Merge branch 'master' into deepme987/auto-register-node-replacements-json

Fix SolidMask and MaskComposite device mismatch with --gpu-only (#13296 )
SolidMask had a hardcoded device="cpu" while other nodes (e.g. EmptyImage) follow intermediate_device(). This causes a RuntimeError when MaskComposite combines masks from different device sources under --gpu-only. - SolidMask: use intermediate_device() instead of hardcoded "cpu" - MaskComposite: align source device to destination before operating Co-authored-by: Alexis Rolland <alexisrolland@hotmail.com> Co-authored-by: Jedrzej Kosinski <kosinkadink1@gmail.com>
2026-05-06 18:27:58 +08:00 · 2026-04-28 02:53:37 -07:00 · 2026-04-28 01:18:19 -07:00 · 2026-04-28 00:59:59 -07:00 · 2026-04-27 19:51:33 -07:00 · 2026-04-27 22:22:31 -04:00
39 changed files with 34234 additions and 1145 deletions
--- a/.github/workflows/tag-dispatch-cloud.yml
+++ b/.github/workflows/tag-dispatch-cloud.yml
@ -0,0 +1,45 @@
+name: Tag Dispatch to Cloud
+
+on:
+  push:
+    tags:
+      - 'v*'
+
+jobs:
+  dispatch-cloud:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Send repository dispatch to cloud
+        env:
+          DISPATCH_TOKEN: ${{ secrets.CLOUD_REPO_DISPATCH_TOKEN }}
+          RELEASE_TAG: ${{ github.ref_name }}
+        run: |
+          set -euo pipefail
+
+          if [ -z "${DISPATCH_TOKEN:-}" ]; then
+            echo "::error::CLOUD_REPO_DISPATCH_TOKEN is required but not set."
+            exit 1
+          fi
+
+          RELEASE_URL="https://github.com/${{ github.repository }}/releases/tag/${RELEASE_TAG}"
+
+          PAYLOAD="$(jq -n \
+            --arg release_tag "$RELEASE_TAG" \
+            --arg release_url "$RELEASE_URL" \
+            '{
+              event_type: "comfyui_tag_pushed",
+              client_payload: {
+                release_tag: $release_tag,
+                release_url: $release_url
+              }
+            }')"
+
+          curl -fsSL \
+            -X POST \
+            -H "Accept: application/vnd.github+json" \
+            -H "Content-Type: application/json" \
+            -H "Authorization: Bearer ${DISPATCH_TOKEN}" \
+            https://api.github.com/repos/Comfy-Org/cloud/dispatches \
+            -d "$PAYLOAD"
+
+          echo "✅ Dispatched ComfyUI tag ${RELEASE_TAG} to Comfy-Org/cloud"
--- a/.gitignore
+++ b/.gitignore
@ -21,6 +21,5 @@ venv*/
 *.log
 web_custom_versions/
 .DS_Store
-openapi.yaml
 filtered-openapi.yaml
 uv.lock
--- a/app/node_replace_manager.py
+++ b/app/node_replace_manager.py
@ -1,5 +1,9 @@
 from __future__ import annotations

+import json
+import logging
+import os
+
 from aiohttp import web

 from typing import TYPE_CHECKING, TypedDict
@ -7,7 +11,6 @@ if TYPE_CHECKING:
    from comfy_api.latest._io_public import NodeReplace

 from comfy_execution.graph_utils import is_link
-import nodes

 class NodeStruct(TypedDict):
    inputs: dict[str, str | int | float | bool | tuple[str, int]]
@ -43,6 +46,7 @@ class NodeReplaceManager:
        return old_node_id in self._replacements

    def apply_replacements(self, prompt: dict[str, NodeStruct]):
+        import nodes
        connections: dict[str, list[tuple[str, str, int]]] = {}
        need_replacement: set[str] = set()
        for node_number, node_struct in prompt.items():
@ -94,6 +98,60 @@ class NodeReplaceManager:
                                previous_input = prompt[conn_node_number]["inputs"][conn_input_id]
                                previous_input[1] = new_output_idx

