ComfyUI v0.16.3

Allows explicit control over the causal_fix flag passed to
latent_to_pixel_coords. Defaults to frame_idx == 0 when not
specified, fixing the previous heuristic.

comfy/ldm/lightricks/vocoders/vocoder.py

@@ -2,6 +2,7 @@ import torch
 import torch.nn.functional as F
 import torch.nn as nn
 import comfy.ops
+import comfy.model_management
 import numpy as np
 import math
 
@@ -81,7 +82,7 @@ class LowPassFilter1d(nn.Module):
         _, C, _ = x.shape
         if self.padding:
             x = F.pad(x, (self.pad_left, self.pad_right), mode=self.padding_mode)
-        return F.conv1d(x, self.filter.expand(C, -1, -1), stride=self.stride, groups=C)
+        return F.conv1d(x, comfy.model_management.cast_to(self.filter.expand(C, -1, -1), dtype=x.dtype, device=x.device), stride=self.stride, groups=C)
 
 
 class UpSample1d(nn.Module):
@@ -125,7 +126,7 @@ class UpSample1d(nn.Module):
         _, C, _ = x.shape
         x = F.pad(x, (self.pad, self.pad), mode="replicate")
         x = self.ratio * F.conv_transpose1d(
-            x, self.filter.expand(C, -1, -1), stride=self.stride, groups=C
+            x, comfy.model_management.cast_to(self.filter.expand(C, -1, -1), dtype=x.dtype, device=x.device), stride=self.stride, groups=C
         )
         x = x[..., self.pad_left : -self.pad_right]
         return x
@@ -190,7 +191,7 @@ class Snake(nn.Module):
         self.eps = 1e-9
 
     def forward(self, x):
-        a = self.alpha.unsqueeze(0).unsqueeze(-1)
+        a = comfy.model_management.cast_to(self.alpha.unsqueeze(0).unsqueeze(-1), dtype=x.dtype, device=x.device)
         if self.alpha_logscale:
             a = torch.exp(a)
         return x + (1.0 / (a + self.eps)) * torch.sin(x * a).pow(2)
@@ -217,8 +218,8 @@ class SnakeBeta(nn.Module):
         self.eps = 1e-9
 
     def forward(self, x):
-        a = self.alpha.unsqueeze(0).unsqueeze(-1)
-        b = self.beta.unsqueeze(0).unsqueeze(-1)
+        a = comfy.model_management.cast_to(self.alpha.unsqueeze(0).unsqueeze(-1), dtype=x.dtype, device=x.device)
+        b = comfy.model_management.cast_to(self.beta.unsqueeze(0).unsqueeze(-1), dtype=x.dtype, device=x.device)
         if self.alpha_logscale:
             a = torch.exp(a)
             b = torch.exp(b)
@@ -596,7 +597,7 @@ class _STFTFn(nn.Module):
             y = y.unsqueeze(1)                                # (B, 1, T)
         left_pad = max(0, self.win_length - self.hop_length)  # causal: left-only
         y = F.pad(y, (left_pad, 0))
-        spec = F.conv1d(y, self.forward_basis, stride=self.hop_length, padding=0)
+        spec = F.conv1d(y, comfy.model_management.cast_to(self.forward_basis, dtype=y.dtype, device=y.device), stride=self.hop_length, padding=0)
         n_freqs = spec.shape[1] // 2
         real, imag = spec[:, :n_freqs], spec[:, n_freqs:]
         magnitude = torch.sqrt(real ** 2 + imag ** 2)
@@ -647,7 +648,7 @@ class MelSTFT(nn.Module):
         """
         magnitude, phase = self.stft_fn(y)
         energy = torch.norm(magnitude, dim=1)
-        mel = torch.matmul(self.mel_basis.to(magnitude.dtype), magnitude)
+        mel = torch.matmul(comfy.model_management.cast_to(self.mel_basis, dtype=magnitude.dtype, device=y.device), magnitude)
         log_mel = torch.log(torch.clamp(mel, min=1e-5))
         return log_mel, magnitude, phase, energy
 

comfy/model_management.py

@@ -1666,12 +1666,16 @@ def lora_compute_dtype(device):
     return dtype
 
 def synchronize():
+    if cpu_mode():
+        return
     if is_intel_xpu():
         torch.xpu.synchronize()
     elif torch.cuda.is_available():
         torch.cuda.synchronize()
 
 def soft_empty_cache(force=False):
+    if cpu_mode():
+        return
     global cpu_state
     if cpu_state == CPUState.MPS:
         torch.mps.empty_cache()

comfy/ops.py

@@ -80,6 +80,21 @@ def cast_to_input(weight, input, non_blocking=False, copy=True):
 
