ComfyUI v0.20.1 because github is broken again and messed up my release.

ComfyUI v0.20.0
chore: update workflow templates to v0.9.63 (#13586 )
2026-05-07 10:47:58 +08:00 · 2026-04-27 16:10:14 -04:00 · 2026-04-27 13:24:36 -04:00 · 2026-04-27 10:06:03 -07:00 · 2026-04-27 09:53:08 -07:00 · 2026-04-26 23:23:57 -04:00
35 changed files with 33926 additions and 1099 deletions
--- a/.gitignore
+++ b/.gitignore
@ -21,6 +21,5 @@ venv*/
 *.log
 web_custom_versions/
 .DS_Store
-openapi.yaml
 filtered-openapi.yaml
 uv.lock
--- 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",
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+      "type": "2d2e3c8e-53b3-4618-be52-6d1d99382f0e",
      "pos": [
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+        -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,
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+          "lastLinkId": 380,
          "lastRerouteId": 0
        },
        "revision": 0,
@ -130,10 +174,10 @@
        "inputNode": {
          "id": -10,
          "bounding": [
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-            523,
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+            720,
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        },
        "outputNode": {
@ -156,8 +200,8 @@
            ],
            "localized_name": "image",
            "pos": [
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@ -168,8 +212,8 @@
              150
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@ -180,8 +224,8 @@
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@ -204,8 +248,56 @@
              159
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            "pos": [
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+          },
+          {
+            "id": "9f76338b-f4ca-4bb3-b61a-57b3f233061e",
+            "name": "seed",
+            "type": "INT",
+            "linkIds": [
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+            "pos": [
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+              840
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+          },
+          {
+            "id": "8d0422d5-5eee-4f7e-9817-dc613cc62eca",
+            "name": "unet_name",
+            "type": "COMBO",
+            "linkIds": [
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+            ],
+            "pos": [
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+              860
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+          {
+            "id": "552eece2-a735-4d00-ae78-ded454622bc1",
+            "name": "clip_name",
+            "type": "COMBO",
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+              880
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+          {
+            "id": "1e6d141c-d0f9-4a2b-895c-b6780e57cfa0",
+            "name": "vae_name",
+            "type": "COMBO",
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@ -231,14 +323,14 @@
            "type": "CLIPLoader",
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              {
@ -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"
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              "models": [
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                  "name": "qwen_2.5_vl_7b_fp8_scaled.safetensors",
@ -312,14 +409,14 @@
            "type": "VAELoader",
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+              580
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            "flags": {},
-            "order": 1,
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              {
@ -329,7 +426,7 @@
                "widget": {
                  "name": "vae_name"
                },
-                "link": null
+                "link": 380
              }
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            "outputs": [
@ -345,9 +442,14 @@
              }
            ],
            "properties": {
-              "Node name for S&R": "VAELoader",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
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+                "input_ue_unconnectable": {},
+                "version": "7.7"
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+              "Node name for S&R": "VAELoader",
              "models": [
                {
                  "name": "qwen_image_layered_vae.safetensors",
@ -375,11 +477,11 @@
              420
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            "flags": {},
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            "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"
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+              "Node name for S&R": "CLIPTextEncode",
              "enableTabs": false,
              "tabWidth": 65,
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@ -432,12 +539,12 @@
            "id": 70,
            "type": "ReferenceLatent",
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@ -470,9 +577,14 @@
              }
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            "properties": {
-              "Node name for S&R": "ReferenceLatent",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
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+              "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": []
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          },
          {
            "id": 69,
            "type": "ReferenceLatent",
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@ -525,9 +636,14 @@
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            "properties": {
-              "Node name for S&R": "ReferenceLatent",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
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              "enableTabs": false,
              "tabWidth": 65,
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@ -535,8 +651,7 @@
              "secondTabText": "Send Back",
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              "secondTabWidth": 65
-            },
-            "widgets_values": []
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@ -547,10 +662,10 @@
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+            "order": 7,
            "mode": 0,
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@ -580,9 +695,14 @@
              }
            ],
            "properties": {
-              "Node name for S&R": "ModelSamplingAuraFlow",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
+              "ue_properties": {
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@ -600,11 +720,11 @@
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@ -646,9 +766,14 @@
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@ -666,12 +791,12 @@
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            "type": "VAEEncode",
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@ -704,9 +829,14 @@
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              "cnr_id": "comfy-core",
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@ -714,24 +844,23 @@
              "secondTabText": "Send Back",
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-            },
-            "widgets_values": []
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@ -759,9 +888,14 @@
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            "properties": {
-              "Node name for S&R": "VAEDecode",
              "cnr_id": "comfy-core",
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@ -769,8 +903,7 @@
              "secondTabText": "Send Back",
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@ -780,11 +913,11 @@
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@ -816,9 +949,14 @@
            ],
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            "properties": {
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              "cnr_id": "comfy-core",
              "ver": "0.5.1",
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@ -838,14 +976,14 @@
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@ -939,9 +1077,14 @@
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              "cnr_id": "comfy-core",
              "ver": "0.5.1",
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@ -964,12 +1107,12 @@
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@ -1007,9 +1150,14 @@
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            "properties": {
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              "cnr_id": "comfy-core",
              "ver": "0.5.1",
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@ -1017,23 +1165,23 @@
              "secondTabText": "Send Back",
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-            "widgets_values": []
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@ -1083,9 +1231,14 @@
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            "properties": {
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              "cnr_id": "comfy-core",
              "ver": "0.5.1",
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@ -1123,7 +1276,7 @@
                "widget": {
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              {
                "localized_name": "weight_dtype",
@ -1147,9 +1300,14 @@
              }
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            "properties": {
-              "Node name for S&R": "UNETLoader",
              "cnr_id": "comfy-core",
              "ver": "0.5.1",
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@ -1191,8 +1349,8 @@
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-              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_api/input/init.py
+++ b/comfy_api/input/init.py
@ -9,6 +9,7 @@ from comfy_api.latest._input import (
    CurveInput,
    MonotoneCubicCurve,
    LinearCurve,
+    RangeInput,
 )