+    def load_from_json(self, module_dir: str, module_name: str, _node_replace_class=None):
+        """Load node_replacements.json from a custom node directory and register replacements.
+
+        Custom node authors can ship a node_replacements.json file in their repo root
+        to define node replacements declaratively. The file format matches the output
+        of NodeReplace.as_dict(), keyed by old_node_id.
+
+        Fail-open: all errors are logged and skipped so a malformed file never
+        prevents the custom node from loading.
+        """
+        replacements_path = os.path.join(module_dir, "node_replacements.json")
+        if not os.path.isfile(replacements_path):
+            return
+
+        try:
+            with open(replacements_path, "r", encoding="utf-8") as f:
+                data = json.load(f)
+
+            if not isinstance(data, dict):
+                logging.warning(f"node_replacements.json in {module_name} must be a JSON object, skipping.")
+                return
+
+            if _node_replace_class is None:
+                from comfy_api.latest._io import NodeReplace
+                _node_replace_class = NodeReplace
+
+            count = 0
+            for old_node_id, replacements in data.items():
+                if not isinstance(replacements, list):
+                    logging.warning(f"node_replacements.json in {module_name}: value for '{old_node_id}' must be a list, skipping.")
+                    continue
+                for entry in replacements:
+                    if not isinstance(entry, dict):
+                        continue
+                    new_node_id = entry.get("new_node_id", "")
+                    if not new_node_id:
+                        logging.warning(f"node_replacements.json in {module_name}: entry for '{old_node_id}' missing 'new_node_id', skipping.")
+                        continue
+                    self.register(_node_replace_class(
+                        new_node_id=new_node_id,
+                        old_node_id=entry.get("old_node_id", old_node_id),
+                        old_widget_ids=entry.get("old_widget_ids"),
+                        input_mapping=entry.get("input_mapping"),
+                        output_mapping=entry.get("output_mapping"),
+                    ))
+                    count += 1
+
+            if count > 0:
+                logging.info(f"Loaded {count} node replacement(s) from {module_name}/node_replacements.json")
+        except json.JSONDecodeError as e:
+            logging.warning(f"Failed to parse node_replacements.json in {module_name}: {e}")
+        except Exception as e:
+            logging.warning(f"Failed to load node_replacements.json from {module_name}: {e}")
+
    def as_dict(self):
        """Serialize all replacements to dict."""
        return {
--- a/blueprints/Crop
+++ b/blueprints/Crop
--- a/blueprints/Crop
+++ b/blueprints/Crop
--- a/(Z-Image-Turbo).json
+++ b/(Z-Image-Turbo).json
@ -160,7 +160,7 @@
        },
        "revision": 0,
        "config": {},
-        "name": "local-Depth to Image (Z-Image-Turbo)",
+        "name": "Depth to Image (Z-Image-Turbo)",
        "inputNode": {
          "id": -10,
          "bounding": [
@ -2482,4 +2482,4 @@
    "VHS_KeepIntermediate": true
  },
  "version": 0.4
-}
+}
--- a/blueprints/Depth
+++ b/blueprints/Depth
@ -261,7 +261,7 @@
        },
        "revision": 0,
        "config": {},
-        "name": "local-Depth to Video (LTX 2.0)",
+        "name": "Depth to Video (LTX 2.0)",
        "inputNode": {
          "id": -10,
          "bounding": [
@ -5208,4 +5208,4 @@
    "workflowRendererVersion": "LG"
  },
  "version": 0.4
-}
+}
--- a/blueprints/First-Last-Frame
+++ b/blueprints/First-Last-Frame
--- a/blueprints/Image
+++ b/blueprints/Image
--- a/blueprints/Image
+++ b/blueprints/Image
@ -128,7 +128,7 @@
        },
        "revision": 0,
        "config": {},
-        "name": "local-Image Edit (Flux.2 Klein 4B)",
+        "name": "Image Edit (Flux.2 Klein 4B)",
        "inputNode": {
          "id": -10,
          "bounding": [
@ -1837,4 +1837,4 @@
    }
  },
  "version": 0.4
-}
+}
--- a/blueprints/Image
+++ b/blueprints/Image
--- a/blueprints/Image
+++ b/blueprints/Image
--- a/(Qwen-image).json
+++ b/(Qwen-image).json
@ -124,7 +124,7 @@
        },
        "revision": 0,
        "config": {},
-        "name": "local-Image Inpainting (Qwen-image)",
+        "name": "Image Inpainting (Qwen-image)",
        "inputNode": {
          "id": -10,
          "bounding": [
@ -1923,4 +1923,4 @@
    "workflowRendererVersion": "LG"
  },
  "version": 0.4
-}
+}
--- a/(Qwen-Image).json
+++ b/(Qwen-Image).json
@ -204,7 +204,7 @@
        },
        "revision": 0,
        "config": {},
-        "name": "local-Image Outpainting (Qwen-Image)",
+        "name": "Image Outpainting (Qwen-Image)",
        "inputNode": {
          "id": -10,
          "bounding": [
@ -2749,4 +2749,4 @@
    }
  },
  "version": 0.4
-}
+}
--- a/Layers(Qwen-Image-Layered).json
+++ b/Layers(Qwen-Image-Layered).json
@ -1,15 +1,14 @@
 {
-  "id": "1a761372-7c82-4016-b9bf-fa285967e1e9",
  "revision": 0,
-  "last_node_id": 83,
+  "last_node_id": 176,
  "last_link_id": 0,
  "nodes": [
    {
-      "id": 83,
-      "type": "f754a936-daaf-4b6e-9658-41fdc54d301d",
+      "id": 176,
+      "type": "2d2e3c8e-53b3-4618-be52-6d1d99382f0e",
      "pos": [
-        61.999827823554256,
-        153.3332507624185
+        -1150,
+        200
      ],
      "size": [
        400,
@ -56,6 +55,38 @@
            "name": "layers"
          },
          "link": null
+        },
+        {
+          "name": "seed",
+          "type": "INT",
+          "widget": {
+            "name": "seed"
+          },
+          "link": null
+        },
+        {
+          "name": "unet_name",
+          "type": "COMBO",
+          "widget": {
+            "name": "unet_name"
+          },
+          "link": null
+        },
+        {
+          "name": "clip_name",
+          "type": "COMBO",
+          "widget": {
+            "name": "clip_name"
+          },
+          "link": null
+        },
+        {
+          "name": "vae_name",
+          "type": "COMBO",
+          "widget": {
+            "name": "vae_name"
+          },
+          "link": null
        }
      ],
      "outputs": [
@ -66,28 +97,41 @@
          "links": []
        }
      ],
+      "title": "Image to Layers (Qwen-Image-Layered)",
      "properties": {
        "proxyWidgets": [
          [
-            "-1",
+            "6",
            "text"
          ],
          [
-            "-1",
+            "3",
            "steps"
          ],
          [
-            "-1",
+            "3",
            "cfg"
          ],
          [
-            "-1",
+            "83",
            "layers"
          ],
          [
            "3",
            "seed"
          ],
+          [
+            "37",
+            "unet_name"
+          ],
+          [
+            "38",
+            "clip_name"
+          ],
+          [
+            "39",
+            "vae_name"
+          ],
          [
            "3",
            "control_after_generate"
@ -95,6 +139,11 @@
        ],
        "cnr_id": "comfy-core",
        "ver": "0.5.1",
+        "ue_properties": {
+          "widget_ue_connectable": {},
+          "input_ue_unconnectable": {},
+          "version": "7.7"
+        },
        "enableTabs": false,
        "tabWidth": 65,
        "tabXOffset": 10,
@ -103,25 +152,20 @@
        "secondTabOffset": 80,
        "secondTabWidth": 65
      },
-      "widgets_values": [
-        "",
-        20,
-        2.5,
-        2
-      ]
+      "widgets_values": []
    }
  ],
  "links": [],
-  "groups": [],
+  "version": 0.4,
  "definitions": {
    "subgraphs": [
      {
-        "id": "f754a936-daaf-4b6e-9658-41fdc54d301d",
+        "id": "2d2e3c8e-53b3-4618-be52-6d1d99382f0e",
        "version": 1,
        "state": {
-          "lastGroupId": 3,
-          "lastNodeId": 83,
-          "lastLinkId": 159,
+          "lastGroupId": 8,
+          "lastNodeId": 176,
+          "lastLinkId": 380,
          "lastRerouteId": 0
        },
        "revision": 0,
@ -130,10 +174,10 @@
        "inputNode": {
          "id": -10,
          "bounding": [
-            -510,
-            523,
+            -720,
+            720,
            120,
-            140
+            220
          ]
        },
        "outputNode": {
@ -156,8 +200,8 @@
            ],
            "localized_name": "image",
            "pos": [
-              -410,
-              543
+              -620,
+              740
            ]
          },
          {
@ -168,8 +212,8 @@
              150
            ],
            "pos": [
-              -410,
-              563
+              -620,
+              760
            ]
          },
          {
@ -180,8 +224,8 @@
              153
            ],
            "pos": [
-              -410,
-              583
+              -620,
+              780
            ]
          },
          {
@ -192,8 +236,8 @@
              154
            ],
            "pos": [
-              -410,
-              603
+              -620,
+              800
            ]
          },
          {
@ -204,8 +248,56 @@
              159
            ],
            "pos": [
-              -410,
-              623
+              -620,
+              820
+            ]
+          },
+          {
+            "id": "9f76338b-f4ca-4bb3-b61a-57b3f233061e",
+            "name": "seed",
+            "type": "INT",
+            "linkIds": [
+              377
+            ],
+            "pos": [
+              -620,
+              840
+            ]
+          },
+          {
+            "id": "8d0422d5-5eee-4f7e-9817-dc613cc62eca",
+            "name": "unet_name",
+            "type": "COMBO",
+            "linkIds": [
+              378
+            ],
+            "pos": [
+              -620,
+              860
+            ]
+          },
+          {
+            "id": "552eece2-a735-4d00-ae78-ded454622bc1",
+            "name": "clip_name",
+            "type": "COMBO",
+            "linkIds": [
+              379
+            ],
+            "pos": [
+              -620,
+              880
+            ]
+          },
+          {
+            "id": "1e6d141c-d0f9-4a2b-895c-b6780e57cfa0",
+            "name": "vae_name",
+            "type": "COMBO",
+            "linkIds": [
+              380
+            ],
+            "pos": [
+              -620,
+              900
            ]
          }
        ],
@ -231,14 +323,14 @@
            "type": "CLIPLoader",
            "pos": [
              -320,
-              310
+              360
            ],
            "size": [
-              346.7470703125,
-              106
+              350,
+              150
            ],
            "flags": {},
-            "order": 0,
+            "order": 5,
            "mode": 0,
            "inputs": [
              {
@ -248,7 +340,7 @@
                "widget": {
                  "name": "clip_name"
                },
-                "link": null
+                "link": 379
              },
              {
                "localized_name": "type",
@ -283,9 +375,14 @@
              }
            ],
            "properties": {
-              "Node name for S&R": "CLIPLoader",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "input_ue_unconnectable": {},
+                "version": "7.7"
+              },
+              "Node name for S&R": "CLIPLoader",
              "models": [
                {
                  "name": "qwen_2.5_vl_7b_fp8_scaled.safetensors",
@ -312,14 +409,14 @@
            "type": "VAELoader",
            "pos": [
              -320,
-              460
+              580
            ],
            "size": [
-              346.7470703125,
-              58
+              350,
+              110
            ],
            "flags": {},
-            "order": 1,
+            "order": 6,
            "mode": 0,
            "inputs": [
              {
@ -329,7 +426,7 @@
                "widget": {
                  "name": "vae_name"
                },
-                "link": null
+                "link": 380
              }
            ],
            "outputs": [
@ -345,9 +442,14 @@
              }
            ],
            "properties": {
-              "Node name for S&R": "VAELoader",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "input_ue_unconnectable": {},
+                "version": "7.7"
+              },
+              "Node name for S&R": "VAELoader",
              "models": [
                {
                  "name": "qwen_image_layered_vae.safetensors",
@ -375,11 +477,11 @@
              420
            ],
            "size": [
-              425.27801513671875,
-              180.6060791015625
+              430,
+              190
            ],
            "flags": {},
-            "order": 3,
+            "order": 2,
            "mode": 0,
            "inputs": [
              {
@ -411,9 +513,14 @@
            ],
            "title": "CLIP Text Encode (Negative Prompt)",
            "properties": {
-              "Node name for S&R": "CLIPTextEncode",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "input_ue_unconnectable": {},
+                "version": "7.7"
+              },
+              "Node name for S&R": "CLIPTextEncode",
              "enableTabs": false,
              "tabWidth": 65,
              "tabXOffset": 10,
@ -432,12 +539,12 @@
            "id": 70,
            "type": "ReferenceLatent",
            "pos": [
-              330,
-              670
+              140,
+              700
            ],
            "size": [
-              204.1666717529297,
-              46
+              210,
+              50
            ],
            "flags": {
              "collapsed": true
@ -470,9 +577,14 @@
              }
            ],
            "properties": {
-              "Node name for S&R": "ReferenceLatent",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "input_ue_unconnectable": {},
+                "version": "7.7"
+              },
+              "Node name for S&R": "ReferenceLatent",
              "enableTabs": false,
              "tabWidth": 65,
              "tabXOffset": 10,
@ -480,19 +592,18 @@
              "secondTabText": "Send Back",
              "secondTabOffset": 80,
              "secondTabWidth": 65
-            },
-            "widgets_values": []
+            }
          },
          {
            "id": 69,
            "type": "ReferenceLatent",
            "pos": [
-              330,
-              710
+              160,
+              820
            ],
            "size": [
-              204.1666717529297,
-              46
+              210,
+              50
            ],
            "flags": {
              "collapsed": true
@ -525,9 +636,14 @@
              }
            ],
            "properties": {
-              "Node name for S&R": "ReferenceLatent",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "input_ue_unconnectable": {},
+                "version": "7.7"
+              },
+              "Node name for S&R": "ReferenceLatent",
              "enableTabs": false,
              "tabWidth": 65,
              "tabXOffset": 10,
@ -535,8 +651,7 @@
              "secondTabText": "Send Back",
              "secondTabOffset": 80,
              "secondTabWidth": 65
-            },
-            "widgets_values": []
+            }
          },
          {
            "id": 66,
@ -547,10 +662,10 @@
            ],
            "size": [
              270,
-              58
+              110
            ],
            "flags": {},
-            "order": 4,
+            "order": 7,
            "mode": 0,
            "inputs": [
              {
@ -580,9 +695,14 @@
              }
            ],
            "properties": {
-              "Node name for S&R": "ModelSamplingAuraFlow",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "input_ue_unconnectable": {},
+                "version": "7.7"
+              },
+              "Node name for S&R": "ModelSamplingAuraFlow",
              "enableTabs": false,
              "tabWidth": 65,
              "tabXOffset": 10,
@ -600,11 +720,11 @@
            "type": "LatentCutToBatch",
            "pos": [
              830,
-              160
+              140
            ],
            "size": [
              270,
-              82
+              140
            ],
            "flags": {},
            "order": 11,
@ -646,9 +766,14 @@
              }
            ],
            "properties": {
-              "Node name for S&R": "LatentCutToBatch",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "input_ue_unconnectable": {},
+                "version": "7.7"
+              },
+              "Node name for S&R": "LatentCutToBatch",
              "enableTabs": false,
              "tabWidth": 65,
              "tabXOffset": 10,
@ -666,12 +791,12 @@
            "id": 71,
            "type": "VAEEncode",
            "pos": [
-              100,
-              690
+              -280,
+              780
            ],
            "size": [
-              140,
-              46
+              230,
+              100
            ],
            "flags": {
              "collapsed": false
@ -704,9 +829,14 @@
              }
            ],
            "properties": {
-              "Node name for S&R": "VAEEncode",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "input_ue_unconnectable": {},
+                "version": "7.7"
+              },
+              "Node name for S&R": "VAEEncode",
              "enableTabs": false,
              "tabWidth": 65,
              "tabXOffset": 10,
@ -714,24 +844,23 @@
              "secondTabText": "Send Back",
              "secondTabOffset": 80,
              "secondTabWidth": 65
-            },
-            "widgets_values": []
+            }
          },
          {
            "id": 8,
            "type": "VAEDecode",
            "pos": [
              850,
-              310
+              370
            ],
            "size": [
              210,
-              46
+              50
            ],
            "flags": {
              "collapsed": true
            },
-            "order": 7,
+            "order": 3,
            "mode": 0,
            "inputs": [
              {
@ -759,9 +888,14 @@
              }
            ],
            "properties": {
-              "Node name for S&R": "VAEDecode",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "input_ue_unconnectable": {},
+                "version": "7.7"
+              },
+              "Node name for S&R": "VAEDecode",
              "enableTabs": false,
              "tabWidth": 65,
              "tabXOffset": 10,
@ -769,8 +903,7 @@
              "secondTabText": "Send Back",
              "secondTabOffset": 80,
              "secondTabWidth": 65
-            },
-            "widgets_values": []
+            }
          },
          {
            "id": 6,
@ -780,11 +913,11 @@
              180
            ],
            "size": [
-              422.84503173828125,
-              164.31304931640625
+              430,
+              170
            ],
            "flags": {},
-            "order": 6,
+            "order": 1,
            "mode": 0,
            "inputs": [
              {
@ -816,9 +949,14 @@
            ],
            "title": "CLIP Text Encode (Positive Prompt)",
            "properties": {
-              "Node name for S&R": "CLIPTextEncode",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "input_ue_unconnectable": {},
+                "version": "7.7"
+              },
+              "Node name for S&R": "CLIPTextEncode",
              "enableTabs": false,
              "tabWidth": 65,
              "tabXOffset": 10,
@ -838,14 +976,14 @@
            "type": "KSampler",
            "pos": [
              530,
-              280
+              340
            ],
            "size": [
              270,
              400
            ],
            "flags": {},
-            "order": 5,
+            "order": 0,
            "mode": 0,
            "inputs": [
              {
@ -879,7 +1017,7 @@
                "widget": {
                  "name": "seed"
                },
-                "link": null
+                "link": 377
              },
              {
                "localized_name": "steps",
@ -939,9 +1077,14 @@
              }
            ],
            "properties": {
-              "Node name for S&R": "KSampler",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "input_ue_unconnectable": {},
+                "version": "7.7"
+              },
+              "Node name for S&R": "KSampler",
              "enableTabs": false,
              "tabWidth": 65,
              "tabXOffset": 10,
@ -964,12 +1107,12 @@
            "id": 78,
            "type": "GetImageSize",
            "pos": [
-              80,
-              790
+              -280,
+              930
            ],
            "size": [
-              210,
-              136
+              230,
+              140
            ],
            "flags": {},
            "order": 12,
@ -1007,9 +1150,14 @@
              }
            ],
            "properties": {
-              "Node name for S&R": "GetImageSize",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "input_ue_unconnectable": {},
+                "version": "7.7"
+              },
+              "Node name for S&R": "GetImageSize",
              "enableTabs": false,
              "tabWidth": 65,
              "tabXOffset": 10,
@ -1017,23 +1165,23 @@
              "secondTabText": "Send Back",
              "secondTabOffset": 80,
              "secondTabWidth": 65
-            },
-            "widgets_values": []
+            }
          },
          {
            "id": 83,
            "type": "EmptyQwenImageLayeredLatentImage",
            "pos": [
-              320,
-              790
+              -280,
+              1120
            ],
            "size": [
-              330.9341796875,
-              130
+              340,
+              200
            ],
            "flags": {},
            "order": 13,
            "mode": 0,
+            "showAdvanced": true,
            "inputs": [
              {
                "localized_name": "width",
@ -1083,9 +1231,14 @@
              }
            ],
            "properties": {
-              "Node name for S&R": "EmptyQwenImageLayeredLatentImage",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "input_ue_unconnectable": {},
+                "version": "7.7"
+              },
+              "Node name for S&R": "EmptyQwenImageLayeredLatentImage",
              "enableTabs": false,
              "tabWidth": 65,
              "tabXOffset": 10,
@ -1109,11 +1262,11 @@
              180
            ],
            "size": [
-              346.7470703125,
-              82
+              350,
+              110
            ],
            "flags": {},
-            "order": 2,
+            "order": 4,
            "mode": 0,
            "inputs": [
              {
@ -1123,7 +1276,7 @@
                "widget": {
                  "name": "unet_name"
                },
-                "link": null
+                "link": 378
              },
              {
                "localized_name": "weight_dtype",
@ -1147,9 +1300,14 @@
              }
            ],
            "properties": {
-              "Node name for S&R": "UNETLoader",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
+                "widget_ue_connectable": {},
+                "input_ue_unconnectable": {},
+                "version": "7.7"
+              },
+              "Node name for S&R": "UNETLoader",
              "models": [
                {
                  "name": "qwen_image_layered_bf16.safetensors",
@ -1191,8 +1349,8 @@
            "bounding": [
              -330,
              110,
-              366.7470703125,
-              421.6
+              370,
+              610
            ],
            "color": "#3f789e",
            "font_size": 24,
@ -1391,6 +1549,38 @@
            "target_id": 83,
            "target_slot": 2,
            "type": "INT"
+          },
+          {
+            "id": 377,
+            "origin_id": -10,
+            "origin_slot": 5,
+            "target_id": 3,
+            "target_slot": 4,
+            "type": "INT"
+          },
+          {
+            "id": 378,
+            "origin_id": -10,
+            "origin_slot": 6,
+            "target_id": 37,
+            "target_slot": 0,
+            "type": "COMBO"
+          },
+          {
+            "id": 379,
+            "origin_id": -10,
+            "origin_slot": 7,
+            "target_id": 38,
+            "target_slot": 0,
+            "type": "COMBO"
+          },
+          {
+            "id": 380,
+            "origin_id": -10,
+            "origin_slot": 8,
+            "target_id": 39,
+            "target_slot": 0,
+            "type": "COMBO"
          }
        ],
        "extra": {
@ -1400,7 +1590,6 @@
      }
    ]
  },
-  "config": {},
  "extra": {
    "ds": {
      "scale": 1.14,
@ -1409,7 +1598,6 @@
        6.855893974423647
      ]
    },
-    "workflowRendererVersion": "LG"
-  },
-  "version": 0.4
-}
+    "ue_links": []
+  }
+}
--- a/blueprints/Image
+++ b/blueprints/Image
--- a/blueprints/Pose
+++ b/blueprints/Pose
--- a/blueprints/Text
+++ b/blueprints/Text
--- a/blueprints/Text
+++ b/blueprints/Text
--- a/blueprints/Text
+++ b/blueprints/Text
--- a/blueprints/Text
+++ b/blueprints/Text
--- a/(Qwen-Image).json
+++ b/(Qwen-Image).json
--- a/blueprints/Text
+++ b/blueprints/Text
--- a/comfy/model_patcher.py
+++ b/comfy/model_patcher.py
@ -31,6 +31,7 @@ import comfy.float
 import comfy.hooks
 import comfy.lora
 import comfy.model_management
+import comfy.ops
 import comfy.patcher_extension
 import comfy.utils
 from comfy.comfy_types import UnetWrapperFunction
@ -856,7 +857,9 @@ class ModelPatcher:
                    if m.comfy_patched_weights == True:
                        continue

