comfy/model_management.py

@@ -721,15 +721,13 @@ def load_models_gpu(models, memory_required=0, force_patch_weights=False, minimu
     else:
         minimum_memory_required = max(inference_memory, minimum_memory_required + extra_reserved_memory())
 
-    # Order-preserving dedup. A plain set() would randomize iteration order across runs
-    models_temp = {}
+    models_temp = set()
     for m in models:
-        models_temp[m] = None
+        models_temp.add(m)
         for mm in m.model_patches_models():
-            models_temp[mm] = None
+            models_temp.add(mm)
 
-    models = list(models_temp)
-    models.reverse()
+    models = models_temp
 
     models_to_load = []
 

comfy/model_prefetch.py

@@ -37,8 +37,7 @@ def prefetch_queue_pop(queue, device, module):
     consumed = queue.pop(0)
     if consumed is not None:
         offload_stream, prefetch_state = consumed
-        if offload_stream is not None:
-            offload_stream.wait_stream(comfy.model_management.current_stream(device))
+        offload_stream.wait_stream(comfy.model_management.current_stream(device))
         _, comfy_modules = prefetch_state
         if comfy_modules is not None:
             cleanup_prefetched_modules(comfy_modules)

comfy/ops.py

@@ -253,9 +253,6 @@ def resolve_cast_module_with_vbar(s, dtype, device, bias_dtype, compute_dtype, w
     if bias is not None:
         bias = post_cast(s, "bias", bias, bias_dtype, prefetch["resident"], update_weight)
 
-    if prefetch["signature"] is not None:
-        prefetch["resident"] = True
-
     return weight, bias
 
 

comfy/sampler_helpers.py

@@ -89,8 +89,7 @@ def get_additional_models(conds, dtype):
         gligen += get_models_from_cond(conds[k], "gligen")
         add_models += get_models_from_cond(conds[k], "additional_models")
 
-    # Order-preserving dedup. A plain set() would randomize iteration order across runs
-    control_nets = list(dict.fromkeys(cnets))
+    control_nets = set(cnets)
 
     inference_memory = 0
     control_models = []

comfy_api/feature_flags.py

@@ -28,22 +28,8 @@ CLI_FEATURE_FLAG_REGISTRY: dict[str, FeatureFlagInfo] = {
 }
 
 
-def _coerce_bool(v: str) -> bool:
-    """Strict bool coercion: only 'true'/'false' (case-insensitive).
-
-    Anything else raises ValueError so the caller can warn and drop the flag,
-    rather than silently treating typos like 'ture' or 'yes' as False.
-    """
-    lower = v.lower()
-    if lower == "true":
-        return True
-    if lower == "false":
-        return False
-    raise ValueError(f"expected 'true' or 'false', got {v!r}")
-
-
 _COERCE_FNS: dict[str, Any] = {
-    "bool": _coerce_bool,
+    "bool": lambda v: v.lower() == "true",
     "int": lambda v: int(v),
     "float": lambda v: float(v),
 }
@@ -52,9 +38,8 @@ _COERCE_FNS: dict[str, Any] = {
 def _coerce_flag_value(key: str, raw_value: str) -> Any:
     """Coerce a raw string value using the registry type, or keep as string.
 
-    Returns the raw string if the key is unregistered or the type is unknown.
-    Raises ValueError/TypeError if the key is registered with a known type but
-    the value cannot be coerced; callers are expected to warn and drop the flag.
+    Returns the raw string if the key is unregistered, the type is unknown,
+    or coercion fails (with a warning logged in the failure case).
     """
     info = CLI_FEATURE_FLAG_REGISTRY.get(key)
     if info is None:
@@ -62,16 +47,20 @@ def _coerce_flag_value(key: str, raw_value: str) -> Any:
     coerce = _COERCE_FNS.get(info["type"])
     if coerce is None:
         return raw_value
-    return coerce(raw_value)
+    try:
+        return coerce(raw_value)
+    except (ValueError, TypeError):
+        logging.warning(
+            "Could not coerce --feature-flag %s=%r to %s; using raw string.",
+            key, raw_value, info["type"],
+        )
+        return raw_value
 
 
 def _parse_cli_feature_flags() -> dict[str, Any]:
     """Parse --feature-flag key=value pairs from CLI args into a dict.
 
