kind": "input", + "input": "any", + "orig_default": false, + "orig_required": false, + "title": "Condition", + "type": "boolean" + }, + "true_input": { + "anyOf": [ + {}, + { + "type": "null" + } + ], + "default": null, + "description": "Selected when the condition is true", + "field_kind": "input", + "input": "any", + "orig_default": null, + "orig_required": false, + "title": "True Input", + "ui_type": "AnyField" + }, + "false_input": { + "anyOf": [ + {}, + { + "type": "null" + } + ], + "default": null, + "description": "Selected when the condition is false", + "field_kind": "input", + "input": "any", + "orig_default": null, + "orig_required": false, + "title": "False Input", + "ui_type": "AnyField" + }, + "type": { + "const": "if", + "default": "if", + "field_kind": "node_attribute", + "title": "type", + "type": "string" + } + }, + "required": ["type", "id"], + "tags": ["logic", "conditional"], + "title": "If", + "type": "object", + "version": "1.0.0", + "output": { + "$ref": "#/components/schemas/IfInvocationOutput" + } + }, + "IfInvocationOutput": { + "class": "output", + "properties": { + "value": { + "anyOf": [ + {}, + { + "type": "null" + } + ], + "default": null, + "description": "The selected value", + "field_kind": "output", + "title": "Output", + "ui_hidden": false, + "ui_type": "AnyField" + }, + "type": { + "const": "if_output", + "default": "if_output", + "field_kind": "node_attribute", + "title": "type", + "type": "string" + } + }, + "required": ["output_meta", "value", "type", "type"], + "title": "IfInvocationOutput", + "type": "object" + }, + "ImageBatchInvocation": { + "category": "batch", + "class": "invocation", + "classification": "special", + "description": "Create a batched generation, where the workflow is executed once for each image in the batch.", + "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" + }, + "batch_group_id": { + "default": "None", + "description": "The ID of this batch node's group. If provided, all batch nodes in with the same ID will be 'zipped' before execution, and all nodes' collections must be of the same size.", + "enum": ["None", "Group 1", "Group 2", "Group 3", "Group 4", "Group 5"], + "field_kind": "input", + "input": "direct", + "orig_default": "None", + "orig_required": false, + "title": "Batch Group", + "type": "string" + }, + "images": { + "anyOf": [ + { + "items": { + "$ref": "#/components/schemas/ImageField" + }, + "minItems": 1, + "type": "array" + }, + { + "type": "null" + } + ], + "default": null, + "description": "The images to batch over", + "field_kind": "input", + "input": "any", + "orig_required": true, + "title": "Images" + }, + "type": { + "const": "image_batch", + "default": "image_batch", + "field_kind": "node_attribute", + "title": "type", + "type": "string" + } + }, + "required": ["type", "id"], + "tags": ["primitives", "image", "batch", "special"], + "title": "Image Batch", + "type": "object", + "version": "1.0.0", + "output": { + "$ref": "#/components/schemas/ImageOutput" + } + }, + "ImageBlurInvocation": { + "category": "image", + "class": "invocation", + "classification": "stable", + "description": "Blurs an image", "node_pack": "invokeai", "properties": { "board": { @@ -37347,6 +38026,21 @@ { "$ref": "#/components/schemas/IdealSizeInvocation" }, + { + "$ref": "#/components/schemas/Ideogram4CaptionBuilderInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4DenoiseInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4LatentsToImageInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4ModelLoaderInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4TextEncoderInvocation" + }, { "$ref": "#/components/schemas/IfInvocation" }, @@ -37961,6 +38655,12 @@ { "$ref": "#/components/schemas/IdealSizeOutput" }, + { + "$ref": "#/components/schemas/Ideogram4ConditioningOutput" + }, + { + "$ref": "#/components/schemas/Ideogram4ModelLoaderOutput" + }, { "$ref": "#/components/schemas/IfInvocationOutput" }, @@ -38503,6 +39203,21 @@ { "$ref": "#/components/schemas/IdealSizeInvocation" }, + { + "$ref": "#/components/schemas/Ideogram4CaptionBuilderInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4DenoiseInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4LatentsToImageInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4ModelLoaderInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4TextEncoderInvocation" + }, { "$ref": "#/components/schemas/IfInvocation" }, @@ -39319,6 +40034,21 @@ "ideal_size": { "$ref": "#/components/schemas/IdealSizeOutput" }, + "ideogram4_caption_builder": { + "$ref": "#/components/schemas/StringOutput" + }, + "ideogram4_denoise": { + "$ref": "#/components/schemas/LatentsOutput" + }, + "ideogram4_l2i": { + "$ref": "#/components/schemas/ImageOutput" + }, + "ideogram4_model_loader": { + "$ref": "#/components/schemas/Ideogram4ModelLoaderOutput" + }, + "ideogram4_text_encoder": { + "$ref": "#/components/schemas/Ideogram4ConditioningOutput" + }, "if": { "$ref": "#/components/schemas/IfInvocationOutput" }, @@ -39911,6 +40641,11 @@ "heuristic_resize", "i2l", "ideal_size", + "ideogram4_caption_builder", + "ideogram4_denoise", + "ideogram4_l2i", + "ideogram4_model_loader", + "ideogram4_text_encoder", "if", "image", "image_batch", @@ -40435,6 +41170,21 @@ { "$ref": "#/components/schemas/IdealSizeInvocation" }, + { + "$ref": "#/components/schemas/Ideogram4CaptionBuilderInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4DenoiseInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4LatentsToImageInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4ModelLoaderInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4TextEncoderInvocation" + }, { "$ref": "#/components/schemas/IfInvocation" }, @@ -41337,6 +42087,21 @@ { "$ref": "#/components/schemas/IdealSizeInvocation" }, + { + "$ref": "#/components/schemas/Ideogram4CaptionBuilderInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4DenoiseInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4LatentsToImageInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4ModelLoaderInvocation" + }, + { + "$ref": "#/components/schemas/Ideogram4TextEncoderInvocation" + }, { "$ref": "#/components/schemas/IfInvocation" }, @@ -48291,18 +49056,184 @@ }, "base": { "type": "string", - "const": "flux", + "const": "flux", + "title": "Base", + "default": "flux" + }, + "format": { + "type": "string", + "const": "bnb_quantized_nf4b", + "title": "Format", + "default": "bnb_quantized_nf4b" + }, + "variant": { + "$ref": "#/components/schemas/FluxVariantType" + } + }, + "type": "object", + "required": [ + "key", + "hash", + "path", + "file_size", + "name", + "description", + "source", + "source_type", + "source_api_response", + "source_url", + "cover_image", + "type", + "trigger_phrases", + "default_settings", + "config_path", + "base", + "format", + "variant" + ], + "title": "Main_BnBNF4_FLUX_Config", + "description": "Model config for main checkpoint models." + }, + "Main_Checkpoint_Anima_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": { + "$ref": "#/components/schemas/ModelSourceType", + "description": "The type of source" + }, + "source_api_response": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Source Api Response", + "description": "The original API response from the source, as stringified JSON." + }, + "source_url": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Source Url", + "description": "Optional URL for the model (e.g. download page or model page)." + }, + "cover_image": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Cover Image", + "description": "Url for image to preview model" + }, + "type": { + "type": "string", + "const": "main", + "title": "Type", + "default": "main" + }, + "trigger_phrases": { + "anyOf": [ + { + "items": { + "type": "string" + }, + "type": "array", + "uniqueItems": true + }, + { + "type": "null" + } + ], + "title": "Trigger Phrases", + "description": "Set of trigger phrases for this model" + }, + "default_settings": { + "anyOf": [ + { + "$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": "anima", "title": "Base", - "default": "flux" + "default": "anima" }, "format": { "type": "string", - "const": "bnb_quantized_nf4b", + "const": "checkpoint", "title": "Format", - "default": "bnb_quantized_nf4b" - }, - "variant": { - "$ref": "#/components/schemas/FluxVariantType" + "default": "checkpoint" } }, "type": "object", @@ -48323,13 +49254,12 @@ "default_settings", "config_path", "base", - "format", - "variant" + "format" ], - "title": "Main_BnBNF4_FLUX_Config", - "description": "Model config for main checkpoint models." + "title": "Main_Checkpoint_Anima_Config", + "description": "Model config for Anima single-file checkpoint models (safetensors).\n\nAnima is built on NVIDIA Cosmos Predict2 DiT with a custom LLM Adapter\nthat bridges Qwen3 0.6B text encoder outputs to the DiT." }, - "Main_Checkpoint_Anima_Config": { + "Main_Checkpoint_FLUX_Config": { "properties": { "key": { "type": "string", @@ -48458,17 +49388,20 @@ "title": "Config Path", "description": "Path to the config for this model, if any." }, - "base": { - "type": "string", - "const": "anima", - "title": "Base", - "default": "anima" - }, "format": { "type": "string", "const": "checkpoint", "title": "Format", "default": "checkpoint" + }, + "base": { + "type": "string", + "const": "flux", + "title": "Base", + "default": "flux" + }, + "variant": { + "$ref": "#/components/schemas/FluxVariantType" } }, "type": "object", @@ -48488,13 +49421,14 @@ "trigger_phrases", "default_settings", "config_path", + "format", "base", - "format" + "variant" ], - "title": "Main_Checkpoint_Anima_Config", - "description": "Model config for Anima single-file checkpoint models (safetensors).\n\nAnima is built on NVIDIA Cosmos Predict2 DiT with a custom LLM Adapter\nthat bridges Qwen3 0.6B text encoder outputs to the DiT." + "title": "Main_Checkpoint_FLUX_Config", + "description": "Model config for main checkpoint models." }, - "Main_Checkpoint_FLUX_Config": { + "Main_Checkpoint_Flux2_Config": { "properties": { "key": { "type": "string", @@ -48631,12 +49565,12 @@ }, "base": { "type": "string", - "const": "flux", + "const": "flux2", "title": "Base", - "default": "flux" + "default": "flux2" }, "variant": { - "$ref": "#/components/schemas/FluxVariantType" + "$ref": "#/components/schemas/Flux2VariantType" } }, "type": "object", @@ -48660,10 +49594,10 @@ "base", "variant" ], - "title": "Main_Checkpoint_FLUX_Config", - "description": "Model config for main checkpoint models." + "title": "Main_Checkpoint_Flux2_Config", + "description": "Model config for FLUX.2 checkpoint models (e.g. Klein)." }, - "Main_Checkpoint_Flux2_Config": { + "Main_Checkpoint_QwenImage_Config": { "properties": { "key": { "type": "string", @@ -48792,20 +49726,27 @@ "title": "Config Path", "description": "Path to the config for this model, if any." }, + "base": { + "type": "string", + "const": "qwen-image", + "title": "Base", + "default": "qwen-image" + }, "format": { "type": "string", "const": "checkpoint", "title": "Format", "default": "checkpoint" }, - "base": { - "type": "string", - "const": "flux2", - "title": "Base", - "default": "flux2" - }, "variant": { - "$ref": "#/components/schemas/Flux2VariantType" + "anyOf": [ + { + "$ref": "#/components/schemas/QwenImageVariantType" + }, + { + "type": "null" + } + ] } }, "type": "object", @@ -48825,14 +49766,14 @@ "trigger_phrases", "default_settings", "config_path", - "format", "base", + "format", "variant" ], - "title": "Main_Checkpoint_Flux2_Config", - "description": "Model config for FLUX.2 checkpoint models (e.g. Klein)." + "title": "Main_Checkpoint_QwenImage_Config", + "description": "Model config for Qwen Image single-file checkpoint models (safetensors, etc).\n\nCovers both raw bf16/fp16 checkpoints and ComfyUI-style fp8_scaled checkpoints.\nThe loader dequantizes fp8 weights back to bf16 at load time; the\n`default_settings.fp8_storage` toggle can then optionally re-cast to fp8 for\nVRAM savings." }, - "Main_Checkpoint_QwenImage_Config": { + "Main_Checkpoint_SD1_Config": { "properties": { "key": { "type": "string", @@ -48961,27 +49902,23 @@ "title": "Config Path", "description": "Path to the config for this model, if any." }, - "base": { - "type": "string", - "const": "qwen-image", - "title": "Base", - "default": "qwen-image" - }, "format": { "type": "string", "const": "checkpoint", "title": "Format", "default": "checkpoint" }, + "prediction_type": { + "$ref": "#/components/schemas/SchedulerPredictionType" + }, "variant": { - "anyOf": [ - { - "$ref": "#/components/schemas/QwenImageVariantType" - }, - { - "type": "null" - } - ] + "$ref": "#/components/schemas/ModelVariantType" + }, + "base": { + "type": "string", + "const": "sd-1", + "title": "Base", + "default": "sd-1" } }, "type": "object", @@ -49001,14 +49938,14 @@ "trigger_phrases", "default_settings", "config_path", - "base", "format", - "variant" + "prediction_type", + "variant", + "base" ], - "title": "Main_Checkpoint_QwenImage_Config", - "description": "Model config for Qwen Image single-file checkpoint models (safetensors, etc).\n\nCovers both raw bf16/fp16 checkpoints and ComfyUI-style fp8_scaled checkpoints.\nThe loader dequantizes fp8 weights back to bf16 at load time; the\n`default_settings.fp8_storage` toggle can then optionally re-cast to fp8 for\nVRAM savings." + "title": "Main_Checkpoint_SD1_Config" }, - "Main_Checkpoint_SD1_Config": { + "Main_Checkpoint_SD2_Config": { "properties": { "key": { "type": "string", @@ -49151,9 +50088,9 @@ }, "base": { "type": "string", - "const": "sd-1", + "const": "sd-2", "title": "Base", - "default": "sd-1" + "default": "sd-2" } }, "type": "object", @@ -49178,9 +50115,9 @@ "variant", "base" ], - "title": "Main_Checkpoint_SD1_Config" + "title": "Main_Checkpoint_SD2_Config" }, - "Main_Checkpoint_SD2_Config": { + "Main_Checkpoint_SDXLRefiner_Config": { "properties": { "key": { "type": "string", @@ -49323,9 +50260,9 @@ }, "base": { "type": "string", - "const": "sd-2", + "const": "sdxl-refiner", "title": "Base", - "default": "sd-2" + "default": "sdxl-refiner" } }, "type": "object", @@ -49350,9 +50287,9 @@ "variant", "base" ], - "title": "Main_Checkpoint_SD2_Config" + "title": "Main_Checkpoint_SDXLRefiner_Config" }, - "Main_Checkpoint_SDXLRefiner_Config": { + "Main_Checkpoint_SDXL_Config": { "properties": { "key": { "type": "string", @@ -49495,9 +50432,9 @@ }, "base": { "type": "string", - "const": "sdxl-refiner", + "const": "sdxl", "title": "Base", - "default": "sdxl-refiner" + "default": "sdxl" } }, "type": "object", @@ -49522,9 +50459,9 @@ "variant", "base" ], - "title": "Main_Checkpoint_SDXLRefiner_Config" + "title": "Main_Checkpoint_SDXL_Config" }, - "Main_Checkpoint_SDXL_Config": { + "Main_Checkpoint_ZImage_Config": { "properties": { "key": { "type": "string", @@ -49653,23 +50590,20 @@ "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" }, - "prediction_type": { - "$ref": "#/components/schemas/SchedulerPredictionType" - }, "variant": { - "$ref": "#/components/schemas/ModelVariantType" - }, - "base": { - "type": "string", - "const": "sdxl", - "title": "Base", - "default": "sdxl" + "$ref": "#/components/schemas/ZImageVariantType" } }, "type": "object", @@ -49689,14 +50623,14 @@ "trigger_phrases", "default_settings", "config_path", + "base", "format", - "prediction_type", - "variant", - "base" + "variant" ], - "title": "Main_Checkpoint_SDXL_Config" + "title": "Main_Checkpoint_ZImage_Config", + "description": "Model config for Z-Image single-file checkpoint models (safetensors, etc)." }, - "Main_Checkpoint_ZImage_Config": { + "Main_Diffusers_CogView4_Config": { "properties": { "key": { "type": "string", @@ -49813,32 +50747,21 @@ ], "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", + "const": "diffusers", "title": "Format", - "default": "checkpoint" + "default": "diffusers" }, - "variant": { - "$ref": "#/components/schemas/ZImageVariantType" + "repo_variant": { + "$ref": "#/components/schemas/ModelRepoVariant", + "default": "" + }, + "base": { + "type": "string", + "const": "cogview4", + "title": "Base", + "default": "cogview4" } }, "type": "object", @@ -49857,15 +50780,13 @@ "type", "trigger_phrases", "default_settings", - "config_path", - "base", "format", - "variant" + "repo_variant", + "base" ], - "title": "Main_Checkpoint_ZImage_Config", - "description": "Model config for Z-Image single-file checkpoint models (safetensors, etc)." + "title": "Main_Diffusers_CogView4_Config" }, - "Main_Diffusers_CogView4_Config": { + "Main_Diffusers_FLUX_Config": { "properties": { "key": { "type": "string", @@ -49994,9 +50915,12 @@ }, "base": { "type": "string", - "const": "cogview4", + "const": "flux", "title": "Base", - "default": "cogview4" + "default": "flux" + }, + "variant": { + "$ref": "#/components/schemas/FluxVariantType" } }, "type": "object", @@ -50017,11 +50941,13 @@ "default_settings", "format", "repo_variant", - "base" + "base", + "variant" ], - "title": "Main_Diffusers_CogView4_Config" + "title": "Main_Diffusers_FLUX_Config", + "description": "Model config for FLUX.1 models in diffusers format." }, - "Main_Diffusers_FLUX_Config": { + "Main_Diffusers_Flux2_Config": { "properties": { "key": { "type": "string", @@ -50150,12 +51076,12 @@ }, "base": { "type": "string", - "const": "flux", + "const": "flux2", "title": "Base", - "default": "flux" + "default": "flux2" }, "variant": { - "$ref": "#/components/schemas/FluxVariantType" + "$ref": "#/components/schemas/Flux2VariantType" } }, "type": "object", @@ -50179,10 +51105,10 @@ "base", "variant" ], - "title": "Main_Diffusers_FLUX_Config", - "description": "Model config for FLUX.1 models in diffusers format." + "title": "Main_Diffusers_Flux2_Config", + "description": "Model config for FLUX.2 models in diffusers format (e.g. FLUX.2 Klein)." }, - "Main_Diffusers_Flux2_Config": { + "Main_Diffusers_Ideogram4_Config": { "properties": { "key": { "type": "string", @@ -50311,12 +51237,9 @@ }, "base": { "type": "string", - "const": "flux2", + "const": "ideogram-4", "title": "Base", - "default": "flux2" - }, - "variant": { - "$ref": "#/components/schemas/Flux2VariantType" + "default": "ideogram-4" } }, "type": "object", @@ -50337,11 +51260,10 @@ "default_settings", "format", "repo_variant", - "base", - "variant" + "base" ], - "title": "Main_Diffusers_Flux2_Config", - "description": "Model config for FLUX.2 models in diffusers format (e.g. FLUX.2 Klein)." + "title": "Main_Diffusers_Ideogram4_Config", + "description": "Model config for Ideogram 4 diffusers models (nf4 / fp8 quantized).\n\nThe on-disk layout is a diffusers pipeline folder bundling two transformers\n(transformer/ + unconditional_transformer/), a Qwen3-VL text_encoder/ + tokenizer/,\nand a FLUX.2-style vae/. Quantization (nf4 vs fp8) lives inside the component folders\nand is detected by the loader, not here." }, "Main_Diffusers_QwenImage_Config": { "properties": { @@ -55970,6 +56892,9 @@ { "$ref": "#/components/schemas/Main_Diffusers_ZImage_Config" }, + { + "$ref": "#/components/schemas/Main_Diffusers_Ideogram4_Config" + }, { "$ref": "#/components/schemas/Main_Checkpoint_SD1_Config" }, @@ -56548,6 +57473,9 @@ { "$ref": "#/components/schemas/Main_Diffusers_ZImage_Config" }, + { + "$ref": "#/components/schemas/Main_Diffusers_Ideogram4_Config" + }, { "$ref": "#/components/schemas/Main_Checkpoint_SD1_Config" }, @@ -57011,6 +57939,9 @@ { "$ref": "#/components/schemas/Main_Diffusers_ZImage_Config" }, + { + "$ref": "#/components/schemas/Main_Diffusers_Ideogram4_Config" + }, { "$ref": "#/components/schemas/Main_Checkpoint_SD1_Config" }, @@ -57330,6 +58261,9 @@ { "$ref": "#/components/schemas/Main_Diffusers_ZImage_Config" }, + { + "$ref": "#/components/schemas/Main_Diffusers_Ideogram4_Config" + }, { "$ref": "#/components/schemas/Main_Checkpoint_SD1_Config" }, @@ -58098,6 +59032,9 @@ { "$ref": "#/components/schemas/Main_Diffusers_ZImage_Config" }, + { + "$ref": "#/components/schemas/Main_Diffusers_Ideogram4_Config" + }, { "$ref": "#/components/schemas/Main_Checkpoint_SD1_Config" }, diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json index 373ed36f473..d51a0004efc 100644 --- a/invokeai/frontend/web/public/locales/en.json +++ b/invokeai/frontend/web/public/locales/en.json @@ -1633,6 +1633,14 @@ }, "parameters": { "aspect": "Aspect", + "samplerPreset": "Sampler Preset", + "colorPalette": "Color Palette", + "ideogram4Caption": "Structured Caption", + "ideogram4SamplerPresets": { + "quality": "Quality ({{steps}} steps)", + "default": "Default ({{steps}} steps)", + "turbo": "Turbo ({{steps}} steps)" + }, "duration": "Duration", "lockAspectRatio": "Lock Aspect Ratio", "swapDimensions": "Swap Dimensions", @@ -2450,7 +2458,7 @@ "fluxDevLicense": { "heading": "Non-Commercial License", "paragraphs": [ - "This model is licensed for non-commercial use only. FLUX.1 [dev] models use the FLUX.1 [dev] Non-Commercial License, and FLUX.2 Klein 9B uses the FLUX.2 Non-Commercial License." + "This model is licensed for non-commercial use only. FLUX.1 [dev] models use the FLUX.1 [dev] Non-Commercial License, FLUX.2 Klein 9B uses the FLUX.2 Non-Commercial License, and Ideogram 4 uses the Ideogram 4 Non-Commercial License." ] }, "optimizedDenoising": { @@ -2916,6 +2924,7 @@ "rgReferenceImagesNotSupported": "regional Reference Images not supported for selected base model", "rgAutoNegativeNotSupported": "Auto-Negative not supported for selected base model", "rgNoRegion": "no region drawn", + "ideogram4Txt2ImgOnly": "Ideogram 4 is text-to-image only; raster layers and inpaint masks are not supported", "fluxFillIncompatibleWithControlLoRA": "Control LoRA is not compatible with FLUX Fill", "controlAdapterDuplicateAnimaLLLiteModel": "each Anima control model can only be used by one Control Layer", "bboxHidden": "Bounding box is hidden (shift+o to toggle)" diff --git a/invokeai/frontend/web/src/features/controlLayers/store/paramsSlice.test.ts b/invokeai/frontend/web/src/features/controlLayers/store/paramsSlice.test.ts index d210d2fd2ac..a7192f8595f 100644 --- a/invokeai/frontend/web/src/features/controlLayers/store/paramsSlice.test.ts +++ b/invokeai/frontend/web/src/features/controlLayers/store/paramsSlice.test.ts @@ -17,6 +17,7 @@ import { selectModelSupportsRefImages, selectModelSupportsSeed, selectModelSupportsSteps, + setIdeogram4Steps, } from './paramsSlice'; import { getInitialParamsState } from './types'; @@ -216,3 +217,29 @@ describe('paramsSlice prompt history', () => { expect(removed.positivePromptHistory).toEqual([{ positivePrompt: 'a cat', negativePrompt: 'low quality' }]); }); }); + +describe('paramsSlice ideogram4Steps normalization (backend requires >= 2)', () => { + it('keeps a valid override step count', () => { + const state = paramsSliceConfig.slice.reducer(getInitialParamsState(), setIdeogram4Steps(20)); + expect(state.ideogram4Steps).toBe(20); + }); + + it('accepts null (use the preset)', () => { + const state = paramsSliceConfig.slice.reducer(getInitialParamsState(), setIdeogram4Steps(null)); + expect(state.ideogram4Steps).toBeNull(); + }); + + it('normalizes a stale out-of-range value (1, below the backend min of 2) to null', () => { + const state = paramsSliceConfig.slice.reducer(getInitialParamsState(), setIdeogram4Steps(1)); + expect(state.ideogram4Steps).toBeNull(); + }); + + it('normalizes a stale rehydrated ideogram4Steps of 1 to null instead of failing the whole slice', () => { + const migrate = paramsSliceConfig.persistConfig?.migrate; + expect(migrate).toBeDefined(); + const rehydrated = migrate?.({ ...getInitialParamsState(), ideogram4Steps: 1 }) as ReturnType< + typeof getInitialParamsState + >; + expect(rehydrated.ideogram4Steps).toBeNull(); + }); +}); diff --git a/invokeai/frontend/web/src/features/controlLayers/store/paramsSlice.ts b/invokeai/frontend/web/src/features/controlLayers/store/paramsSlice.ts index b7b1a6ef1c0..6c438a45296 100644 --- a/invokeai/frontend/web/src/features/controlLayers/store/paramsSlice.ts +++ b/invokeai/frontend/web/src/features/controlLayers/store/paramsSlice.ts @@ -39,6 +39,7 @@ import type { ParameterControlLoRAModel, ParameterFluxDypePreset, ParameterGuidance, + ParameterIdeogram4SamplerPreset, ParameterModel, ParameterNegativePrompt, ParameterPositivePrompt, @@ -98,6 +99,23 @@ const slice = createSlice({ setZImageShift: (state, action: PayloadAction) => { state.zImageShift = action.payload; }, + setIdeogram4SamplerPreset: (state, action: PayloadAction) => { + state.ideogram4SamplerPreset = action.payload; + }, + setIdeogram4Steps: (state, action: PayloadAction) => { + // Normalize through the schema so a stale/out-of-range value (e.g. 1, below the backend's min of 2) + // becomes null (= use preset) rather than being dispatched straight into the graph. + state.ideogram4Steps = zParamsState.shape.ideogram4Steps.parse(action.payload); + }, + setIdeogram4GuidanceScale: (state, action: PayloadAction) => { + state.ideogram4GuidanceScale = action.payload; + }, + setIdeogram4Mu: (state, action: PayloadAction) => { + state.ideogram4Mu = action.payload; + }, + setIdeogram4ColorPalette: (state, action: PayloadAction) => { + state.ideogram4ColorPalette = action.payload; + }, setZImageSeedVarianceEnabled: (state, action: PayloadAction) => { state.zImageSeedVarianceEnabled = action.payload; }, @@ -660,6 +678,11 @@ export const { setFluxDypeExponent, setZImageScheduler, setZImageShift, + setIdeogram4SamplerPreset, + setIdeogram4Steps, + setIdeogram4GuidanceScale, + setIdeogram4Mu, + setIdeogram4ColorPalette, setZImageSeedVarianceEnabled, setZImageSeedVarianceStrength, setZImageSeedVarianceRandomizePercent, @@ -775,6 +798,7 @@ export const selectIsFLUX = createParamsSelector((params) => params.model?.base export const selectIsSD3 = createParamsSelector((params) => params.model?.base === 'sd-3'); export const selectIsCogView4 = createParamsSelector((params) => params.model?.base === 'cogview4'); export const selectIsZImage = createParamsSelector((params) => params.model?.base === 'z-image'); +export const selectIsIdeogram4 = createParamsSelector((params) => params.model?.base === 'ideogram-4'); export const selectIsAnima = createParamsSelector((params) => params.model?.base === 'anima'); export const selectIsFlux2 = createParamsSelector((params) => params.model?.base === 'flux2'); export const selectIsExternal = createParamsSelector((params) => params.model?.base === 'external'); @@ -901,6 +925,10 @@ export const selectModelSupportsSteps = createSelector(selectModel, (model) => { if (model.base === 'external') { return false; } + if (model.base === 'ideogram-4') { + // Ideogram 4 bundles step count into its sampler preset, so there is no standalone steps control. + return false; + } return true; }); export const selectModelSupportsDimensions = createSelector(selectModel, selectModelConfig, (model, modelConfig) => { @@ -925,6 +953,11 @@ export const selectFluxDypeScale = createParamsSelector((params) => params.fluxD export const selectFluxDypeExponent = createParamsSelector((params) => params.fluxDypeExponent); export const selectZImageScheduler = createParamsSelector((params) => params.zImageScheduler); export const selectZImageShift = createParamsSelector((params) => params.zImageShift); +export const selectIdeogram4SamplerPreset = createParamsSelector((params) => params.ideogram4SamplerPreset); +export const selectIdeogram4Steps = createParamsSelector((params) => params.ideogram4Steps); +export const selectIdeogram4GuidanceScale = createParamsSelector((params) => params.ideogram4GuidanceScale); +export const selectIdeogram4Mu = createParamsSelector((params) => params.ideogram4Mu); +export const selectIdeogram4ColorPalette = createParamsSelector((params) => params.ideogram4ColorPalette); export const selectZImageSeedVarianceEnabled = createParamsSelector((params) => params.zImageSeedVarianceEnabled); export const selectZImageSeedVarianceStrength = createParamsSelector((params) => params.zImageSeedVarianceStrength); export const selectZImageSeedVarianceRandomizePercent = createParamsSelector( diff --git a/invokeai/frontend/web/src/features/controlLayers/store/types.ts b/invokeai/frontend/web/src/features/controlLayers/store/types.ts index 8cfd0d460dd..ada43ef1e0d 100644 --- a/invokeai/frontend/web/src/features/controlLayers/store/types.ts +++ b/invokeai/frontend/web/src/features/controlLayers/store/types.ts @@ -15,6 +15,7 @@ import { zParameterFluxDypeScale, zParameterFluxScheduler, zParameterGuidance, + zParameterIdeogram4SamplerPreset, zParameterImageDimension, zParameterMaskBlurMethod, zParameterModel, @@ -822,6 +823,17 @@ export const zParamsState = z.object({ fluxDypeExponent: zParameterFluxDypeExponent, zImageScheduler: zParameterZImageScheduler, zImageShift: z.number().min(0).max(3).nullable(), + // Defaults make these resilient to rehydration of persisted state saved before the fields existed. + ideogram4SamplerPreset: zParameterIdeogram4SamplerPreset.default('V4_QUALITY_48'), + // Optional advanced overrides of the Ideogram 4 sampler preset (null = use the preset's value). + // Backend requires steps >= 2 (a polish and a main step). `.catch(null)` normalizes a stale/invalid + // persisted or recalled value (e.g. 1 from an older build) to null (= use preset) instead of letting an + // out-of-range value reach the graph or breaking the whole persisted params slice on rehydrate. + ideogram4Steps: z.number().int().min(2).max(100).nullable().catch(null).default(null), + ideogram4GuidanceScale: z.number().min(1).max(20).nullable().default(null), + ideogram4Mu: z.number().min(-4).max(4).nullable().default(null), + // Hex colors (#RRGGBB) injected into the JSON caption's style_description.color_palette. + ideogram4ColorPalette: z.array(z.string()).default([]), upscaleScheduler: zParameterScheduler, upscaleCfgScale: zParameterCFGScale, seed: zParameterSeed, @@ -912,6 +924,11 @@ export const getInitialParamsState = (): ParamsState => ({ fluxDypeExponent: 2.0, zImageScheduler: 'euler', zImageShift: null, + ideogram4SamplerPreset: 'V4_QUALITY_48', + ideogram4Steps: null, + ideogram4GuidanceScale: null, + ideogram4Mu: null, + ideogram4ColorPalette: [], upscaleScheduler: 'kdpm_2', upscaleCfgScale: 2, seed: 0, diff --git a/invokeai/frontend/web/src/features/controlLayers/store/validators.ts b/invokeai/frontend/web/src/features/controlLayers/store/validators.ts index a497a38a5d7..91c334c8564 100644 --- a/invokeai/frontend/web/src/features/controlLayers/store/validators.ts +++ b/invokeai/frontend/web/src/features/controlLayers/store/validators.ts @@ -19,6 +19,7 @@ const WARNINGS = { RG_REFERENCE_IMAGES_NOT_SUPPORTED: 'controlLayers.warnings.rgReferenceImagesNotSupported', RG_AUTO_NEGATIVE_NOT_SUPPORTED: 'controlLayers.warnings.rgAutoNegativeNotSupported', RG_NO_REGION: 'controlLayers.warnings.rgNoRegion', + IDEOGRAM4_TXT2IMG_ONLY: 'controlLayers.warnings.ideogram4Txt2ImgOnly', IP_ADAPTER_NO_MODEL_SELECTED: 'controlLayers.warnings.ipAdapterNoModelSelected', IP_ADAPTER_INCOMPATIBLE_BASE_MODEL: 'controlLayers.warnings.ipAdapterIncompatibleBaseModel', IP_ADAPTER_NO_IMAGE_SELECTED: 'controlLayers.warnings.ipAdapterNoImageSelected', @@ -100,6 +101,21 @@ export const getRegionalGuidanceWarnings = ( } } + if (model.base === 'ideogram-4') { + // Ideogram 4 regions contribute only a positive prompt + bbox to the structured caption + // (see collectIdeogram4PromptInputs). Negative prompts, auto-negative and reference images are + // silently dropped, so warn they are unsupported rather than letting the layer look effective. + if (entity.negativePrompt !