Merge branch 'master' into feat/api-nodes/seedream-thinking-widget

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

comfy/cli_args.py

@@ -92,7 +92,6 @@ parser.add_argument("--directml", type=int, nargs="?", metavar="DIRECTML_DEVICE"
 parser.add_argument("--oneapi-device-selector", type=str, default=None, metavar="SELECTOR_STRING", help="Sets the oneAPI device(s) this instance will use.")
 parser.add_argument("--supports-fp8-compute", action="store_true", help="ComfyUI will act like if the device supports fp8 compute.")
 parser.add_argument("--enable-triton-backend", action="store_true", help="ComfyUI will enable the use of Triton backend in comfy-kitchen. Is disabled at launch by default.")
-parser.add_argument("--disable-triton-backend", action="store_true", help="Force-disable the comfy-kitchen Triton backend, overriding the automatic ROCm/AMD default and --enable-triton-backend.")
 
 class LatentPreviewMethod(enum.Enum):
     NoPreviews = "none"

comfy/quant_ops.py

@@ -3,22 +3,6 @@ import logging
 
 from comfy.cli_args import args
 
-
-def _rocm_kitchen_arch_supported():
-    """comfy-kitchen's INT8 Triton kernels compile tl.dot to matrix-core instructions.
-    RDNA3/3.5/4 (gfx11xx/gfx12xx) have WMMA and CDNA (gfx9xx) has MFMA; RDNA1/RDNA2
-    (gfx10xx) have neither, so the INT8 path hangs the GPU there. Gates the automatic
-    ROCm default so those cards stay on the eager fallback (an explicit
-    --enable-triton-backend still forces it on any arch)."""
-    try:
-        arch = torch.cuda.get_device_properties(torch.cuda.current_device()).gcnArchName.split(":")[0]
-    except Exception:
-        return False
-    if arch.startswith(("gfx11", "gfx12")):
-        return True
-    return arch in ("gfx908", "gfx90a", "gfx940", "gfx941", "gfx942", "gfx950")
-
-
 try:
     import comfy_kitchen as ck
     from comfy_kitchen.tensor import (
@@ -42,13 +26,9 @@ try:
             logging.warning("WARNING: You need pytorch with cu130 or higher to use optimized CUDA operations.")
 
     # On ROCm/AMD the CUDA backend is unavailable, so Triton is the only accelerated
-    # comfy-kitchen backend. Enable it by default there, but only on Triton >= 3.7 AND a
-    # matrix-core GPU (RDNA3+ WMMA gfx11xx/gfx12xx, CDNA MFMA gfx9xx). RDNA1/RDNA2
-    # (gfx10xx) have no WMMA -> the INT8 tl.dot path hangs the GPU, so they stay eager.
+    # comfy-kitchen backend. Enable it by default there, but only on Triton >= 3.7:
     # older Triton lacks libdevice.rint on the HIP backend and hard-crashes the INT8 path.
-    if args.disable_triton_backend:
-        ck.registry.disable("triton")
-    elif args.enable_triton_backend or (torch.version.hip is not None and _rocm_kitchen_arch_supported()):
+    if args.enable_triton_backend or torch.version.hip is not None:
         try:
             import triton
             triton_version = tuple(int(v) for v in triton.__version__.split(".")[:2])

comfy_api_nodes/apis/hunyuan3d.py

@@ -77,7 +77,6 @@ class To3DUVTaskRequest(BaseModel):
 
 class To3DPartTaskRequest(BaseModel):
     File: TaskFile3DInput = Field(...)
-    EnableStagedGeneration: bool | None = Field(None)
 
 
 class TextureEditImageInfo(BaseModel):

comfy_api_nodes/nodes_hunyuan3d.py

@@ -642,7 +642,6 @@ class Tencent3DPartNode(IO.ComfyNode):
             response_model=To3DProTaskCreateResponse,
             data=To3DPartTaskRequest(
                 File=TaskFile3DInput(Type=file_format.upper(), Url=model_url),
-                EnableStagedGeneration=True,
             ),
             is_rate_limited=_is_tencent_rate_limited,
         )

comfy_execution/jobs.py

@@ -56,9 +56,6 @@ PREVIEWABLE_MEDIA_TYPES = frozenset({'images', 'video', 'audio', '3d', 'text'})
 # 3D file extensions for preview fallback (no dedicated media_type exists)
 THREE_D_EXTENSIONS = frozenset({'.obj', '.fbx', '.gltf', '.glb', '.usdz'})
 