-                for param in params:
+                for param, param_value in params.items():
+                    if hasattr(m, "comfy_cast_weights") and getattr(param_value, "is_meta", False):
+                        comfy.ops.disable_weight_init._zero_init_parameter(m, param)
                    key = key_param_name_to_key(n, param)
                    self.unpin_weight(key)
                    self.patch_weight_to_device(key, device_to=device_to)
--- a/comfy/ops.py
+++ b/comfy/ops.py
@ -79,14 +79,21 @@ def cast_to_input(weight, input, non_blocking=False, copy=True):
    return comfy.model_management.cast_to(weight, input.dtype, input.device, non_blocking=non_blocking, copy=copy)


-def cast_bias_weight_with_vbar(s, dtype, device, bias_dtype, non_blocking, compute_dtype, want_requant):
+def materialize_meta_param(s, param_keys):
+    for param_key in param_keys:
+        param = getattr(s, param_key, None)
+        if param is not None and getattr(param, "is_meta", False):
+            setattr(s, param_key, torch.nn.Parameter(torch.zeros(param.shape, dtype=param.dtype), requires_grad=param.requires_grad))

+
+def cast_bias_weight_with_vbar(s, dtype, device, bias_dtype, non_blocking, compute_dtype, want_requant):
    #vbar doesn't support CPU weights, but some custom nodes have weird paths
    #that might switch the layer to the CPU and expect it to work. We have to take
    #a clone conservatively as we are mmapped and some SFT files are packed misaligned
    #If you are a custom node author reading this, please move your layer to the GPU
    #or declare your ModelPatcher as CPU in the first place.
    if comfy.model_management.is_device_cpu(device):
+        materialize_meta_param(s, ["weight", "bias"])
        weight = s.weight.to(dtype=dtype, copy=True)
        if isinstance(weight, QuantizedTensor):
            weight = weight.dequantize()
@ -108,6 +115,7 @@ def cast_bias_weight_with_vbar(s, dtype, device, bias_dtype, non_blocking, compu
            xfer_dest = comfy_aimdo.torch.aimdo_to_tensor(s._v, device)

    if not resident:
+        materialize_meta_param(s, ["weight", "bias"])
        cast_geometry = comfy.memory_management.tensors_to_geometries([ s.weight, s.bias ])
        cast_dest = None