== null) { + warnings.push(WARNINGS.RG_NEGATIVE_PROMPT_NOT_SUPPORTED); + } + if (entity.autoNegative) { + warnings.push(WARNINGS.RG_AUTO_NEGATIVE_NOT_SUPPORTED); + } + if (entity.referenceImages.length > 0) { + warnings.push(WARNINGS.RG_REFERENCE_IMAGES_NOT_SUPPORTED); + } + } + entity.referenceImages.forEach(({ config }) => { if (!config.model) { // No model selected @@ -239,23 +255,32 @@ export const getControlLayerWarnings = ( }; export const getRasterLayerWarnings = ( - _entity: CanvasRasterLayerState, - _model: MainOrExternalModelConfig | null | undefined + entity: CanvasRasterLayerState, + model: MainOrExternalModelConfig | null | undefined ): WarningTKey[] => { const warnings: WarningTKey[] = []; - // There are no warnings at the moment for raster layers. + // Ideogram 4 is text-to-image only (buildIdeogram4Graph asserts txt2img). A raster layer with content + // makes the compositor pick img2img/outpaint, which the graph builder rejects only at enqueue — warn + // here so canvas readiness blocks it up front. + if (model?.base === 'ideogram-4' && entity.objects.length > 0) { + warnings.push(WARNINGS.IDEOGRAM4_TXT2IMG_ONLY); + } return warnings; }; export const getInpaintMaskWarnings = ( - _entity: CanvasInpaintMaskState, - _model: MainOrExternalModelConfig | null | undefined + entity: CanvasInpaintMaskState, + model: MainOrExternalModelConfig | null | undefined ): WarningTKey[] => { const warnings: WarningTKey[] = []; - // There are no warnings at the moment for inpaint masks. + // Ideogram 4 is text-to-image only; an inpaint mask with content makes the compositor pick inpaint, + // which the Ideogram graph builder cannot handle. Warn so canvas readiness blocks it before enqueue. + if (model?.base === 'ideogram-4' && entity.objects.length > 0) { + warnings.push(WARNINGS.IDEOGRAM4_TXT2IMG_ONLY); + } return warnings; }; diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataActions.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataActions.tsx index b7162e4e5ca..7b206a30afa 100644 --- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataActions.tsx +++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataActions.tsx @@ -62,6 +62,12 @@ export const IMAGE_METADATA_ACTION_HANDLERS: ImageMetadataActionHandler[] = [ ImageMetadataHandlers.QwenImageQuantization, ImageMetadataHandlers.QwenImageShift, ImageMetadataHandlers.ZImageShift, + ImageMetadataHandlers.Ideogram4SamplerPreset, + ImageMetadataHandlers.Ideogram4Steps, + ImageMetadataHandlers.Ideogram4GuidanceScale, + ImageMetadataHandlers.Ideogram4Mu, + ImageMetadataHandlers.Ideogram4ColorPalette, + ImageMetadataHandlers.Ideogram4Caption, ImageMetadataHandlers.CanvasLayers, ImageMetadataHandlers.RefImages, ImageMetadataHandlers.KleinVAEModel, diff --git a/invokeai/frontend/web/src/features/metadata/parsing.tsx b/invokeai/frontend/web/src/features/metadata/parsing.tsx index e71cf018cb8..a93abc71b7d 100644 --- a/invokeai/frontend/web/src/features/metadata/parsing.tsx +++ b/invokeai/frontend/web/src/features/metadata/parsing.tsx @@ -39,6 +39,11 @@ import { setFluxDypeScale, setFluxScheduler, setGuidance, + setIdeogram4ColorPalette, + setIdeogram4GuidanceScale, + setIdeogram4Mu, + setIdeogram4SamplerPreset, + setIdeogram4Steps, setImg2imgStrength, setRefinerCFGScale, setRefinerNegativeAestheticScore, @@ -79,6 +84,7 @@ import type { ParameterFluxDypeScale, ParameterGuidance, ParameterHeight, + ParameterIdeogram4SamplerPreset, ParameterModel, ParameterNegativePrompt, ParameterPositivePrompt, @@ -104,6 +110,7 @@ import { zParameterFluxDypePreset, zParameterFluxDypeScale, zParameterGuidance, + zParameterIdeogram4SamplerPreset, zParameterImageDimension, zParameterNegativePrompt, zParameterPositivePrompt, @@ -887,12 +894,179 @@ const ZImageShift: SingleMetadataHandler = { }, i18nKey: 'metadata.zImageShift', LabelComponent: MetadataLabel, - ValueComponent: ({ value }: SingleMetadataValueProps) => ( - - ), + ValueComponent: ({ value }: SingleMetadataValueProps) => { + const { t } = useTranslation(); + return ; + }, }; //#endregion ZImageShift +//#region Ideogram4SamplerPreset +const Ideogram4SamplerPreset: SingleMetadataHandler = { + [SingleMetadataKey]: true, + type: 'Ideogram4SamplerPreset', + parse: (metadata, _store) => { + const raw = getProperty(metadata, 'ideogram4_sampler_preset'); + const parsed = zParameterIdeogram4SamplerPreset.parse(raw); + return Promise.resolve(parsed); + }, + recall: (value, store) => { + // Only recall onto an Ideogram 4 model so we don't set this (otherwise hidden) field for other bases. + if (selectBase(store.getState()) !== 'ideogram-4') { + return; + } + store.dispatch(setIdeogram4SamplerPreset(value)); + }, + i18nKey: 'parameters.samplerPreset', + LabelComponent: MetadataLabel, + ValueComponent: ({ value }: SingleMetadataValueProps) => ( + + ), +}; +//#endregion Ideogram4SamplerPreset + +//#region Ideogram4Steps +// Optional override of the preset step count. The graph writes 'auto' (sentinel) when unset; recall +// maps that back to null (= use preset). Only recalled onto an Ideogram 4 model. +const Ideogram4Steps: SingleMetadataHandler = { + [SingleMetadataKey]: true, + type: 'Ideogram4Steps', + parse: (metadata, _store) => { + const raw = getProperty(metadata, 'ideogram4_steps'); + if (raw === undefined) { + return Promise.reject(); + } + if (raw === null || raw === 'auto') { + return Promise.resolve(null); + } + // Backend requires steps >= 2; refuse a stale/out-of-range recalled value instead of recalling it. + return Promise.resolve(z.number().int().min(2).max(100).parse(raw)); + }, + recall: (value, store) => { + if (selectBase(store.getState()) !== 'ideogram-4') { + return; + } + store.dispatch(setIdeogram4Steps(value)); + }, + i18nKey: 'parameters.steps', + LabelComponent: MetadataLabel, + ValueComponent: ({ value }: SingleMetadataValueProps) => { + const { t } = useTranslation(); + return ; + }, +}; +//#endregion Ideogram4Steps + +//#region Ideogram4GuidanceScale +const Ideogram4GuidanceScale: SingleMetadataHandler = { + [SingleMetadataKey]: true, + type: 'Ideogram4GuidanceScale', + parse: (metadata, _store) => { + const raw = getProperty(metadata, 'ideogram4_guidance_scale'); + if (raw === undefined) { + return Promise.reject(); + } + if (raw === null || raw === 'auto') { + return Promise.resolve(null); + } + return Promise.resolve(z.number().min(1).max(20).parse(raw)); + }, + recall: (value, store) => { + if (selectBase(store.getState()) !== 'ideogram-4') { + return; + } + store.dispatch(setIdeogram4GuidanceScale(value)); + }, + i18nKey: 'parameters.guidance', + LabelComponent: MetadataLabel, + ValueComponent: ({ value }: SingleMetadataValueProps) => { + const { t } = useTranslation(); + return ; + }, +}; +//#endregion Ideogram4GuidanceScale + +//#region Ideogram4Mu +const Ideogram4Mu: SingleMetadataHandler = { + [SingleMetadataKey]: true, + type: 'Ideogram4Mu', + parse: (metadata, _store) => { + const raw = getProperty(metadata, 'ideogram4_mu'); + if (raw === undefined) { + return Promise.reject(); + } + if (raw === null || raw === 'auto') { + return Promise.resolve(null); + } + return Promise.resolve(z.number().min(-4).max(4).parse(raw)); + }, + recall: (value, store) => { + if (selectBase(store.getState()) !== 'ideogram-4') { + return; + } + store.dispatch(setIdeogram4Mu(value)); + }, + i18nKey: 'parameters.shift', + LabelComponent: MetadataLabel, + ValueComponent: ({ value }: SingleMetadataValueProps) => { + const { t } = useTranslation(); + return ; + }, +}; +//#endregion Ideogram4Mu + +//#region Ideogram4ColorPalette +const Ideogram4ColorPalette: SingleMetadataHandler = { + [SingleMetadataKey]: true, + type: 'Ideogram4ColorPalette', + parse: (metadata, _store) => { + const raw = getProperty(metadata, 'ideogram4_color_palette'); + if (raw === undefined) { + return Promise.reject(); + } + return Promise.resolve(z.array(z.string()).parse(raw)); + }, + recall: (value, store) => { + if (selectBase(store.getState()) !== 'ideogram-4') { + return; + } + store.dispatch(setIdeogram4ColorPalette(value)); + }, + i18nKey: 'parameters.colorPalette', + LabelComponent: MetadataLabel, + ValueComponent: ({ value }: SingleMetadataValueProps) => ( + + ), +}; +//#endregion Ideogram4ColorPalette + +//#region Ideogram4Caption +// For regional/structured prompts the value actually encoded by the model is this assembled JSON +// caption, while `positive_prompt` holds the raw overall description (via the graph's decoy node). +// Recalling it into the positive prompt round-trips: the graph builder detects a leading `{` and passes +// the JSON through unchanged. +const Ideogram4Caption: SingleMetadataHandler = { + [SingleMetadataKey]: true, + type: 'Ideogram4Caption', + parse: (metadata, _store) => { + const raw = getProperty(metadata, 'ideogram4_caption'); + if (raw === undefined) { + return Promise.reject(); + } + return Promise.resolve(z.string().parse(raw)); + }, + recall: (value, store) => { + if (selectBase(store.getState()) !== 'ideogram-4') { + return; + } + store.dispatch(positivePromptChanged(value)); + }, + i18nKey: 'parameters.ideogram4Caption', + LabelComponent: MetadataLabel, + ValueComponent: ({ value }: SingleMetadataValueProps) => , +}; +//#endregion Ideogram4Caption + //#region RefinerModel const RefinerModel: SingleMetadataHandler = { [SingleMetadataKey]: true, @@ -1678,6 +1852,12 @@ export const ImageMetadataHandlers = { QwenImageQuantization, QwenImageShift, ZImageShift, + Ideogram4SamplerPreset, + Ideogram4Steps, + Ideogram4GuidanceScale, + Ideogram4Mu, + Ideogram4ColorPalette, + Ideogram4Caption, LoRAs, CanvasLayers, RefImages, diff --git a/invokeai/frontend/web/src/features/modelManagerV2/models.ts b/invokeai/frontend/web/src/features/modelManagerV2/models.ts index cf295c9af6a..a38cd35dd9a 100644 --- a/invokeai/frontend/web/src/features/modelManagerV2/models.ts +++ b/invokeai/frontend/web/src/features/modelManagerV2/models.ts @@ -163,6 +163,7 @@ export const MODEL_BASE_TO_COLOR: Record = { cogview4: 'red', 'qwen-image': 'orange', 'z-image': 'cyan', + 'ideogram-4': 'pink', external: 'orange', anima: 'invokePurple', unknown: 'red', @@ -210,6 +211,7 @@ export const MODEL_BASE_TO_LONG_NAME: Record = { cogview4: 'CogView4', 'qwen-image': 'Qwen Image', 'z-image': 'Z-Image', + 'ideogram-4': 'Ideogram 4', external: 'External', anima: 'Anima', unknown: 'Unknown', @@ -230,6 +232,7 @@ export const MODEL_BASE_TO_SHORT_NAME: Record = { cogview4: 'CogView4', 'qwen-image': 'QwenImg', 'z-image': 'Z-Image', + 'ideogram-4': 'Ideogram4', external: 'External', anima: 'Anima', unknown: 'Unknown', diff --git a/invokeai/frontend/web/src/features/nodes/types/common.ts b/invokeai/frontend/web/src/features/nodes/types/common.ts index fb2a1ce946a..21c7b254486 100644 --- a/invokeai/frontend/web/src/features/nodes/types/common.ts +++ b/invokeai/frontend/web/src/features/nodes/types/common.ts @@ -75,6 +75,10 @@ export const zZImageSchedulerField = z.enum(['euler', 'heun', 'lcm']); // Anima scheduler options (same flow-matching schedulers, defined separately to avoid coupling) export const zAnimaSchedulerField = z.enum(['euler', 'heun', 'dpmpp_2m', 'dpmpp_2m_sde', 'er_sde', 'lcm']); +// Ideogram 4 sampler presets. Each bundles step count, the per-step guidance schedule (with a polish +// tail), and the logit-normal schedule mean/std. V4_QUALITY_48 is the reference default. +export const zIdeogram4SamplerPresetField = z.enum(['V4_QUALITY_48', 'V4_DEFAULT_20', 'V4_TURBO_12']); + // Flux DyPE (Dynamic Position Extrapolation) preset options for high-resolution generation export const zFluxDypePresetField = z.enum(['off', 'manual', 'auto', 'area', '4k']); @@ -98,6 +102,7 @@ export const zBaseModelType = z.enum([ 'cogview4', 'qwen-image', 'z-image', + 'ideogram-4', 'external', 'anima', 'unknown', @@ -113,6 +118,7 @@ export const zMainModelBase = z.enum([ 'cogview4', 'qwen-image', 'z-image', + 'ideogram-4', 'anima', ]); type MainModelBase = z.infer; diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/generation/buildIdeogram4Graph.test.ts b/invokeai/frontend/web/src/features/nodes/util/graph/generation/buildIdeogram4Graph.test.ts new file mode 100644 index 00000000000..f04a6bf581c --- /dev/null +++ b/invokeai/frontend/web/src/features/nodes/util/graph/generation/buildIdeogram4Graph.test.ts @@ -0,0 +1,155 @@ +import { afterEach, describe, expect, it, vi } from 'vitest'; + +vi.mock('app/logging/logger', () => ({ + logger: () => ({ debug: vi.fn() }), +})); + +let nextId = 0; +vi.mock('features/controlLayers/konva/util', () => ({ + getPrefixedId: (prefix: string) => `${prefix}:${nextId++}`, +})); + +const model = { key: 'ideogram4-model', hash: 'ideogram4-hash', name: 'Ideogram 4', base: 'ideogram-4', type: 'main' }; + +// Controlled prompt inputs — the structured case (regions + palette) is the one that used to be +// clobbered by the decoy. globalPrompt is what the linear batch injects into. +let promptInputs = { + globalPrompt: 'a global prompt', + regions: [{ prompt: 'a red bird', bbox: [10, 20, 300, 400] as [number, number, number, number] }], + colorPalette: ['#FF0000'], +}; + +vi.mock('features/controlLayers/store/paramsSlice', () => ({ + selectMainModelConfig: vi.fn(() => model), + selectIdeogram4SamplerPreset: vi.fn(() => 'V4_QUALITY_48'), + selectIdeogram4Steps: vi.fn(() => null), + selectIdeogram4GuidanceScale: vi.fn(() => null), + selectIdeogram4Mu: vi.fn(() => null), +})); + +vi.mock('features/controlLayers/store/selectors', () => ({ + selectCanvasMetadata: vi.fn(() => ({})), +})); + +vi.mock('features/metadata/util/modelFetchingHelpers', () => ({ + fetchModelConfigWithTypeGuard: vi.fn(() => Promise.resolve(model)), +})); + +vi.mock('features/nodes/util/graph/generation/addNSFWChecker', () => ({ + addNSFWChecker: vi.fn((_g, node) => node), +})); + +vi.mock('features/nodes/util/graph/generation/addWatermarker', () => ({ + addWatermarker: vi.fn((_g, node) => node), +})); + +vi.mock('features/nodes/util/graph/generation/buildIdeogram4Prompt', () => ({ + collectIdeogram4PromptInputs: vi.fn(() => promptInputs), +})); + +vi.mock('features/nodes/util/graph/graphBuilderUtils', () => ({ + getOriginalAndScaledSizesForTextToImage: vi.fn(() => ({ + originalSize: { width: 1024, height: 1024 }, + scaledSize: { width: 1024, height: 1024 }, + })), + selectCanvasOutputFields: vi.fn(() => ({})), +})); + +vi.mock('features/ui/store/uiSelectors', () => ({ + selectActiveTab: vi.fn(() => 'generation'), +})); + +vi.mock('services/api/types', async () => { + const actual = await vi.importActual('services/api/types'); + return { ...actual, isNonRefinerMainModelConfig: vi.fn(() => true) }; +}); + +import { buildIdeogram4Graph } from './buildIdeogram4Graph'; + +const state = { system: { shouldUseNSFWChecker: false, shouldUseWatermarker: false } }; + +// eslint-disable-next-line @typescript-eslint/no-explicit-any +const buildArg = (): any => ({ generationMode: 'txt2img', state, manager: null }); + +describe('buildIdeogram4Graph', () => { + afterEach(() => { + nextId = 0; + promptInputs = { + globalPrompt: 'a global prompt', + regions: [{ prompt: 'a red bird', bbox: [10, 20, 300, 400] }], + colorPalette: ['#FF0000'], + }; + }); + + it('routes the batch-injectable prompt node through the caption builder into the text encoder', async () => { + const { g, positivePrompt } = await buildIdeogram4Graph(buildArg()); + + // The returned positivePrompt (the node the linear batch / dynamic prompts inject into) is the real + // prompt node — NOT a decoy — so injected expansions reach the encoder instead of a throwaway node. + expect(positivePrompt.type).toBe('string'); + expect(positivePrompt.id).toContain('ideogram4_prompt'); + expect(positivePrompt.id).not.toContain('decoy'); + expect(positivePrompt.value).toBe('a global prompt'); + + const nodes = g.getNodes(); + const captionBuilder = nodes.find((n) => n.type === 'ideogram4_caption_builder'); + const textEncoder = nodes.find((n) => n.type === 'ideogram4_text_encoder'); + expect(captionBuilder).toBeDefined(); + expect(textEncoder).toBeDefined(); + + const edges = g.getEdges(); + // prompt node -> caption builder (so an injected prompt is what the caption is assembled from) + expect( + edges.some( + (e) => + e.source.node_id === positivePrompt.id && + e.source.field === 'value' && + e.destination.node_id === captionBuilder!.id && + e.destination.field === 'prompt' + ) + ).toBe(true); + // caption builder -> text encoder (the assembled caption is what actually gets encoded) + expect( + edges.some( + (e) => + e.source.node_id === captionBuilder!.id && + e.source.field === 'value' && + e.destination.node_id === textEncoder!.id && + e.destination.field === 'prompt' + ) + ).toBe(true); + }); + + it('bakes the fixed regions and palette into the caption builder node', async () => { + const { g } = await buildIdeogram4Graph(buildArg()); + // eslint-disable-next-line @typescript-eslint/no-explicit-any + const captionBuilder = g.getNodes().find((n) => n.type === 'ideogram4_caption_builder') as any; + expect(captionBuilder.regions).toEqual([{ prompt: 'a red bird', bbox: [10, 20, 300, 400] }]); + expect(captionBuilder.color_palette).toEqual(['#FF0000']); + }); + + // `core_metadata` and the `ideogram4_caption` metadata field are outside Graph's strict typed unions + // (the metadata node is excluded from AnyInvocation), so compare their string values via casts. + const captionEdge = (g: Awaited>['g']) => { + const captionBuilderId = g.getNodes().find((n) => (n.type as string) === 'ideogram4_caption_builder')?.id; + return g + .getEdges() + .find((e) => e.source.node_id === captionBuilderId && (e.destination.field as string) === 'ideogram4_caption'); + }; + + it('records the runtime-assembled caption in metadata via an edge (structured inputs)', async () => { + const { g } = await buildIdeogram4Graph(buildArg()); + // The caption is wired from the runtime builder into metadata, so each batch item records its own. + const edge = captionEdge(g); + expect(edge).toBeDefined(); + expect(edge!.source.field).toBe('value'); + }); + + it('always records the caption edge, even for a plain prompt (so the encoded JSON is visible)', async () => { + // Plain prompts are now wrapped in the JSON schema at runtime, so the caption differs from the raw + // positive_prompt and must be recorded too — otherwise the metadata viewer only shows the raw text. + promptInputs = { globalPrompt: 'just plain text', regions: [], colorPalette: [] }; + const { g } = await buildIdeogram4Graph(buildArg()); + expect(captionEdge(g)).toBeDefined(); + }); +}); diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/generation/buildIdeogram4Graph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/generation/buildIdeogram4Graph.ts new file mode 100644 index 00000000000..3e3bd6f1d8e --- /dev/null +++ b/invokeai/frontend/web/src/features/nodes/util/graph/generation/buildIdeogram4Graph.ts @@ -0,0 +1,179 @@ +import { objectEquals } from '@observ33r/object-equals'; +import { logger } from 'app/logging/logger'; +import { getPrefixedId } from 'features/controlLayers/konva/util'; +import { + selectIdeogram4GuidanceScale, + selectIdeogram4Mu, + selectIdeogram4SamplerPreset, + selectIdeogram4Steps, + selectMainModelConfig, +} from 'features/controlLayers/store/paramsSlice'; +import { selectCanvasMetadata } from 'features/controlLayers/store/selectors'; +import { fetchModelConfigWithTypeGuard } from 'features/metadata/util/modelFetchingHelpers'; +import { addNSFWChecker } from 'features/nodes/util/graph/generation/addNSFWChecker'; +import { addWatermarker } from 'features/nodes/util/graph/generation/addWatermarker'; +import { collectIdeogram4PromptInputs } from 'features/nodes/util/graph/generation/buildIdeogram4Prompt'; +import { Graph } from 'features/nodes/util/graph/generation/Graph'; +import { + getOriginalAndScaledSizesForTextToImage, + selectCanvasOutputFields, +} from 'features/nodes/util/graph/graphBuilderUtils'; +import type { GraphBuilderArg, GraphBuilderReturn, ImageOutputNodes } from 'features/nodes/util/graph/types'; +import { selectActiveTab } from 'features/ui/store/uiSelectors'; +import type { Invocation } from 'services/api/types'; +import { isNonRefinerMainModelConfig } from 'services/api/types'; +import { assert } from 'tsafe'; + +const log = logger('system'); + +/** + * Builds the graph for Ideogram 4 generation. Ideogram 4 is text-to-image only and prompted with a + * structured JSON caption (assembled from the global prompt + Canvas Regional Guidance layers; see + * buildIdeogram4Prompt). There is no negative prompt (the reference uses an asymmetric CFG with a + * zeroed unconditional branch), and no img2img/inpaint/outpaint or mask conditioning. + */ +export const buildIdeogram4Graph = async (arg: GraphBuilderArg): Promise => { + const { generationMode, state, manager } = arg; + + log.debug({ generationMode, manager: manager?.id }, 'Building Ideogram 4 graph'); + + assert(generationMode === 'txt2img', 'Ideogram 4 only supports text-to-image generation'); + + const model = selectMainModelConfig(state); + assert(model, 'No model selected'); + assert(model.base === 'ideogram-4', 'Selected model is not an Ideogram 4 model'); + + const samplerPreset = selectIdeogram4SamplerPreset(state); + // Optional advanced overrides (null = use the preset). + const ideogram4Steps = selectIdeogram4Steps(state); + const ideogram4GuidanceScale = selectIdeogram4GuidanceScale(state); + const ideogram4Mu = selectIdeogram4Mu(state); + + // Collect the raw prompt inputs. The JSON caption is assembled at generation time in the + // ideogram4_caption_builder node so dynamic prompts / prompt batching (which vary the global + // prompt) are folded into the encoded caption. The regions and palette are fixed per generation. + const { globalPrompt, regions, colorPalette } = collectIdeogram4PromptInputs(state, manager); + + const g = new Graph(getPrefixedId('ideogram4_graph')); + + const modelLoader = g.addNode({ + type: 'ideogram4_model_loader', + id: getPrefixedId('ideogram4_model_loader'), + model, + }); + + // The global prompt lives in its own node so the linear batch (dynamic prompts / prompt batching) + // can inject expansions into it — those then flow through the caption builder into the encoder. + const promptNode = g.addNode({ + id: getPrefixedId('ideogram4_prompt'), + type: 'string', + value: globalPrompt, + }); + + // Assembles the structured JSON caption from the (possibly batch-injected) prompt + fixed regions. + const captionBuilder = g.addNode({ + id: getPrefixedId('ideogram4_caption_builder'), + type: 'ideogram4_caption_builder', + regions, + color_palette: colorPalette, + }); + + const textEncoder = g.addNode({ + type: 'ideogram4_text_encoder', + id: getPrefixedId('ideogram4_text_encoder'), + }); + + const seed = g.addNode({ + id: getPrefixedId('seed'), + type: 'integer', + }); + + const denoise = g.addNode({ + type: 'ideogram4_denoise', + id: getPrefixedId('ideogram4_denoise'), + sampler_preset: samplerPreset, + steps: ideogram4Steps ?? undefined, + guidance_scale: ideogram4GuidanceScale ?? undefined, + mu: ideogram4Mu ?? undefined, + }); + + const l2i = g.addNode({ + type: 'ideogram4_l2i', + id: getPrefixedId('ideogram4_l2i'), + }); + + g.addEdge(modelLoader, 'transformer', denoise, 'transformer'); + g.addEdge(modelLoader, 'qwen3_encoder', textEncoder, 'qwen3_encoder'); + g.addEdge(modelLoader, 'vae', l2i, 'vae'); + g.addEdge(promptNode, 'value', captionBuilder, 'prompt'); + g.addEdge(captionBuilder, 'value', textEncoder, 'prompt'); + g.addEdge(textEncoder, 'conditioning', denoise, 'positive_conditioning'); + g.addEdge(seed, 'value', denoise, 'seed'); + g.addEdge(denoise, 'latents', l2i, 'latents'); + + // Text-to-image dimensions. Ideogram 4 requires multiples of 16 (enforced by the bbox grid size). + const { originalSize, scaledSize } = getOriginalAndScaledSizesForTextToImage(state); + denoise.width = scaledSize.width; + denoise.height = scaledSize.height; + + // Return the real prompt node so the linear batch injects dynamic-prompt expansions into it; they + // flow through the caption builder into the encoder. `positive_prompt` metadata is the global prompt. + const positivePrompt: Invocation<'string'> = promptNode; + + const modelConfig = await fetchModelConfigWithTypeGuard(model.key, isNonRefinerMainModelConfig); + assert(modelConfig.base === 'ideogram-4'); + + g.upsertMetadata({ + model: Graph.getModelMetadataField(modelConfig), + ideogram4_sampler_preset: samplerPreset, + // 'auto' sentinel survives the backend's exclude_none metadata serialization; the parser maps it + // back to null (use preset) on recall. + ideogram4_steps: ideogram4Steps ?? 'auto', + ideogram4_guidance_scale: ideogram4GuidanceScale ?? 'auto', + ideogram4_mu: ideogram4Mu ?? 'auto', + ideogram4_color_palette: colorPalette, + width: originalSize.width, + height: originalSize.height, + generation_mode: 'ideogram4_txt2img', + }); + // Always record the actually-encoded caption for reproducibility and transparency (so the metadata + // viewer shows the structured JSON the model really received, not just the raw prompt). It's assembled + // at runtime, so take it via an edge off the builder — this captures each batch item's caption. + g.addEdgeToMetadata(captionBuilder, 'value', 'ideogram4_caption'); + g.addEdgeToMetadata(seed, 'value', 'seed'); + g.addEdgeToMetadata(positivePrompt, 'value', 'positive_prompt'); + + // Resize the output back to the original size if the canvas used a scaled bbox. + let canvasOutput: Invocation = l2i; + if (!objectEquals(scaledSize, originalSize)) { + const resizeImageToOriginalSize = g.addNode({ + id: getPrefixedId('resize_image_to_original_size'), + type: 'img_resize', + ...originalSize, + }); + g.addEdge(l2i, 'image', resizeImageToOriginalSize, 'image'); + canvasOutput = resizeImageToOriginalSize; + } + + if (state.system.shouldUseNSFWChecker) { + canvasOutput = addNSFWChecker(g, canvasOutput); + } + + if (state.system.shouldUseWatermarker) { + canvasOutput = addWatermarker(g, canvasOutput); + } + + g.updateNode(canvasOutput, selectCanvasOutputFields(state)); + + if (selectActiveTab(state) === 'canvas') { + g.upsertMetadata(selectCanvasMetadata(state)); + } + + g.setMetadataReceivingNode(canvasOutput); + + return { + g, + seed, + positivePrompt, + }; +}; diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/generation/buildIdeogram4Prompt.test.ts b/invokeai/frontend/web/src/features/nodes/util/graph/generation/buildIdeogram4Prompt.test.ts new file mode 100644 index 00000000000..279be1bf369 --- /dev/null +++ b/invokeai/frontend/web/src/features/nodes/util/graph/generation/buildIdeogram4Prompt.test.ts @@ -0,0 +1,36 @@ +import type { Rect } from 'features/controlLayers/store/types'; +import { describe, expect, it } from 'vitest'; + +import { rectToIdeogram4Bbox } from './buildIdeogram4Prompt'; + +// The JSON caption assembly moved to the backend `ideogram4_caption_builder` node (so dynamic prompts / +// batching vary the encoded caption); its behavior is covered by tests/backend/ideogram4/test_caption.py. +// Only the bbox normalization stays in the frontend (it needs the canvas generation bbox). + +describe('rectToIdeogram4Bbox', () => { + const genBbox: Rect = { x: 0, y: 0, width: 1024, height: 1024 }; + + it('normalizes a region rect to [y_min, x_min, y_max, x_max] in 0-1000', () => { + // Region occupying the right half, vertically centered band. + const regionRect: Rect = { x: 512, y: 256, width: 512, height: 512 }; + expect(rectToIdeogram4Bbox(regionRect, genBbox)).toEqual([250, 500, 750, 1000]); + }); + + it('accounts for a generation bbox not anchored at the origin', () => { + const offsetBbox: Rect = { x: 100, y: 200, width: 1000, height: 500 }; + const regionRect: Rect = { x: 600, y: 200, width: 500, height: 250 }; + // x: (600-100)/1000=0.5 -> 500, (1100-100)/1000=1.0 -> 1000 + // y: (200-200)/500=0 -> 0, (450-200)/500=0.5 -> 500 + expect(rectToIdeogram4Bbox(regionRect, offsetBbox)).toEqual([0, 500, 500, 1000]); + }); + + it('clamps out-of-bounds regions to the 0-1000 range', () => { + const regionRect: Rect = { x: -200, y: -200, width: 2048, height: 2048 }; + expect(rectToIdeogram4Bbox(regionRect, genBbox)).toEqual([0, 0, 1000, 1000]); + }); + + it('returns zeros for a degenerate (zero-size) generation bbox', () => { + const regionRect: Rect = { x: 10, y: 10, width: 10, height: 10 }; + expect(rectToIdeogram4Bbox(regionRect, { x: 0, y: 0, width: 0, height: 0 })).toEqual([0, 0, 0, 0]); + }); +}); diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/generation/buildIdeogram4Prompt.ts b/invokeai/frontend/web/src/features/nodes/util/graph/generation/buildIdeogram4Prompt.ts new file mode 100644 index 00000000000..4b7c08cf728 --- /dev/null +++ b/invokeai/frontend/web/src/features/nodes/util/graph/generation/buildIdeogram4Prompt.ts @@ -0,0 +1,96 @@ +import type { RootState } from 'app/store/store'; +import type { CanvasManager } from 'features/controlLayers/konva/CanvasManager'; +import { selectIdeogram4ColorPalette, selectPositivePrompt } from 'features/controlLayers/store/paramsSlice'; +import { selectCanvasSlice } from 'features/controlLayers/store/selectors'; +import type { Rect } from 'features/controlLayers/store/types'; + +/** + * Ideogram 4 is prompted with a structured JSON caption describing the scene as a list of regions, + * each with a bounding box and a description. The bbox numbers live inside the prompt string (Ideogram 4 + * does not use spatial attention masks). + * + * This module reads the raw inputs (global prompt, per-region description + bbox, color palette) from + * canvas state. The actual JSON assembly happens at generation time in the backend + * `ideogram4_caption_builder` node (see backend `build_ideogram4_caption`) so that dynamic-prompt + * expansions and prompt batching — which vary the global prompt — are folded into the encoded caption. + * Only the bbox normalization stays here, since it needs the canvas manager / generation bbox. + */ + +/** Ideogram 4 normalizes spatial coordinates to a 0–1000 grid with the origin at the top-left. */ +const IDEOGRAM4_COORD_MAX = 1000; + +const clamp = (value: number, min: number, max: number): number => Math.min(max, Math.max(min, value)); + +type Ideogram4Bbox = [number, number, number, number]; + +/** + * Converts a region's rect (canvas/layer coordinates — the same space as the generation bbox) into an + * Ideogram 4 bounding box `[y_min, x_min, y_max, x_max]`, normalized to 0–1000 relative to the + * generation bbox, clamped and rounded to integers. + */ +export const rectToIdeogram4Bbox = (regionRect: Rect, genBbox: Rect): Ideogram4Bbox => { + const norm = (value: number, origin: number, extent: number): number => + extent <= 0 ? 