Merge 92be83b922 into 96f1cee9f5

Signed-off-by: bigcat88 <bigcat88@icloud.com>

CODEOWNERS

@@ -1,2 +1,2 @@
 # Admins
-* @comfyanonymous @kosinkadink @guill
+* @comfyanonymous @kosinkadink @guill @alexisrolland @rattus128

comfy/lora.py

@@ -342,6 +342,12 @@ def model_lora_keys_unet(model, key_map={}):
                 key_map["base_model.model.{}".format(key_lora)] = k  # Official base model loras
                 key_map["lycoris_{}".format(key_lora.replace(".", "_"))] = k  # LyCORIS/LoKR format
 
+    if isinstance(model, comfy.model_base.ErnieImage):
+        for k in sdk:
+            if k.startswith("diffusion_model.") and k.endswith(".weight"):
+                key_lora = k[len("diffusion_model."):-len(".weight")]
+                key_map["transformer.{}".format(key_lora)] = k
+
     return key_map
 
 

comfy_api/latest/_input_impl/video_types.py

@@ -290,7 +290,7 @@ class VideoFromFile(VideoInput):
                                     alphas = []
                                     alpha_channel = True
                                     break
-                            if frame.format.name in ("yuvj420p", "rgb24", "rgba", "pal8"):
+                            if frame.format.name in ("yuvj420p", "yuvj422p", "yuvj444p", "rgb24", "rgba", "pal8"):
                                 process_image_format = lambda a: a.float() / 255.0
                                 if alpha_channel:
                                     image_format = 'rgba'

comfy_api_nodes/apis/bytedance.py

@@ -157,6 +157,11 @@ class SeedanceCreateAssetResponse(BaseModel):
     asset_id: str = Field(...)
 
 
+class SeedanceVirtualLibraryCreateAssetRequest(BaseModel):
+    url: str = Field(..., description="Publicly accessible URL of the image asset to upload.")
+    hash: str = Field(..., description="Dedup key. Re-submitting the same hash returns the existing asset id.")
+
+
 # Dollars per 1K tokens, keyed by (model_id, has_video_input).
 SEEDANCE2_PRICE_PER_1K_TOKENS = {
     ("dreamina-seedance-2-0-260128", False): 0.007,

comfy_api_nodes/apis/luma.py

@@ -1,15 +1,12 @@
 from __future__ import annotations
 
-
-import torch
-
 from enum import Enum
 from typing import Optional, Union
 
+import torch
 from pydantic import BaseModel, Field, confloat
 
 
-
 class LumaIO:
     LUMA_REF = "LUMA_REF"
     LUMA_CONCEPTS = "LUMA_CONCEPTS"
@@ -183,13 +180,13 @@ class LumaAssets(BaseModel):
 
 
 class LumaImageRef(BaseModel):
-    '''Used for image gen'''
+    """Used for image gen"""
     url: str = Field(..., description='The URL of the image reference')
     weight: confloat(ge=0.0, le=1.0) = Field(..., description='The weight of the image reference')
 
 
 class LumaImageReference(BaseModel):
-    '''Used for video gen'''
+    """Used for video gen"""
     type: Optional[str] = Field('image', description='Input type, defaults to image')
     url: str = Field(..., description='The URL of the image')
 
@@ -251,3 +248,32 @@ class LumaGeneration(BaseModel):
     assets: Optional[LumaAssets] = Field(None, description='The assets of the generation')
     model: str = Field(..., description='The model used for the generation')
     request: Union[LumaGenerationRequest, LumaImageGenerationRequest] = Field(..., description="The request used for the generation")
+
+
+class Luma2ImageRef(BaseModel):
+    url: str | None = None
+    data: str | None = None
+    media_type: str | None = None
+
+
+class Luma2GenerationRequest(BaseModel):
+    prompt: str = Field(..., min_length=1, max_length=6000)
+    model: str | None = None
+    type: str | None = None
+    aspect_ratio: str | None = None
+    style: str | None = None
+    output_format: str | None = None
+    web_search: bool | None = None
+    image_ref: list[Luma2ImageRef] | None = None
+    source: Luma2ImageRef | None = None
+
+
+class Luma2Generation(BaseModel):
+    id: str | None = None
+    type: str | None = None
+    state: str | None = None
+    model: str | None = None
+    created_at: str | None = None
+    output: list[LumaImageReference] | None = None
+    failure_reason: str | None = None
+    failure_code: str | None = None