-# Text file extensions for preview fallback (the formats SaveText can produce)
-TEXT_EXTENSIONS = frozenset({'.txt', '.md', '.json'})
-
 
 def has_3d_extension(filename: str) -> bool:
     lower = filename.lower()
@@ -146,10 +143,9 @@ def is_previewable(media_type: str, item: dict) -> bool:
     Maintains backwards compatibility with existing logic.
 
     Priority:
-    1. media_type is 'images', 'video', 'audio', '3d', or 'text'
+    1. media_type is 'images', 'video', 'audio', or '3d'
     2. format field starts with 'video/' or 'audio/'
     3. filename has a 3D extension (.obj, .fbx, .gltf, .glb, .usdz)
-    4. filename has a text extension (.txt, .md, .json, ...)
     """
     if media_type in PREVIEWABLE_MEDIA_TYPES:
         return True
@@ -160,12 +156,10 @@ def is_previewable(media_type: str, item: dict) -> bool:
     if fmt and (fmt.startswith('video/') or fmt.startswith('audio/')):
         return True
 
-    # Check for 3D and text files by extension
+    # Check for 3D files by extension
     filename = item.get('filename', '').lower()
     if any(filename.endswith(ext) for ext in THREE_D_EXTENSIONS):
         return True
-    if any(filename.endswith(ext) for ext in TEXT_EXTENSIONS):
-        return True
 
     return False
 
@@ -261,10 +255,6 @@ def get_outputs_summary(outputs: dict) -> tuple[int, Optional[dict]]:
     Preview priority (matching frontend):
     1. type="output" with previewable media
     2. Any previewable media
-
-    Text content entries (strings under 'text') are preview-only metadata,
-    matching the frontend's METADATA_KEYS: they can serve as the fallback
-    preview but are not counted as outputs.
     """
     count = 0
     preview_output = None
@@ -285,6 +275,7 @@ def get_outputs_summary(outputs: dict) -> tuple[int, Optional[dict]]:
                     if normalized is None:
                         # Not a 3D file string — check for text preview
                         if media_type == 'text':
+                            count += 1
                             if preview_output is None:
                                 if isinstance(item, tuple):
                                     text_value = item[0] if item else ''

comfy_extras/nodes_bounding_boxes.py

@@ -1,5 +1,3 @@
-import json
-
 import numpy as np
 import torch
 from PIL import Image, ImageDraw, ImageEnhance, ImageFont
@@ -168,111 +166,6 @@ def boxes_to_regions(boxes, width: int, height: int) -> list:
     return regions
 