     Items without '=' default to the value 'true' (bare flag form).
-    Flags whose value cannot be coerced to the registered type are dropped
-    with a warning, so a typo like '--feature-flag some_bool=ture' does not
-    silently take effect as the wrong value.
     """
     result: dict[str, Any] = {}
     for item in getattr(args, "feature_flag", []):
@@ -81,14 +70,7 @@ def _parse_cli_feature_flags() -> dict[str, Any]:
             continue
         if not sep:
             raw_value = "true"
-        try:
-            result[key] = _coerce_flag_value(key, raw_value.strip())
-        except (ValueError, TypeError) as e:
-            info = CLI_FEATURE_FLAG_REGISTRY.get(key, {})
-            logging.warning(
-                "Could not coerce --feature-flag %s=%r to %s (%s); dropping flag.",
-                key, raw_value.strip(), info.get("type", "?"), e,
-            )
+        result[key] = _coerce_flag_value(key, raw_value.strip())
     return result
 
 

comfy_api_nodes/nodes_sora.py

@@ -33,7 +33,7 @@ class OpenAIVideoSora2(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="OpenAIVideoSora2",
-            display_name="OpenAI Sora - Video (DEPRECATED)",
+            display_name="OpenAI Sora - Video (Deprecated)",
             category="api node/video/Sora",
             description=(
                 "OpenAI video and audio generation.\n\n"

comfy_extras/frame_interpolation_models/film_net.py

@@ -199,9 +199,6 @@ class FILMNet(nn.Module):
     def get_dtype(self):
         return self.extract.extract_sublevels.convs[0][0].conv.weight.dtype
 
-    def memory_used_forward(self, shape, dtype):
-        return 1700 * shape[1] * shape[2] * dtype.itemsize
-
     def _build_warp_grids(self, H, W, device):
         """Pre-compute warp grids for all pyramid levels."""
         if (H, W) in self._warp_grids:

comfy_extras/frame_interpolation_models/ifnet.py

@@ -74,9 +74,6 @@ class IFNet(nn.Module):
     def get_dtype(self):
         return self.encode.cnn0.weight.dtype
 
-    def memory_used_forward(self, shape, dtype):
-        return 300 * shape[1] * shape[2] * dtype.itemsize
-
     def _build_warp_grids(self, H, W, device):
         if (H, W) in self._warp_grids:
             return

comfy_extras/nodes_frame_interpolation.py

@@ -37,7 +37,7 @@ class FrameInterpolationModelLoader(io.ComfyNode):
         model = cls._detect_and_load(sd)
         dtype = torch.float16 if model_management.should_use_fp16(model_management.get_torch_device()) else torch.float32
         model.eval().to(dtype)
-        patcher = comfy.model_patcher.CoreModelPatcher(
+        patcher = comfy.model_patcher.ModelPatcher(
             model,
             load_device=model_management.get_torch_device(),
             offload_device=model_management.unet_offload_device(),
@@ -78,7 +78,7 @@ class FrameInterpolate(io.ComfyNode):
         return io.Schema(
             node_id="FrameInterpolate",
             display_name="Frame Interpolate",
-            category="video",
+            category="image/video",
             search_aliases=["rife", "film", "frame interpolation", "slow motion", "interpolate frames", "vfi"],
             inputs=[
                 FrameInterpolationModel.Input("interp_model"),
@@ -98,13 +98,16 @@ class FrameInterpolate(io.ComfyNode):
         if num_frames < 2 or multiplier < 2:
             return io.NodeOutput(images)
 
+        model_management.load_model_gpu(interp_model)
         device = interp_model.load_device
         dtype = interp_model.model_dtype()
         inference_model = interp_model.model
-        activation_mem = inference_model.memory_used_forward(images.shape, dtype)
-        model_management.load_models_gpu([interp_model], memory_required=activation_mem)
-        align = getattr(inference_model, "pad_align", 1)
+
+        # Free VRAM for inference activations (model weights + ~20x a single frame's worth)
         H, W = images.shape[1], images.shape[2]
+        activation_mem = H * W * 3 * images.element_size() * 20
+        model_management.free_memory(activation_mem, device)
+        align = getattr(inference_model, "pad_align", 1)
 