comfy_api_nodes/nodes_bytedance.py

@@ -1,3 +1,4 @@
+import hashlib
 import logging
 import math
 import re
@@ -20,6 +21,7 @@ from comfy_api_nodes.apis.bytedance import (
     SeedanceCreateAssetResponse,
     SeedanceCreateVisualValidateSessionResponse,
     SeedanceGetVisualValidateSessionResponse,
+    SeedanceVirtualLibraryCreateAssetRequest,
     Seedream4Options,
     Seedream4TaskCreationRequest,
     TaskAudioContent,
@@ -271,6 +273,30 @@ async def _wait_for_asset_active(cls: type[IO.ComfyNode], asset_id: str, group_i
     )
 
 
+async def _seedance_virtual_library_upload_image_asset(
+    cls: type[IO.ComfyNode],
+    image: torch.Tensor,
+    *,
+    wait_label: str = "Uploading image",
+) -> str:
+    """Upload an image into the caller's per-customer Seedance virtual library."""
+    public_url = await upload_image_to_comfyapi(cls, image, wait_label=wait_label)
+    normalized = image.detach().cpu().contiguous().to(torch.float32)
+    digest = hashlib.sha256()
+    digest.update(str(tuple(normalized.shape)).encode("utf-8"))
+    digest.update(b"\0")
+    digest.update(normalized.numpy().tobytes())
+    image_hash = digest.hexdigest()
+    create_resp = await sync_op(
+        cls,
+        ApiEndpoint(path="/proxy/seedance/virtual-library/assets", method="POST"),
+        response_model=SeedanceCreateAssetResponse,
+        data=SeedanceVirtualLibraryCreateAssetRequest(url=public_url, hash=image_hash),
+    )
+    await _wait_for_asset_active(cls, create_resp.asset_id, group_id="virtual-library")
+    return f"asset://{create_resp.asset_id}"
+
+
 def _seedance2_price_extractor(model_id: str, has_video_input: bool):
     """Returns a price_extractor closure for Seedance 2.0 poll_op."""
     rate = SEEDANCE2_PRICE_PER_1K_TOKENS.get((model_id, has_video_input))
@@ -1507,7 +1533,9 @@ class ByteDance2FirstLastFrameNode(IO.ComfyNode):
         if first_frame_asset_id:
             first_frame_url = image_assets[first_frame_asset_id]
         else:
-            first_frame_url = await upload_image_to_comfyapi(cls, first_frame, wait_label="Uploading first frame.")
+            first_frame_url = await _seedance_virtual_library_upload_image_asset(
+                cls, first_frame, wait_label="Uploading first frame."
+            )
 
         content: list[TaskTextContent | TaskImageContent] = [
             TaskTextContent(text=model["prompt"]),
@@ -1527,7 +1555,9 @@ class ByteDance2FirstLastFrameNode(IO.ComfyNode):
             content.append(
                 TaskImageContent(
                     image_url=TaskImageContentUrl(
-                        url=await upload_image_to_comfyapi(cls, last_frame, wait_label="Uploading last frame.")
+                        url=await _seedance_virtual_library_upload_image_asset(
+                            cls, last_frame, wait_label="Uploading last frame."
+                        )
                     ),
                     role="last_frame",
                 ),
@@ -1805,9 +1835,9 @@ class ByteDance2ReferenceNode(IO.ComfyNode):
             content.append(
                 TaskImageContent(
                     image_url=TaskImageContentUrl(
-                        url=await upload_image_to_comfyapi(
+                        url=await _seedance_virtual_library_upload_image_asset(
                             cls,
-                            image=reference_images[key],
+                            reference_images[key],
                             wait_label=f"Uploading image {i}",
                         ),
                     ),

comfy_api_nodes/nodes_luma.py

@@ -1,10 +1,11 @@
-from typing import Optional
-
 import torch
 from typing_extensions import override
 