 
 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):
+        weight = s.weight.to(dtype=dtype, copy=True)
+        if isinstance(weight, QuantizedTensor):
+            weight = weight.dequantize()
+        bias = None
+        if s.bias is not None:
+            bias = s.bias.to(dtype=bias_dtype, copy=True)
+        return weight, bias, (None, None, None)
+
     offload_stream = None
     xfer_dest = None
 
@@ -660,23 +675,29 @@ class fp8_ops(manual_cast):
 
 CUBLAS_IS_AVAILABLE = False
 try:
-    from cublas_ops import CublasLinear
+    from cublas_ops import CublasLinear, cublas_half_matmul
     CUBLAS_IS_AVAILABLE = True
 except ImportError:
     pass
 
 if CUBLAS_IS_AVAILABLE:
-    class cublas_ops(disable_weight_init):
-        class Linear(CublasLinear, disable_weight_init.Linear):
+    class cublas_ops(manual_cast):
+        class Linear(CublasLinear, manual_cast.Linear):
             def reset_parameters(self):
                 return None
 
             def forward_comfy_cast_weights(self, input):
-                return super().forward(input)
+                weight, bias, offload_stream = cast_bias_weight(self, input, offloadable=True)
+                x = cublas_half_matmul(input, weight, bias, self._epilogue_str, self.has_bias)
+                uncast_bias_weight(self, weight, bias, offload_stream)
+                return x
 
             def forward(self, *args, **kwargs):
-                return super().forward(*args, **kwargs)
-
+                run_every_op()
+                if self.comfy_cast_weights or len(self.weight_function) > 0 or len(self.bias_function) > 0:
+                    return self.forward_comfy_cast_weights(*args, **kwargs)
+                else:
+                    return super().forward(*args, **kwargs)
 
 # ==============================================================================
 # Mixed Precision Operations

comfy/quant_ops.py

@@ -1,38 +1,33 @@
 import torch
 import logging
-from comfy.cli_args import args
 
-if args.cpu:
-    _CK_AVAILABLE = False
-else:
-    try:
-        import comfy_kitchen as ck
-        from comfy_kitchen.tensor import (
-            QuantizedTensor,
-            QuantizedLayout,
-            TensorCoreFP8Layout as _CKFp8Layout,
-            TensorCoreNVFP4Layout as _CKNvfp4Layout,
-            register_layout_op,
-            register_layout_class,
-            get_layout_class,
-        )
-        _CK_AVAILABLE = True
-        if torch.version.cuda is None:
+try:
+    import comfy_kitchen as ck
+    from comfy_kitchen.tensor import (
+        QuantizedTensor,
+        QuantizedLayout,
+        TensorCoreFP8Layout as _CKFp8Layout,
+        TensorCoreNVFP4Layout as _CKNvfp4Layout,
+        register_layout_op,
+        register_layout_class,
+        get_layout_class,
+    )
+    _CK_AVAILABLE = True
+    if torch.version.cuda is None:
+        ck.registry.disable("cuda")
+    else:
+        cuda_version = tuple(map(int, str(torch.version.cuda).split('.')))
+        if cuda_version < (13,):
             ck.registry.disable("cuda")
-        else:
-            cuda_version = tuple(map(int, str(torch.version.cuda).split('.')))
-            if cuda_version < (13,):
-                ck.registry.disable("cuda")
-                logging.warning("WARNING: You need pytorch with cu130 or higher to use optimized CUDA operations.")
+            logging.warning("WARNING: You need pytorch with cu130 or higher to use optimized CUDA operations.")
 
