Deprecate legacy nodes

The /ws path uses HTTP 101 (Switching Protocols), which is the correct
response for a WebSocket upgrade but not a 2xx. The built-in
operation-success-response rule fires as a false positive because
OpenAPI 3.x has no native WebSocket support.

Add a path-scoped override in .spectral.yaml to disable the rule for
/ws only, leaving it active for all other operations.

.spectral.yaml

@@ -89,3 +89,12 @@ rules:
     then:
       field: description
       function: truthy
+
+overrides:
+  # /ws uses HTTP 101 (Switching Protocols) — a legitimate response for a
+  # WebSocket upgrade, but not a 2xx, so operation-success-response fires
+  # as a false positive. OpenAPI 3.x has no native WebSocket support.
+  - files:
+      - "openapi.yaml#/paths/~1ws"
+    rules:
+      operation-success-response: off

comfy/supported_models.py

@@ -1443,7 +1443,7 @@ class HiDreamO1(supported_models_base.BASE):
     }
 
     latent_format = latent_formats.HiDreamO1Pixel
-    memory_usage_factor = 0.6
+    memory_usage_factor = 0.033
     # fp16 not supported: LM MLP down_proj activations fp16 overflow, causing NaNs
     supported_inference_dtypes = [torch.bfloat16, torch.float32]
 

comfy_api_nodes/nodes_quiver.py

@@ -143,7 +143,7 @@ class QuiverTextToSVGNode(IO.ComfyNode):
         if reference_images:
             references = []
             for key in reference_images:
-                url = await upload_image_to_comfyapi(cls, reference_images[key])
+                url = await upload_image_to_comfyapi(cls, reference_images[key], mime_type="image/png")
                 references.append(QuiverImageObject(url=url))
             if len(references) > 4:
                 raise ValueError("Maximum 4 reference images are allowed.")
@@ -252,7 +252,7 @@ class QuiverImageToSVGNode(IO.ComfyNode):
         model: dict,
         seed: int,
     ) -> IO.NodeOutput:
-        image_url = await upload_image_to_comfyapi(cls, image)
+        image_url = await upload_image_to_comfyapi(cls, image, mime_type="image/png")
 
         response = await sync_op(
             cls,

comfy_extras/nodes_audio.py

@@ -158,7 +158,7 @@ class SaveAudio(IO.ComfyNode):
         return IO.Schema(
             node_id="SaveAudio",
             search_aliases=["export flac"],
-            display_name="Save Audio (FLAC)",
+            display_name="Save Audio (FLAC) (Deprecated)",
             category="audio",
             essentials_category="Audio",
             inputs=[
@@ -167,6 +167,7 @@ class SaveAudio(IO.ComfyNode):
             ],
             hidden=[IO.Hidden.prompt, IO.Hidden.extra_pnginfo],
             is_output_node=True,
+            is_deprecated=True,
         )
 
     @classmethod
@@ -184,7 +185,7 @@ class SaveAudioMP3(IO.ComfyNode):
         return IO.Schema(
             node_id="SaveAudioMP3",
             search_aliases=["export mp3"],
-            display_name="Save Audio (MP3)",
+            display_name="Save Audio (MP3) (Deprecated)",
             category="audio",
             essentials_category="Audio",
             inputs=[
@@ -194,6 +195,7 @@ class SaveAudioMP3(IO.ComfyNode):
             ],
             hidden=[IO.Hidden.prompt, IO.Hidden.extra_pnginfo],
             is_output_node=True,
+            is_deprecated=True,
         )
 
     @classmethod
@@ -213,7 +215,7 @@ class SaveAudioOpus(IO.ComfyNode):
         return IO.Schema(
             node_id="SaveAudioOpus",
             search_aliases=["export opus"],
-            display_name="Save Audio (Opus)",
+            display_name="Save Audio (Opus) (Deprecated)",
             category="audio",
             inputs=[
                 IO.Audio.Input("audio"),
@@ -222,6 +224,7 @@ class SaveAudioOpus(IO.ComfyNode):
             ],
             hidden=[IO.Hidden.prompt, IO.Hidden.extra_pnginfo],
             is_output_node=True,
+            is_deprecated=True,
         )
 
     @classmethod
@@ -235,6 +238,54 @@ class SaveAudioOpus(IO.ComfyNode):
     save_opus = execute  # TODO: remove
 