-from comfy_api.latest import IO, ComfyExtension
+from comfy_api.latest import IO, ComfyExtension, Input
 from comfy_api_nodes.apis.luma import (
+    Luma2Generation,
+    Luma2GenerationRequest,
+    Luma2ImageRef,
     LumaAspectRatio,
     LumaCharacterRef,
     LumaConceptChain,
@@ -30,6 +31,7 @@ from comfy_api_nodes.util import (
     download_url_to_video_output,
     poll_op,
     sync_op,
+    upload_image_to_comfyapi,
     upload_images_to_comfyapi,
     validate_string,
 )
@@ -212,9 +214,9 @@ class LumaImageGenerationNode(IO.ComfyNode):
         aspect_ratio: str,
         seed,
         style_image_weight: float,
-        image_luma_ref: Optional[LumaReferenceChain] = None,
-        style_image: Optional[torch.Tensor] = None,
-        character_image: Optional[torch.Tensor] = None,
+        image_luma_ref: LumaReferenceChain | None = None,
+        style_image: torch.Tensor | None = None,
+        character_image: torch.Tensor | None = None,
     ) -> IO.NodeOutput:
         validate_string(prompt, strip_whitespace=True, min_length=3)
         # handle image_luma_ref
@@ -434,7 +436,7 @@ class LumaTextToVideoGenerationNode(IO.ComfyNode):
         duration: str,
         loop: bool,
         seed,
-        luma_concepts: Optional[LumaConceptChain] = None,
+        luma_concepts: LumaConceptChain | None = None,
     ) -> IO.NodeOutput:
         validate_string(prompt, strip_whitespace=False, min_length=3)
         duration = duration if model != LumaVideoModel.ray_1_6 else None
@@ -533,7 +535,6 @@ class LumaImageToVideoGenerationNode(IO.ComfyNode):
             ],
             is_api_node=True,
             price_badge=PRICE_BADGE_VIDEO,
-
         )
 
     @classmethod
@@ -644,6 +645,243 @@ PRICE_BADGE_VIDEO = IO.PriceBadge(
 )
 