-        ck.registry.disable("triton")
-        for k, v in ck.list_backends().items():
-            logging.info(f"Found comfy_kitchen backend {k}: {v}")
-    except ImportError as e:
-        logging.error(f"Failed to import comfy_kitchen, Error: {e}, fp8 and fp4 support will not be available.")
-        _CK_AVAILABLE = False
+    ck.registry.disable("triton")
+    for k, v in ck.list_backends().items():
+        logging.info(f"Found comfy_kitchen backend {k}: {v}")
+except ImportError as e:
+    logging.error(f"Failed to import comfy_kitchen, Error: {e}, fp8 and fp4 support will not be available.")
+    _CK_AVAILABLE = False
 
-if not _CK_AVAILABLE:
     class QuantizedTensor:
         pass
 

comfy_api_nodes/apis/grok.py

@@ -7,7 +7,8 @@ class ImageGenerationRequest(BaseModel):
     aspect_ratio: str = Field(...)
     n: int = Field(...)
     seed: int = Field(...)
-    response_for: str = Field("url")
+    response_format: str = Field("url")
+    resolution: str = Field(...)
 
 
 class InputUrlObject(BaseModel):
@@ -16,12 +17,13 @@ class InputUrlObject(BaseModel):
 
 class ImageEditRequest(BaseModel):
     model: str = Field(...)
-    image: InputUrlObject = Field(...)
+    images: list[InputUrlObject] = Field(...)
     prompt: str = Field(...)
     resolution: str = Field(...)
     n: int = Field(...)
     seed: int = Field(...)
-    response_for: str = Field("url")
+    response_format: str = Field("url")
+    aspect_ratio: str | None = Field(...)
 
 
 class VideoGenerationRequest(BaseModel):
@@ -47,8 +49,13 @@ class ImageResponseObject(BaseModel):
     revised_prompt: str | None = Field(None)
 
 
+class UsageObject(BaseModel):
+    cost_in_usd_ticks: int | None = Field(None)
+
+
 class ImageGenerationResponse(BaseModel):
     data: list[ImageResponseObject] = Field(...)
+    usage: UsageObject | None = Field(None)
 
 
 class VideoGenerationResponse(BaseModel):
@@ -65,3 +72,4 @@ class VideoStatusResponse(BaseModel):
     status: str | None = Field(None)
     video: VideoResponseObject | None = Field(None)
     model: str | None = Field(None)
+    usage: UsageObject | None = Field(None)

comfy_api_nodes/apis/kling.py

@@ -148,3 +148,4 @@ class MotionControlRequest(BaseModel):
     keep_original_sound: str = Field(...)
     character_orientation: str = Field(...)
     mode: str = Field(..., description="'pro' or 'std'")
+    model_name: str = Field(...)

comfy_api_nodes/nodes_grok.py

@@ -27,6 +27,12 @@ from comfy_api_nodes.util import (
 )
 
 
+def _extract_grok_price(response) -> float | None:
+    if response.usage and response.usage.cost_in_usd_ticks is not None:
+        return response.usage.cost_in_usd_ticks / 10_000_000_000
+    return None
+
+
 class GrokImageNode(IO.ComfyNode):
 
     @classmethod
@@ -37,7 +43,10 @@ class GrokImageNode(IO.ComfyNode):
             category="api node/image/Grok",
             description="Generate images using Grok based on a text prompt",
             inputs=[
-                IO.Combo.Input("model", options=["grok-imagine-image-beta"]),
+                IO.Combo.Input(
+                    "model",
+                    options=["grok-imagine-image-pro", "grok-imagine-image", "grok-imagine-image-beta"],
+                ),
                 IO.String.Input(
                     "prompt",
                     multiline=True,
@@ -81,6 +90,7 @@ class GrokImageNode(IO.ComfyNode):
                     tooltip="Seed to determine if node should re-run; "
                     "actual results are nondeterministic regardless of seed.",
                 ),
+                IO.Combo.Input("resolution", options=["1K", "2K"], optional=True),
             ],
             outputs=[
                 IO.Image.Output(),
@@ -92,8 +102,13 @@ class GrokImageNode(IO.ComfyNode):
             ],
             is_api_node=True,
             price_badge=IO.PriceBadge(
-                depends_on=IO.PriceBadgeDepends(widgets=["number_of_images"]),
-                expr="""{"type":"usd","usd":0.033 * widgets.number_of_images}""",
+                depends_on=IO.PriceBadgeDepends(widgets=["model", "number_of_images"]),
+                expr="""
+                (
+                  $rate := $contains(widgets.model, "pro") ? 0.07 : 0.02;
+                  {"type":"usd","usd": $rate * widgets.number_of_images}
+                )
+                """,
             ),
         )
 