 
-def normalize_incoming_boxes(bboxes) -> list:
-    if isinstance(bboxes, dict):
-        frame = [bboxes]
-    elif not isinstance(bboxes, list) or not bboxes:
-        frame = []
-    elif isinstance(bboxes[0], dict):
-        frame = bboxes
-    else:
-        frame = bboxes[0] if isinstance(bboxes[0], list) else []
-    boxes = []
-    for box in frame:
-        if not isinstance(box, dict):
-            continue
-        norm = {
-            "x": box.get("x", 0),
-            "y": box.get("y", 0),
-            "width": box.get("width", 0),
-            "height": box.get("height", 0),
-        }
-        meta = box.get("metadata")
-        if isinstance(meta, dict):
-            norm["metadata"] = meta
-        boxes.append(norm)
-    return boxes
-
-
-def _looks_like_element(box: dict) -> bool:
-    bbox = box.get("bbox")
-    return isinstance(bbox, (list, tuple)) and len(bbox) == 4
-
-
-def _looks_like_bbox(box: dict) -> bool:
-    return all(key in box for key in ("x", "y", "width", "height"))
-
-
-def elements_to_boxes(elements: list, width: int, height: int) -> list:
-    boxes = []
-    for element in elements:
-        if not isinstance(element, dict):
-            continue
-        bbox = element.get("bbox")
-        if not (isinstance(bbox, (list, tuple)) and len(bbox) == 4):
-            raise ValueError("bboxes element is missing a valid 'bbox' [ymin, xmin, ymax, xmax]")
-        try:
-            ymin, xmin, ymax, xmax = (float(v) / 1000.0 for v in bbox)
-        except (TypeError, ValueError):
-            raise ValueError("bboxes element 'bbox' must contain four numbers")
-        etype = "text" if element.get("type") == "text" else "obj"
-        boxes.append({
-            "x": round(min(xmin, xmax) * width),
-            "y": round(min(ymin, ymax) * height),
-            "width": round(abs(xmax - xmin) * width),
-            "height": round(abs(ymax - ymin) * height),
-            "metadata": {
-                "type": etype,
-                "text": element.get("text", "") if etype == "text" else "",
-                "desc": element.get("desc", ""),
-                "palette": element.get("color_palette", []) or [],
-            },
-        })
-    return boxes
-
-
-def boxes_from_input(data, width: int, height: int) -> list:
-    if data is None:
-        return []
-    if isinstance(data, str):
-        text = data.strip()
-        if not text:
-            return []
-        try:
-            data = json.loads(text)
-        except (ValueError, TypeError) as exc:
-            raise ValueError(f"bboxes string input is not valid JSON: {exc}") from exc
-    if isinstance(data, dict):
-        if _looks_like_element(data):
-            return elements_to_boxes([data], width, height)
-        if _looks_like_bbox(data):
-            return normalize_incoming_boxes(data)
-        raise ValueError(
-            "bboxes dict must be a bounding box (x, y, width, height) or an element (with a 'bbox')"
-        )
-    if not isinstance(data, list):
-        raise ValueError(
-            "bboxes input must be bounding boxes, elements, or a JSON string, "
-            f"got {type(data).__name__}"
-        )
-    if not data:
-        return []
-    first = data[0]
-    if isinstance(first, list):
-        return normalize_incoming_boxes(data)
-    if isinstance(first, dict):
-        if _looks_like_element(first):
-            return elements_to_boxes(data, width, height)
-        if _looks_like_bbox(first):
-            return normalize_incoming_boxes(data)
-        raise ValueError(
-            "bboxes items must be bounding boxes (x, y, width, height) or elements (with a 'bbox')"
-        )
-    raise ValueError(
-        f"bboxes list must contain bounding boxes or elements, got {type(first).__name__}"
-    )
-
-
 def _norm_bbox(region: dict) -> list[int]:
     def grid(value: float) -> int:
         return max(0, min(1000, round(value * 1000)))
@@ -324,48 +217,29 @@ class CreateBoundingBoxes(io.ComfyNode):
                     optional=True,
                     tooltip="Optional image used as background in the canvas and preview.",
                 ),
-                io.MultiType.Input(
-                    "bboxes",
-                    [io.BoundingBox, io.Array, io.String],
-                    optional=True,
-                    tooltip="Bounding boxes, elements, or a JSON string to initialize the canvas. A new upstream value initializes the canvas; edits made on the canvas take priority and are kept until the upstream value changes again.",
-                ),
                 io.Int.Input("width", default=1024, min=64, max=16384, step=16,
                              tooltip="Width of the canvas and the pixel grid for the bounding boxes."),
                 io.Int.Input("height", default=1024, min=64, max=16384, step=16,
                              tooltip="Height of the canvas and the pixel grid for the bounding boxes."),
                 editor_state,
-                io.BoundingBoxes.Input(
-                    "last_incoming",
-                    optional=True,
-                    tooltip="Internal state managed by the canvas: the upstream bboxes value that last initialized it. Leave empty to re-initialize the canvas from the bboxes input on the next run.",
-                ),
             ],
             outputs=[
                 io.Image.Output(display_name="preview"),
                 io.BoundingBox.Output(display_name="bboxes"),
                 io.Array.Output(display_name="elements"),
             ],
-            is_output_node=True,
             is_experimental=True,
         )
 