 
+def _luma2_uni1_common_inputs(max_image_refs: int) -> list:
+    return [
+        IO.Combo.Input(
+            "style",
+            options=["auto", "manga"],
+            default="auto",
+            tooltip="Style preset. 'auto' picks based on the prompt; "
+            "'manga' applies a manga/anime aesthetic and requires a portrait "
+            "aspect ratio (2:3, 9:16, 1:2, 1:3).",
+        ),
+        IO.Boolean.Input(
+            "web_search",
+            default=False,
+            tooltip="Search the web for visual references before generating.",
+        ),
+        IO.Autogrow.Input(
+            "image_ref",
+            template=IO.Autogrow.TemplateNames(
+                IO.Image.Input("image"),
+                names=[f"image_{i}" for i in range(1, max_image_refs + 1)],
+                min=0,
+            ),
+            optional=True,
+            tooltip=f"Up to {max_image_refs} reference images for style/content guidance.",
+        ),
+    ]
+
+
+async def _luma2_upload_image_refs(
+    cls: type[IO.ComfyNode],
+    refs: dict | None,
+    max_count: int,
+) -> list[Luma2ImageRef] | None:
+    if not refs:
+        return None
+    out: list[Luma2ImageRef] = []
+    for key in refs:
+        url = await upload_image_to_comfyapi(cls, refs[key])
+        out.append(Luma2ImageRef(url=url))
+    if len(out) > max_count:
+        raise ValueError(f"Maximum {max_count} reference images are allowed.")
+    return out or None
+
+
+async def _luma2_submit_and_poll(
+    cls: type[IO.ComfyNode],
+    request: Luma2GenerationRequest,
+) -> Input.Image:
+    initial = await sync_op(
+        cls,
+        ApiEndpoint(path="/proxy/luma_2/generations", method="POST"),
+        response_model=Luma2Generation,
+        data=request,
+    )
+    if not initial.id:
+        raise RuntimeError("Luma 2 API did not return a generation id.")
+    final = await poll_op(
+        cls,
+        ApiEndpoint(path=f"/proxy/luma_2/generations/{initial.id}", method="GET"),
+        response_model=Luma2Generation,
+        status_extractor=lambda r: r.state,
+        progress_extractor=lambda r: None,
+    )
+    if not final.output:
+        msg = final.failure_reason or "no output returned"
+        raise RuntimeError(f"Luma 2 generation failed: {msg}")
+    url = final.output[0].url
+    if not url:
+        raise RuntimeError("Luma 2 generation completed without an output URL.")
+    return await download_url_to_image_tensor(url)
+
+
+class LumaImageNode(IO.ComfyNode):
+
+    @classmethod
+    def define_schema(cls) -> IO.Schema:
+        return IO.Schema(
+            node_id="LumaImageNode2",
+            display_name="Luma UNI-1 Image",
+            category="api node/image/Luma",
+            description="Generate images from text using the Luma UNI-1 model.",
+            inputs=[
+                IO.String.Input(
+                    "prompt",
+                    multiline=True,
+                    default="",
+                    tooltip="Text description of the desired image. 1–6000 characters.",
+                ),
+                IO.DynamicCombo.Input(
+                    "model",
+                    options=[
+                        IO.DynamicCombo.Option(
+                            "uni-1",
+                            [
+                                IO.Combo.Input(
+                                    "aspect_ratio",
+                                    options=[
+                                        "auto",
+                                        "3:1",
+                                        "2:1",
+                                        "16:9",
+                                        "3:2",
+                                        "1:1",
+                                        "2:3",
+                                        "9:16",
+                                        "1:2",
+                                        "1:3",
+                                    ],
+                                    default="auto",
+                                    tooltip="Output image aspect ratio. 'auto' lets "
+                                    "the model pick based on the prompt.",
+                                ),
+                                *_luma2_uni1_common_inputs(max_image_refs=9),
+                            ],
+                        ),
+                    ],
+                    tooltip="Model to use for generation.",
+                ),
+                IO.Int.Input(
+                    "seed",
+                    default=0,
+                    min=0,
+                    max=2147483647,
+                    control_after_generate=True,
+                    tooltip="Seed controls whether the node should re-run; "
+                    "results are non-deterministic regardless of seed.",
+                ),
+            ],
+            outputs=[IO.Image.Output()],
+            hidden=[
+                IO.Hidden.auth_token_comfy_org,
+                IO.Hidden.api_key_comfy_org,
+                IO.Hidden.unique_id,
+            ],
+            is_api_node=True,