@ -306,6 +314,12 @@ class CastWeightBiasOp:
    bias_function = []

 class disable_weight_init:
+    @staticmethod
+    def _zero_init_parameter(module, name):
+        param = getattr(module, name)
+        device = None if getattr(param, "is_meta", False) else param.device
+        setattr(module, name, torch.nn.Parameter(torch.zeros(param.shape, device=device, dtype=param.dtype), requires_grad=False))
+
    @staticmethod
    def _lazy_load_from_state_dict(module, state_dict, prefix, local_metadata,
                                   missing_keys, unexpected_keys, weight_shape,
--- a/comfy_api/latest/_input_impl/video_types.py
+++ b/comfy_api/latest/_input_impl/video_types.py
@ -12,6 +12,7 @@ import numpy as np
 import math
 import torch
 from .._util import VideoContainer, VideoCodec, VideoComponents
+import logging


 def container_to_output_format(container_format: str | None) -> str | None:
@ -238,64 +239,107 @@ class VideoFromFile(VideoInput):
            start_time = max(self._get_raw_duration() + self.__start_time, 0)
        else:
            start_time = self.__start_time
+
        # Get video frames
        frames = []
+        audio_frames = []
+        alphas = None
        start_pts = int(start_time / video_stream.time_base)
        end_pts = int((start_time + self.__duration) / video_stream.time_base)
-        container.seek(start_pts, stream=video_stream)
-        for frame in container.decode(video_stream):
-            if frame.pts < start_pts:
-                continue
-            if self.__duration and frame.pts >= end_pts:
-                break
-            img = frame.to_ndarray(format='rgb24')  # shape: (H, W, 3)
-            img = torch.from_numpy(img) / 255.0  # shape: (H, W, 3)
-            frames.append(img)

-        images = torch.stack(frames) if len(frames) > 0 else torch.zeros(0, 3, 0, 0)
+        if start_pts != 0:
+            container.seek(start_pts, stream=video_stream)
+
+        image_format = 'gbrpf32le'
+        audio = None
+
+        streams = [video_stream]
+        has_first_audio_frame = False
+        checked_alpha = False
+
+        # Default to False so we decode until EOF if duration is 0
+        video_done = False
+        audio_done = True
+
+        if len(container.streams.audio):
+            audio_stream = container.streams.audio[-1]
+            streams += [audio_stream]
+            resampler = av.audio.resampler.AudioResampler(format='fltp')
+            audio_done = False
+
+        for packet in container.demux(*streams):
+            if video_done and audio_done:
+                break
+
+            if packet.stream.type == "video":
+                if video_done:
+                    continue
+                try:
+                    for frame in packet.decode():
+                        if frame.pts < start_pts:
+                            continue
+                        if self.__duration and frame.pts >= end_pts:
+                            video_done = True
+                            break
+
+                        if not checked_alpha:
+                            for comp in frame.format.components:
+                                if comp.is_alpha:
+                                    alphas = []
+                                    image_format = 'gbrapf32le'
+                                    break
+                            checked_alpha = True
+
+                        img = frame.to_ndarray(format=image_format)  # shape: (H, W, 4)
+                        if alphas is None:
+                            frames.append(torch.from_numpy(img))
+                        else:
+                            frames.append(torch.from_numpy(img[..., :-1]))
+                            alphas.append(torch.from_numpy(img[..., -1:]))
+                except av.error.InvalidDataError:
+                    logging.info("pyav decode error")
+
+            elif packet.stream.type == "audio":
+                if audio_done:
+                    continue
+
+                aframes = itertools.chain.from_iterable(
+                    map(resampler.resample, packet.decode())
+                )
+                for frame in aframes:
+                    if self.__duration and frame.time > start_time + self.__duration:
+                        audio_done = True
+                        break
+
+                    if not has_first_audio_frame:
+                        offset_seconds = start_time - frame.pts * audio_stream.time_base
+                        to_skip = max(0, int(offset_seconds * audio_stream.sample_rate))
+                        if to_skip < frame.samples:
+                            has_first_audio_frame = True
+                            audio_frames.append(frame.to_ndarray()[..., to_skip:])
+                    else:
+                        audio_frames.append(frame.to_ndarray())
+
+        images = torch.stack(frames) if len(frames) > 0 else torch.zeros(0, 0, 0, 3)
+        if alphas is not None:
+            alphas = torch.stack(alphas) if len(alphas) > 0 else torch.zeros(0, 0, 0, 1)

        # Get frame rate
        frame_rate = Fraction(video_stream.average_rate) if video_stream.average_rate else Fraction(1)

-        # Get audio if available
-        audio = None
-        container.seek(start_pts, stream=video_stream)
-        # Use last stream for consistency
-        if len(container.streams.audio):
-            audio_stream = container.streams.audio[-1]
-            audio_frames = []
-            resample = av.audio.resampler.AudioResampler(format='fltp').resample
-            frames = itertools.chain.from_iterable(
-                map(resample, container.decode(audio_stream))
-            )
+        if len(audio_frames) > 0:
+            audio_data = np.concatenate(audio_frames, axis=1)  # shape: (channels, total_samples)
+            if self.__duration:
+                audio_data = audio_data[..., :int(self.__duration * audio_stream.sample_rate)]

-            has_first_frame = False
-            for frame in frames:
-                offset_seconds = start_time - frame.pts * audio_stream.time_base
-                to_skip = max(0, int(offset_seconds * audio_stream.sample_rate))
-                if to_skip < frame.samples:
-                    has_first_frame = True
-                    break
-            if has_first_frame:
-                audio_frames.append(frame.to_ndarray()[..., to_skip:])
-
-            for frame in frames:
-                if self.__duration and frame.time > start_time + self.__duration:
-                    break
-                audio_frames.append(frame.to_ndarray())  # shape: (channels, samples)
-            if len(audio_frames) > 0:
-                audio_data = np.concatenate(audio_frames, axis=1)  # shape: (channels, total_samples)
-                if self.__duration:
-                    audio_data = audio_data[..., :int(self.__duration * audio_stream.sample_rate)]
-
-                audio_tensor = torch.from_numpy(audio_data).unsqueeze(0)  # shape: (1, channels, total_samples)
-                audio = AudioInput({
-                    "waveform": audio_tensor,
-                    "sample_rate": int(audio_stream.sample_rate) if audio_stream.sample_rate else 1,
-                })
+            audio_tensor = torch.from_numpy(audio_data).unsqueeze(0)  # shape: (1, channels, total_samples)
+            audio = AudioInput({
+                "waveform": audio_tensor,
+                "sample_rate": int(audio_stream.sample_rate) if audio_stream.sample_rate else 1,
+            })

        metadata = container.metadata
-        return VideoComponents(images=images, audio=audio, frame_rate=frame_rate, metadata=metadata)
+        return VideoComponents(images=images, alpha=alphas, audio=audio, frame_rate=frame_rate, metadata=metadata)

    def get_components(self) -> VideoComponents:
        if isinstance(self.__file, io.BytesIO):
--- a/comfy_api/latest/_util/video_types.py
+++ b/comfy_api/latest/_util/video_types.py
@ -3,7 +3,7 @@ from dataclasses import dataclass
 from enum import Enum
 from fractions import Fraction
 from typing import Optional
-from .._input import ImageInput, AudioInput
+from .._input import ImageInput, AudioInput, MaskInput

 class VideoCodec(str, Enum):
    AUTO = "auto"
@ -48,5 +48,4 @@ class VideoComponents:
    frame_rate: Fraction
    audio: Optional[AudioInput] = None
    metadata: Optional[dict] = None
-
-
+    alpha: Optional[MaskInput] = None
--- a/comfy_api_nodes/apis/wan.py
+++ b/comfy_api_nodes/apis/wan.py
@ -118,7 +118,7 @@ class Wan27ReferenceVideoInputField(BaseModel):
 class Wan27ReferenceVideoParametersField(BaseModel):
    resolution: str = Field(...)
    ratio: str | None = Field(None)
-    duration: int = Field(5, ge=2, le=10)
+    duration: int = Field(5, ge=2, le=15)
    watermark: bool = Field(False)
    seed: int = Field(..., ge=0, le=2147483647)

@ -157,7 +157,7 @@ class Wan27VideoEditInputField(BaseModel):
 class Wan27VideoEditParametersField(BaseModel):
    resolution: str = Field(...)
    ratio: str | None = Field(None)
-    duration: int = Field(0)
+    duration: int | None = Field(0)
    audio_setting: str = Field("auto")
    watermark: bool = Field(False)
    seed: int = Field(..., ge=0, le=2147483647)
--- a/comfy_api_nodes/nodes_sora.py
+++ b/comfy_api_nodes/nodes_sora.py
@ -33,9 +33,13 @@ class OpenAIVideoSora2(IO.ComfyNode):
    def define_schema(cls):
        return IO.Schema(
            node_id="OpenAIVideoSora2",
-            display_name="OpenAI Sora - Video",
+            display_name="OpenAI Sora - Video (Deprecated)",
            category="api node/video/Sora",
-            description="OpenAI video and audio generation.",
+            description=(
+                "OpenAI video and audio generation.\n\n"
+                "DEPRECATION NOTICE: OpenAI will stop serving the Sora v2 API in September 2026. "
+                "This node will be removed from ComfyUI at that time."
+            ),
            inputs=[
                IO.Combo.Input(
                    "model",
--- a/comfy_api_nodes/nodes_wan.py
+++ b/comfy_api_nodes/nodes_wan.py
@ -1646,6 +1646,557 @@ class Wan2ReferenceVideoApi(IO.ComfyNode):
        return IO.NodeOutput(await download_url_to_video_output(response.output.video_url))