     @classmethod
-    def execute(cls, width, height, editor_state=None, last_incoming=None, background=None, bboxes=None) -> io.NodeOutput:
-        incoming = boxes_from_input(bboxes, width, height)
-        applied = last_incoming if isinstance(last_incoming, list) else []
-        upstream_changed = bool(incoming) and incoming != applied
-        source = incoming if upstream_changed else (editor_state or [])
-        regions = boxes_to_regions(source, width, height)
+    def execute(cls, width, height, editor_state=None, background=None) -> io.NodeOutput:
+        regions = boxes_to_regions(editor_state, width, height)
         preview = render_preview(regions, width, height, _bg_from_image(background))
-        ui = {"dims": [width, height]}
-        if incoming:
-            ui["input_bboxes"] = incoming
         return io.NodeOutput(
             preview,
             fractions_to_bbox_frame(regions, width, height),
             build_elements(regions),
-            ui=ui,
+            ui={"dims": [width, height]},
         )
 
 

comfy_extras/nodes_save_3d.py

@@ -13,7 +13,7 @@ from typing_extensions import override
 
 import folder_paths
 from comfy.cli_args import args
-from comfy_api.latest import ComfyExtension, IO, Types, UI
+from comfy_api.latest import ComfyExtension, IO, Types
 
 
 def pack_variable_mesh_batch(vertices, faces, colors=None, uvs=None, texture=None, unlit=False):
@@ -406,164 +406,10 @@ class SaveGLB(IO.ComfyNode):
         return IO.NodeOutput(ui={"3d": results})
 