+        )
+
+    @classmethod
+    async def execute(
+        cls,
+        prompt: str,
+        model: dict,
+        seed: int,
+    ) -> IO.NodeOutput:
+        validate_string(prompt, min_length=1, max_length=6000)
+        aspect_ratio = model["aspect_ratio"]
+        style = model["style"]
+        allowed_manga_ratios = {"2:3", "9:16", "1:2", "1:3"}
+        if style == "manga" and aspect_ratio != "auto" and aspect_ratio not in allowed_manga_ratios:
+            raise ValueError(
+                f"'manga' style requires a portrait aspect ratio "
+                f"({', '.join(sorted(allowed_manga_ratios))}) or 'auto'; got '{aspect_ratio}'."
+            )
+        request = Luma2GenerationRequest(
+            prompt=prompt,
+            model=model["model"],
+            type="image",
+            aspect_ratio=aspect_ratio if aspect_ratio != "auto" else None,
+            style=style if style != "auto" else None,
+            output_format="png",
+            web_search=model["web_search"],
+            image_ref=await _luma2_upload_image_refs(cls, model.get("image_ref"), max_count=9),
+        )
+        return IO.NodeOutput(await _luma2_submit_and_poll(cls, request))
+
+
+class LumaImageEditNode(IO.ComfyNode):
+
+    @classmethod
+    def define_schema(cls) -> IO.Schema:
+        return IO.Schema(
+            node_id="LumaImageEditNode2",
+            display_name="Luma UNI-1 Image Edit",
+            category="api node/image/Luma",
+            description="Edit an existing image with a text prompt using the Luma UNI-1 model.",
+            inputs=[
+                IO.Image.Input(
+                    "source",
+                    tooltip="Source image to edit.",
+                ),
+                IO.String.Input(
+                    "prompt",
+                    multiline=True,
+                    default="",
+                    tooltip="Description of the desired edit. 1–6000 characters.",
+                ),
+                IO.DynamicCombo.Input(
+                    "model",
+                    options=[
+                        IO.DynamicCombo.Option(
+                            "uni-1",
+                            _luma2_uni1_common_inputs(max_image_refs=8),
+                        ),
+                    ],
+                    tooltip="Model to use for editing.",
+                ),
+                IO.Int.Input(
+                    "seed",
+                    default=0,
+                    min=0,
+                    max=2147483647,
+                    control_after_generate=True,
+                    tooltip="Seed controls whether the node should re-run; "
+                    "results are non-deterministic regardless of seed.",
+                ),
+            ],
+            outputs=[IO.Image.Output()],
+            hidden=[
+                IO.Hidden.auth_token_comfy_org,
+                IO.Hidden.api_key_comfy_org,
+                IO.Hidden.unique_id,
+            ],
+            is_api_node=True,
+        )
+
+    @classmethod
+    async def execute(
+        cls,
+        source: Input.Image,
+        prompt: str,
+        model: dict,
+        seed: int,
+    ) -> IO.NodeOutput:
+        validate_string(prompt, min_length=1, max_length=6000)
+        request = Luma2GenerationRequest(
+            prompt=prompt,
+            model=model["model"],
+            type="image_edit",
+            source=Luma2ImageRef(url=await upload_image_to_comfyapi(cls, source)),
+            style=model["style"] if model["style"] != "auto" else None,
+            output_format="png",
+            web_search=model["web_search"],
+            image_ref=await _luma2_upload_image_refs(cls, model.get("image_ref"), max_count=8),
+        )
+        return IO.NodeOutput(await _luma2_submit_and_poll(cls, request))
+
+
 class LumaExtension(ComfyExtension):
     @override
     async def get_node_list(self) -> list[type[IO.ComfyNode]]:
@@ -654,6 +892,8 @@ class LumaExtension(ComfyExtension):
             LumaImageToVideoGenerationNode,
             LumaReferenceNode,
             LumaConceptsNode,
+            LumaImageNode,
+            LumaImageEditNode,
         ]
 
 

comfy_api_nodes/nodes_openai.py

@@ -454,7 +454,6 @@ class OpenAIGPTImage1(IO.ComfyNode):
                     step=16,
                     tooltip="Used only when `size` is 'Custom'. Must be a multiple of 16 (GPT Image 2 only).",
                     optional=True,
-                    advanced=True,
                 ),
                 IO.Int.Input(
                     "custom_height",
@@ -464,7 +463,6 @@ class OpenAIGPTImage1(IO.ComfyNode):
                     step=16,
                     tooltip="Used only when `size` is 'Custom'. Must be a multiple of 16 (GPT Image 2 only).",
                     optional=True,
-                    advanced=True,
                 ),
             ],
             outputs=[

requirements.txt

@@ -1,5 +1,5 @@
 comfyui-frontend-package==1.42.15
-comfyui-workflow-templates==0.9.63
+comfyui-workflow-templates==0.9.65
 comfyui-embedded-docs==0.4.4
 torch
 torchsde