         # Prepare a single padded frame on device for determining output dimensions
         def prepare_frame(idx):

comfy_extras/nodes_image_compare.py

@@ -11,7 +11,7 @@ class ImageCompare(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="ImageCompare",
-            display_name="Compare Images",
+            display_name="Image Compare",
             description="Compares two images side by side with a slider.",
             category="image",
             essentials_category="Image Tools",

comfy_extras/nodes_images.py

@@ -24,7 +24,7 @@ class ImageCrop(IO.ComfyNode):
         return IO.Schema(
             node_id="ImageCrop",
             search_aliases=["trim"],
-            display_name="Crop Image (DEPRECATED)",
+            display_name="Image Crop (Deprecated)",
             category="image/transform",
             is_deprecated=True,
             essentials_category="Image Tools",
@@ -56,7 +56,7 @@ class ImageCropV2(IO.ComfyNode):
         return IO.Schema(
             node_id="ImageCropV2",
             search_aliases=["trim"],
-            display_name="Crop Image",
+            display_name="Image Crop",
             category="image/transform",
             essentials_category="Image Tools",
             has_intermediate_output=True,
@@ -109,7 +109,6 @@ class RepeatImageBatch(IO.ComfyNode):
         return IO.Schema(
             node_id="RepeatImageBatch",
             search_aliases=["duplicate image", "clone image"],
-            display_name="Repeat Image Batch",
             category="image/batch",
             inputs=[
                 IO.Image.Input("image"),
@@ -132,7 +131,6 @@ class ImageFromBatch(IO.ComfyNode):
         return IO.Schema(
             node_id="ImageFromBatch",
             search_aliases=["select image", "pick from batch", "extract image"],
-            display_name="Get Image from Batch",
             category="image/batch",
             inputs=[
                 IO.Image.Input("image"),
@@ -159,8 +157,7 @@ class ImageAddNoise(IO.ComfyNode):
         return IO.Schema(
             node_id="ImageAddNoise",
             search_aliases=["film grain"],
-            display_name="Add Noise to Image",
-            category="image/postprocessing",
+            category="image",
             inputs=[
                 IO.Image.Input("image"),
                 IO.Int.Input(
@@ -262,7 +259,7 @@ class ImageStitch(IO.ComfyNode):
         return IO.Schema(
             node_id="ImageStitch",
             search_aliases=["combine images", "join images", "concatenate images", "side by side"],
-            display_name="Stitch Images",
+            display_name="Image Stitch",
             description="Stitches image2 to image1 in the specified direction.\n"
             "If image2 is not provided, returns image1 unchanged.\n"
             "Optional spacing can be added between images.",
@@ -437,7 +434,6 @@ class ResizeAndPadImage(IO.ComfyNode):
         return IO.Schema(
             node_id="ResizeAndPadImage",
             search_aliases=["fit to size"],
-            display_name="Resize And Pad Image",
             category="image/transform",
             inputs=[
                 IO.Image.Input("image"),
@@ -489,7 +485,6 @@ class SaveSVGNode(IO.ComfyNode):
         return IO.Schema(
             node_id="SaveSVGNode",
             search_aliases=["export vector", "save vector graphics"],
-            display_name="Save SVG",
             description="Save SVG files on disk.",
             category="image/save",
             inputs=[
@@ -596,7 +591,7 @@ class ImageRotate(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="ImageRotate",
-            display_name="Rotate Image",
+            display_name="Image Rotate",
             search_aliases=["turn", "flip orientation"],
             category="image/transform",
             essentials_category="Image Tools",
@@ -629,7 +624,6 @@ class ImageFlip(IO.ComfyNode):
         return IO.Schema(
             node_id="ImageFlip",
             search_aliases=["mirror", "reflect"],
-            display_name="Flip Image",
             category="image/transform",
             inputs=[
                 IO.Image.Input("image"),
@@ -656,7 +650,6 @@ class ImageScaleToMaxDimension(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="ImageScaleToMaxDimension",
-            display_name="Scale Image to Max Dimension",
             category="image/upscaling",
             inputs=[
                 IO.Image.Input("image"),