 
+class SaveAudioAdvanced(IO.ComfyNode):
+    @classmethod
+    def define_schema(cls):
+        return IO.Schema(
+            node_id="SaveAudioAdvanced",
+            search_aliases=["save audio", "export audio", "output audio", "write audio", "flac", "mp3", "opus"],
+            display_name="Save Audio (Advanced)",
+            description="Saves the input audio to your ComfyUI output directory.",
+            category="audio",
+            inputs=[
+                IO.Audio.Input("audio", tooltip="The audio to save."),
+                IO.String.Input(
+                    "filename_prefix",
+                    default="audio/ComfyUI",
+                    tooltip=(
+                        "The prefix for the file to save. May include formatting tokens "
+                        "such as %date:yyyy-MM-dd%."
+                    ),
+                ),
+                IO.DynamicCombo.Input(
+                    "format",
+                    options=[
+                        IO.DynamicCombo.Option("flac", []),
+                        IO.DynamicCombo.Option("mp3", [
+                            IO.Combo.Input("quality", options=["V0", "128k", "320k"], default="V0"),
+                        ]),
+                        IO.DynamicCombo.Option("opus", [
+                            IO.Combo.Input("quality", options=["64k", "96k", "128k", "192k", "320k"], default="128k"),
+                        ]),
+                    ],
+                    tooltip="The file format in which to save the audio.",
+                ),
+            ],
+            hidden=[IO.Hidden.prompt, IO.Hidden.extra_pnginfo],
+            is_output_node=True,
+        )
+
+    @classmethod
+    def execute(cls, audio, filename_prefix: str, format: dict) -> IO.NodeOutput:
+        file_format = format.get("format", None)
+        quality = format.get("quality", None)
+        if quality:
+            ui=UI.AudioSaveHelper.get_save_audio_ui(audio, filename_prefix=filename_prefix, cls=cls, format=file_format, quality=quality)
+        else:
+            ui=UI.AudioSaveHelper.get_save_audio_ui(audio, filename_prefix=filename_prefix, cls=cls, format=file_format)
+        return IO.NodeOutput(ui=ui)
+
+
 class PreviewAudio(IO.ComfyNode):
     @classmethod
     def define_schema(cls):
@@ -297,6 +348,7 @@ class LoadAudio(IO.ComfyNode):
     @classmethod
     def define_schema(cls):
         input_dir = folder_paths.get_input_directory()
+        os.makedirs(input_dir, exist_ok=True)
         files = folder_paths.filter_files_content_types(os.listdir(input_dir), ["audio", "video"])
         return IO.Schema(
             node_id="LoadAudio",
@@ -776,6 +828,7 @@ class AudioExtension(ComfyExtension):
             SaveAudio,
             SaveAudioMP3,
             SaveAudioOpus,
+            SaveAudioAdvanced,
             LoadAudio,
             PreviewAudio,
             ConditioningStableAudio,

comfy_extras/nodes_images.py

@@ -3,23 +3,15 @@ from __future__ import annotations
 import nodes
 import folder_paths
 
-import av
 import json
-
 import os
 import re
 import math
-import numpy as np
-import struct
 import torch
-
-import zlib
 import comfy.utils
-from fractions import Fraction
 
 from server import PromptServer
 from comfy_api.latest import ComfyExtension, IO, UI
-from comfy.cli_args import args
 from typing_extensions import override
 
 SVG = IO.SVG.Type  # TODO: temporary solution for backward compatibility, will be removed later.
@@ -838,405 +830,6 @@ class ImageMergeTileList(IO.ComfyNode):
         return IO.NodeOutput(merged_image)
 