0 : clamp(Math.round(((value - origin) / extent) * IDEOGRAM4_COORD_MAX), 0, IDEOGRAM4_COORD_MAX); + const yMin = norm(regionRect.y, genBbox.y, genBbox.height); + const xMin = norm(regionRect.x, genBbox.x, genBbox.width); + const yMax = norm(regionRect.y + regionRect.height, genBbox.y, genBbox.height); + const xMax = norm(regionRect.x + regionRect.width, genBbox.x, genBbox.width); + return [yMin, xMin, yMax, xMax]; +}; + +type Ideogram4RegionInput = { + /** The region's positive prompt — becomes the element's `desc`. */ + prompt: string; + /** The region's normalized bbox, or null when the region has no drawn content. */ + bbox: Ideogram4Bbox | null; +}; + +type Ideogram4PromptInputs = { + /** The global positive prompt (batch-injectable; becomes `high_level_description` / raw text). */ + globalPrompt: string; + /** Enabled Regional Guidance layers with a non-empty prompt (description + normalized bbox). */ + regions: Ideogram4RegionInput[]; + /** The raw color palette (normalized/validated by the backend caption builder). */ + colorPalette: string[]; +}; + +/** + * Reads the raw Ideogram 4 prompt inputs from state: the global prompt, each enabled Regional Guidance + * layer (prompt + normalized bbox), and the color palette. The JSON caption is assembled later, at + * generation time, by the backend `ideogram4_caption_builder` node — so the batch-injectable global + * prompt is reflected in the encoded caption. Regions with no drawn content contribute a null bbox. + */ +export const collectIdeogram4PromptInputs = ( + state: RootState, + manager: CanvasManager | null +): Ideogram4PromptInputs => { + const globalPrompt = selectPositivePrompt(state); + const colorPalette = selectIdeogram4ColorPalette(state); + + // No canvas manager (e.g. the Generate tab) → no regions to read. + if (manager === null) { + return { globalPrompt, regions: [], colorPalette }; + } + + const canvas = selectCanvasSlice(state); + const genBbox = canvas.bbox.rect; + + const regions: Ideogram4RegionInput[] = []; + for (const region of canvas.regionalGuidance.entities) { + if (!region.isEnabled) { + continue; + } + const prompt = region.positivePrompt; + if (!prompt || prompt.trim().length === 0) { + continue; + } + const adapter = manager.adapters.regionMasks.get(region.id); + const bbox = + adapter && adapter.renderer.hasObjects() + ? rectToIdeogram4Bbox(adapter.transformer.getRelativeRect(), genBbox) + : null; + regions.push({ prompt, bbox }); + } + + return { globalPrompt, regions, colorPalette }; +}; diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/types.ts b/invokeai/frontend/web/src/features/nodes/util/graph/types.ts index d6a18f3f9c0..b3683082507 100644 --- a/invokeai/frontend/web/src/features/nodes/util/graph/types.ts +++ b/invokeai/frontend/web/src/features/nodes/util/graph/types.ts @@ -17,6 +17,7 @@ export type ImageOutputNodes = | 'cogview4_l2i' | 'qwen_image_l2i' | 'z_image_l2i' + | 'ideogram4_l2i' | 'anima_l2i'; export type LatentToImageNodes = diff --git a/invokeai/frontend/web/src/features/parameters/components/Core/ParamIdeogram4ColorPalette.tsx b/invokeai/frontend/web/src/features/parameters/components/Core/ParamIdeogram4ColorPalette.tsx new file mode 100644 index 00000000000..b9a7e726a37 --- /dev/null +++ b/invokeai/frontend/web/src/features/parameters/components/Core/ParamIdeogram4ColorPalette.tsx @@ -0,0 +1,91 @@ +import { Flex, FormControl, FormLabel, IconButton } from '@invoke-ai/ui-library'; +import { useAppDispatch, useAppSelector } from 'app/store/storeHooks'; +import { selectIdeogram4ColorPalette, setIdeogram4ColorPalette } from 'features/controlLayers/store/paramsSlice'; +import type { ChangeEvent } from 'react'; +import { memo, useCallback } from 'react'; +import { useTranslation } from 'react-i18next'; +import { PiPlusBold, PiXBold } from 'react-icons/pi'; + +const MAX_COLORS = 16; +const DEFAULT_COLOR = '#808080'; +const HEX_RE = /^#[0-9A-Fa-f]{6}$/; + +const SWATCH_STYLE = { + width: 28, + height: 28, + padding: 0, + border: 'none', + background: 'none', + cursor: 'pointer', +} as const; + +type ColorSwatchProps = { + index: number; + color: string; + onSet: (index: number, value: string) => void; + onRemove: (index: number) => void; +}; + +const ColorSwatch = memo(({ index, color, onSet, onRemove }: ColorSwatchProps) => { + const { t } = useTranslation(); + const handleChange = useCallback((e: ChangeEvent) => onSet(index, e.target.value), [index, onSet]); + const handleRemove = useCallback(() => onRemove(index), [index, onRemove]); + return ( + + + } size="xs" variant="ghost" onClick={handleRemove} /> + + ); +}); +ColorSwatch.displayName = 'ColorSwatch'; + +// Up to 16 hex colors injected into the JSON caption's style_description.color_palette. Only applies +// in auto-build mode (ignored when the prompt is raw JSON). +const ParamIdeogram4ColorPalette = () => { + const { t } = useTranslation(); + const palette = useAppSelector(selectIdeogram4ColorPalette); + const dispatch = useAppDispatch(); + + const setColor = useCallback( + (index: number, value: string) => { + const next = palette.slice(); + next[index] = value.toUpperCase(); + dispatch(setIdeogram4ColorPalette(next)); + }, + [palette, dispatch] + ); + const removeColor = useCallback( + (index: number) => { + dispatch(setIdeogram4ColorPalette(palette.filter((_, i) => i !== index))); + }, + [palette, dispatch] + ); + const addColor = useCallback(() => { + if (palette.length >= MAX_COLORS) { + return; + } + dispatch(setIdeogram4ColorPalette([...palette, DEFAULT_COLOR])); + }, [palette, dispatch]); + + return ( + + {t('parameters.colorPalette')} + + {palette.map((color, index) => ( + + ))} + {palette.length < MAX_COLORS && ( + } size="sm" variant="ghost" onClick={addColor} /> + )} + + + ); +}; + +export default memo(ParamIdeogram4ColorPalette); diff --git a/invokeai/frontend/web/src/features/parameters/components/Core/ParamIdeogram4GuidanceScale.tsx b/invokeai/frontend/web/src/features/parameters/components/Core/ParamIdeogram4GuidanceScale.tsx new file mode 100644 index 00000000000..c5d579e73b5 --- /dev/null +++ b/invokeai/frontend/web/src/features/parameters/components/Core/ParamIdeogram4GuidanceScale.tsx @@ -0,0 +1,68 @@ +import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel, Text } from '@invoke-ai/ui-library'; +import { useAppDispatch, useAppSelector } from 'app/store/storeHooks'; +import { selectIdeogram4GuidanceScale, setIdeogram4GuidanceScale } from 'features/controlLayers/store/paramsSlice'; +import type React from 'react'; +import { memo, useCallback } from 'react'; +import { useTranslation } from 'react-i18next'; +import { PiXBold } from 'react-icons/pi'; + +// The preset's main per-step guidance weight (gw) is 7.0; shown as the "auto" default. +const PRESET_MAIN_GW = 7; +const MARKS = [1, 4, 7, 10, 12]; + +// Optional override of the main guidance weight. null = use the preset's guidance schedule. +const ParamIdeogram4GuidanceScale = () => { + const { t } = useTranslation(); + const guidanceScale = useAppSelector(selectIdeogram4GuidanceScale); + const dispatch = useAppDispatch(); + + const onChange = useCallback((v: number) => dispatch(setIdeogram4GuidanceScale(v)), [dispatch]); + const onReset = useCallback( + (e: React.MouseEvent) => { + e.preventDefault(); + e.stopPropagation(); + dispatch(setIdeogram4GuidanceScale(null)); + }, + [dispatch] + ); + + const displayValue = guidanceScale ?? PRESET_MAIN_GW; + + return ( + + + {t('parameters.guidance')}{' '} + {guidanceScale !== null ? ( + + + + ) : ( + + ({t('common.auto').toLowerCase()}) + + )} + + + + + ); +}; + +export default memo(ParamIdeogram4GuidanceScale); diff --git a/invokeai/frontend/web/src/features/parameters/components/Core/ParamIdeogram4Mu.tsx b/invokeai/frontend/web/src/features/parameters/components/Core/ParamIdeogram4Mu.tsx new file mode 100644 index 00000000000..6a5c2e01e74 --- /dev/null +++ b/invokeai/frontend/web/src/features/parameters/components/Core/ParamIdeogram4Mu.tsx @@ -0,0 +1,73 @@ +import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel, Text } from '@invoke-ai/ui-library'; +import { useAppDispatch, useAppSelector } from 'app/store/storeHooks'; +import { + selectIdeogram4Mu, + selectIdeogram4SamplerPreset, + setIdeogram4Mu, +} from 'features/controlLayers/store/paramsSlice'; +import { IDEOGRAM4_PRESET_DEFAULTS } from 'features/parameters/components/Core/ParamIdeogram4SamplerPreset'; +import type React from 'react'; +import { memo, useCallback } from 'react'; +import { useTranslation } from 'react-i18next'; +import { PiXBold } from 'react-icons/pi'; + +const MARKS = [0, 0.5, 1, 1.5, 2]; + +// Optional override of the logit-normal schedule mean (mu). null = use the preset's mu. +const ParamIdeogram4Mu = () => { + const { t } = useTranslation(); + const mu = useAppSelector(selectIdeogram4Mu); + const preset = useAppSelector(selectIdeogram4SamplerPreset); + const dispatch = useAppDispatch(); + + const presetMu = IDEOGRAM4_PRESET_DEFAULTS[preset]?.mu ?? 0; + const onChange = useCallback((v: number) => dispatch(setIdeogram4Mu(v)), [dispatch]); + const onReset = useCallback( + (e: React.MouseEvent) => { + e.preventDefault(); + e.stopPropagation(); + dispatch(setIdeogram4Mu(null)); + }, + [dispatch] + ); + + const displayValue = mu ?? presetMu; + + return ( + + + {t('parameters.shift')}{' '} + {mu !== null ? ( + + + + ) : ( + + ({t('common.auto').toLowerCase()}) + + )} + + + + + ); +}; + +export default memo(ParamIdeogram4Mu); diff --git a/invokeai/frontend/web/src/features/parameters/components/Core/ParamIdeogram4SamplerPreset.tsx b/invokeai/frontend/web/src/features/parameters/components/Core/ParamIdeogram4SamplerPreset.tsx new file mode 100644 index 00000000000..c01f48a4db3 --- /dev/null +++ b/invokeai/frontend/web/src/features/parameters/components/Core/ParamIdeogram4SamplerPreset.tsx @@ -0,0 +1,59 @@ +import type { ComboboxOnChange, ComboboxOption, SystemStyleObject } from '@invoke-ai/ui-library'; +import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library'; +import { useAppDispatch, useAppSelector } from 'app/store/storeHooks'; +import { selectIdeogram4SamplerPreset, setIdeogram4SamplerPreset } from 'features/controlLayers/store/paramsSlice'; +import { isParameterIdeogram4SamplerPreset } from 'features/parameters/types/parameterSchemas'; +import { memo, useCallback, useMemo } from 'react'; +import { useTranslation } from 'react-i18next'; + +// Each preset bundles a step count, the per-step guidance schedule (with a polish tail), and the +// logit-normal schedule mean/std. The primary quality/speed control for Ideogram 4. The visible +// labels are localized (the step count is interpolated so translators can reposition it). +const IDEOGRAM4_SAMPLER_PRESET_I18N: { value: string; i18nKey: string; steps: number }[] = [ + { value: 'V4_QUALITY_48', i18nKey: 'parameters.ideogram4SamplerPresets.quality', steps: 48 }, + { value: 'V4_DEFAULT_20', i18nKey: 'parameters.ideogram4SamplerPresets.default', steps: 20 }, + { value: 'V4_TURBO_12', i18nKey: 'parameters.ideogram4SamplerPresets.turbo', steps: 12 }, +]; + +// Per-preset step count and schedule mean (mu), mirroring the backend PRESETS. Used by the advanced +// override controls to show the active preset's value as the "auto" default. +export const IDEOGRAM4_PRESET_DEFAULTS: Record = { + V4_QUALITY_48: { steps: 48, mu: 0.0 }, + V4_DEFAULT_20: { steps: 20, mu: 0.0 }, + V4_TURBO_12: { steps: 12, mu: 0.5 }, +}; + +// Cap the width so the dropdown doesn't span the whole row, and push it to the right edge of the row +// (ms: 'auto') so it lines up with the other controls' right edge. The label keeps its normal position. +const comboboxSx: SystemStyleObject = { maxW: '13rem', ms: 'auto' }; + +const ParamIdeogram4SamplerPreset = () => { + const dispatch = useAppDispatch(); + const { t } = useTranslation(); + const samplerPreset = useAppSelector(selectIdeogram4SamplerPreset); + + const onChange = useCallback( + (v) => { + if (!isParameterIdeogram4SamplerPreset(v?.value)) { + return; + } + dispatch(setIdeogram4SamplerPreset(v.value)); + }, + [dispatch] + ); + + const options = useMemo( + () => IDEOGRAM4_SAMPLER_PRESET_I18N.map((o) => ({ value: o.value, label: t(o.i18nKey, { steps: o.steps }) })), + [t] + ); + const value = useMemo(() => options.find((o) => o.value === samplerPreset), [options, samplerPreset]); + + return ( + + {t('parameters.samplerPreset')} + + + ); +}; + +export default memo(ParamIdeogram4SamplerPreset); diff --git a/invokeai/frontend/web/src/features/parameters/components/Core/ParamIdeogram4Steps.tsx b/invokeai/frontend/web/src/features/parameters/components/Core/ParamIdeogram4Steps.tsx new file mode 100644 index 00000000000..5233a0dea1f --- /dev/null +++ b/invokeai/frontend/web/src/features/parameters/components/Core/ParamIdeogram4Steps.tsx @@ -0,0 +1,71 @@ +import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel, Text } from '@invoke-ai/ui-library'; +import { useAppDispatch, useAppSelector } from 'app/store/storeHooks'; +import { + selectIdeogram4SamplerPreset, + selectIdeogram4Steps, + setIdeogram4Steps, +} from 'features/controlLayers/store/paramsSlice'; +import { IDEOGRAM4_PRESET_DEFAULTS } from 'features/parameters/components/Core/ParamIdeogram4SamplerPreset'; +import type React from 'react'; +import { memo, useCallback } from 'react'; +import { useTranslation } from 'react-i18next'; +import { PiXBold } from 'react-icons/pi'; + +const MARKS = [2, 12, 20, 48, 100]; + +// Optional override of the sampler preset's step count. null = use the preset. +const ParamIdeogram4Steps = () => { + const { t } = useTranslation(); + const steps = useAppSelector(selectIdeogram4Steps); + const preset = useAppSelector(selectIdeogram4SamplerPreset); + const dispatch = useAppDispatch(); + + const presetSteps = IDEOGRAM4_PRESET_DEFAULTS[preset]?.steps ?? 48; + const onChange = useCallback((v: number) => dispatch(setIdeogram4Steps(v)), [dispatch]); + const onReset = useCallback( + (e: React.MouseEvent) => { + e.preventDefault(); + e.stopPropagation(); + dispatch(setIdeogram4Steps(null)); + }, + [dispatch] + ); + + const displayValue = steps ?? presetSteps; + + return ( + + + {t('parameters.steps')}{' '} + {steps !== null ? ( + + + + ) : ( + + ({t('common.auto').toLowerCase()}) + + )} + + + + + ); +}; + +export default memo(ParamIdeogram4Steps); diff --git a/invokeai/frontend/web/src/features/parameters/components/ModelPicker.tsx b/invokeai/frontend/web/src/features/parameters/components/ModelPicker.tsx index c32a8a51be7..2ed1e050a50 100644 --- a/invokeai/frontend/web/src/features/parameters/components/ModelPicker.tsx +++ b/invokeai/frontend/web/src/features/parameters/components/ModelPicker.tsx @@ -249,7 +249,18 @@ export const ModelPicker = typedMemo( const _options: Group>[] = []; // Add groups in the original order - for (const groupId of ['api', 'flux', 'z-image', 'qwen-image', 'cogview4', 'sdxl', 'sd-3', 'sd-2', 'sd-1']) { + for (const groupId of [ + 'api', + 'flux', + 'z-image', + 'ideogram-4', + 'qwen-image', + 'cogview4', + 'sdxl', + 'sd-3', + 'sd-2', + 'sd-1', + ]) { const group = groups[groupId]; if (group) { // Sort options within each group so starred ones come first diff --git a/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts b/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts index eb2f1e6c15b..08e78488916 100644 --- a/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts +++ b/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts @@ -8,6 +8,7 @@ import { zFluxDypePresetField, zFluxDypeScaleField, zFluxSchedulerField, + zIdeogram4SamplerPresetField, zModelIdentifierField, zSchedulerField, zZImageSchedulerField, @@ -86,6 +87,12 @@ export const [zParameterAnimaScheduler, isParameterAnimaScheduler] = buildParame export type ParameterAnimaScheduler = z.infer; // #endregion +// #region Ideogram 4 Sampler Preset +export const [zParameterIdeogram4SamplerPreset, isParameterIdeogram4SamplerPreset] = + buildParameter(zIdeogram4SamplerPresetField); +export type ParameterIdeogram4SamplerPreset = z.infer; +// #endregion + // #region Flux DyPE Preset export const [zParameterFluxDypePreset, isParameterFluxDypePreset] = buildParameter(zFluxDypePresetField); export type ParameterFluxDypePreset = z.infer; diff --git a/invokeai/frontend/web/src/features/parameters/util/optimalDimension.ts b/invokeai/frontend/web/src/features/parameters/util/optimalDimension.ts index 2ac59a32e2b..2548f907ac5 100644 --- a/invokeai/frontend/web/src/features/parameters/util/optimalDimension.ts +++ b/invokeai/frontend/web/src/features/parameters/util/optimalDimension.ts @@ -20,6 +20,7 @@ export const getOptimalDimension = (base?: BaseModelType | null): number => { case 'cogview4': case 'qwen-image': case 'z-image': + case 'ideogram-4': case 'anima': default: return 1024; @@ -78,6 +79,7 @@ export const getGridSize = (base?: BaseModelType | null): number => { case 'sd-3': case 'qwen-image': case 'z-image': + case 'ideogram-4': return 16; case 'sd-1': case 'sd-2': diff --git a/invokeai/frontend/web/src/features/queue/hooks/useEnqueueCanvas.ts b/invokeai/frontend/web/src/features/queue/hooks/useEnqueueCanvas.ts index 1229371b6e8..aa8ddad612a 100644 --- a/invokeai/frontend/web/src/features/queue/hooks/useEnqueueCanvas.ts +++ b/invokeai/frontend/web/src/features/queue/hooks/useEnqueueCanvas.ts @@ -17,6 +17,7 @@ import { buildAnimaGraph } from 'features/nodes/util/graph/generation/buildAnima import { buildCogView4Graph } from 'features/nodes/util/graph/generation/buildCogView4Graph'; import { buildExternalGraph } from 'features/nodes/util/graph/generation/buildExternalGraph'; import { buildFLUXGraph } from 'features/nodes/util/graph/generation/buildFLUXGraph'; +import { buildIdeogram4Graph } from 'features/nodes/util/graph/generation/buildIdeogram4Graph'; import { buildQwenImageGraph } from 'features/nodes/util/graph/generation/buildQwenImageGraph'; import { buildSD1Graph } from 'features/nodes/util/graph/generation/buildSD1Graph'; import { buildSD3Graph } from 'features/nodes/util/graph/generation/buildSD3Graph'; @@ -69,6 +70,8 @@ const enqueueCanvas = async (store: AppStore, canvasManager: CanvasManager, prep return await buildQwenImageGraph(graphBuilderArg); case 'z-image': return await buildZImageGraph(graphBuilderArg); + case 'ideogram-4': + return await buildIdeogram4Graph(graphBuilderArg); case 'external': return await buildExternalGraph(graphBuilderArg); case 'anima': diff --git a/invokeai/frontend/web/src/features/queue/hooks/useEnqueueGenerate.ts b/invokeai/frontend/web/src/features/queue/hooks/useEnqueueGenerate.ts index 8b0c30d924f..de165a7a4ef 100644 --- a/invokeai/frontend/web/src/features/queue/hooks/useEnqueueGenerate.ts +++ b/invokeai/frontend/web/src/features/queue/hooks/useEnqueueGenerate.ts @@ -15,6 +15,7 @@ import { buildAnimaGraph } from 'features/nodes/util/graph/generation/buildAnima import { buildCogView4Graph } from 'features/nodes/util/graph/generation/buildCogView4Graph'; import { buildExternalGraph } from 'features/nodes/util/graph/generation/buildExternalGraph'; import { buildFLUXGraph } from 'features/nodes/util/graph/generation/buildFLUXGraph'; +import { buildIdeogram4Graph } from 'features/nodes/util/graph/generation/buildIdeogram4Graph'; import { buildQwenImageGraph } from 'features/nodes/util/graph/generation/buildQwenImageGraph'; import { buildSD1Graph } from 'features/nodes/util/graph/generation/buildSD1Graph'; import { buildSD3Graph } from 'features/nodes/util/graph/generation/buildSD3Graph'; @@ -62,6 +63,8 @@ const enqueueGenerate = async (store: AppStore, prepend: boolean) => { return await buildQwenImageGraph(graphBuilderArg); case 'z-image': return await buildZImageGraph(graphBuilderArg); + case 'ideogram-4': + return await buildIdeogram4Graph(graphBuilderArg); case 'external': return await buildExternalGraph(graphBuilderArg); case 'anima': diff --git a/invokeai/frontend/web/src/features/queue/store/readiness.test.ts b/invokeai/frontend/web/src/features/queue/store/readiness.test.ts index 632006050e6..98ae1a2244a 100644 --- a/invokeai/frontend/web/src/features/queue/store/readiness.test.ts +++ b/invokeai/frontend/web/src/features/queue/store/readiness.test.ts @@ -270,3 +270,117 @@ describe('FLUX.2 Klein readiness checks – canvas tab', () => { expect(hasFlux2Qwen3Reason(reasons)).toBe(true); }); }); + +const ideogram4Model = { + key: 'ideogram-4', + hash: 'h', + name: 'Ideogram 4', + base: 'ideogram-4', + type: 'main', + format: 'diffusers', +} as unknown as MainModelConfig; + +const buildIdeogram4CanvasArg = (canvasOverrides: { + bbox?: { width: number; height: number }; + rasterLayers?: unknown[]; + inpaintMasks?: unknown[]; + regionalGuidance?: unknown[]; +}) => ({ + ...buildCanvasTabArg({ model: ideogram4Model }), + canvas: { + bbox: { + scaleMethod: 'none', + rect: canvasOverrides.bbox ?? { width: 1024, height: 1024 }, + scaledSize: canvasOverrides.bbox ?? { width: 1024, height: 1024 }, + }, + controlLayers: { entities: [] }, + regionalGuidance: { entities: canvasOverrides.regionalGuidance ?? [] }, + rasterLayers: { entities: canvasOverrides.rasterLayers ?? [] }, + inpaintMasks: { entities: canvasOverrides.inpaintMasks ?? [] }, + }, +}); + +const hasReasonWith = (reasons: { content: string }[], key: string) => reasons.some((r) => r.content.includes(key)); + +describe('Ideogram 4 readiness checks - canvas tab', () => { + it('blocks a bbox whose width is not a multiple of 16', () => { + const reasons = getReasonsWhyCannotEnqueueCanvasTab( + buildIdeogram4CanvasArg({ bbox: { width: 1025, height: 1024 } }) as never + ); + expect(hasReasonWith(reasons, 'modelIncompatibleBboxWidth')).toBe(true); + }); + + it('allows a bbox that is a multiple of 16', () => { + const reasons = getReasonsWhyCannotEnqueueCanvasTab( + buildIdeogram4CanvasArg({ bbox: { width: 1024, height: 1024 } }) as never + ); + expect(hasReasonWith(reasons, 'modelIncompatibleBbox')).toBe(false); + }); + + it('blocks an enabled raster layer with content (Ideogram 4 is txt2img only)', () => { + const reasons = getReasonsWhyCannotEnqueueCanvasTab( + buildIdeogram4CanvasArg({ + rasterLayers: [{ id: 'r1', isEnabled: true, type: 'raster_layer', objects: [{}] }], + }) as never + ); + expect(hasReasonWith(reasons, 'ideogram4Txt2ImgOnly')).toBe(true); + }); + + it('blocks an enabled inpaint mask with content', () => { + const reasons = getReasonsWhyCannotEnqueueCanvasTab( + buildIdeogram4CanvasArg({ + inpaintMasks: [{ id: 'm1', isEnabled: true, type: 'inpaint_mask', objects: [{}] }], + }) as never + ); + expect(hasReasonWith(reasons, 'ideogram4Txt2ImgOnly')).toBe(true); + }); + + it('does not block an empty (fully transparent) enabled raster layer', () => { + const reasons = getReasonsWhyCannotEnqueueCanvasTab( + buildIdeogram4CanvasArg({ + rasterLayers: [{ id: 'r1', isEnabled: true, type: 'raster_layer', objects: [] }], + }) as never + ); + expect(hasReasonWith(reasons, 'ideogram4Txt2ImgOnly')).toBe(false); + }); + + it('warns a regional guidance layer whose only input is a negative prompt', () => { + const reasons = getReasonsWhyCannotEnqueueCanvasTab( + buildIdeogram4CanvasArg({ + regionalGuidance: [ + { + id: 'rg1', + isEnabled: true, + type: 'regional_guidance', + objects: [{}], + positivePrompt: null, + negativePrompt: 'no cats', + autoNegative: false, + referenceImages: [], + }, + ], + }) as never + ); + expect(hasReasonWith(reasons, 'rgNegativePromptNotSupported')).toBe(true); + }); + + it('warns a regional guidance layer whose only input is a reference image', () => { + const reasons = getReasonsWhyCannotEnqueueCanvasTab( + buildIdeogram4CanvasArg({ + regionalGuidance: [ + { + id: 'rg1', + isEnabled: true, + type: 'regional_guidance', + objects: [{}], + positivePrompt: null, + negativePrompt: null, + autoNegative: false, + referenceImages: [{ id: 'ri1', config: { model: null, image: null } }], + }, + ], + }) as never + ); + expect(hasReasonWith(reasons, 'rgReferenceImagesNotSupported')).toBe(true); + }); +}); diff --git a/invokeai/frontend/web/src/features/queue/store/readiness.ts b/invokeai/frontend/web/src/features/queue/store/readiness.ts index 1e40cc6ce18..4e13020b2df 100644 --- a/invokeai/frontend/web/src/features/queue/store/readiness.ts +++ b/invokeai/frontend/web/src/features/queue/store/readiness.ts @@ -761,6 +761,52 @@ export const getReasonsWhyCannotEnqueueCanvasTab = (arg: { } } + if (model?.base === 'ideogram-4') { + // Ideogram 4 requires bbox dimensions that are multiples of 16 (enforced by ideogram4_denoise). + const { bbox } = canvas; + const gridSize = getGridSize('ideogram-4'); + + if (bbox.scaleMethod === 'none') { + if (bbox.rect.width % gridSize !== 0) { + reasons.push({ + content: i18n.t('parameters.invoke.modelIncompatibleBboxWidth', { + model: 'Ideogram 4', + width: bbox.rect.width, + multiple: gridSize, + }), + }); + } + if (bbox.rect.height % gridSize !== 0) { + reasons.push({ + content: i18n.t('parameters.invoke.modelIncompatibleBboxHeight', { + model: 'Ideogram 4', + height: bbox.rect.height, + multiple: gridSize, + }), + }); + } + } else { + if (bbox.scaledSize.width % gridSize !== 0) { + reasons.push({ + content: i18n.t('parameters.invoke.modelIncompatibleScaledBboxWidth', { + model: 'Ideogram 4', + width: bbox.scaledSize.width, + multiple: gridSize, + }), + }); + } + if (bbox.scaledSize.height % gridSize !== 0) { + reasons.push({ + content: i18n.t('parameters.invoke.modelIncompatibleScaledBboxHeight', { + model: 'Ideogram 4', + height: bbox.scaledSize.height, + multiple: gridSize, + }), + }); + } + } + } + if (model?.base === 'qwen-image' && model.format === 'gguf_quantized') { // GGUF needs sources for VAE + encoder. Each can come from either a standalone // model or the Component Source (Diffusers). diff --git a/invokeai/frontend/web/src/features/settingsAccordions/components/AdvancedSettingsAccordion/AdvancedSettingsAccordion.tsx b/invokeai/frontend/web/src/features/settingsAccordions/components/AdvancedSettingsAccordion/AdvancedSettingsAccordion.tsx index bfb69b945c8..29070c39d45 100644 --- a/invokeai/frontend/web/src/features/settingsAccordions/components/AdvancedSettingsAccordion/AdvancedSettingsAccordion.tsx +++ b/invokeai/frontend/web/src/features/settingsAccordions/components/AdvancedSettingsAccordion/AdvancedSettingsAccordion.tsx @@ -8,6 +8,7 @@ import { selectIsExternal, selectIsFLUX, selectIsFlux2, + selectIsIdeogram4, selectIsQwenImage, selectIsSD3, selectIsZImage, @@ -25,6 +26,10 @@ import ParamQwenImageComponentSourceSelect from 'features/parameters/components/ import ParamQwenImageQuantization from 'features/parameters/components/Advanced/ParamQwenImageQuantization'; import ParamT5EncoderModelSelect from 'features/parameters/components/Advanced/ParamT5EncoderModelSelect'; import ParamZImageQwen3VaeModelSelect from 'features/parameters/components/Advanced/ParamZImageQwen3VaeModelSelect'; +import ParamIdeogram4ColorPalette from 'features/parameters/components/Core/ParamIdeogram4ColorPalette'; +import ParamIdeogram4GuidanceScale from 'features/parameters/components/Core/ParamIdeogram4GuidanceScale'; +import ParamIdeogram4Mu from 'features/parameters/components/Core/ParamIdeogram4Mu'; +import ParamIdeogram4Steps from 'features/parameters/components/Core/ParamIdeogram4Steps'; import ParamSeamlessXAxis from 'features/parameters/components/Seamless/ParamSeamlessXAxis'; import ParamSeamlessYAxis from 'features/parameters/components/Seamless/ParamSeamlessYAxis'; import ParamColorCompensation from 'features/parameters/components/VAEModel/ParamColorCompensation'; @@ -51,46 +56,52 @@ export const AdvancedSettingsAccordion = memo(() => { const isFlux2 = useAppSelector(selectIsFlux2); const isSD3 = useAppSelector(selectIsSD3); const isZImage = useAppSelector(selectIsZImage); + const isIdeogram4 = useAppSelector(selectIsIdeogram4); const isExternal = useAppSelector(selectIsExternal); const isQwenImage = useAppSelector(selectIsQwenImage); const isAnima = useAppSelector(selectIsAnima); const selectBadges = useMemo( () => - createMemoizedSelector([selectParamsSlice, selectIsFLUX, selectIsFlux2], (params, isFLUX, isFlux2) => { - const badges: (string | number)[] = []; - // FLUX.2 has VAE built into main model - no badge needed - if (isFLUX && !isFlux2) { - if (vaeConfig) { - let vaeBadge = vaeConfig.name; - if (params.vaePrecision === 'fp16') { - vaeBadge += ` ${params.vaePrecision}`; + createMemoizedSelector( + [selectParamsSlice, selectIsFLUX, selectIsFlux2, selectIsIdeogram4], + (params, isFLUX, isFlux2, isIdeogram4) => { + const badges: (string | number)[] = []; + // FLUX.2 has VAE built into main model - no badge needed + if (isFLUX && !isFlux2) { + if (vaeConfig) { + let vaeBadge = vaeConfig.name; + if (params.vaePrecision === 'fp16') { + vaeBadge += ` ${params.vaePrecision}`; + } + badges.push(vaeBadge); } - badges.push(vaeBadge); - } - } else if (!isFlux2) { - if (vaeConfig) { - let vaeBadge = vaeConfig.name; - if (params.vaePrecision === 'fp16') { - vaeBadge += ` ${params.vaePrecision}`; + // Ideogram 4 hides the VAE / clip skip / CFG rescale / seamless controls (they don't apply), + // so it must not advertise stale badges for them either. + } else if (!isFlux2 && !isIdeogram4) { + if (vaeConfig) { + let vaeBadge = vaeConfig.name; + if (params.vaePrecision === 'fp16') { + vaeBadge += ` ${params.vaePrecision}`; + } + badges.push(vaeBadge); + } else if (params.vaePrecision === 'fp16') { + badges.push(`VAE ${params.vaePrecision}`); + } + if (params.clipSkip) { + badges.push(`Skip ${params.clipSkip}`); + } + if (params.cfgRescaleMultiplier) { + badges.push(`Rescale ${params.cfgRescaleMultiplier}`); + } + if (params.seamlessXAxis || params.seamlessYAxis) { + badges.push('seamless'); } - badges.push(vaeBadge); - } else if (params.vaePrecision === 'fp16') { - badges.push(`VAE ${params.vaePrecision}`); - } - if (params.clipSkip) { - badges.push(`Skip ${params.clipSkip}`); - } - if (params.cfgRescaleMultiplier) { - badges.push(`Rescale ${params.cfgRescaleMultiplier}`); - } - if (params.seamlessXAxis || params.seamlessYAxis) { - badges.push('seamless'); } - } - return badges; - }), + return badges; + } + ), [vaeConfig] ); const badges = useAppSelector(selectBadges); @@ -107,13 +118,13 @@ export const AdvancedSettingsAccordion = memo(() => { return ( - {!isZImage && !isAnima && !isFlux2 && !isQwenImage && ( + {!isZImage && !isAnima && !isFlux2 && !isQwenImage && !isIdeogram4 && ( {isFLUX ? : } {!isFLUX && !isSD3 && } )} - {!isFLUX && !isFlux2 && !isSD3 && !isZImage && !isQwenImage && !isAnima && ( + {!isFLUX && !isFlux2 && !isSD3 && !isZImage && !isQwenImage && !isAnima && !isIdeogram4 && ( <> @@ -166,6 +177,16 @@ export const AdvancedSettingsAccordion = memo(() => { )} + {isIdeogram4 && ( + <> + + + + + + + + )} ); diff --git a/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx b/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx index 220008a38b0..30cd28fc82c 100644 --- a/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx +++ b/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx @@ -11,6 +11,7 @@ import { selectIsExternal, selectIsFLUX, selectIsFlux2, + selectIsIdeogram4, selectIsQwenImage, selectIsSD3, selectIsZImage, @@ -26,6 +27,7 @@ import ParamFluxDypePreset from 'features/parameters/components/Core/ParamFluxDy import ParamFluxDypeScale from 'features/parameters/components/Core/ParamFluxDypeScale'; import ParamFluxScheduler from 'features/parameters/components/Core/ParamFluxScheduler'; import ParamGuidance from 'features/parameters/components/Core/ParamGuidance'; +import ParamIdeogram4SamplerPreset from 'features/parameters/components/Core/ParamIdeogram4SamplerPreset'; import ParamQwenImageShift from 'features/parameters/components/Core/ParamQwenImageShift'; import ParamScheduler from 'features/parameters/components/Core/ParamScheduler'; import ParamSteps from 'features/parameters/components/Core/ParamSteps'; @@ -52,6 +54,7 @@ export const GenerationSettingsAccordion = memo(() => { const isSD3 = useAppSelector(selectIsSD3); const isCogView4 = useAppSelector(selectIsCogView4); const isZImage = useAppSelector(selectIsZImage); + const isIdeogram4 = useAppSelector(selectIsIdeogram4); const isExternal = useAppSelector(selectIsExternal); const isQwenImage = useAppSelector(selectIsQwenImage); const isAnima = useAppSelector(selectIsAnima); @@ -103,17 +106,19 @@ export const GenerationSettingsAccordion = memo(() => { !isSD3 && !isCogView4 && !isZImage && + !isIdeogram4 && !isQwenImage && !isAnima && } {!isExternal && (isFLUX || isFlux2) && } {!isExternal && isZImage && } + {!isExternal && isIdeogram4 && } {!isExternal && isAnima && } {modelSupportsSteps && } {isExternal && modelSupportsGuidance && } {!isExternal && isFLUX && modelConfig && !isFluxFillMainModelModelConfig(modelConfig) && ( )} - {!isExternal && !isFLUX && !isFlux2 && } + {!isExternal && !isFLUX && !isFlux2 && !isIdeogram4 && } {!isExternal && isZImage && } {!isExternal && isQwenImage && } {!isExternal && isFLUX && } diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts index 3f08dc0c7e2..f8dd26bf139 100644 --- a/invokeai/frontend/web/src/services/api/schema.ts +++ b/invokeai/frontend/web/src/services/api/schema.ts @@ -3745,7 +3745,7 @@ export type components = { */ type: "anima_text_encoder"; }; - AnyModelConfig: components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; + AnyModelConfig: components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Diffusers_Ideogram4_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; /** * AppVersion * @description App Version Response @@ -3897,7 +3897,7 @@ export type components = { * fallback/null value `BaseModelType.Any` for these models, instead of making the model base optional. * @enum {string} */ - BaseModelType: "any" | "sd-1" | "sd-2" | "sd-3" | "sdxl" | "sdxl-refiner" | "flux" | "flux2" | "cogview4" | "z-image" | "external" | "qwen-image" | "anima" | "unknown"; + BaseModelType: "any" | "sd-1" | "sd-2" | "sd-3" | "sdxl" | "sdxl-refiner" | "flux" | "flux2" | "cogview4" | "z-image" | "ideogram-4" | "external" | "qwen-image" | "anima" | "unknown"; /** Batch */ Batch: { /** @@ -7883,7 +7883,7 @@ export type components = { * @description The generation mode that output this image * @default null */ - generation_mode?: ("txt2img" | "img2img" | "inpaint" | "outpaint" | "sdxl_txt2img" | "sdxl_img2img" | "sdxl_inpaint" | "sdxl_outpaint" | "flux_txt2img" | "flux_img2img" | "flux_inpaint" | "flux_outpaint" | "flux2_txt2img" | "flux2_img2img" | "flux2_inpaint" | "flux2_outpaint" | "sd3_txt2img" | "sd3_img2img" | "sd3_inpaint" | "sd3_outpaint" | "cogview4_txt2img" | "cogview4_img2img" | "cogview4_inpaint" | "cogview4_outpaint" | "z_image_txt2img" | "z_image_img2img" | "z_image_inpaint" | "z_image_outpaint" | "qwen_image_txt2img" | "qwen_image_img2img" | "qwen_image_inpaint" | "qwen_image_outpaint" | "anima_txt2img" | "anima_img2img" | "anima_inpaint" | "anima_outpaint") | null; + generation_mode?: ("txt2img" | "img2img" | "inpaint" | "outpaint" | "sdxl_txt2img" | "sdxl_img2img" | "sdxl_inpaint" | "sdxl_outpaint" | "flux_txt2img" | "flux_img2img" | "flux_inpaint" | "flux_outpaint" | "flux2_txt2img" | "flux2_img2img" | "flux2_inpaint" | "flux2_outpaint" | "sd3_txt2img" | "sd3_img2img" | "sd3_inpaint" | "sd3_outpaint" | "cogview4_txt2img" | "cogview4_img2img" | "cogview4_inpaint" | "cogview4_outpaint" | "z_image_txt2img" | "z_image_img2img" | "z_image_inpaint" | "z_image_outpaint" | "ideogram4_txt2img" | "qwen_image_txt2img" | "qwen_image_img2img" | "qwen_image_inpaint" | "qwen_image_outpaint" | "anima_txt2img" | "anima_img2img" | "anima_inpaint" | "anima_outpaint") | null; /** * Positive Prompt * @description The positive prompt parameter @@ -8013,6 +8013,12 @@ export type components = { * @default null */ qwen3_encoder?: components["schemas"]["ModelIdentifierField"] | null; + /** + * Ideogram4 Caption + * @description The structured JSON caption encoded for Ideogram 4 inference + * @default null + */ + ideogram4_caption?: string | null; /** * Hrf Enabled * @description Whether or not high resolution fix was enabled. @@ -12606,7 +12612,7 @@ export type components = { * @description The nodes in this graph */ nodes?: { - [key: string]: components["schemas"]["AddInvocation"] | components["schemas"]["AlibabaCloudImageGenerationInvocation"] | components["schemas"]["AlphaMaskToTensorInvocation"] | components["schemas"]["AnimaDenoiseInvocation"] | components["schemas"]["AnimaImageToLatentsInvocation"] | components["schemas"]["AnimaLLLiteInvocation"] | components["schemas"]["AnimaLatentsToImageInvocation"] | components["schemas"]["AnimaLoRACollectionLoader"] | components["schemas"]["AnimaLoRALoaderInvocation"] | components["schemas"]["AnimaModelLoaderInvocation"] | components["schemas"]["AnimaTextEncoderInvocation"] | components["schemas"]["ApplyMaskTensorToImageInvocation"] | components["schemas"]["ApplyMaskToImageInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["BoundingBoxInvocation"] | components["schemas"]["CLIPSkipInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["CallSavedWorkflowInvocation"] | components["schemas"]["CannyEdgeDetectionInvocation"] | components["schemas"]["CanvasOutputInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["CanvasV2MaskAndCropInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["CogView4DenoiseInvocation"] | components["schemas"]["CogView4ImageToLatentsInvocation"] | components["schemas"]["CogView4LatentsToImageInvocation"] | components["schemas"]["CogView4ModelLoaderInvocation"] | components["schemas"]["CogView4TextEncoderInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ColorMapInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ContentShuffleInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["CropImageToBoundingBoxInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["DWOpenposeDetectionInvocation"] | components["schemas"]["DecodeInvisibleWatermarkInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["DenoiseLatentsMetaInvocation"] | components["schemas"]["DepthAnythingDepthEstimationInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ExpandMaskWithFadeInvocation"] | components["schemas"]["FLUXLoRACollectionLoader"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["FloatBatchInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["FloatGenerator"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["Flux2DenoiseInvocation"] | components["schemas"]["Flux2KleinLoRACollectionLoader"] | components["schemas"]["Flux2KleinLoRALoaderInvocation"] | components["schemas"]["Flux2KleinModelLoaderInvocation"] | components["schemas"]["Flux2KleinTextEncoderInvocation"] | components["schemas"]["Flux2VaeDecodeInvocation"] | components["schemas"]["Flux2VaeEncodeInvocation"] | components["schemas"]["FluxControlLoRALoaderInvocation"] | components["schemas"]["FluxControlNetInvocation"] | components["schemas"]["FluxDenoiseInvocation"] | components["schemas"]["FluxDenoiseLatentsMetaInvocation"] | components["schemas"]["FluxFillInvocation"] | components["schemas"]["FluxIPAdapterInvocation"] | components["schemas"]["FluxKontextConcatenateImagesInvocation"] | components["schemas"]["FluxKontextInvocation"] | components["schemas"]["FluxLoRALoaderInvocation"] | components["schemas"]["FluxModelLoaderInvocation"] | components["schemas"]["FluxReduxInvocation"] | components["schemas"]["FluxTextEncoderInvocation"] | components["schemas"]["FluxVaeDecodeInvocation"] | components["schemas"]["FluxVaeEncodeInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["GeminiImageGenerationInvocation"] | components["schemas"]["GetMaskBoundingBoxInvocation"] | components["schemas"]["GroundingDinoInvocation"] | components["schemas"]["HEDEdgeDetectionInvocation"] | components["schemas"]["HeuristicResizeInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["IfInvocation"] | components["schemas"]["ImageBatchInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImageGenerator"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageMaskToTensorInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageNoiseInvocation"] | components["schemas"]["ImagePanelLayoutInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["IntegerBatchInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["IntegerGenerator"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["InvertTensorMaskInvocation"] | components["schemas"]["InvokeAdjustImageHuePlusInvocation"] | components["schemas"]["InvokeEquivalentAchromaticLightnessInvocation"] | components["schemas"]["InvokeImageBlendInvocation"] | components["schemas"]["InvokeImageCompositorInvocation"] | components["schemas"]["InvokeImageDilateOrErodeInvocation"] | components["schemas"]["InvokeImageEnhanceInvocation"] | components["schemas"]["InvokeImageValueThresholdsInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["LineartAnimeEdgeDetectionInvocation"] | components["schemas"]["LineartEdgeDetectionInvocation"] | components["schemas"]["LlavaOnevisionVllmInvocation"] | components["schemas"]["LoRACollectionLoader"] | components["schemas"]["LoRALoaderInvocation"] | components["schemas"]["LoRASelectorInvocation"] | components["schemas"]["MLSDDetectionInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["MaskFromIDInvocation"] | components["schemas"]["MaskTensorToImageInvocation"] | components["schemas"]["MediaPipeFaceDetectionInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["MetadataFieldExtractorInvocation"] | components["schemas"]["MetadataFromImageInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MetadataItemLinkedInvocation"] | components["schemas"]["MetadataToBoolCollectionInvocation"] | components["schemas"]["MetadataToBoolInvocation"] | components["schemas"]["MetadataToControlnetsInvocation"] | components["schemas"]["MetadataToFloatCollectionInvocation"] | components["schemas"]["MetadataToFloatInvocation"] | components["schemas"]["MetadataToIPAdaptersInvocation"] | components["schemas"]["MetadataToIntegerCollectionInvocation"] | components["schemas"]["MetadataToIntegerInvocation"] | components["schemas"]["MetadataToLorasCollectionInvocation"] | components["schemas"]["MetadataToLorasInvocation"] | components["schemas"]["MetadataToModelInvocation"] | components["schemas"]["MetadataToSDXLLorasInvocation"] | components["schemas"]["MetadataToSDXLModelInvocation"] | components["schemas"]["MetadataToSchedulerInvocation"] | components["schemas"]["MetadataToStringCollectionInvocation"] | components["schemas"]["MetadataToStringInvocation"] | components["schemas"]["MetadataToT2IAdaptersInvocation"] | components["schemas"]["MetadataToVAEInvocation"] | components["schemas"]["ModelIdentifierInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["NormalMapInvocation"] | components["schemas"]["OklabUnsharpMaskInvocation"] | components["schemas"]["OklchImageHueAdjustmentInvocation"] | components["schemas"]["OpenAIImageGenerationInvocation"] | components["schemas"]["PBRMapsInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["PasteImageIntoBoundingBoxInvocation"] | components["schemas"]["PiDiNetEdgeDetectionInvocation"] | components["schemas"]["PromptTemplateInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["QwenImageDenoiseInvocation"] | components["schemas"]["QwenImageImageToLatentsInvocation"] | components["schemas"]["QwenImageLatentsToImageInvocation"] | components["schemas"]["QwenImageLoRACollectionLoader"] | components["schemas"]["QwenImageLoRALoaderInvocation"] | components["schemas"]["QwenImageModelLoaderInvocation"] | components["schemas"]["QwenImageTextEncoderInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RectangleMaskInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["SD3DenoiseInvocation"] | components["schemas"]["SD3ImageToLatentsInvocation"] | components["schemas"]["SD3LatentsToImageInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["SDXLLoRACollectionLoader"] | components["schemas"]["SDXLLoRALoaderInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["SaveImageToFileInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["Sd3ModelLoaderInvocation"] | components["schemas"]["Sd3TextEncoderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["SeedreamImageGenerationInvocation"] | components["schemas"]["SegmentAnythingInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["SpandrelImageToImageAutoscaleInvocation"] | components["schemas"]["SpandrelImageToImageInvocation"] | components["schemas"]["StringBatchInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["StringGenerator"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["TextLLMInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["TiledMultiDiffusionDenoiseLatents"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["VAELoaderInvocation"] | components["schemas"]["WorkflowReturnGetInvocation"] | components["schemas"]["WorkflowReturnInvocation"] | components["schemas"]["WorkflowReturnValueInvocation"] | components["schemas"]["ZImageControlInvocation"] | components["schemas"]["ZImageDenoiseInvocation"] | components["schemas"]["ZImageDenoiseMetaInvocation"] | components["schemas"]["ZImageImageToLatentsInvocation"] | components["schemas"]["ZImageLatentsToImageInvocation"] | components["schemas"]["ZImageLoRACollectionLoader"] | components["schemas"]["ZImageLoRALoaderInvocation"] | components["schemas"]["ZImageModelLoaderInvocation"] | components["schemas"]["ZImageSeedVarianceEnhancerInvocation"] | components["schemas"]["ZImageTextEncoderInvocation"]; + [key: string]: components["schemas"]["AddInvocation"] | components["schemas"]["AlibabaCloudImageGenerationInvocation"] | components["schemas"]["AlphaMaskToTensorInvocation"] | components["schemas"]["AnimaDenoiseInvocation"] | components["schemas"]["AnimaImageToLatentsInvocation"] | components["schemas"]["AnimaLLLiteInvocation"] | components["schemas"]["AnimaLatentsToImageInvocation"] | components["schemas"]["AnimaLoRACollectionLoader"] | components["schemas"]["AnimaLoRALoaderInvocation"] | components["schemas"]["AnimaModelLoaderInvocation"] | components["schemas"]["AnimaTextEncoderInvocation"] | components["schemas"]["ApplyMaskTensorToImageInvocation"] | components["schemas"]["ApplyMaskToImageInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["BoundingBoxInvocation"] | components["schemas"]["CLIPSkipInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["CallSavedWorkflowInvocation"] | components["schemas"]["CannyEdgeDetectionInvocation"] | components["schemas"]["CanvasOutputInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["CanvasV2MaskAndCropInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["CogView4DenoiseInvocation"] | components["schemas"]["CogView4ImageToLatentsInvocation"] | components["schemas"]["CogView4LatentsToImageInvocation"] | components["schemas"]["CogView4ModelLoaderInvocation"] | components["schemas"]["CogView4TextEncoderInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ColorMapInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ContentShuffleInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["CropImageToBoundingBoxInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["DWOpenposeDetectionInvocation"] | components["schemas"]["DecodeInvisibleWatermarkInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["DenoiseLatentsMetaInvocation"] | components["schemas"]["DepthAnythingDepthEstimationInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ExpandMaskWithFadeInvocation"] | components["schemas"]["FLUXLoRACollectionLoader"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["FloatBatchInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["FloatGenerator"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["Flux2DenoiseInvocation"] | components["schemas"]["Flux2KleinLoRACollectionLoader"] | components["schemas"]["Flux2KleinLoRALoaderInvocation"] | components["schemas"]["Flux2KleinModelLoaderInvocation"] | components["schemas"]["Flux2KleinTextEncoderInvocation"] | components["schemas"]["Flux2VaeDecodeInvocation"] | components["schemas"]["Flux2VaeEncodeInvocation"] | components["schemas"]["FluxControlLoRALoaderInvocation"] | components["schemas"]["FluxControlNetInvocation"] | components["schemas"]["FluxDenoiseInvocation"] | components["schemas"]["FluxDenoiseLatentsMetaInvocation"] | components["schemas"]["FluxFillInvocation"] | components["schemas"]["FluxIPAdapterInvocation"] | components["schemas"]["FluxKontextConcatenateImagesInvocation"] | components["schemas"]["FluxKontextInvocation"] | components["schemas"]["FluxLoRALoaderInvocation"] | components["schemas"]["FluxModelLoaderInvocation"] | components["schemas"]["FluxReduxInvocation"] | components["schemas"]["FluxTextEncoderInvocation"] | components["schemas"]["FluxVaeDecodeInvocation"] | components["schemas"]["FluxVaeEncodeInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["GeminiImageGenerationInvocation"] | components["schemas"]["GetMaskBoundingBoxInvocation"] | components["schemas"]["GroundingDinoInvocation"] | components["schemas"]["HEDEdgeDetectionInvocation"] | components["schemas"]["HeuristicResizeInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["Ideogram4CaptionBuilderInvocation"] | components["schemas"]["Ideogram4DenoiseInvocation"] | components["schemas"]["Ideogram4LatentsToImageInvocation"] | components["schemas"]["Ideogram4ModelLoaderInvocation"] | components["schemas"]["Ideogram4TextEncoderInvocation"] | components["schemas"]["IfInvocation"] | components["schemas"]["ImageBatchInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImageGenerator"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageMaskToTensorInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageNoiseInvocation"] | components["schemas"]["ImagePanelLayoutInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["IntegerBatchInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["IntegerGenerator"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["InvertTensorMaskInvocation"] | components["schemas"]["InvokeAdjustImageHuePlusInvocation"] | components["schemas"]["InvokeEquivalentAchromaticLightnessInvocation"] | components["schemas"]["InvokeImageBlendInvocation"] | components["schemas"]["InvokeImageCompositorInvocation"] | components["schemas"]["InvokeImageDilateOrErodeInvocation"] | components["schemas"]["InvokeImageEnhanceInvocation"] | components["schemas"]["InvokeImageValueThresholdsInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["LineartAnimeEdgeDetectionInvocation"] | components["schemas"]["LineartEdgeDetectionInvocation"] | components["schemas"]["LlavaOnevisionVllmInvocation"] | components["schemas"]["LoRACollectionLoader"] | components["schemas"]["LoRALoaderInvocation"] | components["schemas"]["LoRASelectorInvocation"] | components["schemas"]["MLSDDetectionInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["MaskFromIDInvocation"] | components["schemas"]["MaskTensorToImageInvocation"] | components["schemas"]["MediaPipeFaceDetectionInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["MetadataFieldExtractorInvocation"] | components["schemas"]["MetadataFromImageInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MetadataItemLinkedInvocation"] | components["schemas"]["MetadataToBoolCollectionInvocation"] | components["schemas"]["MetadataToBoolInvocation"] | components["schemas"]["MetadataToControlnetsInvocation"] | components["schemas"]["MetadataToFloatCollectionInvocation"] | components["schemas"]["MetadataToFloatInvocation"] | components["schemas"]["MetadataToIPAdaptersInvocation"] | components["schemas"]["MetadataToIntegerCollectionInvocation"] | components["schemas"]["MetadataToIntegerInvocation"] | components["schemas"]["MetadataToLorasCollectionInvocation"] | components["schemas"]["MetadataToLorasInvocation"] | components["schemas"]["MetadataToModelInvocation"] | components["schemas"]["MetadataToSDXLLorasInvocation"] | components["schemas"]["MetadataToSDXLModelInvocation"] | components["schemas"]["MetadataToSchedulerInvocation"] | components["schemas"]["MetadataToStringCollectionInvocation"] | components["schemas"]["MetadataToStringInvocation"] | components["schemas"]["MetadataToT2IAdaptersInvocation"] | components["schemas"]["MetadataToVAEInvocation"] | components["schemas"]["ModelIdentifierInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["NormalMapInvocation"] | components["schemas"]["OklabUnsharpMaskInvocation"] | components["schemas"]["OklchImageHueAdjustmentInvocation"] | components["schemas"]["OpenAIImageGenerationInvocation"] | components["schemas"]["PBRMapsInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["PasteImageIntoBoundingBoxInvocation"] | components["schemas"]["PiDiNetEdgeDetectionInvocation"] | components["schemas"]["PromptTemplateInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["QwenImageDenoiseInvocation"] | components["schemas"]["QwenImageImageToLatentsInvocation"] | components["schemas"]["QwenImageLatentsToImageInvocation"] | components["schemas"]["QwenImageLoRACollectionLoader"] | components["schemas"]["QwenImageLoRALoaderInvocation"] | components["schemas"]["QwenImageModelLoaderInvocation"] | components["schemas"]["QwenImageTextEncoderInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RectangleMaskInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["SD3DenoiseInvocation"] | components["schemas"]["SD3ImageToLatentsInvocation"] | components["schemas"]["SD3LatentsToImageInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["SDXLLoRACollectionLoader"] | components["schemas"]["SDXLLoRALoaderInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["SaveImageToFileInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["Sd3ModelLoaderInvocation"] | components["schemas"]["Sd3TextEncoderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["SeedreamImageGenerationInvocation"] | components["schemas"]["SegmentAnythingInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["SpandrelImageToImageAutoscaleInvocation"] | components["schemas"]["SpandrelImageToImageInvocation"] | components["schemas"]["StringBatchInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["StringGenerator"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["TextLLMInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["TiledMultiDiffusionDenoiseLatents"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["VAELoaderInvocation"] | components["schemas"]["WorkflowReturnGetInvocation"] | components["schemas"]["WorkflowReturnInvocation"] | components["schemas"]["WorkflowReturnValueInvocation"] | components["schemas"]["ZImageControlInvocation"] | components["schemas"]["ZImageDenoiseInvocation"] | components["schemas"]["ZImageDenoiseMetaInvocation"] | components["schemas"]["ZImageImageToLatentsInvocation"] | components["schemas"]["ZImageLatentsToImageInvocation"] | components["schemas"]["ZImageLoRACollectionLoader"] | components["schemas"]["ZImageLoRALoaderInvocation"] | components["schemas"]["ZImageModelLoaderInvocation"] | components["schemas"]["ZImageSeedVarianceEnhancerInvocation"] | components["schemas"]["ZImageTextEncoderInvocation"]; }; /** * Edges @@ -12643,7 +12649,7 @@ export type components = { * @description The results of node executions */ results: { - [key: string]: components["schemas"]["AnimaConditioningOutput"] | components["schemas"]["AnimaLLLiteOutput"] | components["schemas"]["AnimaLoRALoaderOutput"] | components["schemas"]["AnimaModelLoaderOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["BoundingBoxCollectionOutput"] | components["schemas"]["BoundingBoxOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["CLIPSkipInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["CogView4ConditioningOutput"] | components["schemas"]["CogView4ModelLoaderOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["FloatGeneratorOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["Flux2KleinLoRALoaderOutput"] | components["schemas"]["Flux2KleinModelLoaderOutput"] | components["schemas"]["FluxConditioningCollectionOutput"] | components["schemas"]["FluxConditioningOutput"] | components["schemas"]["FluxControlLoRALoaderOutput"] | components["schemas"]["FluxControlNetOutput"] | components["schemas"]["FluxFillOutput"] | components["schemas"]["FluxKontextOutput"] | components["schemas"]["FluxLoRALoaderOutput"] | components["schemas"]["FluxModelLoaderOutput"] | components["schemas"]["FluxReduxOutput"] | components["schemas"]["GradientMaskOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["IfInvocationOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["ImageGeneratorOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["ImagePanelCoordinateOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["IntegerGeneratorOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["LatentsMetaOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["LoRALoaderOutput"] | components["schemas"]["LoRASelectorOutput"] | components["schemas"]["MDControlListOutput"] | components["schemas"]["MDIPAdapterListOutput"] | components["schemas"]["MDT2IAdapterListOutput"] | components["schemas"]["MaskOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["MetadataToLorasCollectionOutput"] | components["schemas"]["MetadataToModelOutput"] | components["schemas"]["MetadataToSDXLModelOutput"] | components["schemas"]["ModelIdentifierOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["PBRMapsOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["PromptTemplateOutput"] | components["schemas"]["QwenImageConditioningOutput"] | components["schemas"]["QwenImageLoRALoaderOutput"] | components["schemas"]["QwenImageModelLoaderOutput"] | components["schemas"]["SD3ConditioningOutput"] | components["schemas"]["SDXLLoRALoaderOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["Sd3ModelLoaderOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["String2Output"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["StringGeneratorOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["WorkflowReturnGetOutput"] | components["schemas"]["WorkflowReturnOutput"] | components["schemas"]["WorkflowReturnValueOutput"] | components["schemas"]["ZImageConditioningOutput"] | components["schemas"]["ZImageControlOutput"] | components["schemas"]["ZImageLoRALoaderOutput"] | components["schemas"]["ZImageModelLoaderOutput"]; + [key: string]: components["schemas"]["AnimaConditioningOutput"] | components["schemas"]["AnimaLLLiteOutput"] | components["schemas"]["AnimaLoRALoaderOutput"] | components["schemas"]["AnimaModelLoaderOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["BoundingBoxCollectionOutput"] | components["schemas"]["BoundingBoxOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["CLIPSkipInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["CogView4ConditioningOutput"] | components["schemas"]["CogView4ModelLoaderOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["FloatGeneratorOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["Flux2KleinLoRALoaderOutput"] | components["schemas"]["Flux2KleinModelLoaderOutput"] | components["schemas"]["FluxConditioningCollectionOutput"] | components["schemas"]["FluxConditioningOutput"] | components["schemas"]["FluxControlLoRALoaderOutput"] | components["schemas"]["FluxControlNetOutput"] | components["schemas"]["FluxFillOutput"] | components["schemas"]["FluxKontextOutput"] | components["schemas"]["FluxLoRALoaderOutput"] | components["schemas"]["FluxModelLoaderOutput"] | components["schemas"]["FluxReduxOutput"] | components["schemas"]["GradientMaskOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["Ideogram4ConditioningOutput"] | components["schemas"]["Ideogram4ModelLoaderOutput"] | components["schemas"]["IfInvocationOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["ImageGeneratorOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["ImagePanelCoordinateOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["IntegerGeneratorOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["LatentsMetaOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["LoRALoaderOutput"] | components["schemas"]["LoRASelectorOutput"] | components["schemas"]["MDControlListOutput"] | components["schemas"]["MDIPAdapterListOutput"] | components["schemas"]["MDT2IAdapterListOutput"] | components["schemas"]["MaskOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["MetadataToLorasCollectionOutput"] | components["schemas"]["MetadataToModelOutput"] | components["schemas"]["MetadataToSDXLModelOutput"] | components["schemas"]["ModelIdentifierOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["PBRMapsOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["PromptTemplateOutput"] | components["schemas"]["QwenImageConditioningOutput"] | components["schemas"]["QwenImageLoRALoaderOutput"] | components["schemas"]["QwenImageModelLoaderOutput"] | components["schemas"]["SD3ConditioningOutput"] | components["schemas"]["SDXLLoRALoaderOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["Sd3ModelLoaderOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["String2Output"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["StringGeneratorOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["WorkflowReturnGetOutput"] | components["schemas"]["WorkflowReturnOutput"] | components["schemas"]["WorkflowReturnValueOutput"] | components["schemas"]["ZImageConditioningOutput"] | components["schemas"]["ZImageControlOutput"] | components["schemas"]["ZImageLoRALoaderOutput"] | components["schemas"]["ZImageModelLoaderOutput"]; }; /** * Errors @@ -13746,6 +13752,342 @@ export type components = { */ type: "ideal_size_output"; }; + /** + * Caption Builder - Ideogram 4 + * @description Assembles the Ideogram 4 structured JSON caption at generation time. + * + * The caption is built here (not in the graph builder) so the batch-injectable global `prompt` — which + * dynamic prompts and prompt batching vary — is folded into the encoded caption. The regions and color + * palette are fixed per generation and supplied as inputs. If the prompt is already a JSON object it is + * passed through verbatim; otherwise it is always wrapped in the structured JSON schema (never bare + * plain text — Ideogram's safety filter false-positives far more on plain text). + */ + Ideogram4CaptionBuilderInvocation: { + /** + * Id + * @description The id of this instance of an invocation. Must be unique among all instances of invocations. + */ + id: string; + /** + * Is Intermediate + * @description Whether or not this is an intermediate invocation. + * @default false + */ + is_intermediate?: boolean; + /** + * Use Cache + * @description Whether or not to use the cache + * @default true + */ + use_cache?: boolean; + /** + * Prompt + * @description The global prompt (becomes `high_level_description`, or is used verbatim if it is already a JSON caption). + * @default + */ + prompt?: string; + /** + * Regions + * @description Regional descriptions and bounding boxes assembled from Canvas Regional Guidance layers. + * @default [] + */ + regions?: components["schemas"]["Ideogram4Region"][]; + /** + * Color Palette + * @description Optional color palette as hex colors (#RRGGBB). + * @default [] + */ + color_palette?: string[]; + /** + * type + * @default ideogram4_caption_builder + * @constant + */ + type: "ideogram4_caption_builder"; + }; + /** + * Ideogram4ConditioningField + * @description An Ideogram 4 conditioning tensor primitive value + */ + Ideogram4ConditioningField: { + /** + * Conditioning Name + * @description The name of conditioning tensor + */ + conditioning_name: string; + }; + /** + * Ideogram4ConditioningOutput + * @description Base class for nodes that output an Ideogram 4 text conditioning tensor. + */ + Ideogram4ConditioningOutput: { + /** @description Conditioning tensor */ + conditioning: components["schemas"]["Ideogram4ConditioningField"]; + /** + * type + * @default ideogram4_conditioning_output + * @constant + */ + type: "ideogram4_conditioning_output"; + }; + /** + * Denoise - Ideogram 4 + * @description Runs the Ideogram 4 dual-branch flow-matching denoising loop (text-to-image). + */ + Ideogram4DenoiseInvocation: { + /** + * Id + * @description The id of this instance of an invocation. Must be unique among all instances of invocations. + */ + id: string; + /** + * Is Intermediate + * @description Whether or not this is an intermediate invocation. + * @default false + */ + is_intermediate?: boolean; + /** + * Use Cache + * @description Whether or not to use the cache + * @default true + */ + use_cache?: boolean; + /** + * Transformer + * @description Transformer + * @default null + */ + transformer?: components["schemas"]["TransformerField"] | null; + /** + * @description Positive conditioning tensor + * @default null + */ + positive_conditioning?: components["schemas"]["Ideogram4ConditioningField"] | null; + /** + * Sampler Preset + * @description Sampler preset (steps + guidance schedule + schedule mean/std). + * @default V4_QUALITY_48 + * @enum {string} + */ + sampler_preset?: "V4_QUALITY_48" | "V4_DEFAULT_20" | "V4_TURBO_12"; + /** + * Width + * @description Width of the generated image. + * @default 1024 + */ + width?: number; + /** + * Height + * @description Height of the generated image. + * @default 1024 + */ + height?: number; + /** + * Seed + * @description Randomness seed for reproducibility. + * @default 0 + */ + seed?: number; + /** + * Steps + * @description Override the preset's step count (minimum 2, so a polish and a main step both exist). Leave empty to use the preset. + * @default null + */ + steps?: number | null; + /** + * Guidance Scale + * @description Override the main guidance weight (the preset's polish tail is preserved). Empty = use the preset. + * @default null + */ + guidance_scale?: number | null; + /** + * Mu + * @description Override the logit-normal schedule mean (resolution-adjusted internally). Empty = use the preset. + * @default null + */ + mu?: number | null; + /** + * type + * @default ideogram4_denoise + * @constant + */ + type: "ideogram4_denoise"; + }; + /** + * Latents to Image - Ideogram 4 + * @description Decodes Ideogram 4 packed latents to an image with the FLUX.2-style VAE. + */ + Ideogram4LatentsToImageInvocation: { + /** + * @description The board to save the image to + * @default null + */ + board?: components["schemas"]["BoardField"] | null; + /** + * @description Optional metadata to be saved with the image + * @default null + */ + metadata?: components["schemas"]["MetadataField"] | null; + /** + * Id + * @description The id of this instance of an invocation. Must be unique among all instances of invocations. + */ + id: string; + /** + * Is Intermediate + * @description Whether or not this is an intermediate invocation. + * @default false + */ + is_intermediate?: boolean; + /** + * Use Cache + * @description Whether or not to use the cache + * @default true + */ + use_cache?: boolean; + /** + * @description Latents tensor + * @default null + */ + latents?: components["schemas"]["LatentsField"] | null; + /** + * @description VAE + * @default null + */ + vae?: components["schemas"]["VAEField"] | null; + /** + * type + * @default ideogram4_l2i + * @constant + */ + type: "ideogram4_l2i"; + }; + /** + * Main Model - Ideogram 4 + * @description Loads an Ideogram 4 model, outputting its submodels. + * + * Ideogram 4 is distributed as a single bundled diffusers folder, so the transformer + * (both branches), the Qwen3-VL text encoder + tokenizer, and the VAE are all loaded + * from the one selected model. + */ + Ideogram4ModelLoaderInvocation: { + /** + * Id + * @description The id of this instance of an invocation. Must be unique among all instances of invocations. + */ + id: string; + /** + * Is Intermediate + * @description Whether or not this is an intermediate invocation. + * @default false + */ + is_intermediate?: boolean; + /** + * Use Cache + * @description Whether or not to use the cache + * @default true + */ + use_cache?: boolean; + /** + * Model + * @description The Ideogram 4 model to load. + */ + model: components["schemas"]["ModelIdentifierField"]; + /** + * type + * @default ideogram4_model_loader + * @constant + */ + type: "ideogram4_model_loader"; + }; + /** + * Ideogram4ModelLoaderOutput + * @description Ideogram 4 model loader output. + */ + Ideogram4ModelLoaderOutput: { + /** + * Transformer + * @description Transformer + */ + transformer: components["schemas"]["TransformerField"]; + /** + * Qwen3-VL Encoder + * @description Qwen3 tokenizer and text encoder + */ + qwen3_encoder: components["schemas"]["Qwen3EncoderField"]; + /** + * VAE + * @description VAE + */ + vae: components["schemas"]["VAEField"]; + /** + * type + * @default ideogram4_model_loader_output + * @constant + */ + type: "ideogram4_model_loader_output"; + }; + /** + * Ideogram4Region + * @description A single region of an Ideogram 4 structured caption (description + optional bounding box). + */ + Ideogram4Region: { + /** + * Prompt + * @description The region's description (becomes the element's `desc`). + */ + prompt: string; + /** + * Bbox + * @description Normalized bounding box [y_min, x_min, y_max, x_max] (0–1000), or null for a region with no drawn content. + * @default null + */ + bbox?: number[] | null; + }; + /** + * Prompt - Ideogram 4 + * @description Encodes a prompt for Ideogram 4 using the Qwen3-VL encoder. + * + * The prompt is normally a structured JSON caption (see the Ideogram 4 prompting guide); + * plain text also works but yields lower-quality results. + */ + Ideogram4TextEncoderInvocation: { + /** + * Id + * @description The id of this instance of an invocation. Must be unique among all instances of invocations. + */ + id: string; + /** + * Is Intermediate + * @description Whether or not this is an intermediate invocation. + * @default false + */ + is_intermediate?: boolean; + /** + * Use Cache + * @description Whether or not to use the cache + * @default true + */ + use_cache?: boolean; + /** + * Prompt + * @description The prompt to encode. A structured JSON caption is recommended. + * @default null + */ + prompt?: string | null; + /** + * Qwen3-VL Encoder + * @description Qwen3 tokenizer and text encoder + * @default null + */ + qwen3_encoder?: components["schemas"]["Qwen3EncoderField"] | null; + /** + * type + * @default ideogram4_text_encoder + * @constant + */ + type: "ideogram4_text_encoder"; + }; /** * If * @description Selects between two optional inputs based on a boolean condition. @@ -16083,7 +16425,7 @@ export type components = { * Invocation * @description The ID of the invocation */ - invocation: components["schemas"]["AddInvocation"] | components["schemas"]["AlibabaCloudImageGenerationInvocation"] | components["schemas"]["AlphaMaskToTensorInvocation"] | components["schemas"]["AnimaDenoiseInvocation"] | components["schemas"]["AnimaImageToLatentsInvocation"] | components["schemas"]["AnimaLLLiteInvocation"] | components["schemas"]["AnimaLatentsToImageInvocation"] | components["schemas"]["AnimaLoRACollectionLoader"] | components["schemas"]["AnimaLoRALoaderInvocation"] | components["schemas"]["AnimaModelLoaderInvocation"] | components["schemas"]["AnimaTextEncoderInvocation"] | components["schemas"]["ApplyMaskTensorToImageInvocation"] | components["schemas"]["ApplyMaskToImageInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["BoundingBoxInvocation"] | components["schemas"]["CLIPSkipInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["CallSavedWorkflowInvocation"] | components["schemas"]["CannyEdgeDetectionInvocation"] | components["schemas"]["CanvasOutputInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["CanvasV2MaskAndCropInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["CogView4DenoiseInvocation"] | components["schemas"]["CogView4ImageToLatentsInvocation"] | components["schemas"]["CogView4LatentsToImageInvocation"] | components["schemas"]["CogView4ModelLoaderInvocation"] | components["schemas"]["CogView4TextEncoderInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ColorMapInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ContentShuffleInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["CropImageToBoundingBoxInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["DWOpenposeDetectionInvocation"] | components["schemas"]["DecodeInvisibleWatermarkInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["DenoiseLatentsMetaInvocation"] | components["schemas"]["DepthAnythingDepthEstimationInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ExpandMaskWithFadeInvocation"] | components["schemas"]["FLUXLoRACollectionLoader"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["FloatBatchInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["FloatGenerator"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["Flux2DenoiseInvocation"] | components["schemas"]["Flux2KleinLoRACollectionLoader"] | components["schemas"]["Flux2KleinLoRALoaderInvocation"] | components["schemas"]["Flux2KleinModelLoaderInvocation"] | components["schemas"]["Flux2KleinTextEncoderInvocation"] | components["schemas"]["Flux2VaeDecodeInvocation"] | components["schemas"]["Flux2VaeEncodeInvocation"] | components["schemas"]["FluxControlLoRALoaderInvocation"] | components["schemas"]["FluxControlNetInvocation"] | components["schemas"]["FluxDenoiseInvocation"] | components["schemas"]["FluxDenoiseLatentsMetaInvocation"] | components["schemas"]["FluxFillInvocation"] | components["schemas"]["FluxIPAdapterInvocation"] | components["schemas"]["FluxKontextConcatenateImagesInvocation"] | components["schemas"]["FluxKontextInvocation"] | components["schemas"]["FluxLoRALoaderInvocation"] | components["schemas"]["FluxModelLoaderInvocation"] | components["schemas"]["FluxReduxInvocation"] | components["schemas"]["FluxTextEncoderInvocation"] | components["schemas"]["FluxVaeDecodeInvocation"] | components["schemas"]["FluxVaeEncodeInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["GeminiImageGenerationInvocation"] | components["schemas"]["GetMaskBoundingBoxInvocation"] | components["schemas"]["GroundingDinoInvocation"] | components["schemas"]["HEDEdgeDetectionInvocation"] | components["schemas"]["HeuristicResizeInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["IfInvocation"] | components["schemas"]["ImageBatchInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImageGenerator"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageMaskToTensorInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageNoiseInvocation"] | components["schemas"]["ImagePanelLayoutInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["IntegerBatchInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["IntegerGenerator"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["InvertTensorMaskInvocation"] | components["schemas"]["InvokeAdjustImageHuePlusInvocation"] | components["schemas"]["InvokeEquivalentAchromaticLightnessInvocation"] | components["schemas"]["InvokeImageBlendInvocation"] | components["schemas"]["InvokeImageCompositorInvocation"] | components["schemas"]["InvokeImageDilateOrErodeInvocation"] | components["schemas"]["InvokeImageEnhanceInvocation"] | components["schemas"]["InvokeImageValueThresholdsInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["LineartAnimeEdgeDetectionInvocation"] | components["schemas"]["LineartEdgeDetectionInvocation"] | components["schemas"]["LlavaOnevisionVllmInvocation"] | components["schemas"]["LoRACollectionLoader"] | components["schemas"]["LoRALoaderInvocation"] | components["schemas"]["LoRASelectorInvocation"] | components["schemas"]["MLSDDetectionInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["MaskFromIDInvocation"] | components["schemas"]["MaskTensorToImageInvocation"] | components["schemas"]["MediaPipeFaceDetectionInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["MetadataFieldExtractorInvocation"] | components["schemas"]["MetadataFromImageInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MetadataItemLinkedInvocation"] | components["schemas"]["MetadataToBoolCollectionInvocation"] | components["schemas"]["MetadataToBoolInvocation"] | components["schemas"]["MetadataToControlnetsInvocation"] | components["schemas"]["MetadataToFloatCollectionInvocation"] | components["schemas"]["MetadataToFloatInvocation"] | components["schemas"]["MetadataToIPAdaptersInvocation"] | components["schemas"]["MetadataToIntegerCollectionInvocation"] | components["schemas"]["MetadataToIntegerInvocation"] | components["schemas"]["MetadataToLorasCollectionInvocation"] | components["schemas"]["MetadataToLorasInvocation"] | components["schemas"]["MetadataToModelInvocation"] | components["schemas"]["MetadataToSDXLLorasInvocation"] | components["schemas"]["MetadataToSDXLModelInvocation"] | components["schemas"]["MetadataToSchedulerInvocation"] | components["schemas"]["MetadataToStringCollectionInvocation"] | components["schemas"]["MetadataToStringInvocation"] | components["schemas"]["MetadataToT2IAdaptersInvocation"] | components["schemas"]["MetadataToVAEInvocation"] | components["schemas"]["ModelIdentifierInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["NormalMapInvocation"] | components["schemas"]["OklabUnsharpMaskInvocation"] | components["schemas"]["OklchImageHueAdjustmentInvocation"] | components["schemas"]["OpenAIImageGenerationInvocation"] | components["schemas"]["PBRMapsInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["PasteImageIntoBoundingBoxInvocation"] | components["schemas"]["PiDiNetEdgeDetectionInvocation"] | components["schemas"]["PromptTemplateInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["QwenImageDenoiseInvocation"] | components["schemas"]["QwenImageImageToLatentsInvocation"] | components["schemas"]["QwenImageLatentsToImageInvocation"] | components["schemas"]["QwenImageLoRACollectionLoader"] | components["schemas"]["QwenImageLoRALoaderInvocation"] | components["schemas"]["QwenImageModelLoaderInvocation"] | components["schemas"]["QwenImageTextEncoderInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RectangleMaskInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["SD3DenoiseInvocation"] | components["schemas"]["SD3ImageToLatentsInvocation"] | components["schemas"]["SD3LatentsToImageInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["SDXLLoRACollectionLoader"] | components["schemas"]["SDXLLoRALoaderInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["SaveImageToFileInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["Sd3ModelLoaderInvocation"] | components["schemas"]["Sd3TextEncoderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["SeedreamImageGenerationInvocation"] | components["schemas"]["SegmentAnythingInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["SpandrelImageToImageAutoscaleInvocation"] | components["schemas"]["SpandrelImageToImageInvocation"] | components["schemas"]["StringBatchInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["StringGenerator"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["TextLLMInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["TiledMultiDiffusionDenoiseLatents"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["VAELoaderInvocation"] | components["schemas"]["WorkflowReturnGetInvocation"] | components["schemas"]["WorkflowReturnInvocation"] | components["schemas"]["WorkflowReturnValueInvocation"] | components["schemas"]["ZImageControlInvocation"] | components["schemas"]["ZImageDenoiseInvocation"] | components["schemas"]["ZImageDenoiseMetaInvocation"] | components["schemas"]["ZImageImageToLatentsInvocation"] | components["schemas"]["ZImageLatentsToImageInvocation"] | components["schemas"]["ZImageLoRACollectionLoader"] | components["schemas"]["ZImageLoRALoaderInvocation"] | components["schemas"]["ZImageModelLoaderInvocation"] | components["schemas"]["ZImageSeedVarianceEnhancerInvocation"] | components["schemas"]["ZImageTextEncoderInvocation"]; + invocation: components["schemas"]["AddInvocation"] | components["schemas"]["AlibabaCloudImageGenerationInvocation"] | components["schemas"]["AlphaMaskToTensorInvocation"] | components["schemas"]["AnimaDenoiseInvocation"] | components["schemas"]["AnimaImageToLatentsInvocation"] | components["schemas"]["AnimaLLLiteInvocation"] | components["schemas"]["AnimaLatentsToImageInvocation"] | components["schemas"]["AnimaLoRACollectionLoader"] | components["schemas"]["AnimaLoRALoaderInvocation"] | components["schemas"]["AnimaModelLoaderInvocation"] | components["schemas"]["AnimaTextEncoderInvocation"] | components["schemas"]["ApplyMaskTensorToImageInvocation"] | components["schemas"]["ApplyMaskToImageInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["BoundingBoxInvocation"] | components["schemas"]["CLIPSkipInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["CallSavedWorkflowInvocation"] | components["schemas"]["CannyEdgeDetectionInvocation"] | components["schemas"]["CanvasOutputInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["CanvasV2MaskAndCropInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["CogView4DenoiseInvocation"] | components["schemas"]["CogView4ImageToLatentsInvocation"] | components["schemas"]["CogView4LatentsToImageInvocation"] | components["schemas"]["CogView4ModelLoaderInvocation"] | components["schemas"]["CogView4TextEncoderInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ColorMapInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ContentShuffleInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["CropImageToBoundingBoxInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["DWOpenposeDetectionInvocation"] | components["schemas"]["DecodeInvisibleWatermarkInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["DenoiseLatentsMetaInvocation"] | components["schemas"]["DepthAnythingDepthEstimationInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ExpandMaskWithFadeInvocation"] | components["schemas"]["FLUXLoRACollectionLoader"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["FloatBatchInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["FloatGenerator"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["Flux2DenoiseInvocation"] | components["schemas"]["Flux2KleinLoRACollectionLoader"] | components["schemas"]["Flux2KleinLoRALoaderInvocation"] | components["schemas"]["Flux2KleinModelLoaderInvocation"] | components["schemas"]["Flux2KleinTextEncoderInvocation"] | components["schemas"]["Flux2VaeDecodeInvocation"] | components["schemas"]["Flux2VaeEncodeInvocation"] | components["schemas"]["FluxControlLoRALoaderInvocation"] | components["schemas"]["FluxControlNetInvocation"] | components["schemas"]["FluxDenoiseInvocation"] | components["schemas"]["FluxDenoiseLatentsMetaInvocation"] | components["schemas"]["FluxFillInvocation"] | components["schemas"]["FluxIPAdapterInvocation"] | components["schemas"]["FluxKontextConcatenateImagesInvocation"] | components["schemas"]["FluxKontextInvocation"] | components["schemas"]["FluxLoRALoaderInvocation"] | components["schemas"]["FluxModelLoaderInvocation"] | components["schemas"]["FluxReduxInvocation"] | components["schemas"]["FluxTextEncoderInvocation"] | components["schemas"]["FluxVaeDecodeInvocation"] | components["schemas"]["FluxVaeEncodeInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["GeminiImageGenerationInvocation"] | components["schemas"]["GetMaskBoundingBoxInvocation"] | components["schemas"]["GroundingDinoInvocation"] | components["schemas"]["HEDEdgeDetectionInvocation"] | components["schemas"]["HeuristicResizeInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["Ideogram4CaptionBuilderInvocation"] | components["schemas"]["Ideogram4DenoiseInvocation"] | components["schemas"]["Ideogram4LatentsToImageInvocation"] | components["schemas"]["Ideogram4ModelLoaderInvocation"] | components["schemas"]["Ideogram4TextEncoderInvocation"] | components["schemas"]["IfInvocation"] | components["schemas"]["ImageBatchInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImageGenerator"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageMaskToTensorInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageNoiseInvocation"] | components["schemas"]["ImagePanelLayoutInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["IntegerBatchInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["IntegerGenerator"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["InvertTensorMaskInvocation"] | components["schemas"]["InvokeAdjustImageHuePlusInvocation"] | components["schemas"]["InvokeEquivalentAchromaticLightnessInvocation"] | components["schemas"]["InvokeImageBlendInvocation"] | components["schemas"]["InvokeImageCompositorInvocation"] | components["schemas"]["InvokeImageDilateOrErodeInvocation"] | components["schemas"]["InvokeImageEnhanceInvocation"] | components["schemas"]["InvokeImageValueThresholdsInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["LineartAnimeEdgeDetectionInvocation"] | components["schemas"]["LineartEdgeDetectionInvocation"] | components["schemas"]["LlavaOnevisionVllmInvocation"] | components["schemas"]["LoRACollectionLoader"] | components["schemas"]["LoRALoaderInvocation"] | components["schemas"]["LoRASelectorInvocation"] | components["schemas"]["MLSDDetectionInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["MaskFromIDInvocation"] | components["schemas"]["MaskTensorToImageInvocation"] | components["schemas"]["MediaPipeFaceDetectionInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["MetadataFieldExtractorInvocation"] | components["schemas"]["MetadataFromImageInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MetadataItemLinkedInvocation"] | components["schemas"]["MetadataToBoolCollectionInvocation"] | components["schemas"]["MetadataToBoolInvocation"] | components["schemas"]["MetadataToControlnetsInvocation"] | components["schemas"]["MetadataToFloatCollectionInvocation"] | components["schemas"]["MetadataToFloatInvocation"] | components["schemas"]["MetadataToIPAdaptersInvocation"] | components["schemas"]["MetadataToIntegerCollectionInvocation"] | components["schemas"]["MetadataToIntegerInvocation"] | components["schemas"]["MetadataToLorasCollectionInvocation"] | components["schemas"]["MetadataToLorasInvocation"] | components["schemas"]["MetadataToModelInvocation"] | components["schemas"]["MetadataToSDXLLorasInvocation"] | components["schemas"]["MetadataToSDXLModelInvocation"] | components["schemas"]["MetadataToSchedulerInvocation"] | components["schemas"]["MetadataToStringCollectionInvocation"] | components["schemas"]["MetadataToStringInvocation"] | components["schemas"]["MetadataToT2IAdaptersInvocation"] | components["schemas"]["MetadataToVAEInvocation"] | components["schemas"]["ModelIdentifierInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["NormalMapInvocation"] | components["schemas"]["OklabUnsharpMaskInvocation"] | components["schemas"]["OklchImageHueAdjustmentInvocation"] | components["schemas"]["OpenAIImageGenerationInvocation"] | components["schemas"]["PBRMapsInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["PasteImageIntoBoundingBoxInvocation"] | components["schemas"]["PiDiNetEdgeDetectionInvocation"] | components["schemas"]["PromptTemplateInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["QwenImageDenoiseInvocation"] | components["schemas"]["QwenImageImageToLatentsInvocation"] | components["schemas"]["QwenImageLatentsToImageInvocation"] | components["schemas"]["QwenImageLoRACollectionLoader"] | components["schemas"]["QwenImageLoRALoaderInvocation"] | components["schemas"]["QwenImageModelLoaderInvocation"] | components["schemas"]["QwenImageTextEncoderInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RectangleMaskInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["SD3DenoiseInvocation"] | components["schemas"]["SD3ImageToLatentsInvocation"] | components["schemas"]["SD3LatentsToImageInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["SDXLLoRACollectionLoader"] | components["schemas"]["SDXLLoRALoaderInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["SaveImageToFileInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["Sd3ModelLoaderInvocation"] | components["schemas"]["Sd3TextEncoderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["SeedreamImageGenerationInvocation"] | components["schemas"]["SegmentAnythingInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["SpandrelImageToImageAutoscaleInvocation"] | components["schemas"]["SpandrelImageToImageInvocation"] | components["schemas"]["StringBatchInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["StringGenerator"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["TextLLMInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["TiledMultiDiffusionDenoiseLatents"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["VAELoaderInvocation"] | components["schemas"]["WorkflowReturnGetInvocation"] | components["schemas"]["WorkflowReturnInvocation"] | components["schemas"]["WorkflowReturnValueInvocation"] | components["schemas"]["ZImageControlInvocation"] | components["schemas"]["ZImageDenoiseInvocation"] | components["schemas"]["ZImageDenoiseMetaInvocation"] | components["schemas"]["ZImageImageToLatentsInvocation"] | components["schemas"]["ZImageLatentsToImageInvocation"] | components["schemas"]["ZImageLoRACollectionLoader"] | components["schemas"]["ZImageLoRALoaderInvocation"] | components["schemas"]["ZImageModelLoaderInvocation"] | components["schemas"]["ZImageSeedVarianceEnhancerInvocation"] | components["schemas"]["ZImageTextEncoderInvocation"]; /** * Invocation Source Id * @description The ID of the prepared invocation's source node @@ -16093,7 +16435,7 @@ export type components = { * Result * @description The result of the invocation */ - result: components["schemas"]["AnimaConditioningOutput"] | components["schemas"]["AnimaLLLiteOutput"] | components["schemas"]["AnimaLoRALoaderOutput"] | components["schemas"]["AnimaModelLoaderOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["BoundingBoxCollectionOutput"] | components["schemas"]["BoundingBoxOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["CLIPSkipInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["CogView4ConditioningOutput"] | components["schemas"]["CogView4ModelLoaderOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["FloatGeneratorOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["Flux2KleinLoRALoaderOutput"] | components["schemas"]["Flux2KleinModelLoaderOutput"] | components["schemas"]["FluxConditioningCollectionOutput"] | components["schemas"]["FluxConditioningOutput"] | components["schemas"]["FluxControlLoRALoaderOutput"] | components["schemas"]["FluxControlNetOutput"] | components["schemas"]["FluxFillOutput"] | components["schemas"]["FluxKontextOutput"] | components["schemas"]["FluxLoRALoaderOutput"] | components["schemas"]["FluxModelLoaderOutput"] | components["schemas"]["FluxReduxOutput"] | components["schemas"]["GradientMaskOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["IfInvocationOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["ImageGeneratorOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["ImagePanelCoordinateOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["IntegerGeneratorOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["LatentsMetaOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["LoRALoaderOutput"] | components["schemas"]["LoRASelectorOutput"] | components["schemas"]["MDControlListOutput"] | components["schemas"]["MDIPAdapterListOutput"] | components["schemas"]["MDT2IAdapterListOutput"] | components["schemas"]["MaskOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["MetadataToLorasCollectionOutput"] | components["schemas"]["MetadataToModelOutput"] | components["schemas"]["MetadataToSDXLModelOutput"] | components["schemas"]["ModelIdentifierOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["PBRMapsOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["PromptTemplateOutput"] | components["schemas"]["QwenImageConditioningOutput"] | components["schemas"]["QwenImageLoRALoaderOutput"] | components["schemas"]["QwenImageModelLoaderOutput"] | components["schemas"]["SD3ConditioningOutput"] | components["schemas"]["SDXLLoRALoaderOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["Sd3ModelLoaderOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["String2Output"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["StringGeneratorOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["WorkflowReturnGetOutput"] | components["schemas"]["WorkflowReturnOutput"] | components["schemas"]["WorkflowReturnValueOutput"] | components["schemas"]["ZImageConditioningOutput"] | components["schemas"]["ZImageControlOutput"] | components["schemas"]["ZImageLoRALoaderOutput"] | components["schemas"]["ZImageModelLoaderOutput"]; + result: components["schemas"]["AnimaConditioningOutput"] | components["schemas"]["AnimaLLLiteOutput"] | components["schemas"]["AnimaLoRALoaderOutput"] | components["schemas"]["AnimaModelLoaderOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["BoundingBoxCollectionOutput"] | components["schemas"]["BoundingBoxOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["CLIPSkipInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["CogView4ConditioningOutput"] | components["schemas"]["CogView4ModelLoaderOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["FloatGeneratorOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["Flux2KleinLoRALoaderOutput"] | components["schemas"]["Flux2KleinModelLoaderOutput"] | components["schemas"]["FluxConditioningCollectionOutput"] | components["schemas"]["FluxConditioningOutput"] | components["schemas"]["FluxControlLoRALoaderOutput"] | components["schemas"]["FluxControlNetOutput"] | components["schemas"]["FluxFillOutput"] | components["schemas"]["FluxKontextOutput"] | components["schemas"]["FluxLoRALoaderOutput"] | components["schemas"]["FluxModelLoaderOutput"] | components["schemas"]["FluxReduxOutput"] | components["schemas"]["GradientMaskOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["Ideogram4ConditioningOutput"] | components["schemas"]["Ideogram4ModelLoaderOutput"] | components["schemas"]["IfInvocationOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["ImageGeneratorOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["ImagePanelCoordinateOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["IntegerGeneratorOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["LatentsMetaOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["LoRALoaderOutput"] | components["schemas"]["LoRASelectorOutput"] | components["schemas"]["MDControlListOutput"] | components["schemas"]["MDIPAdapterListOutput"] | components["schemas"]["MDT2IAdapterListOutput"] | components["schemas"]["MaskOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["MetadataToLorasCollectionOutput"] | components["schemas"]["MetadataToModelOutput"] | components["schemas"]["MetadataToSDXLModelOutput"] | components["schemas"]["ModelIdentifierOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["PBRMapsOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["PromptTemplateOutput"] | components["schemas"]["QwenImageConditioningOutput"] | components["schemas"]["QwenImageLoRALoaderOutput"] | components["schemas"]["QwenImageModelLoaderOutput"] | components["schemas"]["SD3ConditioningOutput"] | components["schemas"]["SDXLLoRALoaderOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["Sd3ModelLoaderOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["String2Output"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["StringGeneratorOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["WorkflowReturnGetOutput"] | components["schemas"]["WorkflowReturnOutput"] | components["schemas"]["WorkflowReturnValueOutput"] | components["schemas"]["ZImageConditioningOutput"] | components["schemas"]["ZImageControlOutput"] | components["schemas"]["ZImageLoRALoaderOutput"] | components["schemas"]["ZImageModelLoaderOutput"]; }; /** * InvocationErrorEvent @@ -16147,7 +16489,7 @@ export type components = { * Invocation * @description The ID of the invocation */ - invocation: components["schemas"]["AddInvocation"] | components["schemas"]["AlibabaCloudImageGenerationInvocation"] | components["schemas"]["AlphaMaskToTensorInvocation"] | components["schemas"]["AnimaDenoiseInvocation"] | components["schemas"]["AnimaImageToLatentsInvocation"] | components["schemas"]["AnimaLLLiteInvocation"] | components["schemas"]["AnimaLatentsToImageInvocation"] | components["schemas"]["AnimaLoRACollectionLoader"] | components["schemas"]["AnimaLoRALoaderInvocation"] | components["schemas"]["AnimaModelLoaderInvocation"] | components["schemas"]["AnimaTextEncoderInvocation"] | components["schemas"]["ApplyMaskTensorToImageInvocation"] | components["schemas"]["ApplyMaskToImageInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["BoundingBoxInvocation"] | components["schemas"]["CLIPSkipInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["CallSavedWorkflowInvocation"] | components["schemas"]["CannyEdgeDetectionInvocation"] | components["schemas"]["CanvasOutputInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["CanvasV2MaskAndCropInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["CogView4DenoiseInvocation"] | components["schemas"]["CogView4ImageToLatentsInvocation"] | components["schemas"]["CogView4LatentsToImageInvocation"] | components["schemas"]["CogView4ModelLoaderInvocation"] | components["schemas"]["CogView4TextEncoderInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ColorMapInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ContentShuffleInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["CropImageToBoundingBoxInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["DWOpenposeDetectionInvocation"] | components["schemas"]["DecodeInvisibleWatermarkInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["DenoiseLatentsMetaInvocation"] | components["schemas"]["DepthAnythingDepthEstimationInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ExpandMaskWithFadeInvocation"] | components["schemas"]["FLUXLoRACollectionLoader"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["FloatBatchInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["FloatGenerator"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["Flux2DenoiseInvocation"] | components["schemas"]["Flux2KleinLoRACollectionLoader"] | components["schemas"]["Flux2KleinLoRALoaderInvocation"] | components["schemas"]["Flux2KleinModelLoaderInvocation"] | components["schemas"]["Flux2KleinTextEncoderInvocation"] | components["schemas"]["Flux2VaeDecodeInvocation"] | components["schemas"]["Flux2VaeEncodeInvocation"] | components["schemas"]["FluxControlLoRALoaderInvocation"] | components["schemas"]["FluxControlNetInvocation"] | components["schemas"]["FluxDenoiseInvocation"] | components["schemas"]["FluxDenoiseLatentsMetaInvocation"] | components["schemas"]["FluxFillInvocation"] | components["schemas"]["FluxIPAdapterInvocation"] | components["schemas"]["FluxKontextConcatenateImagesInvocation"] | components["schemas"]["FluxKontextInvocation"] | components["schemas"]["FluxLoRALoaderInvocation"] | components["schemas"]["FluxModelLoaderInvocation"] | components["schemas"]["FluxReduxInvocation"] | components["schemas"]["FluxTextEncoderInvocation"] | components["schemas"]["FluxVaeDecodeInvocation"] | components["schemas"]["FluxVaeEncodeInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["GeminiImageGenerationInvocation"] | components["schemas"]["GetMaskBoundingBoxInvocation"] | components["schemas"]["GroundingDinoInvocation"] | components["schemas"]["HEDEdgeDetectionInvocation"] | components["schemas"]["HeuristicResizeInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["IfInvocation"] | components["schemas"]["ImageBatchInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImageGenerator"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageMaskToTensorInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageNoiseInvocation"] | components["schemas"]["ImagePanelLayoutInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["IntegerBatchInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["IntegerGenerator"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["InvertTensorMaskInvocation"] | components["schemas"]["InvokeAdjustImageHuePlusInvocation"] | components["schemas"]["InvokeEquivalentAchromaticLightnessInvocation"] | components["schemas"]["InvokeImageBlendInvocation"] | components["schemas"]["InvokeImageCompositorInvocation"] | components["schemas"]["InvokeImageDilateOrErodeInvocation"] | components["schemas"]["InvokeImageEnhanceInvocation"] | components["schemas"]["InvokeImageValueThresholdsInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["LineartAnimeEdgeDetectionInvocation"] | components["schemas"]["LineartEdgeDetectionInvocation"] | components["schemas"]["LlavaOnevisionVllmInvocation"] | components["schemas"]["LoRACollectionLoader"] | components["schemas"]["LoRALoaderInvocation"] | components["schemas"]["LoRASelectorInvocation"] | components["schemas"]["MLSDDetectionInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["MaskFromIDInvocation"] | components["schemas"]["MaskTensorToImageInvocation"] | components["schemas"]["MediaPipeFaceDetectionInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["MetadataFieldExtractorInvocation"] | components["schemas"]["MetadataFromImageInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MetadataItemLinkedInvocation"] | components["schemas"]["MetadataToBoolCollectionInvocation"] | components["schemas"]["MetadataToBoolInvocation"] | components["schemas"]["MetadataToControlnetsInvocation"] | components["schemas"]["MetadataToFloatCollectionInvocation"] | components["schemas"]["MetadataToFloatInvocation"] | components["schemas"]["MetadataToIPAdaptersInvocation"] | components["schemas"]["MetadataToIntegerCollectionInvocation"] | components["schemas"]["MetadataToIntegerInvocation"] | components["schemas"]["MetadataToLorasCollectionInvocation"] | components["schemas"]["MetadataToLorasInvocation"] | components["schemas"]["MetadataToModelInvocation"] | components["schemas"]["MetadataToSDXLLorasInvocation"] | components["schemas"]["MetadataToSDXLModelInvocation"] | components["schemas"]["MetadataToSchedulerInvocation"] | components["schemas"]["MetadataToStringCollectionInvocation"] | components["schemas"]["MetadataToStringInvocation"] | components["schemas"]["MetadataToT2IAdaptersInvocation"] | components["schemas"]["MetadataToVAEInvocation"] | components["schemas"]["ModelIdentifierInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["NormalMapInvocation"] | components["schemas"]["OklabUnsharpMaskInvocation"] | components["schemas"]["OklchImageHueAdjustmentInvocation"] | components["schemas"]["OpenAIImageGenerationInvocation"] | components["schemas"]["PBRMapsInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["PasteImageIntoBoundingBoxInvocation"] | components["schemas"]["PiDiNetEdgeDetectionInvocation"] | components["schemas"]["PromptTemplateInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["QwenImageDenoiseInvocation"] | components["schemas"]["QwenImageImageToLatentsInvocation"] | components["schemas"]["QwenImageLatentsToImageInvocation"] | components["schemas"]["QwenImageLoRACollectionLoader"] | components["schemas"]["QwenImageLoRALoaderInvocation"] | components["schemas"]["QwenImageModelLoaderInvocation"] | components["schemas"]["QwenImageTextEncoderInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RectangleMaskInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["SD3DenoiseInvocation"] | components["schemas"]["SD3ImageToLatentsInvocation"] | components["schemas"]["SD3LatentsToImageInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["SDXLLoRACollectionLoader"] | components["schemas"]["SDXLLoRALoaderInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["SaveImageToFileInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["Sd3ModelLoaderInvocation"] | components["schemas"]["Sd3TextEncoderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["SeedreamImageGenerationInvocation"] | components["schemas"]["SegmentAnythingInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["SpandrelImageToImageAutoscaleInvocation"] | components["schemas"]["SpandrelImageToImageInvocation"] | components["schemas"]["StringBatchInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["StringGenerator"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["TextLLMInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["TiledMultiDiffusionDenoiseLatents"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["VAELoaderInvocation"] | components["schemas"]["WorkflowReturnGetInvocation"] | components["schemas"]["WorkflowReturnInvocation"] | components["schemas"]["WorkflowReturnValueInvocation"] | components["schemas"]["ZImageControlInvocation"] | components["schemas"]["ZImageDenoiseInvocation"] | components["schemas"]["ZImageDenoiseMetaInvocation"] | components["schemas"]["ZImageImageToLatentsInvocation"] | components["schemas"]["ZImageLatentsToImageInvocation"] | components["schemas"]["ZImageLoRACollectionLoader"] | components["schemas"]["ZImageLoRALoaderInvocation"] | components["schemas"]["ZImageModelLoaderInvocation"] | components["schemas"]["ZImageSeedVarianceEnhancerInvocation"] | components["schemas"]["ZImageTextEncoderInvocation"]; + invocation: components["schemas"]["AddInvocation"] | components["schemas"]["AlibabaCloudImageGenerationInvocation"] | components["schemas"]["AlphaMaskToTensorInvocation"] | components["schemas"]["AnimaDenoiseInvocation"] | components["schemas"]["AnimaImageToLatentsInvocation"] | components["schemas"]["AnimaLLLiteInvocation"] | components["schemas"]["AnimaLatentsToImageInvocation"] | components["schemas"]["AnimaLoRACollectionLoader"] | components["schemas"]["AnimaLoRALoaderInvocation"] | components["schemas"]["AnimaModelLoaderInvocation"] | components["schemas"]["AnimaTextEncoderInvocation"] | components["schemas"]["ApplyMaskTensorToImageInvocation"] | components["schemas"]["ApplyMaskToImageInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["BoundingBoxInvocation"] | components["schemas"]["CLIPSkipInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["CallSavedWorkflowInvocation"] | components["schemas"]["CannyEdgeDetectionInvocation"] | components["schemas"]["CanvasOutputInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["CanvasV2MaskAndCropInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["CogView4DenoiseInvocation"] | components["schemas"]["CogView4ImageToLatentsInvocation"] | components["schemas"]["CogView4LatentsToImageInvocation"] | components["schemas"]["CogView4ModelLoaderInvocation"] | components["schemas"]["CogView4TextEncoderInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ColorMapInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ContentShuffleInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["CropImageToBoundingBoxInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["DWOpenposeDetectionInvocation"] | components["schemas"]["DecodeInvisibleWatermarkInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["DenoiseLatentsMetaInvocation"] | components["schemas"]["DepthAnythingDepthEstimationInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ExpandMaskWithFadeInvocation"] | components["schemas"]["FLUXLoRACollectionLoader"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["FloatBatchInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["FloatGenerator"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["Flux2DenoiseInvocation"] | components["schemas"]["Flux2KleinLoRACollectionLoader"] | components["schemas"]["Flux2KleinLoRALoaderInvocation"] | components["schemas"]["Flux2KleinModelLoaderInvocation"] | components["schemas"]["Flux2KleinTextEncoderInvocation"] | components["schemas"]["Flux2VaeDecodeInvocation"] | components["schemas"]["Flux2VaeEncodeInvocation"] | components["schemas"]["FluxControlLoRALoaderInvocation"] | components["schemas"]["FluxControlNetInvocation"] | components["schemas"]["FluxDenoiseInvocation"] | components["schemas"]["FluxDenoiseLatentsMetaInvocation"] | components["schemas"]["FluxFillInvocation"] | components["schemas"]["FluxIPAdapterInvocation"] | components["schemas"]["FluxKontextConcatenateImagesInvocation"] | components["schemas"]["FluxKontextInvocation"] | components["schemas"]["FluxLoRALoaderInvocation"] | components["schemas"]["FluxModelLoaderInvocation"] | components["schemas"]["FluxReduxInvocation"] | components["schemas"]["FluxTextEncoderInvocation"] | components["schemas"]["FluxVaeDecodeInvocation"] | components["schemas"]["FluxVaeEncodeInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["GeminiImageGenerationInvocation"] | components["schemas"]["GetMaskBoundingBoxInvocation"] | components["schemas"]["GroundingDinoInvocation"] | components["schemas"]["HEDEdgeDetectionInvocation"] | components["schemas"]["HeuristicResizeInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["Ideogram4CaptionBuilderInvocation"] | components["schemas"]["Ideogram4DenoiseInvocation"] | components["schemas"]["Ideogram4LatentsToImageInvocation"] | components["schemas"]["Ideogram4ModelLoaderInvocation"] | components["schemas"]["Ideogram4TextEncoderInvocation"] | components["schemas"]["IfInvocation"] | components["schemas"]["ImageBatchInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImageGenerator"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageMaskToTensorInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageNoiseInvocation"] | components["schemas"]["ImagePanelLayoutInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["IntegerBatchInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["IntegerGenerator"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["InvertTensorMaskInvocation"] | components["schemas"]["InvokeAdjustImageHuePlusInvocation"] | components["schemas"]["InvokeEquivalentAchromaticLightnessInvocation"] | components["schemas"]["InvokeImageBlendInvocation"] | components["schemas"]["InvokeImageCompositorInvocation"] | components["schemas"]["InvokeImageDilateOrErodeInvocation"] | components["schemas"]["InvokeImageEnhanceInvocation"] | components["schemas"]["InvokeImageValueThresholdsInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["LineartAnimeEdgeDetectionInvocation"] | components["schemas"]["LineartEdgeDetectionInvocation"] | components["schemas"]["LlavaOnevisionVllmInvocation"] | components["schemas"]["LoRACollectionLoader"] | components["schemas"]["LoRALoaderInvocation"] | components["schemas"]["LoRASelectorInvocation"] | components["schemas"]["MLSDDetectionInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["MaskFromIDInvocation"] | components["schemas"]["MaskTensorToImageInvocation"] | components["schemas"]["MediaPipeFaceDetectionInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["MetadataFieldExtractorInvocation"] | components["schemas"]["MetadataFromImageInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MetadataItemLinkedInvocation"] | components["schemas"]["MetadataToBoolCollectionInvocation"] | components["schemas"]["MetadataToBoolInvocation"] | components["schemas"]["MetadataToControlnetsInvocation"] | components["schemas"]["MetadataToFloatCollectionInvocation"] | components["schemas"]["MetadataToFloatInvocation"] | components["schemas"]["MetadataToIPAdaptersInvocation"] | components["schemas"]["MetadataToIntegerCollectionInvocation"] | components["schemas"]["MetadataToIntegerInvocation"] | components["schemas"]["MetadataToLorasCollectionInvocation"] | components["schemas"]["MetadataToLorasInvocation"] | components["schemas"]["MetadataToModelInvocation"] | components["schemas"]["MetadataToSDXLLorasInvocation"] | components["schemas"]["MetadataToSDXLModelInvocation"] | components["schemas"]["MetadataToSchedulerInvocation"] | components["schemas"]["MetadataToStringCollectionInvocation"] | components["schemas"]["MetadataToStringInvocation"] | components["schemas"]["MetadataToT2IAdaptersInvocation"] | components["schemas"]["MetadataToVAEInvocation"] | components["schemas"]["ModelIdentifierInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["NormalMapInvocation"] | components["schemas"]["OklabUnsharpMaskInvocation"] | components["schemas"]["OklchImageHueAdjustmentInvocation"] | components["schemas"]["OpenAIImageGenerationInvocation"] | components["schemas"]["PBRMapsInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["PasteImageIntoBoundingBoxInvocation"] | components["schemas"]["PiDiNetEdgeDetectionInvocation"] | components["schemas"]["PromptTemplateInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["QwenImageDenoiseInvocation"] | components["schemas"]["QwenImageImageToLatentsInvocation"] | components["schemas"]["QwenImageLatentsToImageInvocation"] | components["schemas"]["QwenImageLoRACollectionLoader"] | components["schemas"]["QwenImageLoRALoaderInvocation"] | components["schemas"]["QwenImageModelLoaderInvocation"] | components["schemas"]["QwenImageTextEncoderInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RectangleMaskInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["SD3DenoiseInvocation"] | components["schemas"]["SD3ImageToLatentsInvocation"] | components["schemas"]["SD3LatentsToImageInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["SDXLLoRACollectionLoader"] | components["schemas"]["SDXLLoRALoaderInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["SaveImageToFileInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["Sd3ModelLoaderInvocation"] | components["schemas"]["Sd3TextEncoderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["SeedreamImageGenerationInvocation"] | components["schemas"]["SegmentAnythingInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["SpandrelImageToImageAutoscaleInvocation"] | components["schemas"]["SpandrelImageToImageInvocation"] | components["schemas"]["StringBatchInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["StringGenerator"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["TextLLMInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["TiledMultiDiffusionDenoiseLatents"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["VAELoaderInvocation"] | components["schemas"]["WorkflowReturnGetInvocation"] | components["schemas"]["WorkflowReturnInvocation"] | components["schemas"]["WorkflowReturnValueInvocation"] | components["schemas"]["ZImageControlInvocation"] | components["schemas"]["ZImageDenoiseInvocation"] | components["schemas"]["ZImageDenoiseMetaInvocation"] | components["schemas"]["ZImageImageToLatentsInvocation"] | components["schemas"]["ZImageLatentsToImageInvocation"] | components["schemas"]["ZImageLoRACollectionLoader"] | components["schemas"]["ZImageLoRALoaderInvocation"] | components["schemas"]["ZImageModelLoaderInvocation"] | components["schemas"]["ZImageSeedVarianceEnhancerInvocation"] | components["schemas"]["ZImageTextEncoderInvocation"]; /** * Invocation Source Id * @description The ID of the prepared invocation's source node @@ -16265,6 +16607,11 @@ export type components = { heuristic_resize: components["schemas"]["ImageOutput"]; i2l: components["schemas"]["LatentsOutput"]; ideal_size: components["schemas"]["IdealSizeOutput"]; + ideogram4_caption_builder: components["schemas"]["StringOutput"]; + ideogram4_denoise: components["schemas"]["LatentsOutput"]; + ideogram4_l2i: components["schemas"]["ImageOutput"]; + ideogram4_model_loader: components["schemas"]["Ideogram4ModelLoaderOutput"]; + ideogram4_text_encoder: components["schemas"]["Ideogram4ConditioningOutput"]; if: components["schemas"]["IfInvocationOutput"]; image: components["schemas"]["ImageOutput"]; image_batch: components["schemas"]["ImageOutput"]; @@ -16483,7 +16830,7 @@ export type components = { * Invocation * @description The ID of the invocation */ - invocation: components["schemas"]["AddInvocation"] | components["schemas"]["AlibabaCloudImageGenerationInvocation"] | components["schemas"]["AlphaMaskToTensorInvocation"] | components["schemas"]["AnimaDenoiseInvocation"] | components["schemas"]["AnimaImageToLatentsInvocation"] | components["schemas"]["AnimaLLLiteInvocation"] | components["schemas"]["AnimaLatentsToImageInvocation"] | components["schemas"]["AnimaLoRACollectionLoader"] | components["schemas"]["AnimaLoRALoaderInvocation"] | components["schemas"]["AnimaModelLoaderInvocation"] | components["schemas"]["AnimaTextEncoderInvocation"] | components["schemas"]["ApplyMaskTensorToImageInvocation"] | components["schemas"]["ApplyMaskToImageInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["BoundingBoxInvocation"] | components["schemas"]["CLIPSkipInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["CallSavedWorkflowInvocation"] | components["schemas"]["CannyEdgeDetectionInvocation"] | components["schemas"]["CanvasOutputInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["CanvasV2MaskAndCropInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["CogView4DenoiseInvocation"] | components["schemas"]["CogView4ImageToLatentsInvocation"] | components["schemas"]["CogView4LatentsToImageInvocation"] | components["schemas"]["CogView4ModelLoaderInvocation"] | components["schemas"]["CogView4TextEncoderInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ColorMapInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ContentShuffleInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["CropImageToBoundingBoxInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["DWOpenposeDetectionInvocation"] | components["schemas"]["DecodeInvisibleWatermarkInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["DenoiseLatentsMetaInvocation"] | components["schemas"]["DepthAnythingDepthEstimationInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ExpandMaskWithFadeInvocation"] | components["schemas"]["FLUXLoRACollectionLoader"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["FloatBatchInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["FloatGenerator"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["Flux2DenoiseInvocation"] | components["schemas"]["Flux2KleinLoRACollectionLoader"] | components["schemas"]["Flux2KleinLoRALoaderInvocation"] | components["schemas"]["Flux2KleinModelLoaderInvocation"] | components["schemas"]["Flux2KleinTextEncoderInvocation"] | components["schemas"]["Flux2VaeDecodeInvocation"] | components["schemas"]["Flux2VaeEncodeInvocation"] | components["schemas"]["FluxControlLoRALoaderInvocation"] | components["schemas"]["FluxControlNetInvocation"] | components["schemas"]["FluxDenoiseInvocation"] | components["schemas"]["FluxDenoiseLatentsMetaInvocation"] | components["schemas"]["FluxFillInvocation"] | components["schemas"]["FluxIPAdapterInvocation"] | components["schemas"]["FluxKontextConcatenateImagesInvocation"] | components["schemas"]["FluxKontextInvocation"] | components["schemas"]["FluxLoRALoaderInvocation"] | components["schemas"]["FluxModelLoaderInvocation"] | components["schemas"]["FluxReduxInvocation"] | components["schemas"]["FluxTextEncoderInvocation"] | components["schemas"]["FluxVaeDecodeInvocation"] | components["schemas"]["FluxVaeEncodeInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["GeminiImageGenerationInvocation"] | components["schemas"]["GetMaskBoundingBoxInvocation"] | components["schemas"]["GroundingDinoInvocation"] | components["schemas"]["HEDEdgeDetectionInvocation"] | components["schemas"]["HeuristicResizeInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["IfInvocation"] | components["schemas"]["ImageBatchInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImageGenerator"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageMaskToTensorInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageNoiseInvocation"] | components["schemas"]["ImagePanelLayoutInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["IntegerBatchInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["IntegerGenerator"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["InvertTensorMaskInvocation"] | components["schemas"]["InvokeAdjustImageHuePlusInvocation"] | components["schemas"]["InvokeEquivalentAchromaticLightnessInvocation"] | components["schemas"]["InvokeImageBlendInvocation"] | components["schemas"]["InvokeImageCompositorInvocation"] | components["schemas"]["InvokeImageDilateOrErodeInvocation"] | components["schemas"]["InvokeImageEnhanceInvocation"] | components["schemas"]["InvokeImageValueThresholdsInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["LineartAnimeEdgeDetectionInvocation"] | components["schemas"]["LineartEdgeDetectionInvocation"] | components["schemas"]["LlavaOnevisionVllmInvocation"] | components["schemas"]["LoRACollectionLoader"] | components["schemas"]["LoRALoaderInvocation"] | components["schemas"]["LoRASelectorInvocation"] | components["schemas"]["MLSDDetectionInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["MaskFromIDInvocation"] | components["schemas"]["MaskTensorToImageInvocation"] | components["schemas"]["MediaPipeFaceDetectionInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["MetadataFieldExtractorInvocation"] | components["schemas"]["MetadataFromImageInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MetadataItemLinkedInvocation"] | components["schemas"]["MetadataToBoolCollectionInvocation"] | components["schemas"]["MetadataToBoolInvocation"] | components["schemas"]["MetadataToControlnetsInvocation"] | components["schemas"]["MetadataToFloatCollectionInvocation"] | components["schemas"]["MetadataToFloatInvocation"] | components["schemas"]["MetadataToIPAdaptersInvocation"] | components["schemas"]["MetadataToIntegerCollectionInvocation"] | components["schemas"]["MetadataToIntegerInvocation"] | components["schemas"]["MetadataToLorasCollectionInvocation"] | components["schemas"]["MetadataToLorasInvocation"] | components["schemas"]["MetadataToModelInvocation"] | components["schemas"]["MetadataToSDXLLorasInvocation"] | components["schemas"]["MetadataToSDXLModelInvocation"] | components["schemas"]["MetadataToSchedulerInvocation"] | components["schemas"]["MetadataToStringCollectionInvocation"] | components["schemas"]["MetadataToStringInvocation"] | components["schemas"]["MetadataToT2IAdaptersInvocation"] | components["schemas"]["MetadataToVAEInvocation"] | components["schemas"]["ModelIdentifierInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["NormalMapInvocation"] | components["schemas"]["OklabUnsharpMaskInvocation"] | components["schemas"]["OklchImageHueAdjustmentInvocation"] | components["schemas"]["OpenAIImageGenerationInvocation"] | components["schemas"]["PBRMapsInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["PasteImageIntoBoundingBoxInvocation"] | components["schemas"]["PiDiNetEdgeDetectionInvocation"] | components["schemas"]["PromptTemplateInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["QwenImageDenoiseInvocation"] | components["schemas"]["QwenImageImageToLatentsInvocation"] | components["schemas"]["QwenImageLatentsToImageInvocation"] | components["schemas"]["QwenImageLoRACollectionLoader"] | components["schemas"]["QwenImageLoRALoaderInvocation"] | components["schemas"]["QwenImageModelLoaderInvocation"] | components["schemas"]["QwenImageTextEncoderInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RectangleMaskInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["SD3DenoiseInvocation"] | components["schemas"]["SD3ImageToLatentsInvocation"] | components["schemas"]["SD3LatentsToImageInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["SDXLLoRACollectionLoader"] | components["schemas"]["SDXLLoRALoaderInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["SaveImageToFileInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["Sd3ModelLoaderInvocation"] | components["schemas"]["Sd3TextEncoderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["SeedreamImageGenerationInvocation"] | components["schemas"]["SegmentAnythingInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["SpandrelImageToImageAutoscaleInvocation"] | components["schemas"]["SpandrelImageToImageInvocation"] | components["schemas"]["StringBatchInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["StringGenerator"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["TextLLMInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["TiledMultiDiffusionDenoiseLatents"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["VAELoaderInvocation"] | components["schemas"]["WorkflowReturnGetInvocation"] | components["schemas"]["WorkflowReturnInvocation"] | components["schemas"]["WorkflowReturnValueInvocation"] | components["schemas"]["ZImageControlInvocation"] | components["schemas"]["ZImageDenoiseInvocation"] | components["schemas"]["ZImageDenoiseMetaInvocation"] | components["schemas"]["ZImageImageToLatentsInvocation"] | components["schemas"]["ZImageLatentsToImageInvocation"] | components["schemas"]["ZImageLoRACollectionLoader"] | components["schemas"]["ZImageLoRALoaderInvocation"] | components["schemas"]["ZImageModelLoaderInvocation"] | components["schemas"]["ZImageSeedVarianceEnhancerInvocation"] | components["schemas"]["ZImageTextEncoderInvocation"]; + invocation: components["schemas"]["AddInvocation"] | components["schemas"]["AlibabaCloudImageGenerationInvocation"] | components["schemas"]["AlphaMaskToTensorInvocation"] | components["schemas"]["AnimaDenoiseInvocation"] | components["schemas"]["AnimaImageToLatentsInvocation"] | components["schemas"]["AnimaLLLiteInvocation"] | components["schemas"]["AnimaLatentsToImageInvocation"] | components["schemas"]["AnimaLoRACollectionLoader"] | components["schemas"]["AnimaLoRALoaderInvocation"] | components["schemas"]["AnimaModelLoaderInvocation"] | components["schemas"]["AnimaTextEncoderInvocation"] | components["schemas"]["ApplyMaskTensorToImageInvocation"] | components["schemas"]["ApplyMaskToImageInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["BoundingBoxInvocation"] | components["schemas"]["CLIPSkipInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["CallSavedWorkflowInvocation"] | components["schemas"]["CannyEdgeDetectionInvocation"] | components["schemas"]["CanvasOutputInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["CanvasV2MaskAndCropInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["CogView4DenoiseInvocation"] | components["schemas"]["CogView4ImageToLatentsInvocation"] | components["schemas"]["CogView4LatentsToImageInvocation"] | components["schemas"]["CogView4ModelLoaderInvocation"] | components["schemas"]["CogView4TextEncoderInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ColorMapInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ContentShuffleInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["CropImageToBoundingBoxInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["DWOpenposeDetectionInvocation"] | components["schemas"]["DecodeInvisibleWatermarkInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["DenoiseLatentsMetaInvocation"] | components["schemas"]["DepthAnythingDepthEstimationInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ExpandMaskWithFadeInvocation"] | components["schemas"]["FLUXLoRACollectionLoader"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["FloatBatchInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["FloatGenerator"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["Flux2DenoiseInvocation"] | components["schemas"]["Flux2KleinLoRACollectionLoader"] | components["schemas"]["Flux2KleinLoRALoaderInvocation"] | components["schemas"]["Flux2KleinModelLoaderInvocation"] | components["schemas"]["Flux2KleinTextEncoderInvocation"] | components["schemas"]["Flux2VaeDecodeInvocation"] | components["schemas"]["Flux2VaeEncodeInvocation"] | components["schemas"]["FluxControlLoRALoaderInvocation"] | components["schemas"]["FluxControlNetInvocation"] | components["schemas"]["FluxDenoiseInvocation"] | components["schemas"]["FluxDenoiseLatentsMetaInvocation"] | components["schemas"]["FluxFillInvocation"] | components["schemas"]["FluxIPAdapterInvocation"] | components["schemas"]["FluxKontextConcatenateImagesInvocation"] | components["schemas"]["FluxKontextInvocation"] | components["schemas"]["FluxLoRALoaderInvocation"] | components["schemas"]["FluxModelLoaderInvocation"] | components["schemas"]["FluxReduxInvocation"] | components["schemas"]["FluxTextEncoderInvocation"] | components["schemas"]["FluxVaeDecodeInvocation"] | components["schemas"]["FluxVaeEncodeInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["GeminiImageGenerationInvocation"] | components["schemas"]["GetMaskBoundingBoxInvocation"] | components["schemas"]["GroundingDinoInvocation"] | components["schemas"]["HEDEdgeDetectionInvocation"] | components["schemas"]["HeuristicResizeInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["Ideogram4CaptionBuilderInvocation"] | components["schemas"]["Ideogram4DenoiseInvocation"] | components["schemas"]["Ideogram4LatentsToImageInvocation"] | components["schemas"]["Ideogram4ModelLoaderInvocation"] | components["schemas"]["Ideogram4TextEncoderInvocation"] | components["schemas"]["IfInvocation"] | components["schemas"]["ImageBatchInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImageGenerator"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageMaskToTensorInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageNoiseInvocation"] | components["schemas"]["ImagePanelLayoutInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["IntegerBatchInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["IntegerGenerator"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["InvertTensorMaskInvocation"] | components["schemas"]["InvokeAdjustImageHuePlusInvocation"] | components["schemas"]["InvokeEquivalentAchromaticLightnessInvocation"] | components["schemas"]["InvokeImageBlendInvocation"] | components["schemas"]["InvokeImageCompositorInvocation"] | components["schemas"]["InvokeImageDilateOrErodeInvocation"] | components["schemas"]["InvokeImageEnhanceInvocation"] | components["schemas"]["InvokeImageValueThresholdsInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["LineartAnimeEdgeDetectionInvocation"] | components["schemas"]["LineartEdgeDetectionInvocation"] | components["schemas"]["LlavaOnevisionVllmInvocation"] | components["schemas"]["LoRACollectionLoader"] | components["schemas"]["LoRALoaderInvocation"] | components["schemas"]["LoRASelectorInvocation"] | components["schemas"]["MLSDDetectionInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["MaskFromIDInvocation"] | components["schemas"]["MaskTensorToImageInvocation"] | components["schemas"]["MediaPipeFaceDetectionInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["MetadataFieldExtractorInvocation"] | components["schemas"]["MetadataFromImageInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MetadataItemLinkedInvocation"] | components["schemas"]["MetadataToBoolCollectionInvocation"] | components["schemas"]["MetadataToBoolInvocation"] | components["schemas"]["MetadataToControlnetsInvocation"] | components["schemas"]["MetadataToFloatCollectionInvocation"] | components["schemas"]["MetadataToFloatInvocation"] | components["schemas"]["MetadataToIPAdaptersInvocation"] | components["schemas"]["MetadataToIntegerCollectionInvocation"] | components["schemas"]["MetadataToIntegerInvocation"] | components["schemas"]["MetadataToLorasCollectionInvocation"] | components["schemas"]["MetadataToLorasInvocation"] | components["schemas"]["MetadataToModelInvocation"] | components["schemas"]["MetadataToSDXLLorasInvocation"] | components["schemas"]["MetadataToSDXLModelInvocation"] | components["schemas"]["MetadataToSchedulerInvocation"] | components["schemas"]["MetadataToStringCollectionInvocation"] | components["schemas"]["MetadataToStringInvocation"] | components["schemas"]["MetadataToT2IAdaptersInvocation"] | components["schemas"]["MetadataToVAEInvocation"] | components["schemas"]["ModelIdentifierInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["NormalMapInvocation"] | components["schemas"]["OklabUnsharpMaskInvocation"] | components["schemas"]["OklchImageHueAdjustmentInvocation"] | components["schemas"]["OpenAIImageGenerationInvocation"] | components["schemas"]["PBRMapsInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["PasteImageIntoBoundingBoxInvocation"] | components["schemas"]["PiDiNetEdgeDetectionInvocation"] | components["schemas"]["PromptTemplateInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["QwenImageDenoiseInvocation"] | components["schemas"]["QwenImageImageToLatentsInvocation"] | components["schemas"]["QwenImageLatentsToImageInvocation"] | components["schemas"]["QwenImageLoRACollectionLoader"] | components["schemas"]["QwenImageLoRALoaderInvocation"] | components["schemas"]["QwenImageModelLoaderInvocation"] | components["schemas"]["QwenImageTextEncoderInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RectangleMaskInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["SD3DenoiseInvocation"] | components["schemas"]["SD3ImageToLatentsInvocation"] | components["schemas"]["SD3LatentsToImageInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["SDXLLoRACollectionLoader"] | components["schemas"]["SDXLLoRALoaderInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["SaveImageToFileInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["Sd3ModelLoaderInvocation"] | components["schemas"]["Sd3TextEncoderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["SeedreamImageGenerationInvocation"] | components["schemas"]["SegmentAnythingInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["SpandrelImageToImageAutoscaleInvocation"] | components["schemas"]["SpandrelImageToImageInvocation"] | components["schemas"]["StringBatchInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["StringGenerator"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["TextLLMInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["TiledMultiDiffusionDenoiseLatents"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["VAELoaderInvocation"] | components["schemas"]["WorkflowReturnGetInvocation"] | components["schemas"]["WorkflowReturnInvocation"] | components["schemas"]["WorkflowReturnValueInvocation"] | components["schemas"]["ZImageControlInvocation"] | components["schemas"]["ZImageDenoiseInvocation"] | components["schemas"]["ZImageDenoiseMetaInvocation"] | components["schemas"]["ZImageImageToLatentsInvocation"] | components["schemas"]["ZImageLatentsToImageInvocation"] | components["schemas"]["ZImageLoRACollectionLoader"] | components["schemas"]["ZImageLoRALoaderInvocation"] | components["schemas"]["ZImageModelLoaderInvocation"] | components["schemas"]["ZImageSeedVarianceEnhancerInvocation"] | components["schemas"]["ZImageTextEncoderInvocation"]; /** * Invocation Source Id * @description The ID of the prepared invocation's source node @@ -16558,7 +16905,7 @@ export type components = { * Invocation * @description The ID of the invocation */ - invocation: components["schemas"]["AddInvocation"] | components["schemas"]["AlibabaCloudImageGenerationInvocation"] | components["schemas"]["AlphaMaskToTensorInvocation"] | components["schemas"]["AnimaDenoiseInvocation"] | components["schemas"]["AnimaImageToLatentsInvocation"] | components["schemas"]["AnimaLLLiteInvocation"] | components["schemas"]["AnimaLatentsToImageInvocation"] | components["schemas"]["AnimaLoRACollectionLoader"] | components["schemas"]["AnimaLoRALoaderInvocation"] | components["schemas"]["AnimaModelLoaderInvocation"] | components["schemas"]["AnimaTextEncoderInvocation"] | components["schemas"]["ApplyMaskTensorToImageInvocation"] | components["schemas"]["ApplyMaskToImageInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["BoundingBoxInvocation"] | components["schemas"]["CLIPSkipInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["CallSavedWorkflowInvocation"] | components["schemas"]["CannyEdgeDetectionInvocation"] | components["schemas"]["CanvasOutputInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["CanvasV2MaskAndCropInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["CogView4DenoiseInvocation"] | components["schemas"]["CogView4ImageToLatentsInvocation"] | components["schemas"]["CogView4LatentsToImageInvocation"] | components["schemas"]["CogView4ModelLoaderInvocation"] | components["schemas"]["CogView4TextEncoderInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ColorMapInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ContentShuffleInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["CropImageToBoundingBoxInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["DWOpenposeDetectionInvocation"] | components["schemas"]["DecodeInvisibleWatermarkInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["DenoiseLatentsMetaInvocation"] | components["schemas"]["DepthAnythingDepthEstimationInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ExpandMaskWithFadeInvocation"] | components["schemas"]["FLUXLoRACollectionLoader"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["FloatBatchInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["FloatGenerator"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["Flux2DenoiseInvocation"] | components["schemas"]["Flux2KleinLoRACollectionLoader"] | components["schemas"]["Flux2KleinLoRALoaderInvocation"] | components["schemas"]["Flux2KleinModelLoaderInvocation"] | components["schemas"]["Flux2KleinTextEncoderInvocation"] | components["schemas"]["Flux2VaeDecodeInvocation"] | components["schemas"]["Flux2VaeEncodeInvocation"] | components["schemas"]["FluxControlLoRALoaderInvocation"] | components["schemas"]["FluxControlNetInvocation"] | components["schemas"]["FluxDenoiseInvocation"] | components["schemas"]["FluxDenoiseLatentsMetaInvocation"] | components["schemas"]["FluxFillInvocation"] | components["schemas"]["FluxIPAdapterInvocation"] | components["schemas"]["FluxKontextConcatenateImagesInvocation"] | components["schemas"]["FluxKontextInvocation"] | components["schemas"]["FluxLoRALoaderInvocation"] | components["schemas"]["FluxModelLoaderInvocation"] | components["schemas"]["FluxReduxInvocation"] | components["schemas"]["FluxTextEncoderInvocation"] | components["schemas"]["FluxVaeDecodeInvocation"] | components["schemas"]["FluxVaeEncodeInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["GeminiImageGenerationInvocation"] | components["schemas"]["GetMaskBoundingBoxInvocation"] | components["schemas"]["GroundingDinoInvocation"] | components["schemas"]["HEDEdgeDetectionInvocation"] | components["schemas"]["HeuristicResizeInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["IfInvocation"] | components["schemas"]["ImageBatchInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImageGenerator"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageMaskToTensorInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageNoiseInvocation"] | components["schemas"]["ImagePanelLayoutInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["IntegerBatchInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["IntegerGenerator"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["InvertTensorMaskInvocation"] | components["schemas"]["InvokeAdjustImageHuePlusInvocation"] | components["schemas"]["InvokeEquivalentAchromaticLightnessInvocation"] | components["schemas"]["InvokeImageBlendInvocation"] | components["schemas"]["InvokeImageCompositorInvocation"] | components["schemas"]["InvokeImageDilateOrErodeInvocation"] | components["schemas"]["InvokeImageEnhanceInvocation"] | components["schemas"]["InvokeImageValueThresholdsInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["LineartAnimeEdgeDetectionInvocation"] | components["schemas"]["LineartEdgeDetectionInvocation"] | components["schemas"]["LlavaOnevisionVllmInvocation"] | components["schemas"]["LoRACollectionLoader"] | components["schemas"]["LoRALoaderInvocation"] | components["schemas"]["LoRASelectorInvocation"] | components["schemas"]["MLSDDetectionInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["MaskFromIDInvocation"] | components["schemas"]["MaskTensorToImageInvocation"] | components["schemas"]["MediaPipeFaceDetectionInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["MetadataFieldExtractorInvocation"] | components["schemas"]["MetadataFromImageInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MetadataItemLinkedInvocation"] | components["schemas"]["MetadataToBoolCollectionInvocation"] | components["schemas"]["MetadataToBoolInvocation"] | components["schemas"]["MetadataToControlnetsInvocation"] | components["schemas"]["MetadataToFloatCollectionInvocation"] | components["schemas"]["MetadataToFloatInvocation"] | components["schemas"]["MetadataToIPAdaptersInvocation"] | components["schemas"]["MetadataToIntegerCollectionInvocation"] | components["schemas"]["MetadataToIntegerInvocation"] | components["schemas"]["MetadataToLorasCollectionInvocation"] | components["schemas"]["MetadataToLorasInvocation"] | components["schemas"]["MetadataToModelInvocation"] | components["schemas"]["MetadataToSDXLLorasInvocation"] | components["schemas"]["MetadataToSDXLModelInvocation"] | components["schemas"]["MetadataToSchedulerInvocation"] | components["schemas"]["MetadataToStringCollectionInvocation"] | components["schemas"]["MetadataToStringInvocation"] | components["schemas"]["MetadataToT2IAdaptersInvocation"] | components["schemas"]["MetadataToVAEInvocation"] | components["schemas"]["ModelIdentifierInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["NormalMapInvocation"] | components["schemas"]["OklabUnsharpMaskInvocation"] | components["schemas"]["OklchImageHueAdjustmentInvocation"] | components["schemas"]["OpenAIImageGenerationInvocation"] | components["schemas"]["PBRMapsInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["PasteImageIntoBoundingBoxInvocation"] | components["schemas"]["PiDiNetEdgeDetectionInvocation"] | components["schemas"]["PromptTemplateInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["QwenImageDenoiseInvocation"] | components["schemas"]["QwenImageImageToLatentsInvocation"] | components["schemas"]["QwenImageLatentsToImageInvocation"] | components["schemas"]["QwenImageLoRACollectionLoader"] | components["schemas"]["QwenImageLoRALoaderInvocation"] | components["schemas"]["QwenImageModelLoaderInvocation"] | components["schemas"]["QwenImageTextEncoderInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RectangleMaskInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["SD3DenoiseInvocation"] | components["schemas"]["SD3ImageToLatentsInvocation"] | components["schemas"]["SD3LatentsToImageInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["SDXLLoRACollectionLoader"] | components["schemas"]["SDXLLoRALoaderInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["SaveImageToFileInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["Sd3ModelLoaderInvocation"] | components["schemas"]["Sd3TextEncoderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["SeedreamImageGenerationInvocation"] | components["schemas"]["SegmentAnythingInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["SpandrelImageToImageAutoscaleInvocation"] | components["schemas"]["SpandrelImageToImageInvocation"] | components["schemas"]["StringBatchInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["StringGenerator"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["TextLLMInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["TiledMultiDiffusionDenoiseLatents"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["VAELoaderInvocation"] | components["schemas"]["WorkflowReturnGetInvocation"] | components["schemas"]["WorkflowReturnInvocation"] | components["schemas"]["WorkflowReturnValueInvocation"] | components["schemas"]["ZImageControlInvocation"] | components["schemas"]["ZImageDenoiseInvocation"] | components["schemas"]["ZImageDenoiseMetaInvocation"] | components["schemas"]["ZImageImageToLatentsInvocation"] | components["schemas"]["ZImageLatentsToImageInvocation"] | components["schemas"]["ZImageLoRACollectionLoader"] | components["schemas"]["ZImageLoRALoaderInvocation"] | components["schemas"]["ZImageModelLoaderInvocation"] | components["schemas"]["ZImageSeedVarianceEnhancerInvocation"] | components["schemas"]["ZImageTextEncoderInvocation"]; + invocation: components["schemas"]["AddInvocation"] | components["schemas"]["AlibabaCloudImageGenerationInvocation"] | components["schemas"]["AlphaMaskToTensorInvocation"] | components["schemas"]["AnimaDenoiseInvocation"] | components["schemas"]["AnimaImageToLatentsInvocation"] | components["schemas"]["AnimaLLLiteInvocation"] | components["schemas"]["AnimaLatentsToImageInvocation"] | components["schemas"]["AnimaLoRACollectionLoader"] | components["schemas"]["AnimaLoRALoaderInvocation"] | components["schemas"]["AnimaModelLoaderInvocation"] | components["schemas"]["AnimaTextEncoderInvocation"] | components["schemas"]["ApplyMaskTensorToImageInvocation"] | components["schemas"]["ApplyMaskToImageInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["BoundingBoxInvocation"] | components["schemas"]["CLIPSkipInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["CallSavedWorkflowInvocation"] | components["schemas"]["CannyEdgeDetectionInvocation"] | components["schemas"]["CanvasOutputInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["CanvasV2MaskAndCropInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["CogView4DenoiseInvocation"] | components["schemas"]["CogView4ImageToLatentsInvocation"] | components["schemas"]["CogView4LatentsToImageInvocation"] | components["schemas"]["CogView4ModelLoaderInvocation"] | components["schemas"]["CogView4TextEncoderInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ColorMapInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ContentShuffleInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["CropImageToBoundingBoxInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["DWOpenposeDetectionInvocation"] | components["schemas"]["DecodeInvisibleWatermarkInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["DenoiseLatentsMetaInvocation"] | components["schemas"]["DepthAnythingDepthEstimationInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ExpandMaskWithFadeInvocation"] | components["schemas"]["FLUXLoRACollectionLoader"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["FloatBatchInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["FloatGenerator"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["Flux2DenoiseInvocation"] | components["schemas"]["Flux2KleinLoRACollectionLoader"] | components["schemas"]["Flux2KleinLoRALoaderInvocation"] | components["schemas"]["Flux2KleinModelLoaderInvocation"] | components["schemas"]["Flux2KleinTextEncoderInvocation"] | components["schemas"]["Flux2VaeDecodeInvocation"] | components["schemas"]["Flux2VaeEncodeInvocation"] | components["schemas"]["FluxControlLoRALoaderInvocation"] | components["schemas"]["FluxControlNetInvocation"] | components["schemas"]["FluxDenoiseInvocation"] | components["schemas"]["FluxDenoiseLatentsMetaInvocation"] | components["schemas"]["FluxFillInvocation"] | components["schemas"]["FluxIPAdapterInvocation"] | components["schemas"]["FluxKontextConcatenateImagesInvocation"] | components["schemas"]["FluxKontextInvocation"] | components["schemas"]["FluxLoRALoaderInvocation"] | components["schemas"]["FluxModelLoaderInvocation"] | components["schemas"]["FluxReduxInvocation"] | components["schemas"]["FluxTextEncoderInvocation"] | components["schemas"]["FluxVaeDecodeInvocation"] | components["schemas"]["FluxVaeEncodeInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["GeminiImageGenerationInvocation"] | components["schemas"]["GetMaskBoundingBoxInvocation"] | components["schemas"]["GroundingDinoInvocation"] | components["schemas"]["HEDEdgeDetectionInvocation"] | components["schemas"]["HeuristicResizeInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["Ideogram4CaptionBuilderInvocation"] | components["schemas"]["Ideogram4DenoiseInvocation"] | components["schemas"]["Ideogram4LatentsToImageInvocation"] | components["schemas"]["Ideogram4ModelLoaderInvocation"] | components["schemas"]["Ideogram4TextEncoderInvocation"] | components["schemas"]["IfInvocation"] | components["schemas"]["ImageBatchInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImageGenerator"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageMaskToTensorInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageNoiseInvocation"] | components["schemas"]["ImagePanelLayoutInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["IntegerBatchInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["IntegerGenerator"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["InvertTensorMaskInvocation"] | components["schemas"]["InvokeAdjustImageHuePlusInvocation"] | components["schemas"]["InvokeEquivalentAchromaticLightnessInvocation"] | components["schemas"]["InvokeImageBlendInvocation"] | components["schemas"]["InvokeImageCompositorInvocation"] | components["schemas"]["InvokeImageDilateOrErodeInvocation"] | components["schemas"]["InvokeImageEnhanceInvocation"] | components["schemas"]["InvokeImageValueThresholdsInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["LineartAnimeEdgeDetectionInvocation"] | components["schemas"]["LineartEdgeDetectionInvocation"] | components["schemas"]["LlavaOnevisionVllmInvocation"] | components["schemas"]["LoRACollectionLoader"] | components["schemas"]["LoRALoaderInvocation"] | components["schemas"]["LoRASelectorInvocation"] | components["schemas"]["MLSDDetectionInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["MaskFromIDInvocation"] | components["schemas"]["MaskTensorToImageInvocation"] | components["schemas"]["MediaPipeFaceDetectionInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["MetadataFieldExtractorInvocation"] | components["schemas"]["MetadataFromImageInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MetadataItemLinkedInvocation"] | components["schemas"]["MetadataToBoolCollectionInvocation"] | components["schemas"]["MetadataToBoolInvocation"] | components["schemas"]["MetadataToControlnetsInvocation"] | components["schemas"]["MetadataToFloatCollectionInvocation"] | components["schemas"]["MetadataToFloatInvocation"] | components["schemas"]["MetadataToIPAdaptersInvocation"] | components["schemas"]["MetadataToIntegerCollectionInvocation"] | components["schemas"]["MetadataToIntegerInvocation"] | components["schemas"]["MetadataToLorasCollectionInvocation"] | components["schemas"]["MetadataToLorasInvocation"] | components["schemas"]["MetadataToModelInvocation"] | components["schemas"]["MetadataToSDXLLorasInvocation"] | components["schemas"]["MetadataToSDXLModelInvocation"] | components["schemas"]["MetadataToSchedulerInvocation"] | components["schemas"]["MetadataToStringCollectionInvocation"] | components["schemas"]["MetadataToStringInvocation"] | components["schemas"]["MetadataToT2IAdaptersInvocation"] | components["schemas"]["MetadataToVAEInvocation"] | components["schemas"]["ModelIdentifierInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["NormalMapInvocation"] | components["schemas"]["OklabUnsharpMaskInvocation"] | components["schemas"]["OklchImageHueAdjustmentInvocation"] | components["schemas"]["OpenAIImageGenerationInvocation"] | components["schemas"]["PBRMapsInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["PasteImageIntoBoundingBoxInvocation"] | components["schemas"]["PiDiNetEdgeDetectionInvocation"] | components["schemas"]["PromptTemplateInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["QwenImageDenoiseInvocation"] | components["schemas"]["QwenImageImageToLatentsInvocation"] | components["schemas"]["QwenImageLatentsToImageInvocation"] | components["schemas"]["QwenImageLoRACollectionLoader"] | components["schemas"]["QwenImageLoRALoaderInvocation"] | components["schemas"]["QwenImageModelLoaderInvocation"] | components["schemas"]["QwenImageTextEncoderInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RectangleMaskInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["SD3DenoiseInvocation"] | components["schemas"]["SD3ImageToLatentsInvocation"] | components["schemas"]["SD3LatentsToImageInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["SDXLLoRACollectionLoader"] | components["schemas"]["SDXLLoRALoaderInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["SaveImageToFileInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["Sd3ModelLoaderInvocation"] | components["schemas"]["Sd3TextEncoderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["SeedreamImageGenerationInvocation"] | components["schemas"]["SegmentAnythingInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["SpandrelImageToImageAutoscaleInvocation"] | components["schemas"]["SpandrelImageToImageInvocation"] | components["schemas"]["StringBatchInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["StringGenerator"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["TextLLMInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["TiledMultiDiffusionDenoiseLatents"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["VAELoaderInvocation"] | components["schemas"]["WorkflowReturnGetInvocation"] | components["schemas"]["WorkflowReturnInvocation"] | components["schemas"]["WorkflowReturnValueInvocation"] | components["schemas"]["ZImageControlInvocation"] | components["schemas"]["ZImageDenoiseInvocation"] | components["schemas"]["ZImageDenoiseMetaInvocation"] | components["schemas"]["ZImageImageToLatentsInvocation"] | components["schemas"]["ZImageLatentsToImageInvocation"] | components["schemas"]["ZImageLoRACollectionLoader"] | components["schemas"]["ZImageLoRALoaderInvocation"] | components["schemas"]["ZImageModelLoaderInvocation"] | components["schemas"]["ZImageSeedVarianceEnhancerInvocation"] | components["schemas"]["ZImageTextEncoderInvocation"]; /** * Invocation