 __all__ = [
@ -21,4 +22,5 @@ __all__ = [
    "CurveInput",
    "MonotoneCubicCurve",
    "LinearCurve",
+    "RangeInput",
 ]
--- a/comfy_api/latest/_input/init.py
+++ b/comfy_api/latest/_input/init.py
@ -1,5 +1,6 @@
 from .basic_types import ImageInput, AudioInput, MaskInput, LatentInput
 from .curve_types import CurvePoint, CurveInput, MonotoneCubicCurve, LinearCurve
+from .range_types import RangeInput
 from .video_types import VideoInput

 __all__ = [
@ -12,4 +13,5 @@ __all__ = [
    "CurveInput",
    "MonotoneCubicCurve",
    "LinearCurve",
+    "RangeInput",
 ]
--- a/comfy_api/latest/_input/range_types.py
+++ b/comfy_api/latest/_input/range_types.py
@ -0,0 +1,70 @@
+from __future__ import annotations
+
+import logging
+import math
+import numpy as np
+
+logger = logging.getLogger(__name__)
+
+
+class RangeInput:
+    """Represents a levels/range adjustment: input range [min, max] with
+    optional midpoint (gamma control).
+
+    Generates a 1D LUT identical to GIMP's levels mapping:
+        1. Normalize input to [0, 1] using [min, max]
+        2. Apply gamma correction: pow(value, 1/gamma)
+        3. Clamp to [0, 1]
+
+    The midpoint field is a position in [0, 1] representing where the
+    midtone falls within [min, max]. It maps to gamma via:
+        gamma = -log2(midpoint)
+    So midpoint=0.5 → gamma=1.0 (linear).
+    """
+
+    def __init__(self, min_val: float, max_val: float, midpoint: float | None = None):
+        self.min_val = min_val
+        self.max_val = max_val
+        self.midpoint = midpoint
+
+    @staticmethod
+    def from_raw(data) -> RangeInput:
+        if isinstance(data, RangeInput):
+            return data
+        if isinstance(data, dict):
+            return RangeInput(
+                min_val=float(data.get("min", 0.0)),
+                max_val=float(data.get("max", 1.0)),
+                midpoint=float(data["midpoint"]) if data.get("midpoint") is not None else None,
+            )
+        raise TypeError(f"Cannot convert {type(data)} to RangeInput")
+
+    def to_lut(self, size: int = 256) -> np.ndarray:
+        """Generate a float64 lookup table mapping [0, 1] input through this
+        levels adjustment.
+
+        The LUT maps normalized input values (0..1) to output values (0..1),
+        matching the GIMP levels formula.
+        """
+        xs = np.linspace(0.0, 1.0, size, dtype=np.float64)
+
+        in_range = self.max_val - self.min_val
+        if abs(in_range) < 1e-10:
+            return np.where(xs >= self.min_val, 1.0, 0.0).astype(np.float64)
+
+        # Normalize: map [min, max] → [0, 1]
+        result = (xs - self.min_val) / in_range
+        result = np.clip(result, 0.0, 1.0)
+
+        # Gamma correction from midpoint
+        if self.midpoint is not None and self.midpoint > 0 and self.midpoint != 0.5:
+            gamma = max(-math.log2(self.midpoint), 0.001)
+            inv_gamma = 1.0 / gamma
+            mask = result > 0
+            result[mask] = np.power(result[mask], inv_gamma)
+
+        return result
+
+    def __repr__(self) -> str:
+        mid = f", midpoint={self.midpoint}" if self.midpoint is not None else ""
+        return f"RangeInput(min={self.min_val}, max={self.max_val}{mid})"
--- a/comfy_api/latest/_input_impl/video_types.py