 
-# ---------------------------------------------------------------------------
-# Format specifications
-# ---------------------------------------------------------------------------
-
-# Maps (file_format, bit_depth, has_alpha) -> (numpy dtype scale, av pixel format,
-# stream pix_fmt). Keeps the encode path declarative instead of branchy.
-_FORMAT_SPECS = {
-    ("png", "8-bit", False):  {"scale": 255.0,   "dtype": np.uint8,   "frame_fmt": "rgb24",     "stream_fmt": "rgb24"},
-    ("png", "8-bit", True):   {"scale": 255.0,   "dtype": np.uint8,   "frame_fmt": "rgba",      "stream_fmt": "rgba"},
-    ("png", "16-bit", False): {"scale": 65535.0, "dtype": np.uint16,  "frame_fmt": "rgb48le",   "stream_fmt": "rgb48be"},
-    ("png", "16-bit", True):  {"scale": 65535.0, "dtype": np.uint16,  "frame_fmt": "rgba64le",  "stream_fmt": "rgba64be"},
-    ("exr", "32-bit float", False): {"scale": 1.0, "dtype": np.float32, "frame_fmt": "gbrpf32le",  "stream_fmt": "gbrpf32le"},
-    ("exr", "32-bit float", True):  {"scale": 1.0, "dtype": np.float32, "frame_fmt": "gbrapf32le", "stream_fmt": "gbrapf32le"},
-}
-
-
-# ---------------------------------------------------------------------------
-# Color transforms
-# ---------------------------------------------------------------------------
-
-def srgb_to_linear(t: torch.Tensor) -> torch.Tensor:
-    """Inverse sRGB EOTF (IEC 61966-2-1). Operates on RGB channels only;
-    alpha (if present as the 4th channel) is passed through unchanged."""
-    if t.shape[-1] == 4:
-        rgb, alpha = t[..., :3], t[..., 3:]
-        return torch.cat([srgb_to_linear(rgb), alpha], dim=-1)
-
-    # Piecewise: linear toe below 0.04045, gamma curve above.
-    low = t / 12.92
-    high = ((t.clamp(min=0.0) + 0.055) / 1.055) ** 2.4
-    return torch.where(t <= 0.04045, low, high)
-
-
-# HLG OETF constants from BT.2100 Table 5.
-_HLG_A = 0.17883277
-_HLG_B = 0.28466892
-_HLG_C = 0.55991072928   # = 0.5 - a*ln(4*a)
-
-
-def hlg_to_linear(t: torch.Tensor) -> torch.Tensor:
-    """Inverse HLG OETF (BT.2100). Maps a non-linear HLG signal in [0, 1] to
-    *scene*-linear light in [0, 1]. Per BT.2100 Note 5a, this is the correct
-    transform when converting HLG to a linear scene-light representation
-    (rather than display-light, which would also involve the HLG OOTF).
-
-    Operates on RGB channels only; alpha is passed through unchanged."""
-    if t.shape[-1] == 4:
-        rgb, alpha = t[..., :3], t[..., 3:]
-        return torch.cat([hlg_to_linear(rgb), alpha], dim=-1)
-
-    # Piecewise: sqrt branch below 0.5, log branch above.
-    # Clamp inside the log branch so negative / out-of-range values don't blow up;
-    # values above 1.0 are allowed and extrapolate naturally.
-    low = (t ** 2) / 3.0
-    high = (torch.exp((t.clamp(min=_HLG_C) - _HLG_C) / _HLG_A) + _HLG_B) / 12.0
-    return torch.where(t <= 0.5, low, high)
-
-
-# ---------------------------------------------------------------------------
-# Metadata injection
-# ---------------------------------------------------------------------------
-
-_PNG_SIGNATURE = b"\x89PNG\r\n\x1a\n"
-
-
-def _png_chunk(chunk_type: bytes, data: bytes) -> bytes:
-    """Build a single PNG chunk: length | type | data | CRC32(type+data)."""
-    crc = zlib.crc32(chunk_type + data) & 0xFFFFFFFF
-    return struct.pack(">I", len(data)) + chunk_type + data + struct.pack(">I", crc)
-
-
-def _png_text_chunk(keyword: str, text: str) -> bytes:
-    """tEXt chunk: latin-1 keyword + NUL + latin-1 text."""
-    payload = keyword.encode("latin-1") + b"\x00" + text.encode("latin-1", errors="replace")
-    return _png_chunk(b"tEXt", payload)
-
-
-def inject_png_metadata(png_bytes: bytes, prompt: dict | None, extra_pnginfo: dict | None) -> bytes:
-    """Insert ComfyUI prompt/workflow as tEXt chunks right after IHDR."""
-    if not png_bytes.startswith(_PNG_SIGNATURE):
-        return png_bytes
-
-    chunks: list[bytes] = []
-    if prompt is not None:
-        chunks.append(_png_text_chunk("prompt", json.dumps(prompt)))
-    if extra_pnginfo:
-        for key, value in extra_pnginfo.items():
-            chunks.append(_png_text_chunk(key, json.dumps(value)))
-    if not chunks:
-        return png_bytes
-
-    # IHDR is always the first chunk; insert ours immediately after it.
-    ihdr_length = struct.unpack(">I", png_bytes[8:12])[0]
-    ihdr_end = 8 + 8 + ihdr_length + 4  # signature + (len+type) + data + crc
-    return png_bytes[:ihdr_end] + b"".join(chunks) + png_bytes[ihdr_end:]
-
-