@@ -105,6 +120,7 @@ class GrokImageNode(IO.ComfyNode):
         aspect_ratio: str,
         number_of_images: int,
         seed: int,
+        resolution: str = "1K",
     ) -> IO.NodeOutput:
         validate_string(prompt, strip_whitespace=True, min_length=1)
         response = await sync_op(
@@ -116,8 +132,10 @@ class GrokImageNode(IO.ComfyNode):
                 aspect_ratio=aspect_ratio,
                 n=number_of_images,
                 seed=seed,
+                resolution=resolution.lower(),
             ),
             response_model=ImageGenerationResponse,
+            price_extractor=_extract_grok_price,
         )
         if len(response.data) == 1:
             return IO.NodeOutput(await download_url_to_image_tensor(response.data[0].url))
@@ -138,14 +156,17 @@ class GrokImageEditNode(IO.ComfyNode):
             category="api node/image/Grok",
             description="Modify an existing image based on a text prompt",
             inputs=[
-                IO.Combo.Input("model", options=["grok-imagine-image-beta"]),
-                IO.Image.Input("image"),
+                IO.Combo.Input(
+                    "model",
+                    options=["grok-imagine-image-pro", "grok-imagine-image", "grok-imagine-image-beta"],
+                ),
+                IO.Image.Input("image", display_name="images"),
                 IO.String.Input(
                     "prompt",
                     multiline=True,
                     tooltip="The text prompt used to generate the image",
                 ),
-                IO.Combo.Input("resolution", options=["1K"]),
+                IO.Combo.Input("resolution", options=["1K", "2K"]),
                 IO.Int.Input(
                     "number_of_images",
                     default=1,
@@ -166,6 +187,27 @@ class GrokImageEditNode(IO.ComfyNode):
                     tooltip="Seed to determine if node should re-run; "
                     "actual results are nondeterministic regardless of seed.",
                 ),
+                IO.Combo.Input(
+                    "aspect_ratio",
+                    options=[
+                        "auto",
+                        "1:1",
+                        "2:3",
+                        "3:2",
+                        "3:4",
+                        "4:3",
+                        "9:16",
+                        "16:9",
+                        "9:19.5",
+                        "19.5:9",
+                        "9:20",
+                        "20:9",
+                        "1:2",
+                        "2:1",
+                    ],
+                    optional=True,
+                    tooltip="Only allowed when multiple images are connected to the image input.",
+                ),
             ],
             outputs=[
                 IO.Image.Output(),
@@ -177,8 +219,13 @@ class GrokImageEditNode(IO.ComfyNode):
             ],
             is_api_node=True,
             price_badge=IO.PriceBadge(
-                depends_on=IO.PriceBadgeDepends(widgets=["number_of_images"]),
-                expr="""{"type":"usd","usd":0.002 + 0.033 * widgets.number_of_images}""",
+                depends_on=IO.PriceBadgeDepends(widgets=["model", "number_of_images"]),
+                expr="""
+                (
+                  $rate := $contains(widgets.model, "pro") ? 0.07 : 0.02;
+                  {"type":"usd","usd": 0.002 + $rate * widgets.number_of_images}
+                )
+                """,
             ),
         )
 