+++ b/comfy_api/latest/_input_impl/video_types.py
@ -240,19 +240,34 @@ class VideoFromFile(VideoInput):
            start_time = self.__start_time
        # Get video frames
        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)
+        image_format = 'gbrpf32le'
        for frame in container.decode(video_stream):
+            if alphas is None:
+                for comp in frame.format.components:
+                    if comp.is_alpha:
+                        alphas = []
+                        image_format = 'gbrapf32le'
+                        break
+
            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)
+            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:]))
+
+        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)
@ -295,7 +310,7 @@ class VideoFromFile(VideoInput):
                })

        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/_io.py
+++ b/comfy_api/latest/_io.py
@ -1266,6 +1266,43 @@ class Histogram(ComfyTypeIO):
    Type = list[int]


+@comfytype(io_type="RANGE")
+class Range(ComfyTypeIO):
+    from comfy_api.input import RangeInput
+    if TYPE_CHECKING:
+        Type = RangeInput
+
+    class Input(WidgetInput):
+        def __init__(self, id: str, display_name: str=None, optional=False, tooltip: str=None,
+                     socketless: bool=True, default: dict=None,
+                     display: str=None,
+                     gradient_stops: list=None,
+                     show_midpoint: bool=None,
+                     midpoint_scale: str=None,
+                     value_min: float=None,
+                     value_max: float=None,
+                     advanced: bool=None):
+            super().__init__(id, display_name, optional, tooltip, None, default, socketless, None, None, None, None, advanced)
+            if default is None:
+                self.default = {"min": 0.0, "max": 1.0}
+            self.display = display
+            self.gradient_stops = gradient_stops
+            self.show_midpoint = show_midpoint
+            self.midpoint_scale = midpoint_scale
+            self.value_min = value_min
+            self.value_max = value_max
+
+        def as_dict(self):
+            return super().as_dict() | prune_dict({
+                "display": self.display,
+                "gradient_stops": self.gradient_stops,
+                "show_midpoint": self.show_midpoint,
+                "midpoint_scale": self.midpoint_scale,
+                "value_min": self.value_min,
+                "value_max": self.value_max,
+            })
+
+
 DYNAMIC_INPUT_LOOKUP: dict[str, Callable[[dict[str, Any], dict[str, Any], tuple[str, dict[str, Any]], str, list[str] | None], None]] = {}
 def register_dynamic_input_func(io_type: str, func: Callable[[dict[str, Any], dict[str, Any], tuple[str, dict[str, Any]], str, list[str] | None], None]):
    DYNAMIC_INPUT_LOOKUP[io_type] = func
@ -2276,5 +2313,6 @@ __all__ = [
    "BoundingBox",
    "Curve",
    "Histogram",
+    "Range",
    "NodeReplace",
 ]
--- 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_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/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
Author	SHA1	Message	Date
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