comfy_extras/nodes_mask.py

@@ -80,8 +80,7 @@ class ImageCompositeMasked(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="ImageCompositeMasked",
-            search_aliases=["overlay", "layer", "paste image", "images composition"],
-            display_name="Image Composite Masked",
+            search_aliases=["paste image", "overlay", "layer"],
             category="image",
             inputs=[
                 IO.Image.Input("destination"),
@@ -202,7 +201,6 @@ class InvertMask(IO.ComfyNode):
         return IO.Schema(
             node_id="InvertMask",
             search_aliases=["reverse mask", "flip mask"],
-            display_name="Invert Mask",
             category="mask",
             inputs=[
                 IO.Mask.Input("mask"),
@@ -224,7 +222,6 @@ class CropMask(IO.ComfyNode):
         return IO.Schema(
             node_id="CropMask",
             search_aliases=["cut mask", "extract mask region", "mask slice"],
-            display_name="Crop Mask",
             category="mask",
             inputs=[
                 IO.Mask.Input("mask"),
@@ -250,8 +247,7 @@ class MaskComposite(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="MaskComposite",
-            search_aliases=["combine masks", "blend masks", "layer masks", "masks composition"],
-            display_name="Combine Masks",
+            search_aliases=["combine masks", "blend masks", "layer masks"],
             category="mask",
             inputs=[
                 IO.Mask.Input("destination"),
@@ -302,7 +298,6 @@ class FeatherMask(IO.ComfyNode):
         return IO.Schema(
             node_id="FeatherMask",
             search_aliases=["soft edge mask", "blur mask edges", "gradient mask edge"],
-            display_name="Feather Mask",
             category="mask",
             inputs=[
                 IO.Mask.Input("mask"),

comfy_extras/nodes_morphology.py

@@ -59,8 +59,7 @@ class ImageRGBToYUV(io.ComfyNode):
         return io.Schema(
             node_id="ImageRGBToYUV",
             search_aliases=["color space conversion"],
-            display_name="Image RGB to YUV",
-            category="image/color",
+            category="image/batch",
             inputs=[
                 io.Image.Input("image"),
             ],
@@ -82,8 +81,7 @@ class ImageYUVToRGB(io.ComfyNode):
         return io.Schema(
             node_id="ImageYUVToRGB",
             search_aliases=["color space conversion"],
-            display_name="Image YUV to RGB",
-            category="image/color",
+            category="image/batch",
             inputs=[
                 io.Image.Input("Y"),
                 io.Image.Input("U"),

comfy_extras/nodes_post_processing.py

@@ -20,8 +20,7 @@ class Blend(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="ImageBlend",
-            search_aliases=["mix images"],
-            display_name="Blend Images",
+            display_name="Image Blend",
             category="image/postprocessing",
             essentials_category="Image Tools",
             inputs=[
@@ -225,7 +224,6 @@ class ImageScaleToTotalPixels(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="ImageScaleToTotalPixels",
-            display_name="Scale Image to Total Pixels",
             category="image/upscaling",
             inputs=[
                 io.Image.Input("image"),
@@ -570,7 +568,7 @@ class BatchImagesNode(io.ComfyNode):
         return io.Schema(
             node_id="BatchImagesNode",
             display_name="Batch Images",
-            category="image/batch",
+            category="image",
             essentials_category="Image Tools",
             search_aliases=["batch", "image batch", "batch images", "combine images", "merge images", "stack images"],
             inputs=[

comfy_extras/nodes_video.py

@@ -17,8 +17,7 @@ class SaveWEBM(io.ComfyNode):
         return io.Schema(
             node_id="SaveWEBM",
             search_aliases=["export webm"],
-            display_name="Save WEBM",
-            category="video",
+            category="image/video",
             is_experimental=True,
             inputs=[
                 io.Image.Input("images"),
@@ -73,7 +72,7 @@ class SaveVideo(io.ComfyNode):
             node_id="SaveVideo",
             search_aliases=["export video"],
             display_name="Save Video",
-            category="video",
+            category="image/video",
             essentials_category="Basics",
             description="Saves the input images to your ComfyUI output directory.",
             inputs=[
@@ -122,7 +121,7 @@ class CreateVideo(io.ComfyNode):
             node_id="CreateVideo",
             search_aliases=["images to video"],
             display_name="Create Video",
-            category="video",
+            category="image/video",
             description="Create a video from images.",
             inputs=[
                 io.Image.Input("images", tooltip="The images to create a video from."),
@@ -147,7 +146,7 @@ class GetVideoComponents(io.ComfyNode):
             node_id="GetVideoComponents",
             search_aliases=["extract frames", "split video", "video to images", "demux"],
             display_name="Get Video Components",
-            category="video",
+            category="image/video",
             description="Extracts all components from a video: frames, audio, and framerate.",
             inputs=[
                 io.Video.Input("video", tooltip="The video to extract components from."),
@@ -175,7 +174,7 @@ class LoadVideo(io.ComfyNode):
             node_id="LoadVideo",
             search_aliases=["import video", "open video", "video file"],
             display_name="Load Video",
-            category="video",
+            category="image/video",
             essentials_category="Basics",
             inputs=[
                 io.Combo.Input("file", options=sorted(files), upload=io.UploadType.video),
@@ -217,7 +216,7 @@ class VideoSlice(io.ComfyNode):
                 "frame load cap",
                 "start time",
             ],
-            category="video",
+            category="image/video",
             essentials_category="Video Tools",
             inputs=[
                 io.Video.Input("video"),