-# Standard chromaticities (CIE 1931 xy) for the colorspaces this node writes.
-# Each tuple is (Rx, Ry, Gx, Gy, Bx, By, Wx, Wy). All share D65 white point.
-_CHROMATICITIES = {
-    # ITU-R BT.709 / sRGB primaries
-    "Rec.709":  (0.6400, 0.3300, 0.3000, 0.6000, 0.1500, 0.0600, 0.3127, 0.3290),
-    # ITU-R BT.2020 (UHDTV / wide-gamut HDR) primaries
-    "Rec.2020": (0.7080, 0.2920, 0.1700, 0.7970, 0.1310, 0.0460, 0.3127, 0.3290),
-}
-
-
-def _pack_chromaticities(primaries: tuple) -> bytes:
-    """Serialize 8 chromaticity floats into the EXR `chromaticities` payload."""
-    return struct.pack("<8f", *primaries)
-
-
-def _exr_attribute(name: str, attr_type: str, value: bytes) -> bytes:
-    """Serialize one EXR header attribute: name\\0 type\\0 size:int32 value."""
-    return (
-        name.encode("utf-8") + b"\x00"
-        + attr_type.encode("utf-8") + b"\x00"
-        + struct.pack("<i", len(value))
-        + value
-    )
-
-
-def inject_exr_metadata(
-    exr_bytes: bytes,
-    prompt: dict | None,
-    extra_pnginfo: dict | None,
-    colorspace: str | None = None,
-) -> bytes:
-    """Insert ComfyUI metadata and color-space info into an EXR header.
-
-    Color: EXR pixels are linear by convention. The standard way to describe
-    their RGB→XYZ relationship is the `chromaticities` attribute. We pick the
-    primaries that match what the user told us their input was:
-
-      colorspace="sRGB" → Rec. 709 / sRGB primaries (D65)
-      colorspace="HDR"  → Rec. 2020 / BT.2100 primaries (D65)
-
-    Pixels are always converted to linear scene light upstream (sRGB EOTF
-    inverse for sRGB; HLG OETF inverse for HDR), so the file content is
-    scene-linear in the indicated gamut. OpenEXR has no standard transfer-
-    function attribute (the OpenEXR TSC has discussed adding one but it
-    doesn't exist), so we don't invent one — `chromaticities` plus the EXR
-    linear-by-convention rule fully specifies the color.
-
-    Prompt/workflow: written as plain `string` attributes using the same keys
-    (`prompt`, `workflow`, ...) that Comfy uses for PNG tEXt chunks, so the
-    same readers can pull them out symmetrically.
-
-    Implementation note: the chunk-offset table that follows the header stores
-    *absolute* byte offsets into the file. Inserting N bytes into the header
-    means every offset must be incremented by N or the file becomes unreadable.
-    """
-    if len(exr_bytes) < 8 or exr_bytes[:4] != b"\x76\x2f\x31\x01":
-        return exr_bytes
-
-    new_blob = b""
-    if prompt is not None:
-        new_blob += _exr_attribute("prompt", "string", json.dumps(prompt).encode("utf-8"))
-    if extra_pnginfo:
-        for key, value in extra_pnginfo.items():
-            new_blob += _exr_attribute(key, "string", json.dumps(value).encode("utf-8"))
-    if colorspace is not None:
-        # Map each colorspace option to the RGB primaries the linear pixels
-        # are now in. "sRGB" and "linear" both produce Rec. 709 linear; "HDR"
-        # (HLG-encoded Rec. 2020 input) produces Rec. 2020 linear.
-        primaries_name = {
-            "sRGB":   "Rec.709",
-            "linear": "Rec.709",
-            "HDR":    "Rec.2020",
-        }.get(colorspace, "Rec.709")
-        new_blob += _exr_attribute(
-            "chromaticities",
-            "chromaticities",
-            _pack_chromaticities(_CHROMATICITIES[primaries_name]),
-        )
-    if not new_blob:
-        return exr_bytes
-
-    # Walk header attributes to find the terminating null byte, and pick up
-    # dataWindow + compression so we know how many chunks the offset table has.
-    pos = 8  # past magic (4) + version (4)
-    data_window = None
-    compression = 0
-    while pos < len(exr_bytes) and exr_bytes[pos] != 0:
-        name_end = exr_bytes.index(b"\x00", pos)
-        attr_name = exr_bytes[pos:name_end].decode("latin-1", errors="replace")
-        type_end = exr_bytes.index(b"\x00", name_end + 1)
-        attr_type = exr_bytes[name_end + 1:type_end].decode("latin-1", errors="replace")
-        size = struct.unpack("<i", exr_bytes[type_end + 1:type_end + 5])[0]
-        value_start = type_end + 5
-        value = exr_bytes[value_start:value_start + size]
-
-        if attr_name == "dataWindow" and attr_type == "box2i":
-            data_window = struct.unpack("<iiii", value)  # xMin, yMin, xMax, yMax
-        elif attr_name == "compression" and attr_type == "compression":
-            compression = value[0]
-
-        pos = value_start + size
-
-    if data_window is None:
-        return exr_bytes  # required attribute missing — don't risk corrupting
-
-    # Scanlines per chunk by compression, from the OpenEXR spec.
-    scanlines_per_block = {
-        0: 1,   # NO_COMPRESSION
-        1: 1,   # RLE
-        2: 1,   # ZIPS
-        3: 16,  # ZIP
-        4: 32,  # PIZ
-        5: 16,  # PXR24
-        6: 32,  # B44
-        7: 32,  # B44A
-        8: 256, # DWAA
-        9: 256, # DWAB
-    }.get(compression, 1)
-
-    _, y_min, _, y_max = data_window
-    height = y_max - y_min + 1
-    num_chunks = (height + scanlines_per_block - 1) // scanlines_per_block
-
-    header_end = pos  # position of the terminating null byte
-    table_start = header_end + 1
-    pixel_start = table_start + num_chunks * 8
-    delta = len(new_blob)
-
-    old_offsets = struct.unpack(f"<{num_chunks}Q", exr_bytes[table_start:pixel_start])
-    new_table = struct.pack(f"<{num_chunks}Q", *(o + delta for o in old_offsets))
-
-    return (
-        exr_bytes[:header_end]                # header attributes
-        + new_blob                            # our new attributes
-        + exr_bytes[header_end:table_start]   # terminating null byte
-        + new_table                           # shifted offset table
-        + exr_bytes[pixel_start:]             # pixel data, untouched
-    )
-
-
-# ---------------------------------------------------------------------------
-# Encoding
-# ---------------------------------------------------------------------------
-
-def _encode_image(
-    img_tensor: torch.Tensor,
-    file_format: str,
-    bit_depth: str,
-    colorspace: str,
-) -> bytes:
-    """Encode a single HxWxC tensor to PNG or EXR bytes in memory.
-
-    For EXR the input is interpreted according to `colorspace` and converted
-    to scene-linear (EXR's convention) before writing:
-
-      "sRGB"   → input is sRGB-encoded Rec. 709; apply inverse sRGB EOTF.
-      "HDR"    → input is HLG-encoded Rec. 2020 (BT.2100); apply inverse HLG
-                 OETF to get scene-linear, per BT.2100 Note 5a.
-      "linear" → input is already scene-linear (Rec. 709 primaries); write
-                 through unchanged. Use this for renderer/compositor output.
-
-    For PNG, colorspace selection does not modify pixels — PNG is delivered
-    sRGB-encoded and there is no PNG path for wide-gamut HDR in this node.
-    """
-    height, width, num_channels = img_tensor.shape
-    has_alpha = num_channels == 4
-
-    spec = _FORMAT_SPECS[(file_format, bit_depth, has_alpha)]
-
-    if spec["dtype"] == np.float32:
-        # EXR path: preserve full range, no clamp.
-        if colorspace == "sRGB":
-            img_tensor = srgb_to_linear(img_tensor)
-        elif colorspace == "HDR":
-            img_tensor = hlg_to_linear(img_tensor)
-        img_np = img_tensor.cpu().numpy().astype(np.float32)
-    else:
-        # PNG path: quantize to integer range.
-        scaled = (img_tensor * spec["scale"]).clamp(0, spec["scale"])
-        img_np = scaled.to(torch.int32).cpu().numpy().astype(spec["dtype"])
-
-    # Encode directly via CodecContext. PyAV's `image2` muxer does NOT write to
-    # BytesIO (it expects a real file path), so we bypass the container entirely.
-    # For single-frame PNG/EXR the raw codec output IS the file.
-    codec = av.CodecContext.create(file_format, "w")
-    codec.width = width
-    codec.height = height
-    codec.pix_fmt = spec["stream_fmt"]
-    codec.time_base = Fraction(1, 1)
-
-    frame = av.VideoFrame.from_ndarray(img_np, format=spec["frame_fmt"])
-    if spec["frame_fmt"] != spec["stream_fmt"]:
-        frame = frame.reformat(format=spec["stream_fmt"])
-    frame.pts = 0
-    frame.time_base = codec.time_base
-
-    packets = list(codec.encode(frame)) + list(codec.encode(None))  # flush with None
-    return b"".join(bytes(p) for p in packets)
-
-
-# ---------------------------------------------------------------------------
-# Node
-# ---------------------------------------------------------------------------
-
-class SaveImageAdvanced(IO.ComfyNode):
-    @classmethod
-    def define_schema(cls):
-        return IO.Schema(
-            node_id="SaveImageAdvanced",
-            search_aliases=["save", "save image", "export image", "output image", "write image"],
-            display_name="Save Image (Advanced)",
-            description="Saves the input images to your ComfyUI output directory.",
-            category="image",
-            essentials_category="Basics",
-            inputs=[
-                IO.Image.Input("images", tooltip="The images to save."),