+class HappyHorseTextToVideoApi(IO.ComfyNode):
+    @classmethod
+    def define_schema(cls):
+        return IO.Schema(
+            node_id="HappyHorseTextToVideoApi",
+            display_name="HappyHorse Text to Video",
+            category="api node/video/Wan",
+            description="Generates a video based on a text prompt using the HappyHorse model.",
+            inputs=[
+                IO.DynamicCombo.Input(
+                    "model",
+                    options=[
+                        IO.DynamicCombo.Option(
+                            "happyhorse-1.0-t2v",
+                            [
+                                IO.String.Input(
+                                    "prompt",
+                                    multiline=True,
+                                    default="",
+                                    tooltip="Prompt describing the elements and visual features. "
+                                    "Supports English and Chinese.",
+                                ),
+                                IO.Combo.Input(
+                                    "resolution",
+                                    options=["720P", "1080P"],
+                                ),
+                                IO.Combo.Input(
+                                    "ratio",
+                                    options=["16:9", "9:16", "1:1", "4:3", "3:4"],
+                                ),
+                                IO.Int.Input(
+                                    "duration",
+                                    default=5,
+                                    min=3,
+                                    max=15,
+                                    step=1,
+                                    display_mode=IO.NumberDisplay.number,
+                                ),
+                            ],
+                        ),
+                    ],
+                ),
+                IO.Int.Input(
+                    "seed",
+                    default=0,
+                    min=0,
+                    max=2147483647,
+                    step=1,
+                    display_mode=IO.NumberDisplay.number,
+                    control_after_generate=True,
+                    tooltip="Seed to use for generation.",
+                ),
+                IO.Boolean.Input(
+                    "watermark",
+                    default=False,
+                    tooltip="Whether to add an AI-generated watermark to the result.",
+                    advanced=True,
+                ),
+            ],
+            outputs=[
+                IO.Video.Output(),
+            ],
+            hidden=[
+                IO.Hidden.auth_token_comfy_org,
+                IO.Hidden.api_key_comfy_org,
+                IO.Hidden.unique_id,
+            ],
+            is_api_node=True,
+            price_badge=IO.PriceBadge(
+                depends_on=IO.PriceBadgeDepends(widgets=["model", "model.resolution", "model.duration"]),
+                expr="""
+                (
+                  $res := $lookup(widgets, "model.resolution");
+                  $dur := $lookup(widgets, "model.duration");
+                  $ppsTable := { "720p": 0.14, "1080p": 0.24 };
+                  $pps := $lookup($ppsTable, $res);
+                  { "type": "usd", "usd": $pps * $dur }
+                )
+                """,
+            ),
+        )
+
+    @classmethod
+    async def execute(
+        cls,
+        model: dict,
+        seed: int,
+        watermark: bool,
+    ):
+        validate_string(model["prompt"], strip_whitespace=False, min_length=1)
+        initial_response = await sync_op(
+            cls,
+            ApiEndpoint(
+                path="/proxy/wan/api/v1/services/aigc/video-generation/video-synthesis",
+                method="POST",
+            ),
+            response_model=TaskCreationResponse,
+            data=Wan27Text2VideoTaskCreationRequest(
+                model=model["model"],
+                input=Text2VideoInputField(
+                    prompt=model["prompt"],
+                    negative_prompt=None,
+                ),
+                parameters=Wan27Text2VideoParametersField(
+                    resolution=model["resolution"],
+                    ratio=model["ratio"],
+                    duration=model["duration"],
+                    seed=seed,
+                    watermark=watermark,
+                ),
+            ),
+        )
+        if not initial_response.output:
+            raise Exception(f"An unknown error occurred: {initial_response.code} - {initial_response.message}")
+        response = await poll_op(
+            cls,
+            ApiEndpoint(path=f"/proxy/wan/api/v1/tasks/{initial_response.output.task_id}"),
+            response_model=VideoTaskStatusResponse,
+            status_extractor=lambda x: x.output.task_status,
+            poll_interval=7,
+        )
+        return IO.NodeOutput(await download_url_to_video_output(response.output.video_url))
+
+
+class HappyHorseImageToVideoApi(IO.ComfyNode):
+    @classmethod
+    def define_schema(cls):
+        return IO.Schema(
+            node_id="HappyHorseImageToVideoApi",
+            display_name="HappyHorse Image to Video",
+            category="api node/video/Wan",
+            description="Generate a video from a first-frame image using the HappyHorse model.",
+            inputs=[
+                IO.DynamicCombo.Input(
+                    "model",
+                    options=[
+                        IO.DynamicCombo.Option(
+                            "happyhorse-1.0-i2v",
+                            [
+                                IO.String.Input(
+                                    "prompt",
+                                    multiline=True,
+                                    default="",
+                                    tooltip="Prompt describing the elements and visual features. "
+                                    "Supports English and Chinese.",
+                                ),
+                                IO.Combo.Input(
+                                    "resolution",
+                                    options=["720P", "1080P"],
+                                ),
+                                IO.Int.Input(
+                                    "duration",
+                                    default=5,
+                                    min=3,
+                                    max=15,
+                                    step=1,
+                                    display_mode=IO.NumberDisplay.number,
+                                ),
+                            ],
+                        ),
+                    ],
+                ),
+                IO.Image.Input(
+                    "first_frame",
+                    tooltip="First frame image. The output aspect ratio is derived from this image.",
+                ),
+                IO.Int.Input(
+                    "seed",
+                    default=0,
+                    min=0,
+                    max=2147483647,
+                    step=1,
+                    display_mode=IO.NumberDisplay.number,
+                    control_after_generate=True,
+                    tooltip="Seed to use for generation.",
+                ),
+                IO.Boolean.Input(
+                    "watermark",
+                    default=False,
+                    tooltip="Whether to add an AI-generated watermark to the result.",
+                    advanced=True,
+                ),
+            ],
+            outputs=[
+                IO.Video.Output(),
+            ],
+            hidden=[
+                IO.Hidden.auth_token_comfy_org,
+                IO.Hidden.api_key_comfy_org,
+                IO.Hidden.unique_id,
+            ],
+            is_api_node=True,
+            price_badge=IO.PriceBadge(
+                depends_on=IO.PriceBadgeDepends(widgets=["model", "model.resolution", "model.duration"]),
+                expr="""
+                (
+                  $res := $lookup(widgets, "model.resolution");
+                  $dur := $lookup(widgets, "model.duration");
+                  $ppsTable := { "720p": 0.14, "1080p": 0.24 };
+                  $pps := $lookup($ppsTable, $res);
+                  { "type": "usd", "usd": $pps * $dur }
+                )
+                """,
+            ),
+        )
+
+    @classmethod
+    async def execute(
+        cls,
+        model: dict,
+        first_frame: Input.Image,
+        seed: int,
+        watermark: bool,
+    ):
+        media = [
+            Wan27MediaItem(
+                type="first_frame",
+                url=await upload_image_to_comfyapi(cls, image=first_frame),
+            )
+        ]
+        initial_response = await sync_op(
+            cls,
+            ApiEndpoint(
+                path="/proxy/wan/api/v1/services/aigc/video-generation/video-synthesis",
+                method="POST",
+            ),
+            response_model=TaskCreationResponse,
+            data=Wan27ImageToVideoTaskCreationRequest(
+                model=model["model"],
+                input=Wan27ImageToVideoInputField(
+                    prompt=model["prompt"] or None,
+                    negative_prompt=None,
+                    media=media,
+                ),
+                parameters=Wan27ImageToVideoParametersField(
+                    resolution=model["resolution"],
+                    duration=model["duration"],
+                    seed=seed,
+                    watermark=watermark,
+                ),
+            ),
+        )
+        if not initial_response.output:
+            raise Exception(f"An unknown error occurred: {initial_response.code} - {initial_response.message}")
+        response = await poll_op(
+            cls,
+            ApiEndpoint(path=f"/proxy/wan/api/v1/tasks/{initial_response.output.task_id}"),
+            response_model=VideoTaskStatusResponse,
+            status_extractor=lambda x: x.output.task_status,
+            poll_interval=7,
+        )
+        return IO.NodeOutput(await download_url_to_video_output(response.output.video_url))
+
+
+class HappyHorseVideoEditApi(IO.ComfyNode):
+    @classmethod
+    def define_schema(cls):
+        return IO.Schema(
+            node_id="HappyHorseVideoEditApi",
+            display_name="HappyHorse Video Edit",
+            category="api node/video/Wan",
+            description="Edit a video using text instructions or reference images with the HappyHorse model. "
+            "Output duration is 3-15s and matches the input video; inputs longer than 15s are truncated.",
+            inputs=[
+                IO.DynamicCombo.Input(
+                    "model",
+                    options=[
+                        IO.DynamicCombo.Option(
+                            "happyhorse-1.0-video-edit",
+                            [
+                                IO.String.Input(
+                                    "prompt",
+                                    multiline=True,
+                                    default="",
+                                    tooltip="Editing instructions or style transfer requirements.",
+                                ),
+                                IO.Combo.Input(
+                                    "resolution",
+                                    options=["720P", "1080P"],
+                                ),
+                                IO.Combo.Input(
+                                    "ratio",
+                                    options=["16:9", "9:16", "1:1", "4:3", "3:4"],
+                                    tooltip="Aspect ratio. If not changed, approximates the input video ratio.",
+                                ),
+                                IO.Autogrow.Input(
+                                    "reference_images",
+                                    template=IO.Autogrow.TemplateNames(
+                                        IO.Image.Input("reference_image"),
+                                        names=[
+                                            "image1",
+                                            "image2",
+                                            "image3",
+                                            "image4",
+                                            "image5",
+                                        ],
+                                        min=0,
+                                    ),
+                                ),
+                            ],
+                        ),
+                    ],
+                ),
+                IO.Video.Input(
+                    "video",
+                    tooltip="The video to edit.",
+                ),
+                IO.Int.Input(
+                    "seed",
+                    default=0,
+                    min=0,
+                    max=2147483647,
+                    step=1,
+                    display_mode=IO.NumberDisplay.number,
+                    control_after_generate=True,
+                    tooltip="Seed to use for generation.",
+                ),
+                IO.Boolean.Input(
+                    "watermark",
+                    default=False,
+                    tooltip="Whether to add an AI-generated watermark to the result.",
+                    advanced=True,
+                ),
+            ],
+            outputs=[
+                IO.Video.Output(),
+            ],
+            hidden=[
+                IO.Hidden.auth_token_comfy_org,
+                IO.Hidden.api_key_comfy_org,
+                IO.Hidden.unique_id,
+            ],
+            is_api_node=True,
+            price_badge=IO.PriceBadge(
+                depends_on=IO.PriceBadgeDepends(widgets=["model", "model.resolution"]),
+                expr="""
+                (
+                  $res := $lookup(widgets, "model.resolution");
+                  $ppsTable := { "720p": 0.14, "1080p": 0.24 };
+                  $pps := $lookup($ppsTable, $res);
+                  { "type": "usd", "usd": $pps, "format": { "suffix": "/second" } }
+                )
+                """,
+            ),
+        )
+
+    @classmethod
+    async def execute(
+        cls,
+        model: dict,
+        video: Input.Video,
+        seed: int,
+        watermark: bool,
+    ):
+        validate_string(model["prompt"], strip_whitespace=False, min_length=1)
+        validate_video_duration(video, min_duration=3, max_duration=60)
+        media = [Wan27MediaItem(type="video", url=await upload_video_to_comfyapi(cls, video))]
+        reference_images = model.get("reference_images", {})
+        for key in reference_images:
+            media.append(
+                Wan27MediaItem(
+                    type="reference_image", url=await upload_image_to_comfyapi(cls, image=reference_images[key])
+                )
+            )
+        initial_response = await sync_op(
+            cls,
+            ApiEndpoint(
+                path="/proxy/wan/api/v1/services/aigc/video-generation/video-synthesis",
+                method="POST",
+            ),
+            response_model=TaskCreationResponse,
+            data=Wan27VideoEditTaskCreationRequest(
+                model=model["model"],
+                input=Wan27VideoEditInputField(prompt=model["prompt"], media=media),
+                parameters=Wan27VideoEditParametersField(
+                    resolution=model["resolution"],
+                    ratio=model["ratio"],
+                    duration=None,
+                    watermark=watermark,
+                    seed=seed,
+                ),
+            ),
+        )
+        if not initial_response.output:
+            raise Exception(f"An unknown error occurred: {initial_response.code} - {initial_response.message}")
+        response = await poll_op(
+            cls,
+            ApiEndpoint(path=f"/proxy/wan/api/v1/tasks/{initial_response.output.task_id}"),
+            response_model=VideoTaskStatusResponse,
+            status_extractor=lambda x: x.output.task_status,
+            poll_interval=7,
+        )
+        return IO.NodeOutput(await download_url_to_video_output(response.output.video_url))
+
+
+class HappyHorseReferenceVideoApi(IO.ComfyNode):
+    @classmethod
+    def define_schema(cls):
+        return IO.Schema(
+            node_id="HappyHorseReferenceVideoApi",
+            display_name="HappyHorse Reference to Video",
+            category="api node/video/Wan",
+            description="Generate a video featuring a person or object from reference materials with the HappyHorse "
+            "model. Supports single-character performances and multi-character interactions.",
+            inputs=[
+                IO.DynamicCombo.Input(
+                    "model",
+                    options=[
+                        IO.DynamicCombo.Option(
+                            "happyhorse-1.0-r2v",
+                            [
+                                IO.String.Input(
+                                    "prompt",
+                                    multiline=True,
+                                    default="",
+                                    tooltip="Prompt describing the video. Use identifiers such as 'character1' and "
+                                    "'character2' to refer to the reference characters.",
+                                ),
+                                IO.Combo.Input(
+                                    "resolution",
+                                    options=["720P", "1080P"],
+                                ),
+                                IO.Combo.Input(
+                                    "ratio",
+                                    options=["16:9", "9:16", "1:1", "4:3", "3:4"],
+                                ),
+                                IO.Int.Input(
+                                    "duration",
+                                    default=5,
+                                    min=3,
+                                    max=15,
+                                    step=1,
+                                    display_mode=IO.NumberDisplay.number,
+                                ),
+                                IO.Autogrow.Input(
+                                    "reference_images",
+                                    template=IO.Autogrow.TemplateNames(
+                                        IO.Image.Input("reference_image"),
+                                        names=[
+                                            "image1",
+                                            "image2",
+                                            "image3",
+                                            "image4",
+                                            "image5",
+                                            "image6",
+                                            "image7",
+                                            "image8",
+                                            "image9",
+                                        ],
+                                        min=1,
+                                    ),
+                                ),
+                            ],
+                        ),
+                    ],
+                ),
+                IO.Int.Input(
+                    "seed",
+                    default=0,
+                    min=0,
+                    max=2147483647,
+                    step=1,
+                    display_mode=IO.NumberDisplay.number,
+                    control_after_generate=True,
+                    tooltip="Seed to use for generation.",
+                ),
+                IO.Boolean.Input(
+                    "watermark",
+                    default=False,
+                    tooltip="Whether to add an AI-generated watermark to the result.",
+                    advanced=True,
+                ),
+            ],
+            outputs=[
+                IO.Video.Output(),
+            ],
+            hidden=[
+                IO.Hidden.auth_token_comfy_org,
+                IO.Hidden.api_key_comfy_org,
+                IO.Hidden.unique_id,
+            ],
+            is_api_node=True,
+            price_badge=IO.PriceBadge(
+                depends_on=IO.PriceBadgeDepends(widgets=["model", "model.resolution", "model.duration"]),
+                expr="""
+                (
+                  $res := $lookup(widgets, "model.resolution");
+                  $dur := $lookup(widgets, "model.duration");
+                  $ppsTable := { "720p": 0.14, "1080p": 0.24 };
+                  $pps := $lookup($ppsTable, $res);
+                  { "type": "usd", "usd": $pps * $dur }
+                )
+                """,
+            ),
+        )
+
+    @classmethod
+    async def execute(
+        cls,
+        model: dict,
+        seed: int,
+        watermark: bool,
+    ):
+        validate_string(model["prompt"], strip_whitespace=False, min_length=1)
+        media = []
+        reference_images = model.get("reference_images", {})
+        for key in reference_images:
+            media.append(
+                Wan27MediaItem(
+                    type="reference_image",
+                    url=await upload_image_to_comfyapi(cls, image=reference_images[key]),
+                )
+            )
+        if not media:
+            raise ValueError("At least one reference reference image must be provided.")
+
+        initial_response = await sync_op(
+            cls,
+            ApiEndpoint(
+                path="/proxy/wan/api/v1/services/aigc/video-generation/video-synthesis",
+                method="POST",
+            ),
+            response_model=TaskCreationResponse,
+            data=Wan27ReferenceVideoTaskCreationRequest(
+                model=model["model"],
+                input=Wan27ReferenceVideoInputField(
+                    prompt=model["prompt"],
+                    negative_prompt=None,
+                    media=media,
+                ),
+                parameters=Wan27ReferenceVideoParametersField(
+                    resolution=model["resolution"],
+                    ratio=model["ratio"],
+                    duration=model["duration"],
+                    watermark=watermark,
+                    seed=seed,
+                ),
+            ),
+        )
+        if not initial_response.output:
+            raise Exception(f"An unknown error occurred: {initial_response.code} - {initial_response.message}")
+        response = await poll_op(
+            cls,
+            ApiEndpoint(path=f"/proxy/wan/api/v1/tasks/{initial_response.output.task_id}"),
+            response_model=VideoTaskStatusResponse,
+            status_extractor=lambda x: x.output.task_status,
+            poll_interval=7,
+        )
+        return IO.NodeOutput(await download_url_to_video_output(response.output.video_url))
+
+
 class WanApiExtension(ComfyExtension):
    @override
    async def get_node_list(self) -> list[type[IO.ComfyNode]]:
@ -1660,6 +2211,10 @@ class WanApiExtension(ComfyExtension):
            Wan2VideoContinuationApi,
            Wan2VideoEditApi,
            Wan2ReferenceVideoApi,
+            HappyHorseTextToVideoApi,
+            HappyHorseImageToVideoApi,
+            HappyHorseVideoEditApi,
+            HappyHorseReferenceVideoApi,
        ]


