Merge branch 'master' into cursor/mark-deprecated-cloud-endpoints-e81e

Previous commit added new path entries with `deprecated: true` for
`/api/job/{job_id}/status`, `/api/history_v2`, `/api/history_v2/{prompt_id}`,
`/api/logs`, and `/api/viewvideo`, but the canonical entries already existed
elsewhere in the file. Result: 5 duplicate path keys (Spectral parser errors),
and the deprecation flag did not land on the operations that FE clients
consume by operationId.

This commit moves `deprecated: true` plus the standardized "Deprecated."
description onto the canonical operations (`getCloudJobStatus`, `getHistoryV2`,
`getHistoryV2ByPromptId`, `getCloudLogs`, `viewVideo`) and removes the
duplicate entries. Operation IDs and response schemas are unchanged.

Spectral lint passes with zero new warnings.

.spectral.yaml

@@ -89,12 +89,3 @@ 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 = 0.033
+    memory_usage_factor = 0.6
     # fp16 not supported: LM MLP down_proj activations fp16 overflow, causing NaNs
     supported_inference_dtypes = [torch.bfloat16, torch.float32]
 

comfy_api/latest/_ui.py

@@ -285,7 +285,7 @@ class AudioSaveHelper:
         results = []
         for batch_number, waveform in enumerate(audio["waveform"].cpu()):
             filename_with_batch_num = filename.replace("%batch_num%", str(batch_number))
-            file = f"{filename_with_batch_num}_{counter:05}.{format}"
+            file = f"{filename_with_batch_num}_{counter:05}_.{format}"
             output_path = os.path.join(full_output_folder, file)
 
             # Use original sample rate initially

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) (Deprecated)",
+            display_name="Save Audio (FLAC)",
             category="audio",
             essentials_category="Audio",
             inputs=[
@@ -167,7 +167,6 @@ class SaveAudio(IO.ComfyNode):
             ],
             hidden=[IO.Hidden.prompt, IO.Hidden.extra_pnginfo],
             is_output_node=True,
-            is_deprecated=True,
         )
 
     @classmethod
@@ -185,7 +184,7 @@ class SaveAudioMP3(IO.ComfyNode):
         return IO.Schema(
             node_id="SaveAudioMP3",
             search_aliases=["export mp3"],
-            display_name="Save Audio (MP3) (Deprecated)",
+            display_name="Save Audio (MP3)",
             category="audio",
             essentials_category="Audio",
             inputs=[
@@ -195,7 +194,6 @@ class SaveAudioMP3(IO.ComfyNode):
             ],
             hidden=[IO.Hidden.prompt, IO.Hidden.extra_pnginfo],
             is_output_node=True,
-            is_deprecated=True,
         )
 
     @classmethod
@@ -215,7 +213,7 @@ class SaveAudioOpus(IO.ComfyNode):
         return IO.Schema(
             node_id="SaveAudioOpus",
             search_aliases=["export opus"],
-            display_name="Save Audio (Opus) (Deprecated)",
+            display_name="Save Audio (Opus)",
             category="audio",
             inputs=[
                 IO.Audio.Input("audio"),
@@ -224,7 +222,6 @@ class SaveAudioOpus(IO.ComfyNode):
             ],
             hidden=[IO.Hidden.prompt, IO.Hidden.extra_pnginfo],
             is_output_node=True,
-            is_deprecated=True,
         )
 
     @classmethod
@@ -238,54 +235,6 @@ 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):
@@ -348,7 +297,6 @@ 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",
@@ -828,7 +776,6 @@ class AudioExtension(ComfyExtension):
             SaveAudio,
             SaveAudioMP3,
             SaveAudioOpus,
-            SaveAudioAdvanced,
             LoadAudio,
             PreviewAudio,
             ConditioningStableAudio,

comfy_extras/nodes_lt.py

@@ -338,25 +338,8 @@ 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."
 
@@ -369,7 +352,6 @@ 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

@@ -40,13 +40,23 @@ def composite(destination, source, x, y, mask = None, multiplier = 8, resize_sou
 
     inverse_mask = torch.ones_like(mask) - mask
 
-    source_portion = mask * source[..., :visible_height, :visible_width]
-    destination_portion = inverse_mask  * destination[..., top:bottom, left:right]
+    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
 
-    destination[..., top:bottom, left:right] = source_portion + destination_portion
     return destination
 
-
 class LatentCompositeMasked(IO.ComfyNode):
     @classmethod
     def define_schema(cls):
@@ -85,18 +95,23 @@ 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, destination, source, x, y, resize_source, mask = None) -> IO.NodeOutput:
+    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)
         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

@@ -123,7 +123,6 @@ 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."),

requirements.txt

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