Source Id * @description The ID of the prepared invocation's source node @@ -21149,6 +21496,96 @@ export type components = { base: "flux2"; variant: components["schemas"]["Flux2VariantType"]; }; + /** + * Main_Diffusers_Ideogram4_Config + * @description Model config for Ideogram 4 diffusers models (nf4 / fp8 quantized). + * + * The on-disk layout is a diffusers pipeline folder bundling two transformers + * (transformer/ + unconditional_transformer/), a Qwen3-VL text_encoder/ + tokenizer/, + * and a FLUX.2-style vae/. Quantization (nf4 vs fp8) lives inside the component folders + * and is detected by the loader, not here. + */ + Main_Diffusers_Ideogram4_Config: { + /** + * Key + * @description A unique key for this model. + */ + key: string; + /** + * Hash + * @description The hash of the model file(s). + */ + hash: string; + /** + * Path + * @description Path to the model on the filesystem. Relative paths are relative to the Invoke root directory. + */ + path: string; + /** + * File Size + * @description The size of the model in bytes. + */ + file_size: number; + /** + * Name + * @description Name of the model. + */ + name: string; + /** + * Description + * @description Model description + */ + description: string | null; + /** + * Source + * @description The original source of the model (path, URL or repo_id). + */ + source: string; + /** @description The type of source */ + source_type: components["schemas"]["ModelSourceType"]; + /** + * Source Api Response + * @description The original API response from the source, as stringified JSON. + */ + source_api_response: string | null; + /** + * Source Url + * @description Optional URL for the model (e.g. download page or model page). + */ + source_url: string | null; + /** + * Cover Image + * @description Url for image to preview model + */ + cover_image: string | null; + /** + * Type + * @default main + * @constant + */ + type: "main"; + /** + * Trigger Phrases + * @description Set of trigger phrases for this model + */ + trigger_phrases: string[] | null; + /** @description Default settings for this model */ + default_settings: components["schemas"]["MainModelDefaultSettings"] | null; + /** + * Format + * @default diffusers + * @constant + */ + format: "diffusers"; + /** @default */ + repo_variant: components["schemas"]["ModelRepoVariant"]; + /** + * Base + * @default ideogram-4 + * @constant + */ + base: "ideogram-4"; + }; /** * Main_Diffusers_QwenImage_Config * @description Model config for Qwen Image diffusers models (both txt2img and edit). @@ -23930,7 +24367,7 @@ export type components = { * Config * @description The installed model's config */ - config: components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; + config: components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Diffusers_Ideogram4_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; }; /** * ModelInstallDownloadProgressEvent @@ -24096,7 +24533,7 @@ export type components = { * Config Out * @description After successful installation, this will hold the configuration object. */ - config_out?: (components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]) | null; + config_out?: (components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Diffusers_Ideogram4_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]) | null; /** * Inplace * @description Leave model in its current location; otherwise install under models directory @@ -24182,7 +24619,7 @@ export type components = { * Config * @description The model's config */ - config: components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; + config: components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Diffusers_Ideogram4_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; /** * @description The submodel type, if any * @default null @@ -24209,7 +24646,7 @@ export type components = { * Config * @description The model's config */ - config: components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; + config: components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Diffusers_Ideogram4_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; /** * @description The submodel type, if any * @default null @@ -24436,7 +24873,7 @@ export type components = { */ ModelsList: { /** Models */ - models: (components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"])[]; + models: (components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Diffusers_Ideogram4_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"])[]; }; /** * Multiply Integers @@ -34771,7 +35208,7 @@ export interface operations { [name: string]: unknown; }; content: { - "application/json": components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; + "application/json": components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Diffusers_Ideogram4_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; }; }; /** @description Validation Error */ @@ -34803,7 +35240,7 @@ export interface operations { [name: string]: unknown; }; content: { - "application/json": components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; + "application/json": components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Diffusers_Ideogram4_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; }; }; /** @description Validation Error */ @@ -34855,7 +35292,7 @@ export interface operations { * "upcast_attention": false * } */ - "application/json": components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; + "application/json": components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Diffusers_Ideogram4_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; }; }; /** @description Bad request */ @@ -34962,7 +35399,7 @@ export interface operations { * "upcast_attention": false * } */ - "application/json": components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; + "application/json": components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Diffusers_Ideogram4_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; }; }; /** @description Bad request */ @@ -35035,7 +35472,7 @@ export interface operations { * "upcast_attention": false * } */ - "application/json": components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; + "application/json": components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Diffusers_Ideogram4_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; }; }; /** @description Bad request */ @@ -35770,7 +36207,7 @@ export interface operations { * "upcast_attention": false * } */ - "application/json": components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; + "application/json": components["schemas"]["Main_Diffusers_SD1_Config"] | components["schemas"]["Main_Diffusers_SD2_Config"] | components["schemas"]["Main_Diffusers_SDXL_Config"] | components["schemas"]["Main_Diffusers_SDXLRefiner_Config"] | components["schemas"]["Main_Diffusers_SD3_Config"] | components["schemas"]["Main_Diffusers_FLUX_Config"] | components["schemas"]["Main_Diffusers_Flux2_Config"] | components["schemas"]["Main_Diffusers_CogView4_Config"] | components["schemas"]["Main_Diffusers_QwenImage_Config"] | components["schemas"]["Main_Diffusers_ZImage_Config"] | components["schemas"]["Main_Diffusers_Ideogram4_Config"] | components["schemas"]["Main_Checkpoint_SD1_Config"] | components["schemas"]["Main_Checkpoint_SD2_Config"] | components["schemas"]["Main_Checkpoint_SDXL_Config"] | components["schemas"]["Main_Checkpoint_SDXLRefiner_Config"] | components["schemas"]["Main_Checkpoint_Flux2_Config"] | components["schemas"]["Main_Checkpoint_FLUX_Config"] | components["schemas"]["Main_Checkpoint_QwenImage_Config"] | components["schemas"]["Main_Checkpoint_ZImage_Config"] | components["schemas"]["Main_Checkpoint_Anima_Config"] | components["schemas"]["Main_BnBNF4_FLUX_Config"] | components["schemas"]["Main_GGUF_Flux2_Config"] | components["schemas"]["Main_GGUF_FLUX_Config"] | components["schemas"]["Main_GGUF_QwenImage_Config"] | components["schemas"]["Main_GGUF_ZImage_Config"] | components["schemas"]["VAE_Checkpoint_SD1_Config"] | components["schemas"]["VAE_Checkpoint_SD2_Config"] | components["schemas"]["VAE_Checkpoint_SDXL_Config"] | components["schemas"]["VAE_Checkpoint_FLUX_Config"] | components["schemas"]["VAE_Checkpoint_Flux2_Config"] | components["schemas"]["VAE_Checkpoint_QwenImage_Config"] | components["schemas"]["VAE_Checkpoint_Anima_Config"] | components["schemas"]["VAE_Diffusers_SD1_Config"] | components["schemas"]["VAE_Diffusers_SDXL_Config"] | components["schemas"]["VAE_Diffusers_Flux2_Config"] | components["schemas"]["ControlNet_Checkpoint_SD1_Config"] | components["schemas"]["ControlNet_Checkpoint_SD2_Config"] | components["schemas"]["ControlNet_Checkpoint_SDXL_Config"] | components["schemas"]["ControlNet_Checkpoint_FLUX_Config"] | components["schemas"]["ControlNet_Checkpoint_ZImage_Config"] | components["schemas"]["ControlNet_Checkpoint_Anima_Config"] | components["schemas"]["ControlNet_Diffusers_SD1_Config"] | components["schemas"]["ControlNet_Diffusers_SD2_Config"] | components["schemas"]["ControlNet_Diffusers_SDXL_Config"] | components["schemas"]["ControlNet_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_SD1_Config"] | components["schemas"]["LoRA_LyCORIS_SD2_Config"] | components["schemas"]["LoRA_LyCORIS_SDXL_Config"] | components["schemas"]["LoRA_LyCORIS_Flux2_Config"] | components["schemas"]["LoRA_LyCORIS_FLUX_Config"] | components["schemas"]["LoRA_LyCORIS_ZImage_Config"] | components["schemas"]["LoRA_LyCORIS_QwenImage_Config"] | components["schemas"]["LoRA_LyCORIS_Anima_Config"] | components["schemas"]["LoRA_OMI_SDXL_Config"] | components["schemas"]["LoRA_OMI_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_SD1_Config"] | components["schemas"]["LoRA_Diffusers_SD2_Config"] | components["schemas"]["LoRA_Diffusers_SDXL_Config"] | components["schemas"]["LoRA_Diffusers_Flux2_Config"] | components["schemas"]["LoRA_Diffusers_FLUX_Config"] | components["schemas"]["LoRA_Diffusers_ZImage_Config"] | components["schemas"]["ControlLoRA_LyCORIS_FLUX_Config"] | components["schemas"]["T5Encoder_T5Encoder_Config"] | components["schemas"]["T5Encoder_BnBLLMint8_Config"] | components["schemas"]["T5Encoder_GGUF_Config"] | components["schemas"]["Qwen3Encoder_Qwen3Encoder_Config"] | components["schemas"]["Qwen3Encoder_Checkpoint_Config"] | components["schemas"]["Qwen3Encoder_GGUF_Config"] | components["schemas"]["QwenVLEncoder_Diffusers_Config"] | components["schemas"]["QwenVLEncoder_Checkpoint_Config"] | components["schemas"]["TI_File_SD1_Config"] | components["schemas"]["TI_File_SD2_Config"] | components["schemas"]["TI_File_SDXL_Config"] | components["schemas"]["TI_Folder_SD1_Config"] | components["schemas"]["TI_Folder_SD2_Config"] | components["schemas"]["TI_Folder_SDXL_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD1_Config"] | components["schemas"]["IPAdapter_InvokeAI_SD2_Config"] | components["schemas"]["IPAdapter_InvokeAI_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD1_Config"] | components["schemas"]["IPAdapter_Checkpoint_SD2_Config"] | components["schemas"]["IPAdapter_Checkpoint_SDXL_Config"] | components["schemas"]["IPAdapter_Checkpoint_FLUX_Config"] | components["schemas"]["T2IAdapter_Diffusers_SD1_Config"] | components["schemas"]["T2IAdapter_Diffusers_SDXL_Config"] | components["schemas"]["Spandrel_Checkpoint_Config"] | components["schemas"]["CLIPEmbed_Diffusers_G_Config"] | components["schemas"]["CLIPEmbed_Diffusers_L_Config"] | components["schemas"]["CLIPVision_Diffusers_Config"] | components["schemas"]["SigLIP_Diffusers_Config"] | components["schemas"]["FLUXRedux_Checkpoint_Config"] | components["schemas"]["LlavaOnevision_Diffusers_Config"] | components["schemas"]["TextLLM_Diffusers_Config"] | components["schemas"]["ExternalApiModelConfig"] | components["schemas"]["Unknown_Config"]; }; }; /** @description Bad request */ diff --git a/invokeai/frontend/web/src/services/api/types.ts b/invokeai/frontend/web/src/services/api/types.ts index 34d0470db45..f17003c5f50 100644 --- a/invokeai/frontend/web/src/services/api/types.ts +++ b/invokeai/frontend/web/src/services/api/types.ts @@ -484,8 +484,14 @@ const isFlux2Klein9BMainModelConfig = (config: AnyModelConfig): config is MainMo return config.type === 'main' && config.base === 'flux2' && config.name.toLowerCase().includes('9b'); }; +const isIdeogram4MainModelConfig = (config: AnyModelConfig): config is MainModelConfig => { + return config.type === 'main' && config.base === 'ideogram-4'; +}; + export const isNonCommercialMainModelConfig = (config: AnyModelConfig): config is MainModelConfig => { - return isFluxDevMainModelConfig(config) || isFlux2Klein9BMainModelConfig(config); + return ( + isFluxDevMainModelConfig(config) || isFlux2Klein9BMainModelConfig(config) || isIdeogram4MainModelConfig(config) + ); }; export const isFluxFillMainModelModelConfig = (config: AnyModelConfig): config is MainModelConfig => { diff --git a/tests/backend/ideogram4/test_caption.py b/tests/backend/ideogram4/test_caption.py new file mode 100644 index 00000000000..1d031f703ed --- /dev/null +++ b/tests/backend/ideogram4/test_caption.py @@ -0,0 +1,93 @@ +"""Tests for the Ideogram 4 runtime caption assembly (Python port of buildIdeogram4Caption). + +Kept behaviorally identical to the frontend assembler so that moving the work into the +ideogram4_caption_builder node (so dynamic prompts / batching vary the encoded caption) does not +change the encoded output for a given (prompt, regions, palette). +""" + +import json + +from invokeai.backend.ideogram4.caption import build_ideogram4_caption + + +def test_raw_json_passthrough_is_verbatim(): + raw = '{"high_level_description": "a cat"}' + # Regions and palette are ignored for raw-JSON prompts; whitespace preserved verbatim. + assert build_ideogram4_caption(raw, [("ignored", [0, 0, 10, 10])], ["#FFFFFF"]) == raw + + +def test_plain_prompt_without_regions_synthesizes_a_default_partial_frame_element(): + # Never bare plain text, and never an empty/degenerate elements list: a no-region prompt is wrapped + # in the JSON schema with one auto-synthesized element (the whole prompt at a partial, non-full-frame + # bbox). An empty elements list — or a full-frame element repeating the prompt — trips Ideogram's + # safety filter, so the default element uses a partial bbox. + result = build_ideogram4_caption(" a serene lake ", [], []) + assert json.loads(result) == { + "high_level_description": "a serene lake", + "compositional_deconstruction": { + "background": "", + "elements": [{"type": "obj", "bbox": [100, 100, 900, 900], "desc": "a serene lake"}], + }, + } + # The default bbox must never be the degenerate full frame. + assert [100, 100, 900, 900] != [0, 0, 1000, 1000] + + +def test_regions_present_do_not_trigger_the_default_element(): + # When the user drew regions, elements come from them — no synthesized default is added. + result = build_ideogram4_caption("a scene", [("a red bird", [10, 20, 300, 400])], []) + elements = json.loads(result)["compositional_deconstruction"]["elements"] + assert elements == [{"type": "obj", "bbox": [10, 20, 300, 400], "desc": "a red bird"}] + + +def test_region_with_bbox_builds_obj_element_in_key_order(): + result = build_ideogram4_caption("a scene", [("a red bird", [10, 20, 300, 400])], []) + parsed = json.loads(result) + assert parsed == { + "high_level_description": "a scene", + "compositional_deconstruction": { + "background": "", + "elements": [{"type": "obj", "bbox": [10, 20, 300, 400], "desc": "a red bird"}], + }, + } + # obj element key order must be type, bbox, desc (trained schema order). + assert list(parsed["compositional_deconstruction"]["elements"][0].keys()) == ["type", "bbox", "desc"] + + +def test_region_without_bbox_omits_bbox_key(): + result = build_ideogram4_caption("a scene", [("no drawn content", None)], []) + element = json.loads(result)["compositional_deconstruction"]["elements"][0] + assert element == {"type": "obj", "desc": "no drawn content"} + + +def test_blank_region_prompt_is_dropped(): + result = build_ideogram4_caption("a scene", [(" ", [0, 0, 10, 10]), ("kept", None)], []) + elements = json.loads(result)["compositional_deconstruction"]["elements"] + assert len(elements) == 1 + assert elements[0]["desc"] == "kept" + + +def test_palette_is_normalized_and_invalid_entries_dropped(): + result = build_ideogram4_caption("a scene", [], ["#ff0000", "not-a-color", "#00FF00"]) + parsed = json.loads(result) + assert parsed["style_description"]["color_palette"] == ["#FF0000", "#00FF00"] + + +def test_palette_only_still_builds_structured_caption(): + result = build_ideogram4_caption("a scene", [], ["#123ABC"]) + parsed = json.loads(result) + # Strict key order: high_level_description, style_description, compositional_deconstruction. + assert list(parsed.keys()) == ["high_level_description", "style_description", "compositional_deconstruction"] + # No regions -> the default full-scene element is synthesized (elements is never empty). + assert parsed["compositional_deconstruction"]["elements"] == [ + {"type": "obj", "bbox": [100, 100, 900, 900], "desc": "a scene"} + ] + + +def test_compact_separators_and_non_ascii_preserved(): + result = build_ideogram4_caption("café ☕", [("naïve", None)], []) + # Compact separators (no spaces after , or :) and raw non-ASCII characters (not \\uXXXX escapes). + assert ", " not in result + assert '": ' not in result + assert "café ☕" in result + assert "naïve" in result diff --git a/tests/backend/ideogram4/test_caption_builder_node.py b/tests/backend/ideogram4/test_caption_builder_node.py new file mode 100644 index 00000000000..a1403ffc2e1 --- /dev/null +++ b/tests/backend/ideogram4/test_caption_builder_node.py @@ -0,0 +1,37 @@ +"""Validation tests for the Ideogram4CaptionBuilderInvocation region bbox contract. + +The caption builder forwards each region's bbox verbatim into the structured JSON, so a malformed box +(wrong length or out-of-range coordinate) would emit a prompt the model may misapply. The Ideogram4Region +model must reject such boxes up front. +""" + +import pytest +from pydantic import ValidationError + +from invokeai.app.invocations.ideogram4_caption import Ideogram4Region + + +def test_valid_bbox_is_accepted(): + region = Ideogram4Region(prompt="a cat", bbox=[0, 0, 1000, 1000]) + assert region.bbox == [0, 0, 1000, 1000] + + +def test_none_bbox_is_accepted(): + region = Ideogram4Region(prompt="a cat", bbox=None) + assert region.bbox is None + + +@pytest.mark.parametrize( + "bbox", + [ + [0, 0, 1000], # too short + [0, 0, 1000, 1000, 7], # too long + [-1, 0, 1000, 1000], # negative + [0, 0, 1000, 1001], # above 1000 + [900, 900, 100, 100], # inverted (y_min > y_max and x_min > x_max) + [0, 900, 1000, 100], # inverted x only (x_min > x_max) + ], +) +def test_malformed_bbox_is_rejected(bbox: list[int]): + with pytest.raises(ValidationError): + Ideogram4Region(prompt="a cat", bbox=bbox) diff --git a/tests/backend/ideogram4/test_guidance_schedule.py b/tests/backend/ideogram4/test_guidance_schedule.py new file mode 100644 index 00000000000..aff2809e8f3 --- /dev/null +++ b/tests/backend/ideogram4/test_guidance_schedule.py @@ -0,0 +1,48 @@ +"""Tests for Ideogram 4's effective guidance schedule. + +The schedule is ``(polish_gw,)*N_polish + (main_gw,)*N_main`` in loop-index order (index 0 is the +final/polish step). A guidance_scale override must replace the main weight while preserving the +polish tail, and there must always be at least one main step so the override is never silently +dropped — the regression that motivated capping the polish tail at ``num_steps - 1``. +""" + +import pytest + +from invokeai.app.invocations.ideogram4_denoise import _effective_guidance_schedule +from invokeai.backend.ideogram4.sampler_configs import PRESETS + +_QUALITY = PRESETS["V4_QUALITY_48"] # num_steps=48, schedule=(3.0,)*3 + (7.0,)*45 + + +def test_returns_base_schedule_unchanged_at_preset_steps_without_override(): + result = _effective_guidance_schedule(_QUALITY.guidance_schedule, _QUALITY.num_steps, _QUALITY.num_steps, None) + assert result == _QUALITY.guidance_schedule + + +def test_guidance_override_replaces_main_weight_and_preserves_polish(): + result = _effective_guidance_schedule(_QUALITY.guidance_schedule, _QUALITY.num_steps, _QUALITY.num_steps, 12.0) + assert len(result) == _QUALITY.num_steps + # Polish tail (weight 3.0) preserved; every main step now carries the 12.0 override. + assert result[0] == 3.0 + assert result[-1] == 12.0 + assert set(result) == {3.0, 12.0} + + +def test_two_step_override_keeps_one_polish_and_one_main(): + # The minimum allowed step count. Regression: previously polish_count could equal num_steps, + # leaving main_count == 0 and silently dropping the guidance override. + result = _effective_guidance_schedule(_QUALITY.guidance_schedule, _QUALITY.num_steps, 2, 15.0) + assert result == (3.0, 15.0) + + +@pytest.mark.parametrize("num_steps", list(range(2, 60))) +def test_at_least_one_main_step_and_override_always_applied(num_steps: int): + override = 9.5 + result = _effective_guidance_schedule(_QUALITY.guidance_schedule, _QUALITY.num_steps, num_steps, override) + assert len(result) == num_steps + main_count = sum(1 for gw in result if gw == override) + polish_count = len(result) - main_count + assert main_count >= 1, "the guidance override must always occupy at least one step" + assert polish_count >= 1, "the polish tail must always be preserved" + assert result[-1] == override + assert result[0] == _QUALITY.guidance_schedule[0] diff --git a/tests/backend/ideogram4/test_quantized_loading.py b/tests/backend/ideogram4/test_quantized_loading.py new file mode 100644 index 00000000000..fa5e9ad154c --- /dev/null +++ b/tests/backend/ideogram4/test_quantized_loading.py @@ -0,0 +1,142 @@ +"""Tests for the Ideogram 4 weight-only fp8 loading mechanism. + +The Ideogram 4 fp8 text encoder is loaded by building the empty architecture, swapping its +quantized ``nn.Linear`` layers for ``Fp8Linear`` (gated on a saved per-row scale), then loading the +prequantized state dict with ``assign=True`` / ``strict=False`` — the exact pattern the model loader +uses in ``model_loaders/ideogram4.py::_load_text_encoder``. These tests exercise that mechanism on a +tiny CPU model so the fp8 path has regression coverage without a multi-GB checkpoint. +""" + +import accelerate +import pytest +import torch +import torch.nn as nn + +from invokeai.backend.ideogram4.quantized_loading import ( + FP8_TEXT_ENCODER_CONFIG_FLAG, + Fp8Linear, + is_fp8_state_dict, + load_fp8_state_dict, + quantize_weight_to_fp8, + swap_linears_to_fp8, +) + + +class _TinyEncoder(nn.Module): + """A stand-in for the text encoder: two Linears (fp8-quantized) around a non-quantized norm, + plus a non-persistent buffer that mimics the rotary caches transformers models compute in + ``__init__`` (and which must survive the meta-device build).""" + + def __init__(self) -> None: + super().__init__() + self.lin1 = nn.Linear(8, 16) + self.norm = nn.LayerNorm(16) + self.lin2 = nn.Linear(16, 4) + self.register_buffer("rope_cache", torch.arange(4, dtype=torch.float32), persistent=False) + + def forward(self, x: torch.Tensor) -> torch.Tensor: + return self.lin2(self.norm(self.lin1(x))) + + +def _make_fp8_state_dict(ref: _TinyEncoder, compute_dtype: torch.dtype) -> dict[str, torch.Tensor]: + """Build a prequantized state dict: the two Linears become fp8 weight + per-row scale, everything + else stays a normal float tensor. Mirrors the on-disk fp8 checkpoint layout.""" + sd: dict[str, torch.Tensor] = {} + for name in ("lin1", "lin2"): + lin: nn.Linear = getattr(ref, name) + q, scale = quantize_weight_to_fp8(lin.weight) + sd[f"{name}.weight"] = q + sd[f"{name}.weight_scale"] = scale + sd[f"{name}.bias"] = lin.bias.detach().to(compute_dtype) + sd["norm.weight"] = ref.norm.weight.detach().to(compute_dtype) + sd["norm.bias"] = ref.norm.bias.detach().to(compute_dtype) + return sd + + +def _dequant_reference(ref: _TinyEncoder, sd: dict[str, torch.Tensor], x: torch.Tensor) -> torch.Tensor: + """Forward pass using the dequantized fp8 weights — the exact math ``Fp8Linear.forward`` runs, so + the loaded model must match this to within dtype rounding (not the lossy original weights).""" + dtype = x.dtype + + def deq(name: str) -> tuple[torch.Tensor, torch.Tensor]: + w = sd[f"{name}.weight"].to(dtype) * sd[f"{name}.weight_scale"].to(dtype).unsqueeze(1) + return w, sd[f"{name}.bias"].to(dtype) + + w1, b1 = deq("lin1") + w2, b2 = deq("lin2") + h = torch.nn.functional.linear(x, w1, b1) + h = torch.nn.functional.layer_norm(h, (16,), sd["norm.weight"].to(dtype), sd["norm.bias"].to(dtype)) + return torch.nn.functional.linear(h, w2, b2) + + +def test_fp8_load_matches_loader_pattern() -> None: + """Build empty -> swap -> load(assign, strict=False), exactly as the ideogram4 loader does, and + verify no meta tensors survive and the forward matches the dequantized reference.""" + torch.manual_seed(0) + compute_dtype = torch.float32 + + ref = _TinyEncoder().to(compute_dtype).eval() + sd = _make_fp8_state_dict(ref, compute_dtype) + + assert is_fp8_state_dict(sd) + + with accelerate.init_empty_weights(): + model = _TinyEncoder() + swap_linears_to_fp8(model, sd, compute_dtype=compute_dtype) + + # Only the two Linears carry a saved scale, so exactly two get swapped. + assert sum(1 for m in model.modules() if isinstance(m, Fp8Linear)) == 2 + + load_fp8_state_dict(model, sd, device=torch.device("cpu"), dtype=compute_dtype, assign=True, strict=False) + model.eval() + + assert not any(p.is_meta for p in model.parameters()), "meta params remained after fp8 load" + assert not any(b.is_meta for b in model.buffers()), "meta buffers remained after fp8 load" + # The non-persistent rope buffer must have been rebuilt with real data by the meta-device init. + assert torch.equal(model.rope_cache, torch.arange(4, dtype=torch.float32)) + + x = torch.randn(2, 8, dtype=compute_dtype) + with torch.no_grad(): + out = model(x) + expected = _dequant_reference(ref, sd, x) + assert torch.allclose(out, expected, atol=1e-5, rtol=1e-4) + + +def test_fp8_load_rejects_unexpected_keys() -> None: + """A key the model has no home for must fail loudly rather than load silently.""" + torch.manual_seed(1) + compute_dtype = torch.float32 + ref = _TinyEncoder().to(compute_dtype).eval() + sd = _make_fp8_state_dict(ref, compute_dtype) + sd["lin1.bogus_extra"] = torch.zeros(3) + + model = _TinyEncoder().to(compute_dtype) + swap_linears_to_fp8(model, sd, compute_dtype=compute_dtype) + with pytest.raises(RuntimeError, match="unexpected keys"): + load_fp8_state_dict(model, sd, device=torch.device("cpu"), dtype=compute_dtype, strict=False) + + +def test_fp8_missing_key_strictness() -> None: + """strict=True raises on a missing weight; strict=False downgrades it to a warning.""" + torch.manual_seed(2) + compute_dtype = torch.float32 + ref = _TinyEncoder().to(compute_dtype).eval() + sd = _make_fp8_state_dict(ref, compute_dtype) + del sd["norm.bias"] + + def build() -> _TinyEncoder: + m = _TinyEncoder().to(compute_dtype) + swap_linears_to_fp8(m, sd, compute_dtype=compute_dtype) + return m + + with pytest.raises(RuntimeError, match="missing keys"): + load_fp8_state_dict(build(), sd, device=torch.device("cpu"), dtype=compute_dtype, strict=True) + + with pytest.warns(UserWarning, match="missing keys"): + load_fp8_state_dict(build(), sd, device=torch.device("cpu"), dtype=compute_dtype, strict=False) + + +def test_fp8_config_flag_constant() -> None: + """The loader keys the fp8 path off this exact config.json marker; pin it so a rename can't + silently reintroduce the 'importable but fails at encode time' bug.""" + assert FP8_TEXT_ENCODER_CONFIG_FLAG == "ideogram_fp8_weight_only" diff --git a/tests/backend/ideogram4/test_text_encoder_loader.py b/tests/backend/ideogram4/test_text_encoder_loader.py new file mode 100644 index 00000000000..887c70af416 --- /dev/null +++ b/tests/backend/ideogram4/test_text_encoder_loader.py @@ -0,0 +1,57 @@ +"""Tests for the Ideogram 4 text-encoder load-completeness guard. + +The encoder is built under accelerate.init_empty_weights() and filled from the checkpoint. A missing +non-tied weight would leave a tensor on the meta device — passing the load but failing later during +device movement / encoding. _verify_encoder_fully_materialized must reject that, while tolerating tied +weights that transformers resolves via tie_weights(). +""" + +import accelerate +import pytest +import torch + +from invokeai.backend.model_manager.load.model_loaders.ideogram4 import _verify_encoder_fully_materialized + + +class _UntiedModel(torch.nn.Module): + def __init__(self) -> None: + super().__init__() + self.embed = torch.nn.Linear(4, 4, bias=False) + self.extra = torch.nn.Linear(4, 4, bias=False) + + +class _TiedModel(torch.nn.Module): + def __init__(self) -> None: + super().__init__() + self.embed = torch.nn.Linear(4, 4, bias=False) + self.head = torch.nn.Linear(4, 4, bias=False) + + def tie_weights(self) -> None: + # Mirror transformers: the output weight is tied to (shares storage with) the input embedding. + self.head.weight = self.embed.weight + + +def test_passes_when_fully_materialized() -> None: + """A normally-initialized model (no meta tensors) is accepted.""" + _verify_encoder_fully_materialized(_UntiedModel(), context="test") + + +def test_raises_on_leftover_meta_from_missing_non_tied_weight() -> None: + """A missing non-tied weight leaves a meta tensor and must be rejected.""" + with accelerate.init_empty_weights(): + model = _UntiedModel() + # Simulate loading only `embed`; `extra` stays on the meta device (missing non-tied weight). + model.embed.weight = torch.nn.Parameter(torch.zeros(4, 4)) + with pytest.raises(RuntimeError, match="meta device"): + _verify_encoder_fully_materialized(model, context="test") + + +def test_tolerates_tied_weight_resolved_by_tie_weights() -> None: + """A tied output weight left on meta is materialized by tie_weights() and must not raise.""" + with accelerate.init_empty_weights(): + model = _TiedModel() + # Only the source embedding is "loaded"; head.weight is still meta but is tied to embed. + 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