@@ -191,22 +238,32 @@ class GrokImageEditNode(IO.ComfyNode):
         resolution: str,
         number_of_images: int,
         seed: int,
+        aspect_ratio: str = "auto",
     ) -> IO.NodeOutput:
         validate_string(prompt, strip_whitespace=True, min_length=1)
-        if get_number_of_images(image) != 1:
-            raise ValueError("Only one input image is supported.")
+        if model == "grok-imagine-image-pro":
+            if get_number_of_images(image) > 1:
+                raise ValueError("The pro model supports only 1 input image.")
+        elif get_number_of_images(image) > 3:
+            raise ValueError("A maximum of 3 input images is supported.")
+        if aspect_ratio != "auto" and get_number_of_images(image) == 1:
+            raise ValueError(
+                "Custom aspect ratio is only allowed when multiple images are connected to the image input."
+            )
         response = await sync_op(
             cls,
             ApiEndpoint(path="/proxy/xai/v1/images/edits", method="POST"),
             data=ImageEditRequest(
                 model=model,
-                image=InputUrlObject(url=f"data:image/png;base64,{tensor_to_base64_string(image)}"),
+                images=[InputUrlObject(url=f"data:image/png;base64,{tensor_to_base64_string(i)}") for i in image],
                 prompt=prompt,
                 resolution=resolution.lower(),
                 n=number_of_images,
                 seed=seed,
+                aspect_ratio=None if aspect_ratio == "auto" else aspect_ratio,
             ),
             response_model=ImageGenerationResponse,
+            price_extractor=_extract_grok_price,
         )
         if len(response.data) == 1:
             return IO.NodeOutput(await download_url_to_image_tensor(response.data[0].url))
@@ -227,7 +284,7 @@ class GrokVideoNode(IO.ComfyNode):
             category="api node/video/Grok",
             description="Generate video from a prompt or an image",
             inputs=[
-                IO.Combo.Input("model", options=["grok-imagine-video-beta"]),
+                IO.Combo.Input("model", options=["grok-imagine-video", "grok-imagine-video-beta"]),
                 IO.String.Input(
                     "prompt",
                     multiline=True,
@@ -275,10 +332,11 @@ class GrokVideoNode(IO.ComfyNode):
             ],
             is_api_node=True,
             price_badge=IO.PriceBadge(
-                depends_on=IO.PriceBadgeDepends(widgets=["duration"], inputs=["image"]),
+                depends_on=IO.PriceBadgeDepends(widgets=["duration", "resolution"], inputs=["image"]),
                 expr="""
                 (
-                  $base := 0.181 * widgets.duration;
+                  $rate := widgets.resolution = "720p" ? 0.07 : 0.05;
+                  $base := $rate * widgets.duration;
                   {"type":"usd","usd": inputs.image.connected ? $base + 0.002 : $base}
                 )
                 """,
@@ -321,6 +379,7 @@ class GrokVideoNode(IO.ComfyNode):
             ApiEndpoint(path=f"/proxy/xai/v1/videos/{initial_response.request_id}"),
             status_extractor=lambda r: r.status if r.status is not None else "complete",
             response_model=VideoStatusResponse,
+            price_extractor=_extract_grok_price,
         )
         return IO.NodeOutput(await download_url_to_video_output(response.video.url))
 
@@ -335,7 +394,7 @@ class GrokVideoEditNode(IO.ComfyNode):
             category="api node/video/Grok",
             description="Edit an existing video based on a text prompt.",
             inputs=[
-                IO.Combo.Input("model", options=["grok-imagine-video-beta"]),
+                IO.Combo.Input("model", options=["grok-imagine-video", "grok-imagine-video-beta"]),
                 IO.String.Input(
                     "prompt",
                     multiline=True,
@@ -364,7 +423,7 @@ class GrokVideoEditNode(IO.ComfyNode):
             ],
             is_api_node=True,
             price_badge=IO.PriceBadge(
-                expr="""{"type":"usd","usd": 0.191, "format": {"suffix": "/sec", "approximate": true}}""",
+                expr="""{"type":"usd","usd": 0.06, "format": {"suffix": "/sec", "approximate": true}}""",
             ),
         )
 
@@ -398,6 +457,7 @@ class GrokVideoEditNode(IO.ComfyNode):
             ApiEndpoint(path=f"/proxy/xai/v1/videos/{initial_response.request_id}"),
             status_extractor=lambda r: r.status if r.status is not None else "complete",
             response_model=VideoStatusResponse,
+            price_extractor=_extract_grok_price,
         )
         return IO.NodeOutput(await download_url_to_video_output(response.video.url))
 