 
-def _save_file3d_to_output(model_3d: Types.File3D, filename_prefix: str) -> str:
-    full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(
-        filename_prefix, folder_paths.get_output_directory()
-    )
-    ext = model_3d.format or "glb"
-    saved_filename = f"{filename}_{counter:05}.{ext}"
-    model_3d.save_to(os.path.join(full_output_folder, saved_filename))
-    return f"{subfolder}/{saved_filename}" if subfolder else saved_filename
-
-
-def execute_save_3d_advanced(model_3d, viewport_state, width, height, filename_prefix, kwargs) -> IO.NodeOutput:
-    model_file = _save_file3d_to_output(model_3d, filename_prefix)
-    camera_info_input = kwargs.get("camera_info", None)
-    camera_info = camera_info_input if camera_info_input is not None else viewport_state['camera_info']
-    model_3d_info_input = kwargs.get("model_3d_info", None)
-    model_3d_info = model_3d_info_input if model_3d_info_input is not None else viewport_state.get('model_3d_info', [])
-    return IO.NodeOutput(
-        model_3d,
-        model_3d_info,
-        camera_info,
-        width,
-        height,
-        ui=UI.PreviewUI3DAdvanced(model_file, camera_info, model_3d_info),
-    )
-
-
-class Save3DAdvanced(IO.ComfyNode):
-    @classmethod
-    def define_schema(cls):
-        return IO.Schema(
-            node_id="Save3DAdvanced",
-            display_name="Save 3D (Advanced)",
-            search_aliases=["save 3d", "export 3d model", "save mesh advanced"],
-            category="3d",
-            is_experimental=True,
-            is_output_node=True,
-            inputs=[
-                IO.MultiType.Input(
-                    "model_3d",
-                    types=[
-                        IO.File3DGLB,
-                        IO.File3DGLTF,
-                        IO.File3DFBX,
-                        IO.File3DOBJ,
-                        IO.File3DSTL,
-                        IO.File3DUSDZ,
-                        IO.File3DAny,
-                    ],
-                    tooltip="3D model file from an upstream 3D node.",
-                ),
-                IO.String.Input("filename_prefix", default="3d/ComfyUI"),
-                IO.Load3D.Input("viewport_state"),
-                IO.Load3DModelInfo.Input("model_3d_info", optional=True, advanced=True),
-                IO.Load3DCamera.Input("camera_info", optional=True, advanced=True),
-                IO.Int.Input("width", default=1024, min=1, max=4096, step=1),
-                IO.Int.Input("height", default=1024, min=1, max=4096, step=1),
-            ],
-            outputs=[
-                IO.File3DAny.Output(display_name="model_3d"),
-                IO.Load3DModelInfo.Output(display_name="model_3d_info"),
-                IO.Load3DCamera.Output(display_name="camera_info"),
-                IO.Int.Output(display_name="width"),
-                IO.Int.Output(display_name="height"),
-            ],
-        )
-
-    @classmethod
-    def execute(cls, model_3d: Types.File3D, viewport_state, width: int, height: int, filename_prefix: str, **kwargs) -> IO.NodeOutput:
-        return execute_save_3d_advanced(model_3d, viewport_state, width, height, filename_prefix, kwargs)
-
-
-class SaveGaussianSplat(IO.ComfyNode):
-    @classmethod
-    def define_schema(cls):
-        return IO.Schema(
-            node_id="SaveGaussianSplat",
-            display_name="Save Splat",
-            search_aliases=["save splat", "save gaussian splat", "export gaussian", "export splat"],
-            category="3d",
-            is_experimental=True,
-            is_output_node=True,
-            inputs=[
-                IO.MultiType.Input(
-                    "model_3d",
-                    types=[
-                        IO.File3DSplatAny,
-                        IO.File3DPLY,
-                        IO.File3DSPLAT,
-                        IO.File3DSPZ,
-                        IO.File3DKSPLAT,
-                    ],
-                    tooltip="A gaussian splat 3D file.",
-                ),
-                IO.String.Input("filename_prefix", default="3d/ComfyUI"),
-                IO.Load3D.Input("viewport_state"),
-                IO.Load3DModelInfo.Input("model_3d_info", optional=True, advanced=True),
-                IO.Load3DCamera.Input("camera_info", optional=True, advanced=True),
-                IO.Int.Input("width", default=1024, min=1, max=4096, step=1),
-                IO.Int.Input("height", default=1024, min=1, max=4096, step=1),
-            ],
-            outputs=[
-                IO.File3DSplatAny.Output(display_name="model_3d"),
-                IO.Load3DModelInfo.Output(display_name="model_3d_info"),
-                IO.Load3DCamera.Output(display_name="camera_info"),
-                IO.Int.Output(display_name="width"),
-                IO.Int.Output(display_name="height"),
-            ],
-        )
-
-    @classmethod
-    def execute(cls, model_3d: Types.File3D, viewport_state, width: int, height: int, filename_prefix: str, **kwargs) -> IO.NodeOutput:
-        return execute_save_3d_advanced(model_3d, viewport_state, width, height, filename_prefix, kwargs)
-
-
-class SavePointCloud(IO.ComfyNode):
-    @classmethod
-    def define_schema(cls):
-        return IO.Schema(
-            node_id="SavePointCloud",
-            display_name="Save Point Cloud",
-            search_aliases=["save point cloud", "save pointcloud", "export point cloud"],
-            category="3d",
-            is_experimental=True,
-            is_output_node=True,
-            inputs=[
-                IO.MultiType.Input(
-                    "model_3d",
-                    types=[
-                        IO.File3DPointCloudAny,
-                        IO.File3DPLY,
-                    ],
-                    tooltip="Point cloud file (.ply)",
-                ),
-                IO.String.Input("filename_prefix", default="3d/ComfyUI"),
-                IO.Load3D.Input("viewport_state"),
-                IO.Load3DModelInfo.Input("model_3d_info", optional=True, advanced=True),
-                IO.Load3DCamera.Input("camera_info", optional=True, advanced=True),
-                IO.Int.Input("width", default=1024, min=1, max=4096, step=1),
-                IO.Int.Input("height", default=1024, min=1, max=4096, step=1),
-            ],
-            outputs=[
-                IO.File3DPointCloudAny.Output(display_name="model_3d"),
-                IO.Load3DModelInfo.Output(display_name="model_3d_info"),
-                IO.Load3DCamera.Output(display_name="camera_info"),
-                IO.Int.Output(display_name="width"),
-                IO.Int.Output(display_name="height"),
-            ],
-        )
-
-    @classmethod
-    def execute(cls, model_3d: Types.File3D, viewport_state, width: int, height: int, filename_prefix: str, **kwargs) -> IO.NodeOutput:
-        return execute_save_3d_advanced(model_3d, viewport_state, width, height, filename_prefix, kwargs)
-
-
 class Save3DExtension(ComfyExtension):
     @override
     async def get_node_list(self) -> list[type[IO.ComfyNode]]:
-        return [SaveGLB, Save3DAdvanced, SaveGaussianSplat, SavePointCloud]
+        return [SaveGLB]
 