nodes.py

@@ -1887,7 +1887,7 @@ class ImageInvert:
     RETURN_TYPES = ("IMAGE",)
     FUNCTION = "invert"
 
-    CATEGORY = "image/color"
+    CATEGORY = "image"
 
     def invert(self, image):
         s = 1.0 - image
@@ -1903,7 +1903,7 @@ class ImageBatch:
     RETURN_TYPES = ("IMAGE",)
     FUNCTION = "batch"
 
-    CATEGORY = "image/batch"
+    CATEGORY = "image"
     DEPRECATED = True
 
     def batch(self, image1, image2):
@@ -1960,7 +1960,7 @@ class ImagePadForOutpaint:
     RETURN_TYPES = ("IMAGE", "MASK")
     FUNCTION = "expand_image"
 
-    CATEGORY = "image/transform"
+    CATEGORY = "image"
 
     def expand_image(self, image, left, top, right, bottom, feathering):
         d1, d2, d3, d4 = image.size()
@@ -2103,7 +2103,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "ConditioningSetArea": "Conditioning (Set Area)",
     "ConditioningSetAreaPercentage": "Conditioning (Set Area with Percentage)",
     "ConditioningSetMask": "Conditioning (Set Mask)",
-    "ControlNetApply": "Apply ControlNet (DEPRECATED)",
+    "ControlNetApply": "Apply ControlNet (OLD)",
     "ControlNetApplyAdvanced": "Apply ControlNet",
     # Latent
     "VAEEncodeForInpaint": "VAE Encode (for Inpainting)",
@@ -2121,7 +2121,6 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "LatentFromBatch" : "Latent From Batch",
     "RepeatLatentBatch": "Repeat Latent Batch",
     # Image
-    "EmptyImage": "Empty Image",
     "SaveImage": "Save Image",
     "PreviewImage": "Preview Image",
     "LoadImage": "Load Image",
@@ -2129,15 +2128,15 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "LoadImageOutput": "Load Image (from Outputs)",
     "ImageScale": "Upscale Image",
     "ImageScaleBy": "Upscale Image By",
-    "ImageInvert": "Invert Image Colors",
+    "ImageInvert": "Invert Image",
     "ImagePadForOutpaint": "Pad Image for Outpainting",
-    "ImageBatch": "Batch Images (DEPRECATED)",
-    "ImageCrop": "Crop Image",
-    "ImageStitch": "Stitch Images",
-    "ImageBlend": "Blend Images",
-    "ImageBlur": "Blur Image",
-    "ImageQuantize": "Quantize Image",
-    "ImageSharpen": "Sharpen Image",
+    "ImageBatch": "Batch Images",
+    "ImageCrop": "Image Crop",
+    "ImageStitch": "Image Stitch",
+    "ImageBlend": "Image Blend",
+    "ImageBlur": "Image Blur",
+    "ImageQuantize": "Image Quantize",
+    "ImageSharpen": "Image Sharpen",
     "ImageScaleToTotalPixels": "Scale Image to Total Pixels",
     "GetImageSize": "Get Image Size",
     # _for_testing

openapi.yaml

@@ -1999,26 +1999,6 @@ components:
           items:
             type: string
           description: List of node IDs to execute (partial graph execution)
-        workflow_id:
-          type: string
-          format: uuid
-          nullable: true
-          x-runtime: [cloud]
-          description: |
-            UUID identifying a hosted-cloud workflow entity to associate with this
-            job. Local ComfyUI doesn't track workflow entities and returns `null`
-            (or omits the field). The `x-runtime: [cloud]` extension marks this
-            as populated only by the hosted-cloud runtime; absence of the tag
-            means a field is populated by all runtimes.
-        workflow_version_id:
-          type: string
-          format: uuid
-          nullable: true
-          x-runtime: [cloud]
-          description: |
-            UUID identifying a hosted-cloud workflow version to associate with
-            this job. Local ComfyUI returns `null` (or omits the field). See
-            `workflow_id` above for `x-runtime` semantics.
 