--- a/comfy_extras/nodes_hunyuan3d.py
+++ b/comfy_extras/nodes_hunyuan3d.py
@ -637,7 +637,7 @@ class SaveGLB(IO.ComfyNode):
                    ],
                    tooltip="Mesh or 3D file to save",
                ),
-                IO.String.Input("filename_prefix", default="mesh/ComfyUI"),
+                IO.String.Input("filename_prefix", default="3d/ComfyUI"),
            ],
            hidden=[IO.Hidden.prompt, IO.Hidden.extra_pnginfo]
        )
--- a/comfy_extras/nodes_mask.py
+++ b/comfy_extras/nodes_mask.py
@ -2,6 +2,7 @@ import numpy as np
 import scipy.ndimage
 import torch
 import comfy.utils
+import comfy.model_management
 import node_helpers
 from typing_extensions import override
 from comfy_api.latest import ComfyExtension, IO, UI
@ -188,7 +189,7 @@ class SolidMask(IO.ComfyNode):

    @classmethod
    def execute(cls, value, width, height) -> IO.NodeOutput:
-        out = torch.full((1, height, width), value, dtype=torch.float32, device="cpu")
+        out = torch.full((1, height, width), value, dtype=torch.float32, device=comfy.model_management.intermediate_device())
        return IO.NodeOutput(out)

    solid = execute  # TODO: remove
@ -262,6 +263,7 @@ class MaskComposite(IO.ComfyNode):
    def execute(cls, destination, source, x, y, operation) -> IO.NodeOutput:
        output = destination.reshape((-1, destination.shape[-2], destination.shape[-1])).clone()
        source = source.reshape((-1, source.shape[-2], source.shape[-1]))
+        source = source.to(output.device)

        left, top = (x, y,)
        right, bottom = (min(left + source.shape[-1], destination.shape[-1]), min(top + source.shape[-2], destination.shape[-2]))
--- a/comfy_extras/nodes_sd3.py
+++ b/comfy_extras/nodes_sd3.py
@ -54,7 +54,7 @@ class EmptySD3LatentImage(io.ComfyNode):