 
 async def comfy_entrypoint() -> Save3DExtension:

comfy_extras/nodes_text.py

@@ -1,71 +0,0 @@
-import os
-import json
-from typing_extensions import override
-from comfy_api.latest import io, ComfyExtension, ui
-import folder_paths
-
-
-class SaveTextNode(io.ComfyNode):
-    """Save text content to .txt, .md, or .json."""
-
-    @classmethod
-    def define_schema(cls):
-        return io.Schema(
-            node_id="SaveText",
-            search_aliases=["save text", "write text", "export text"],
-            display_name="Save Text",
-            category="text",
-            description="Save text content to a file in the output directory.",
-            inputs=[
-                io.String.Input("text", force_input=True),
-                io.String.Input("filename_prefix", default="ComfyUI"),
-                io.Combo.Input("format", options=["txt", "md", "json"], default="txt"),
-            ],
-            outputs=[io.String.Output(display_name="text")],
-            is_output_node=True,
-        )
-
-    @classmethod
-    def execute(cls, text, filename_prefix, format):
-        full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(
-            filename_prefix,
-            folder_paths.get_output_directory(),
-            1,
-            1,
-        )
-
-        file = f"{filename}_{counter:05}.{format}"
-        filepath = os.path.join(full_output_folder, file)
-
-        if format == "json":
-            # tries to pretty print otherwise saves normally
-            try:
-                data = json.loads(text)
-                with open(filepath, "w", encoding="utf-8") as f:
-                    json.dump(data, f, indent=2, ensure_ascii=False)
-            except json.JSONDecodeError:
-                with open(filepath, "w", encoding="utf-8") as f:
-                    f.write(text)
-        else:
-            with open(filepath, "w", encoding="utf-8") as f:
-                f.write(text)
-
-        return io.NodeOutput(
-            text,
-            ui={
-                "text": (text,),
-                "files": [
-                    ui.SavedResult(file, subfolder, io.FolderType.output)
-                ]
-            }
-        )
-
-class TextExtension(ComfyExtension):
-    @override
-    async def get_node_list(self) -> list[type[io.ComfyNode]]:
-        return [
-            SaveTextNode
-        ]
-
-async def comfy_entrypoint() -> TextExtension:
-    return TextExtension()

nodes.py

@@ -2504,7 +2504,6 @@ async def init_builtin_extra_nodes():
         "nodes_triposplat.py",
         "nodes_depth_anything_3.py",
         "nodes_seed.py",
-        "nodes_text.py",
     ]
 
     import_failed = []