     PromptResponse:
       type: object
@@ -2367,12 +2347,7 @@ components:
           description: Device type (cuda, mps, cpu, etc.)
         index:
           type: number
-          nullable: true
-          description: |
-            Device index within its type (e.g. CUDA ordinal for `cuda:0`,
-            `cuda:1`). `null` for devices with no index, including the CPU
-            device returned in `--cpu` mode (PyTorch's `torch.device('cpu').index`
-            is `None`).
+          description: Device index
         vram_total:
           type: number
           description: Total VRAM in bytes
@@ -2528,18 +2503,7 @@ components:
           description: Alternative search terms for finding this node
         essentials_category:
           type: string
-          nullable: true
-          description: |
-            Category override used by the essentials pack. The
-            `essentials_category` key may be present with a string value,
-            present and `null`, or absent entirely:
-
-            - V1 nodes: `essentials_category` is **omitted** when the node
-              class doesn't define an `ESSENTIALS_CATEGORY` attribute, and
-              **`null`** if the attribute is explicitly set to `None`.
-            - V3 nodes (`comfy_api.latest.io`): `essentials_category` is
-              **always present**, and **`null`** for nodes whose `Schema`
-              doesn't populate it.
+          description: Category override used by the essentials pack
 
     # -------------------------------------------------------------------
     # Models

tests-unit/feature_flags_test.py

@@ -1,7 +1,5 @@
 """Tests for feature flags functionality."""
 
-import pytest
-
 from comfy_api.feature_flags import (
     get_connection_feature,
     supports_feature,
@@ -118,26 +116,14 @@ class TestCoerceFlagValue:
         assert _coerce_flag_value("unknown_flag", "true") == "true"
         assert _coerce_flag_value("unknown_flag", "42") == "42"
 
-    def test_bool_typo_raises(self):
-        """Strict bool: typos like 'ture' or 'yes' must raise so the flag can be dropped."""
-        with pytest.raises(ValueError):
-            _coerce_flag_value("show_signin_button", "ture")
-        with pytest.raises(ValueError):
-            _coerce_flag_value("show_signin_button", "yes")
-        with pytest.raises(ValueError):
-            _coerce_flag_value("show_signin_button", "1")
-        with pytest.raises(ValueError):
-            _coerce_flag_value("show_signin_button", "")
-
-    def test_failed_int_coercion_raises(self, monkeypatch):
-        """Malformed values for typed flags must raise; caller decides what to do."""
+    def test_failed_coercion_falls_back_to_string(self, monkeypatch):
+        """Malformed values for typed flags must not crash; raw string is returned."""
         monkeypatch.setitem(
             CLI_FEATURE_FLAG_REGISTRY,
             "test_int_flag",
             {"type": "int", "default": 0, "description": "test"},
         )
-        with pytest.raises(ValueError):
-            _coerce_flag_value("test_int_flag", "not_a_number")
+        assert _coerce_flag_value("test_int_flag", "not_a_number") == "not_a_number"
 
 
 class TestParseCliFeatureFlags:
@@ -159,19 +145,6 @@ class TestParseCliFeatureFlags:
         result = _parse_cli_feature_flags()
         assert result == {"valid": "1"}
 
-    def test_invalid_bool_value_dropped(self, monkeypatch, caplog):
-        """A typo'd bool value must be dropped entirely, not silently set to False
-        and not stored as a raw string. A warning must be logged."""
-        monkeypatch.setattr(
-            "comfy_api.feature_flags.args",
-            type("Args", (), {"feature_flag": ["show_signin_button=ture", "valid=1"]})(),
-        )
-        with caplog.at_level("WARNING"):
-            result = _parse_cli_feature_flags()
-        assert result == {"valid": "1"}
-        assert "show_signin_button" not in result
-        assert any("show_signin_button" in r.message and "drop" in r.message.lower() for r in caplog.records)
-
 
 class TestCliFeatureFlagRegistry:
     """Test suite for the CLI feature flag registry."""