    @classmethod
    def execute(cls, width, height, batch_size=1) -> io.NodeOutput:
-        latent = torch.zeros([batch_size, 16, height // 8, width // 8], device=comfy.model_management.intermediate_device())
+        latent = torch.zeros([batch_size, 16, height // 8, width // 8], device=comfy.model_management.intermediate_device(), dtype=comfy.model_management.intermediate_dtype())
        return io.NodeOutput({"samples": latent, "downscale_ratio_spacial": 8})

    generate = execute  # TODO: remove
--- a/comfyui_version.py
+++ b/comfyui_version.py
@ -1,3 +1,3 @@
 # This file is automatically generated by the build process when version is
 # updated in pyproject.toml.
-__version__ = "0.19.3"
+__version__ = "0.20.1"
--- a/nodes.py
+++ b/nodes.py
@ -2228,6 +2228,12 @@ async def load_custom_node(module_path: str, ignore=set(), module_parent="custom

        LOADED_MODULE_DIRS[module_name] = os.path.abspath(module_dir)

+        # Only load node_replacements.json from directory-based custom nodes (proper packs).
+        # Single-file .py nodes share a parent dir, so checking there would be incorrect.
+        if os.path.isdir(module_path):
+            from server import PromptServer
+            PromptServer.instance.node_replace_manager.load_from_json(module_dir, module_name)
+
        try:
            from comfy_config import config_parser