-                IO.String.Input(
-                    "filename_prefix",
-                    default="ComfyUI",
-                    tooltip=(
-                        "The prefix for the file to save. May include formatting tokens "
-                        "such as %date:yyyy-MM-dd% or %Empty Latent Image.width%."
-                    ),
-                ),
-                IO.DynamicCombo.Input(
-                    "image_format",
-                    options=[
-                        IO.DynamicCombo.Option("png", [
-                            IO.Combo.Input("bit_depth", options=["8-bit", "16-bit"],
-                                           default="8-bit", advanced=True),
-                            IO.Combo.Input("colorspace", options=["sRGB"],
-                                           default="sRGB", advanced=True),
-                        ]),
-                        IO.DynamicCombo.Option("exr", [
-                            IO.Combo.Input("bit_depth", options=["32-bit float"],
-                                           default="32-bit float", advanced=True),
-                            IO.Combo.Input(
-                                "colorspace",
-                                options=["sRGB", "HDR", "linear"],
-                                default="sRGB",
-                                advanced=True,
-                                tooltip=(
-                                    "Colorspace of the input tensor. The EXR is "
-                                    "always written as scene-linear in the matching "
-                                    "gamut.\n"
-                                    "  'sRGB'   — input is sRGB-encoded Rec.709; "
-                                    "the inverse sRGB EOTF is applied.\n"
-                                    "  'HDR'    — input is HLG-encoded Rec.2020 "
-                                    "(BT.2100); the inverse HLG OETF is applied "
-                                    "to get scene-linear light.\n"
-                                    "  'linear' — input is already scene-linear "
-                                    "(Rec.709 primaries); written through unchanged. "
-                                    "Use this for renderer/compositor output."
-                                ),
-                            ),
-                        ]),
-                    ],
-                    tooltip="The file format in which to save the image.",
-                ),
-            ],
-            hidden=[IO.Hidden.prompt, IO.Hidden.extra_pnginfo],
-            is_output_node=True,
-        )
-
-    @classmethod
-    def execute(cls, images, filename_prefix: str, image_format: dict) -> IO.NodeOutput:
-        file_format = image_format["image_format"]
-        bit_depth = image_format["bit_depth"]
-        colorspace = image_format.get("colorspace", "sRGB")
-
-        output_dir = folder_paths.get_output_directory()
-        full_output_folder, filename, counter, subfolder, filename_prefix = (
-            folder_paths.get_save_image_path(
-                filename_prefix, output_dir, images[0].shape[1], images[0].shape[0]
-            )
-        )
-
-        prompt = cls.hidden.prompt
-        extra_pnginfo = cls.hidden.extra_pnginfo
-        write_metadata = not args.disable_metadata
-
-        results = []
-        for batch_number, image in enumerate(images):
-            encoded = _encode_image(image, file_format, bit_depth, colorspace)
-
-            if write_metadata:
-                if file_format == "png":
-                    encoded = inject_png_metadata(encoded, prompt, extra_pnginfo)
-                elif file_format == "exr":
-                    encoded = inject_exr_metadata(encoded, prompt, extra_pnginfo, colorspace)
-
-            name = filename.replace("%batch_num%", str(batch_number))
-            file = f"{name}_{counter:05}.{file_format}"
-            with open(os.path.join(full_output_folder, file), "wb") as f:
-                f.write(encoded)
-
-            results.append({"filename": file, "subfolder": subfolder, "type": "output"})
-            counter += 1
-
-        return IO.NodeOutput(ui={"images": results})
-
-
 class ImagesExtension(ComfyExtension):
     @override
     async def get_node_list(self) -> list[type[IO.ComfyNode]]:
@@ -1249,7 +842,6 @@ class ImagesExtension(ComfyExtension):
             ImageAddNoise,
             SaveAnimatedWEBP,
             SaveAnimatedPNG,
-            SaveImageAdvanced,
             SaveSVGNode,
             ImageStitch,
             ResizeAndPadImage,