comfy_api_nodes/nodes_kling.py

@@ -2747,6 +2747,7 @@ class MotionControl(IO.ComfyNode):
                     "but the character orientation matches the reference image (camera/other details via prompt).",
                 ),
                 IO.Combo.Input("mode", options=["pro", "std"]),
+                IO.Combo.Input("model", options=["kling-v3", "kling-v2-6"], optional=True),
             ],
             outputs=[
                 IO.Video.Output(),
@@ -2777,6 +2778,7 @@ class MotionControl(IO.ComfyNode):
         keep_original_sound: bool,
         character_orientation: str,
         mode: str,
+        model: str = "kling-v2-6",
     ) -> IO.NodeOutput:
         validate_string(prompt, max_length=2500)
         validate_image_dimensions(reference_image, min_width=340, min_height=340)
@@ -2797,6 +2799,7 @@ class MotionControl(IO.ComfyNode):
                 keep_original_sound="yes" if keep_original_sound else "no",
                 character_orientation=character_orientation,
                 mode=mode,
+                model_name=model,
             ),
         )
         if response.code:

comfy_extras/nodes_lt.py

@@ -253,10 +253,12 @@ class LTXVAddGuide(io.ComfyNode):
         return frame_idx, latent_idx
 
     @classmethod
-    def add_keyframe_index(cls, cond, frame_idx, guiding_latent, scale_factors, latent_downscale_factor=1):
+    def add_keyframe_index(cls, cond, frame_idx, guiding_latent, scale_factors, latent_downscale_factor=1, causal_fix=None):
         keyframe_idxs, _ = get_keyframe_idxs(cond)
         _, latent_coords = cls.PATCHIFIER.patchify(guiding_latent)
-        pixel_coords = latent_to_pixel_coords(latent_coords, scale_factors, causal_fix=frame_idx == 0)  # we need the causal fix only if we're placing the new latents at index 0
+        if causal_fix is None:
+            causal_fix = frame_idx == 0 or guiding_latent.shape[2] == 1
+        pixel_coords = latent_to_pixel_coords(latent_coords, scale_factors, causal_fix=causal_fix)
         pixel_coords[:, 0] += frame_idx
 
         # The following adjusts keyframe end positions for small grid IC-LoRA.
@@ -278,12 +280,12 @@ class LTXVAddGuide(io.ComfyNode):
         return node_helpers.conditioning_set_values(cond, {"keyframe_idxs": keyframe_idxs})
 
     @classmethod
-    def append_keyframe(cls, positive, negative, frame_idx, latent_image, noise_mask, guiding_latent, strength, scale_factors, guide_mask=None, in_channels=128, latent_downscale_factor=1):
+    def append_keyframe(cls, positive, negative, frame_idx, latent_image, noise_mask, guiding_latent, strength, scale_factors, guide_mask=None, in_channels=128, latent_downscale_factor=1, causal_fix=None):
         if latent_image.shape[1] != in_channels or guiding_latent.shape[1] != in_channels:
             raise ValueError("Adding guide to a combined AV latent is not supported.")
 
-        positive = cls.add_keyframe_index(positive, frame_idx, guiding_latent, scale_factors, latent_downscale_factor)
-        negative = cls.add_keyframe_index(negative, frame_idx, guiding_latent, scale_factors, latent_downscale_factor)
+        positive = cls.add_keyframe_index(positive, frame_idx, guiding_latent, scale_factors, latent_downscale_factor, causal_fix=causal_fix)
+        negative = cls.add_keyframe_index(negative, frame_idx, guiding_latent, scale_factors, latent_downscale_factor, causal_fix=causal_fix)
 
         if guide_mask is not None:
             target_h = max(noise_mask.shape[3], guide_mask.shape[3])

comfyui_version.py

@@ -1,3 +1,3 @@
 # This file is automatically generated by the build process when version is
 # updated in pyproject.toml.
-__version__ = "0.15.1"
+__version__ = "0.16.3"

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "ComfyUI"
-version = "0.15.1"
+version = "0.16.3"
 readme = "README.md"
 license = { file = "LICENSE" }
 requires-python = ">=3.10"

requirements.txt

@@ -1,5 +1,5 @@
 comfyui-frontend-package==1.39.19
-comfyui-workflow-templates==0.9.5
+comfyui-workflow-templates==0.9.10
 comfyui-embedded-docs==0.4.3
 torch
 torchsde
@@ -22,7 +22,7 @@ alembic
 SQLAlchemy
 av>=14.2.0
 comfy-kitchen>=0.2.7
-comfy-aimdo>=0.2.6
+comfy-aimdo>=0.2.7
 requests
 
 #non essential dependencies: