convert nodes_flux to V3 schema (#10122)

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Alexander Piskun 2025-10-10 02:07:17 +03:00 committed by GitHub
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@ -1,60 +1,80 @@
import node_helpers
import comfy.utils
from typing_extensions import override
from comfy_api.latest import ComfyExtension, io
class CLIPTextEncodeFlux:
class CLIPTextEncodeFlux(io.ComfyNode):
@classmethod
def INPUT_TYPES(s):
return {"required": {
"clip": ("CLIP", ),
"clip_l": ("STRING", {"multiline": True, "dynamicPrompts": True}),
"t5xxl": ("STRING", {"multiline": True, "dynamicPrompts": True}),
"guidance": ("FLOAT", {"default": 3.5, "min": 0.0, "max": 100.0, "step": 0.1}),
}}
RETURN_TYPES = ("CONDITIONING",)
FUNCTION = "encode"
def define_schema(cls):
return io.Schema(
node_id="CLIPTextEncodeFlux",
category="advanced/conditioning/flux",
inputs=[
io.Clip.Input("clip"),
io.String.Input("clip_l", multiline=True, dynamic_prompts=True),
io.String.Input("t5xxl", multiline=True, dynamic_prompts=True),
io.Float.Input("guidance", default=3.5, min=0.0, max=100.0, step=0.1),
],
outputs=[
io.Conditioning.Output(),
],
)
CATEGORY = "advanced/conditioning/flux"
def encode(self, clip, clip_l, t5xxl, guidance):
@classmethod
def execute(cls, clip, clip_l, t5xxl, guidance) -> io.NodeOutput:
tokens = clip.tokenize(clip_l)
tokens["t5xxl"] = clip.tokenize(t5xxl)["t5xxl"]
return (clip.encode_from_tokens_scheduled(tokens, add_dict={"guidance": guidance}), )
return io.NodeOutput(clip.encode_from_tokens_scheduled(tokens, add_dict={"guidance": guidance}))
class FluxGuidance:
encode = execute # TODO: remove
class FluxGuidance(io.ComfyNode):
@classmethod
def INPUT_TYPES(s):
return {"required": {
"conditioning": ("CONDITIONING", ),
"guidance": ("FLOAT", {"default": 3.5, "min": 0.0, "max": 100.0, "step": 0.1}),
}}
def define_schema(cls):
return io.Schema(
node_id="FluxGuidance",
category="advanced/conditioning/flux",
inputs=[
io.Conditioning.Input("conditioning"),
io.Float.Input("guidance", default=3.5, min=0.0, max=100.0, step=0.1),
],
outputs=[
io.Conditioning.Output(),
],
)
RETURN_TYPES = ("CONDITIONING",)
FUNCTION = "append"
CATEGORY = "advanced/conditioning/flux"
def append(self, conditioning, guidance):
@classmethod
def execute(cls, conditioning, guidance) -> io.NodeOutput:
c = node_helpers.conditioning_set_values(conditioning, {"guidance": guidance})
return (c, )
return io.NodeOutput(c)
append = execute # TODO: remove
class FluxDisableGuidance:
class FluxDisableGuidance(io.ComfyNode):
@classmethod
def INPUT_TYPES(s):
return {"required": {
"conditioning": ("CONDITIONING", ),
}}
def define_schema(cls):
return io.Schema(
node_id="FluxDisableGuidance",
category="advanced/conditioning/flux",
description="This node completely disables the guidance embed on Flux and Flux like models",
inputs=[
io.Conditioning.Input("conditioning"),
],
outputs=[
io.Conditioning.Output(),
],
)
RETURN_TYPES = ("CONDITIONING",)
FUNCTION = "append"
CATEGORY = "advanced/conditioning/flux"
DESCRIPTION = "This node completely disables the guidance embed on Flux and Flux like models"
def append(self, conditioning):
@classmethod
def execute(cls, conditioning) -> io.NodeOutput:
c = node_helpers.conditioning_set_values(conditioning, {"guidance": None})
return (c, )
return io.NodeOutput(c)
append = execute # TODO: remove
PREFERED_KONTEXT_RESOLUTIONS = [
@ -78,52 +98,73 @@ PREFERED_KONTEXT_RESOLUTIONS = [
]
class FluxKontextImageScale:
class FluxKontextImageScale(io.ComfyNode):
@classmethod
def INPUT_TYPES(s):
return {"required": {"image": ("IMAGE", ),
},
}
def define_schema(cls):
return io.Schema(
node_id="FluxKontextImageScale",
category="advanced/conditioning/flux",
description="This node resizes the image to one that is more optimal for flux kontext.",
inputs=[
io.Image.Input("image"),
],
outputs=[
io.Image.Output(),
],
)
RETURN_TYPES = ("IMAGE",)
FUNCTION = "scale"
CATEGORY = "advanced/conditioning/flux"
DESCRIPTION = "This node resizes the image to one that is more optimal for flux kontext."
def scale(self, image):
@classmethod
def execute(cls, image) -> io.NodeOutput:
width = image.shape[2]
height = image.shape[1]
aspect_ratio = width / height
_, width, height = min((abs(aspect_ratio - w / h), w, h) for w, h in PREFERED_KONTEXT_RESOLUTIONS)
image = comfy.utils.common_upscale(image.movedim(-1, 1), width, height, "lanczos", "center").movedim(1, -1)
return (image, )
return io.NodeOutput(image)
scale = execute # TODO: remove
class FluxKontextMultiReferenceLatentMethod:
class FluxKontextMultiReferenceLatentMethod(io.ComfyNode):
@classmethod
def INPUT_TYPES(s):
return {"required": {
"conditioning": ("CONDITIONING", ),
"reference_latents_method": (("offset", "index", "uxo/uno"), ),
}}
def define_schema(cls):
return io.Schema(
node_id="FluxKontextMultiReferenceLatentMethod",
category="advanced/conditioning/flux",
inputs=[
io.Conditioning.Input("conditioning"),
io.Combo.Input(
"reference_latents_method",
options=["offset", "index", "uxo/uno"],
),
],
outputs=[
io.Conditioning.Output(),
],
is_experimental=True,
)
RETURN_TYPES = ("CONDITIONING",)
FUNCTION = "append"
EXPERIMENTAL = True
CATEGORY = "advanced/conditioning/flux"
def append(self, conditioning, reference_latents_method):
@classmethod
def execute(cls, conditioning, reference_latents_method) -> io.NodeOutput:
if "uxo" in reference_latents_method or "uso" in reference_latents_method:
reference_latents_method = "uxo"
c = node_helpers.conditioning_set_values(conditioning, {"reference_latents_method": reference_latents_method})
return (c, )
return io.NodeOutput(c)
NODE_CLASS_MAPPINGS = {
"CLIPTextEncodeFlux": CLIPTextEncodeFlux,
"FluxGuidance": FluxGuidance,
"FluxDisableGuidance": FluxDisableGuidance,
"FluxKontextImageScale": FluxKontextImageScale,
"FluxKontextMultiReferenceLatentMethod": FluxKontextMultiReferenceLatentMethod,
}
append = execute # TODO: remove
class FluxExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[io.ComfyNode]]:
return [
CLIPTextEncodeFlux,
FluxGuidance,
FluxDisableGuidance,
FluxKontextImageScale,
FluxKontextMultiReferenceLatentMethod,
]
async def comfy_entrypoint() -> FluxExtension:
return FluxExtension()