comfy_extras/nodes_lt.py

@@ -338,8 +338,25 @@ class LTXVAddGuide(io.ComfyNode):
         noise_mask = get_noise_mask(latent)
 
         _, _, latent_length, latent_height, latent_width = latent_image.shape
+
+        # For mid-video multi-frame guides, prepend+strip a throwaway first frame so the VAE's "first latent = 1 pixel frame" asymmetry lands on the discarded slot
+        time_scale_factor = scale_factors[0]
+        num_frames_to_keep = ((image.shape[0] - 1) // time_scale_factor) * time_scale_factor + 1
+        resolved_frame_idx = frame_idx
+        if frame_idx < 0:
+            _, num_keyframes = get_keyframe_idxs(positive)
+            resolved_frame_idx = max((latent_length - num_keyframes - 1) * time_scale_factor + 1 + frame_idx, 0)
+        causal_fix = resolved_frame_idx == 0 or num_frames_to_keep == 1
+
+        if not causal_fix:
+            image = torch.cat([image[:1], image], dim=0)
+
         image, t = cls.encode(vae, latent_width, latent_height, image, scale_factors)
 
+        if not causal_fix:
+            t = t[:, :, 1:, :, :]
+            image = image[1:]
+
         frame_idx, latent_idx = cls.get_latent_index(positive, latent_length, len(image), frame_idx, scale_factors)
         assert latent_idx + t.shape[2] <= latent_length, "Conditioning frames exceed the length of the latent sequence."
 
@@ -352,6 +369,7 @@ class LTXVAddGuide(io.ComfyNode):
             t,
             strength,
             scale_factors,
+            causal_fix=causal_fix,
         )
 
         # Track this guide for per-reference attention control.

comfy_extras/nodes_mask.py

@@ -40,23 +40,13 @@ def composite(destination, source, x, y, mask = None, multiplier = 8, resize_sou
 
     inverse_mask = torch.ones_like(mask) - mask
 
-    source_rgb = source[:, :3, :visible_height, :visible_width]
-    dest_slice = destination[..., top:bottom, left:right]
-
-    if destination.shape[1] == 4:
-        if torch.max(dest_slice) == 0:
-            destination[:, :3, top:bottom, left:right] = source_rgb
-            destination[:, 3:4, top:bottom, left:right] = mask
-        else:
-            destination[:, :3, top:bottom, left:right] = (mask * source_rgb) + (inverse_mask * dest_slice[:, :3])
-            destination[:, 3:4, top:bottom, left:right] = torch.max(mask, dest_slice[:, 3:4])
-    else:
-        source_portion = mask * source_rgb
-        destination_portion = inverse_mask * dest_slice
-        destination[..., top:bottom, left:right] = source_portion + destination_portion
+    source_portion = mask * source[..., :visible_height, :visible_width]
+    destination_portion = inverse_mask  * destination[..., top:bottom, left:right]
 
+    destination[..., top:bottom, left:right] = source_portion + destination_portion
     return destination
 
+
 class LatentCompositeMasked(IO.ComfyNode):
     @classmethod
     def define_schema(cls):
@@ -95,23 +85,18 @@ class ImageCompositeMasked(IO.ComfyNode):
             display_name="Image Composite Masked",
             category="image",
             inputs=[
+                IO.Image.Input("destination"),
                 IO.Image.Input("source"),
                 IO.Int.Input("x", default=0, min=0, max=nodes.MAX_RESOLUTION, step=1),
                 IO.Int.Input("y", default=0, min=0, max=nodes.MAX_RESOLUTION, step=1),
                 IO.Boolean.Input("resize_source", default=False),
-                IO.Image.Input("destination", optional=True),
                 IO.Mask.Input("mask", optional=True),
             ],
             outputs=[IO.Image.Output()],
         )
 
     @classmethod
-    def execute(cls, source, x, y, resize_source, destination = None, mask = None) -> IO.NodeOutput:
-        if destination is None: # transparent rgba
-            B, H, W, C = source.shape
-            destination = torch.zeros((B, H, W, 4), dtype=source.dtype, device=source.device)
-            if C == 3:
-                source = torch.nn.functional.pad(source, (0, 1), value=1.0)
+    def execute(cls, destination, source, x, y, resize_source, mask = None) -> IO.NodeOutput:
         destination, source = node_helpers.image_alpha_fix(destination, source)
         destination = destination.clone().movedim(-1, 1)
         output = composite(destination, source.movedim(-1, 1), x, y, mask, 1, resize_source).movedim(1, -1)

comfy_extras/nodes_video.py

@@ -123,6 +123,7 @@ class CreateVideo(io.ComfyNode):
             search_aliases=["images to video"],
             display_name="Create Video",
             category="video",
+            essentials_category="Video Tools",
             description="Create a video from images.",
             inputs=[
                 io.Image.Input("images", tooltip="The images to create a video from."),

openapi.yaml

@@ -2071,7 +2071,6 @@ paths:
                     type: integer
                     description: Number of assets marked as missing
 
-
   # ===========================================================================
   # Cloud-runtime FE-facing operations
   #
@@ -2122,7 +2121,11 @@ paths:
       operationId: getCloudJobStatus
       tags: [queue]
       summary: Get status of a cloud job
-      description: "[cloud-only] Returns the current execution status of a cloud job."
+      deprecated: true
+      description: |
+        **Deprecated.** This endpoint is superseded by `GET /api/jobs/{job_id}`.
+        Clients should migrate; the endpoint is retained for backward
+        compatibility but will be removed in a future release.
       x-runtime: [cloud]
       parameters:
         - name: job_id
@@ -2192,7 +2195,11 @@ paths:
       operationId: getHistoryV2
       tags: [history]
       summary: Get paginated execution history (v2)
-      description: "[cloud-only] Returns a paginated list of execution history entries in the v2 format, with richer metadata than the legacy history endpoint."
+      deprecated: true
+      description: |
+        **Deprecated.** This endpoint is superseded by `GET /api/jobs`.
+        Clients should migrate; the endpoint is retained for backward
+        compatibility but will be removed in a future release.
       x-runtime: [cloud]
       parameters:
         - name: limit
@@ -2231,7 +2238,11 @@ paths:
       operationId: getHistoryV2ByPromptId
       tags: [history]
       summary: Get v2 history for a specific prompt
-      description: "[cloud-only] Returns the v2 history entry for a specific prompt execution."
+      deprecated: true
+      description: |
+        **Deprecated.** This endpoint is superseded by `GET /api/jobs/{prompt_id}`.
+        Clients should migrate; the endpoint is retained for backward
+        compatibility but will be removed in a future release.
       x-runtime: [cloud]
       parameters:
         - name: prompt_id
@@ -2266,7 +2277,12 @@ paths:
       operationId: getCloudLogs
       tags: [system]
       summary: Get cloud execution logs
-      description: "[cloud-only] Returns execution logs for the authenticated user's cloud jobs."
+      deprecated: true
+      description: |
+        **Deprecated.** This endpoint returns a static placeholder response and
+        provides no real log data. It is retained only to avoid breaking clients
+        that still call it. Clients should remove their dependency; the endpoint
+        will be removed in a future release.
       x-runtime: [cloud]
       parameters:
         - name: job_id
@@ -5370,7 +5386,12 @@ paths:
       operationId: viewVideo
       tags: [view]
       summary: View or download a video file
-      description: "[cloud-only] Serves a video file from the output directory. Used by the frontend video player."
+      deprecated: true
+      description: |
+        **Deprecated.** This endpoint is an alias of `GET /api/view` added for
+        legacy history-queue video playback. Callers should use `/api/view`
+        directly; the endpoint is retained for backward compatibility but will
+        be removed in a future release.
       x-runtime: [cloud]
       parameters:
         - name: filename
@@ -5523,7 +5544,6 @@ paths:
               schema:
                 $ref: "#/components/schemas/CloudError"
 
-
 components:
   parameters:
     ComfyUserHeader:
@@ -6875,7 +6895,6 @@ components:
         error:
           type: string
 
-
     # -------------------------------------------------------------------
     # Cloud-runtime schemas
     #

requirements.txt

@@ -1,6 +1,6 @@
 comfyui-frontend-package==1.43.18
 comfyui-workflow-templates==0.9.73
-comfyui-embedded-docs==0.4.4
+comfyui-embedded-docs==0.5.0
 torch
 torchsde
 torchvision