--- a/openapi.yaml
+++ b/openapi.yaml
--- a/pyproject.toml
+++ b/pyproject.toml
@ -1,6 +1,6 @@
 [project]
 name = "ComfyUI"
-version = "0.19.3"
+version = "0.20.1"
 readme = "README.md"
 license = { file = "LICENSE" }
 requires-python = ">=3.10"
--- a/requirements.txt
+++ b/requirements.txt
@ -1,5 +1,5 @@
-comfyui-frontend-package==1.42.14
-comfyui-workflow-templates==0.9.62
+comfyui-frontend-package==1.42.15
+comfyui-workflow-templates==0.9.63
 comfyui-embedded-docs==0.4.4
 torch
 torchsde
--- a/tests/test_node_replacements_json.py
+++ b/tests/test_node_replacements_json.py
@ -0,0 +1,217 @@
+"""Tests for NodeReplaceManager.load_from_json — auto-registration of
+node_replacements.json from custom node directories."""
+import json
+import os
+import tempfile
+import unittest
+
+from app.node_replace_manager import NodeReplaceManager
+
+
+class SimpleNodeReplace:
+    """Lightweight stand-in for comfy_api.latest._io.NodeReplace (avoids torch import)."""
+    def __init__(self, new_node_id, old_node_id, old_widget_ids=None,
+                 input_mapping=None, output_mapping=None):
+        self.new_node_id = new_node_id
+        self.old_node_id = old_node_id
+        self.old_widget_ids = old_widget_ids
+        self.input_mapping = input_mapping
+        self.output_mapping = output_mapping
+
+    def as_dict(self):
+        return {
+            "new_node_id": self.new_node_id,
+            "old_node_id": self.old_node_id,
+            "old_widget_ids": self.old_widget_ids,
+            "input_mapping": list(self.input_mapping) if self.input_mapping else None,
+            "output_mapping": list(self.output_mapping) if self.output_mapping else None,
+        }
+
+
+class TestLoadFromJson(unittest.TestCase):
+    """Test auto-registration of node_replacements.json from custom node directories."""
+
+    def setUp(self):
+        self.tmpdir = tempfile.mkdtemp()
+        self.manager = NodeReplaceManager()
+
+    def _write_json(self, data):
+        path = os.path.join(self.tmpdir, "node_replacements.json")
+        with open(path, "w") as f:
+            json.dump(data, f)
+
+    def _load(self):
+        self.manager.load_from_json(self.tmpdir, "test-node-pack", _node_replace_class=SimpleNodeReplace)
+
+    def test_no_file_does_nothing(self):
+        """No node_replacements.json — should silently do nothing."""
+        self._load()
+        self.assertEqual(self.manager.as_dict(), {})
+
+    def test_empty_object(self):
+        """Empty {} — should do nothing."""
+        self._write_json({})
+        self._load()
+        self.assertEqual(self.manager.as_dict(), {})
+
+    def test_single_replacement(self):
+        """Single replacement entry registers correctly."""
+        self._write_json({
+            "OldNode": [{
+                "new_node_id": "NewNode",
+                "old_node_id": "OldNode",
+                "input_mapping": [{"new_id": "model", "old_id": "ckpt_name"}],
+                "output_mapping": [{"new_idx": 0, "old_idx": 0}],
+            }]
+        })
+        self._load()
+        result = self.manager.as_dict()
+        self.assertIn("OldNode", result)
+        self.assertEqual(len(result["OldNode"]), 1)
+        entry = result["OldNode"][0]
+        self.assertEqual(entry["new_node_id"], "NewNode")
+        self.assertEqual(entry["old_node_id"], "OldNode")
+        self.assertEqual(entry["input_mapping"], [{"new_id": "model", "old_id": "ckpt_name"}])
+        self.assertEqual(entry["output_mapping"], [{"new_idx": 0, "old_idx": 0}])
+
+    def test_multiple_replacements(self):
+        """Multiple old_node_ids each with entries."""
+        self._write_json({
+            "NodeA": [{"new_node_id": "NodeB", "old_node_id": "NodeA"}],
+            "NodeC": [{"new_node_id": "NodeD", "old_node_id": "NodeC"}],
+        })
+        self._load()
+        result = self.manager.as_dict()
+        self.assertEqual(len(result), 2)
+        self.assertIn("NodeA", result)
+        self.assertIn("NodeC", result)
+
+    def test_multiple_alternatives_for_same_node(self):
+        """Multiple replacement options for the same old node."""
+        self._write_json({
+            "OldNode": [
+                {"new_node_id": "AltA", "old_node_id": "OldNode"},
+                {"new_node_id": "AltB", "old_node_id": "OldNode"},
+            ]
+        })
+        self._load()
+        result = self.manager.as_dict()
+        self.assertEqual(len(result["OldNode"]), 2)
+
+    def test_null_mappings(self):
+        """Null input/output mappings (trivial replacement)."""
+        self._write_json({
+            "OldNode": [{
+                "new_node_id": "NewNode",
+                "old_node_id": "OldNode",
+                "input_mapping": None,
+                "output_mapping": None,
+            }]
+        })
+        self._load()
+        entry = self.manager.as_dict()["OldNode"][0]
+        self.assertIsNone(entry["input_mapping"])
+        self.assertIsNone(entry["output_mapping"])
+
+    def test_old_node_id_defaults_to_key(self):
+        """If old_node_id is missing from entry, uses the dict key."""
+        self._write_json({
+            "OldNode": [{"new_node_id": "NewNode"}]
+        })
+        self._load()
+        entry = self.manager.as_dict()["OldNode"][0]
+        self.assertEqual(entry["old_node_id"], "OldNode")
+
+    def test_invalid_json_skips(self):
+        """Invalid JSON file — should warn and skip, not crash."""
+        path = os.path.join(self.tmpdir, "node_replacements.json")
+        with open(path, "w") as f:
+            f.write("{invalid json")
+        self._load()
+        self.assertEqual(self.manager.as_dict(), {})
+
+    def test_non_object_json_skips(self):
+        """JSON array instead of object — should warn and skip."""
+        self._write_json([1, 2, 3])
+        self._load()
+        self.assertEqual(self.manager.as_dict(), {})
+
+    def test_non_list_value_skips(self):
+        """Value is not a list — should warn and skip that key."""
+        self._write_json({
+            "OldNode": "not a list",
+            "GoodNode": [{"new_node_id": "NewNode", "old_node_id": "GoodNode"}],
+        })
+        self._load()
+        result = self.manager.as_dict()
+        self.assertNotIn("OldNode", result)
+        self.assertIn("GoodNode", result)
+
+    def test_with_old_widget_ids(self):
+        """old_widget_ids are passed through."""
+        self._write_json({
+            "OldNode": [{
+                "new_node_id": "NewNode",
+                "old_node_id": "OldNode",
+                "old_widget_ids": ["width", "height"],
+            }]
+        })
+        self._load()
+        entry = self.manager.as_dict()["OldNode"][0]
+        self.assertEqual(entry["old_widget_ids"], ["width", "height"])
+
+    def test_set_value_in_input_mapping(self):
+        """input_mapping with set_value entries."""
+        self._write_json({
+            "OldNode": [{
+                "new_node_id": "NewNode",
+                "old_node_id": "OldNode",
+                "input_mapping": [
+                    {"new_id": "method", "set_value": "lanczos"},
+                    {"new_id": "size", "old_id": "dimension"},
+                ],
+            }]
+        })
+        self._load()
+        entry = self.manager.as_dict()["OldNode"][0]
+        self.assertEqual(len(entry["input_mapping"]), 2)
+
+    def test_missing_new_node_id_skipped(self):
+        """Entry without new_node_id is skipped."""
+        self._write_json({
+            "OldNode": [
+                {"old_node_id": "OldNode"},
+                {"new_node_id": "", "old_node_id": "OldNode"},
+                {"new_node_id": "ValidNew", "old_node_id": "OldNode"},
+            ]
+        })
+        self._load()
+        result = self.manager.as_dict()
+        self.assertEqual(len(result["OldNode"]), 1)
+        self.assertEqual(result["OldNode"][0]["new_node_id"], "ValidNew")
+
+    def test_non_dict_entry_skipped(self):
+        """Non-dict entries in the list are silently skipped."""
+        self._write_json({
+            "OldNode": [
+                "not a dict",
+                {"new_node_id": "NewNode", "old_node_id": "OldNode"},
+            ]
+        })
+        self._load()
+        result = self.manager.as_dict()
+        self.assertEqual(len(result["OldNode"]), 1)
+
+    def test_has_replacement_after_load(self):
+        """Manager reports has_replacement correctly after JSON load."""
+        self._write_json({
+            "OldNode": [{"new_node_id": "NewNode", "old_node_id": "OldNode"}],
+        })
+        self.assertFalse(self.manager.has_replacement("OldNode"))
+        self._load()
+        self.assertTrue(self.manager.has_replacement("OldNode"))
+        self.assertFalse(self.manager.has_replacement("UnknownNode"))
+
+
+if __name__ == "__main__":
+    unittest.main()
Author	SHA1	Message	Date
Jedrzej Kosinski	5225f109a6	Merge branch 'master' into deepme987/auto-register-node-replacements-json	2026-04-28 02:53:37 -07:00
Gilad Schreiber	24de8dc01b	Fix SolidMask and MaskComposite device mismatch with --gpu-only (#13296 ) SolidMask had a hardcoded device="cpu" while other nodes (e.g. EmptyImage) follow intermediate_device(). This causes a RuntimeError when MaskComposite combines masks from different device sources under --gpu-only. - SolidMask: use intermediate_device() instead of hardcoded "cpu" - MaskComposite: align source device to destination before operating Co-authored-by: Alexis Rolland <alexisrolland@hotmail.com> Co-authored-by: Jedrzej Kosinski <kosinkadink1@gmail.com>	2026-04-28 01:18:19 -07:00
Daxiong (Lin)	c0d77a5d53	Change the `save 3d model` node's filename prefix to `3d/ComfyUI` (CORE-106) (#12826 ) * Change save 3d model's filename prefix to 3d/ComfyUI As this node has already changed from `Save GLB` to `Save 3D Model`, using the filename prefix `3d` will be better than `mesh` * use lowercase ---------	2026-04-28 00:59:59 -07:00
Matt Miller	ed201fff08	ci: dispatch tag push to Comfy-Org/cloud (#13541 ) Fires on v* tag push (earlier than release.published, which can lag) and triggers a repository_dispatch on Comfy-Org/cloud with event_type comfyui_tag_pushed. Legacy desktop dispatch in release-webhook.yml is left untouched.	2026-04-27 19:51:33 -07:00
rattus	b47f15f25a	fix: Handle un-inited meta-tensors in models (fixes a CPU TE crash) (CORE-67) (#13578 )	2026-04-27 22:22:31 -04:00
comfyanonymous	3cbf015578	Read audio and video at the same time in video loader node. (#13591 )	2026-04-27 16:44:12 -07:00
comfyanonymous	64b8457f55	ComfyUI v0.20.1 because github is broken again and messed up my release.	2026-04-27 16:10:14 -04:00
comfyanonymous	75143eeb06	ComfyUI v0.20.0	2026-04-27 13:24:36 -04:00
Daxiong (Lin)	1233f077b1	chore: update workflow templates to v0.9.63 (#13586 ) Co-authored-by: Jedrzej Kosinski <kosinkadink1@gmail.com>	2026-04-27 10:06:03 -07:00
Alexander Piskun	6968a70e60	[Partner Nodes] HappyHorse model (#13582 ) * feat(api-nodes): add nodes for HappyHorse model Signed-off-by: bigcat88 <bigcat88@icloud.com> * fix price badges Signed-off-by: bigcat88 <bigcat88@icloud.com> * fix: allow durations up to 15 s Signed-off-by: bigcat88 <bigcat88@icloud.com> --------- Signed-off-by: bigcat88 <bigcat88@icloud.com>	2026-04-27 09:53:08 -07:00
comfyanonymous	115f418b64	Make EmptySD3LatentImage node use intermediate dtype. (#13577 )	2026-04-26 23:23:57 -04:00
Daxiong (Lin)	7385eb2800	Add new ComfyUI blueprints and fix subgraph naming (#13371 ) * Remove local tag from subgraph name * New Subgraph blueprints * Remove duplicate blueprint * Update Subgraph size * Update subgraph * Update Blueprint * Remove local tag from subgraph name * New Subgraph blueprints * Remove duplicate blueprint * Update Subgraph size * Update subgraph * Update Blueprint * Update LTX 2.0 Pose to Video * Fix crop blueprint split coverage Made-with: Cursor * Clean up image edit blueprint metadata Made-with: Cursor * Update subgraph blueprints --------- Co-authored-by: Jedrzej Kosinski <kosinkadink1@gmail.com>	2026-04-26 22:59:16 +08:00
comfyanonymous	df22bcd5e1	Support loading the alpha channel of videos. (#13564 ) Not exposed in nodes yet.	2026-04-25 21:02:58 -04:00
Comfy Org PR Bot	5e3f15a830	Bump comfyui-frontend-package to 1.42.15 (#13556 )	2026-04-24 17:21:39 -07:00
comfyanonymous	4304c15e9b	Properly load higher bit depth videos. (#13542 )	2026-04-24 16:46:10 -04:00
Alexander Piskun	7636599389	chore(api-nodes): add upcoming-deprecation notice to Sora nodes (#13549 )	2026-04-24 06:54:10 -07:00
Matt Miller	443074eee9	Add OpenAPI 3.1 specification for ComfyUI API (#13397 ) * Add OpenAPI 3.1 specification for ComfyUI API Adds a comprehensive OpenAPI 3.1 spec documenting all HTTP endpoints exposed by ComfyUI's server, including prompt execution, queue management, file uploads, userdata, settings, system stats, object info, assets, and internal routes. The spec was validated against the source code with adversarial review from multiple models, and passes Spectral linting with zero errors. Also removes openapi.yaml from .gitignore so the spec is tracked. * Mark /api/history endpoints as deprecated Address Jacob's review feedback on PR #13397 by explicitly marking the three /api/history operations as deprecated in the OpenAPI spec: * GET /api/history -> superseded by GET /api/jobs * POST /api/history -> superseded by /api/jobs management * GET /api/history/{prompt_id} -> superseded by GET /api/jobs/{job_id} Each operation gains deprecated: true plus a description that names the replacement. A formal sunset timeline (RFC 8594 Deprecation and RFC 8553 Sunset headers, minimum-runway policy) is being defined separately and will be applied as a follow-up. * Address Spectral lint findings in openapi.yaml - Add operation descriptions to 52 endpoints (prompt, queue, upload, view, models, userdata, settings, assets, internal, etc.) - Add schema descriptions to 22 component schemas - Add parameter descriptions to 8 path parameters that were missing them - Remove 6 unused component schemas: TaskOutput, EmbeddingsResponse, ExtensionsResponse, LogRawResponse, UserInfo, UserDataFullInfo No wire/shape changes. Reduces Spectral findings from 92 to 4. The remaining 4 are real issues (WebSocket 101 on /ws, loose error schema, and two snake_case warnings on real wire field names) and are worth addressing separately. * fix(openapi): address jtreminio oneOf review on /api/userdata Restructure the UserData response schemas to address the review feedback on the `oneOf` without a discriminator, and fix two accuracy bugs found while doing it. Changes - GET /api/userdata response: extract the inline `oneOf` to a named schema (`ListUserdataResponse`) and add the missing third variant returned when `split=true` and `full_info=false` (array of `[relative_path, ...path_components]`). Previously only two of the three actual server response shapes were described. - UserDataResponse (POST endpoints): correct the description — this schema is a single item, not a list — and point at the canonical `GetUserDataResponseFullFile` schema instead of the duplicate `UserDataResponseFull`. Also removes the malformed blank line in `UserDataResponseShort`. - Delete the now-unused `UserDataResponseFull` and `UserDataResponseShort` schemas (replaced by reuse of `GetUserDataResponseFullFile` and an inline string variant). - Add an `x-variant-selector` vendor extension to both `oneOf` sites documenting which query-parameter combination selects which branch, since a true OpenAPI `discriminator` is not applicable (the variants are type-disjoint and the selector lives in the request, not the response body). This keeps the shapes the server actually emits (no wire-breaking change) while making the selection rule explicit for SDK generators and readers. --------- Co-authored-by: guill <jacob.e.segal@gmail.com>	2026-04-23 21:00:25 -07:00
Terry Jia	2e0503780d	range type (#13322 ) Co-authored-by: guill <jacob.e.segal@gmail.com>	2026-04-23 20:51:34 -07:00
Deep Mehta	e35fe5bc09	Merge branch 'master' into deepme987/auto-register-node-replacements-json	2026-04-21 05:00:15 +05:30
Deep Mehta	77054cd49e	Merge branch 'master' into deepme987/auto-register-node-replacements-json	2026-04-14 19:34:21 -07:00
Deep Mehta	1cd2730b25	Merge branch 'master' into deepme987/auto-register-node-replacements-json	2026-04-06 13:13:42 -07:00
Deep Mehta	d4351f77f8	Merge branch 'master' into deepme987/auto-register-node-replacements-json	2026-03-25 22:50:44 -07:00
Deep Mehta	9837dd368a	refactor: move load_from_json into NodeReplaceManager Address review feedback from Kosinkadink: 1. Move JSON loading logic from nodes.py into NodeReplaceManager as load_from_json() method for better encapsulation and testability 2. Tests now exercise the real NodeReplaceManager (no duplicated logic) 3. Defer `import nodes` in apply_replacements to avoid torch at import 4. nodes.py call site simplified to one line: PromptServer.instance.node_replace_manager.load_from_json(...)	2026-03-25 22:12:23 -07:00
Deep Mehta	62ec9a3238	fix: skip single-file nodes and validate new_node_id Two fixes from code review: 1. Only load node_replacements.json from directory-based custom nodes. Single-file .py nodes share a parent dir (custom_nodes/), so checking there would incorrectly pick up a stray file. 2. Skip entries with missing or empty new_node_id instead of registering a replacement pointing to nothing.	2026-03-23 14:47:11 -07:00
Deep Mehta	b20cb7892e	Merge branch 'master' into deepme987/auto-register-node-replacements-json	2026-03-18 17:14:08 -07:00
Deep Mehta	b9b24d425b	Merge branch 'master' into deepme987/auto-register-node-replacements-json	2026-03-17 20:58:06 -07:00
Deep Mehta	d731cb6ae1	feat: auto-register node replacements from custom node JSON files Custom node authors can now ship a `node_replacements.json` in their repo root to define replacements declaratively. During node loading, ComfyUI reads these files and registers entries via the existing NodeReplaceManager — no Python registration code needed. This enables two use cases: 1. Authors deprecate/rename nodes with a migration path for old workflows 2. Authors offer their nodes as drop-in replacements for other packs	2026-03-17 20:57:32 -07:00