From e77b34dfead9758cf5e32b4cffeada0d0c56ab7d Mon Sep 17 00:00:00 2001
From: Alexander Piskun <13381981+bigcat88@users.noreply.github.com>
Date: Wed, 4 Feb 2026 21:35:38 +0200
Subject: [PATCH 01/10] add File3DAny output to Load3D node; extend SaveGLB to
accept File3DAny as input (#12276)
* add File3DAny output to Load3D node; extend SaveGLB node to accept File3DAny as input
* fix(grammar): capitalize letter
---
comfy_extras/nodes_hunyuan3d.py | 12 ++++++++++--
comfy_extras/nodes_load_3d.py | 4 +++-
2 files changed, 13 insertions(+), 3 deletions(-)
diff --git a/comfy_extras/nodes_hunyuan3d.py b/comfy_extras/nodes_hunyuan3d.py
index eda1639ab..c2df3e859 100644
--- a/comfy_extras/nodes_hunyuan3d.py
+++ b/comfy_extras/nodes_hunyuan3d.py
@@ -618,6 +618,7 @@ class SaveGLB(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="SaveGLB",
+ display_name="Save 3D Model",
search_aliases=["export 3d model", "save mesh"],
category="3d",
is_output_node=True,
@@ -626,8 +627,14 @@ class SaveGLB(IO.ComfyNode):
IO.Mesh.Input("mesh"),
types=[
IO.File3DGLB,
+ IO.File3DGLTF,
+ IO.File3DOBJ,
+ IO.File3DFBX,
+ IO.File3DSTL,
+ IO.File3DUSDZ,
+ IO.File3DAny,
],
- tooltip="Mesh or GLB file to save",
+ tooltip="Mesh or 3D file to save",
),
IO.String.Input("filename_prefix", default="mesh/ComfyUI"),
],
@@ -649,7 +656,8 @@ class SaveGLB(IO.ComfyNode):
if isinstance(mesh, Types.File3D):
# Handle File3D input - save BytesIO data to output folder
- f = f"{filename}_{counter:05}_.glb"
+ ext = mesh.format or "glb"
+ f = f"{filename}_{counter:05}_.{ext}"
mesh.save_to(os.path.join(full_output_folder, f))
results.append({
"filename": f,
diff --git a/comfy_extras/nodes_load_3d.py b/comfy_extras/nodes_load_3d.py
index f29510488..edbb5cd40 100644
--- a/comfy_extras/nodes_load_3d.py
+++ b/comfy_extras/nodes_load_3d.py
@@ -45,6 +45,7 @@ class Load3D(IO.ComfyNode):
IO.Image.Output(display_name="normal"),
IO.Load3DCamera.Output(display_name="camera_info"),
IO.Video.Output(display_name="recording_video"),
+ IO.File3DAny.Output(display_name="model_3d"),
],
)
@@ -66,7 +67,8 @@ class Load3D(IO.ComfyNode):
video = InputImpl.VideoFromFile(recording_video_path)
- return IO.NodeOutput(output_image, output_mask, model_file, normal_image, image['camera_info'], video)
+ file_3d = Types.File3D(folder_paths.get_annotated_filepath(model_file))
+ return IO.NodeOutput(output_image, output_mask, model_file, normal_image, image['camera_info'], video, file_3d)
process = execute # TODO: remove
From 26dd7eb42180fb57c9da47e60d0a2bac659e47ad Mon Sep 17 00:00:00 2001
From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Date: Wed, 4 Feb 2026 15:25:06 -0800
Subject: [PATCH 02/10] Fix ace step nan issue on some hardware/pytorch
configs. (#12289)
---
comfy/text_encoders/llama.py | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/comfy/text_encoders/llama.py b/comfy/text_encoders/llama.py
index 3afd094d1..b6735d210 100644
--- a/comfy/text_encoders/llama.py
+++ b/comfy/text_encoders/llama.py
@@ -651,10 +651,10 @@ class Llama2_(nn.Module):
mask = None
if attention_mask is not None:
mask = 1.0 - attention_mask.to(x.dtype).reshape((attention_mask.shape[0], 1, -1, attention_mask.shape[-1])).expand(attention_mask.shape[0], 1, seq_len, attention_mask.shape[-1])
- mask = mask.masked_fill(mask.to(torch.bool), torch.finfo(x.dtype).min)
+ mask = mask.masked_fill(mask.to(torch.bool), torch.finfo(x.dtype).min / 4)
if seq_len > 1:
- causal_mask = torch.empty(past_len + seq_len, past_len + seq_len, dtype=x.dtype, device=x.device).fill_(torch.finfo(x.dtype).min).triu_(1)
+ causal_mask = torch.empty(past_len + seq_len, past_len + seq_len, dtype=x.dtype, device=x.device).fill_(torch.finfo(x.dtype).min / 4).triu_(1)
if mask is not None:
mask += causal_mask
else:
From c8fcbd66eef0ab48d9fe7e4ee35c683a193af46b Mon Sep 17 00:00:00 2001
From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Date: Wed, 4 Feb 2026 16:37:05 -0800
Subject: [PATCH 03/10] Try to fix ace text encoder slowness on some configs.
(#12290)
---
comfy/ops.py | 2 ++
1 file changed, 2 insertions(+)
diff --git a/comfy/ops.py b/comfy/ops.py
index 53c5e4dc3..0f4eca7c7 100644
--- a/comfy/ops.py
+++ b/comfy/ops.py
@@ -54,6 +54,8 @@ try:
SDPA_BACKEND_PRIORITY.insert(0, SDPBackend.CUDNN_ATTENTION)
def scaled_dot_product_attention(q, k, v, *args, **kwargs):
+ if q.nelement() < 1024 * 128: # arbitrary number, for small inputs cudnn attention seems slower
+ return torch.nn.functional.scaled_dot_product_attention(q, k, v, *args, **kwargs)
with sdpa_kernel(SDPA_BACKEND_PRIORITY, set_priority=True):
return torch.nn.functional.scaled_dot_product_attention(q, k, v, *args, **kwargs)
else:
From 6125b8097952a374009af39639ff45da85f65500 Mon Sep 17 00:00:00 2001
From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Date: Wed, 4 Feb 2026 18:29:22 -0800
Subject: [PATCH 04/10] Add llm sampling options and make reference audio work
on ace step 1.5 (#12295)
---
comfy/ldm/ace/ace_step15.py | 3 +--
comfy/model_base.py | 19 ++++++++++++-------
comfy/text_encoders/ace15.py | 31 +++++++++++++++++++++++--------
comfy_extras/nodes_ace.py | 16 +++++++++++-----
4 files changed, 47 insertions(+), 22 deletions(-)
diff --git a/comfy/ldm/ace/ace_step15.py b/comfy/ldm/ace/ace_step15.py
index d90549658..17a37e573 100644
--- a/comfy/ldm/ace/ace_step15.py
+++ b/comfy/ldm/ace/ace_step15.py
@@ -1035,8 +1035,7 @@ class AceStepConditionGenerationModel(nn.Module):
audio_codes = torch.nn.functional.pad(audio_codes, (0, math.ceil(src_latents.shape[1] / 5) - audio_codes.shape[1]), "constant", 35847)
lm_hints_5Hz = self.tokenizer.quantizer.get_output_from_indices(audio_codes, dtype=text_hidden_states.dtype)
else:
- assert False
- # TODO ?
+ lm_hints_5Hz, indices = self.tokenizer.tokenize(refer_audio_acoustic_hidden_states_packed)
lm_hints = self.detokenizer(lm_hints_5Hz)
diff --git a/comfy/model_base.py b/comfy/model_base.py
index 89944548c..a2a34f191 100644
--- a/comfy/model_base.py
+++ b/comfy/model_base.py
@@ -1548,6 +1548,7 @@ class ACEStep15(BaseModel):
def extra_conds(self, **kwargs):
out = super().extra_conds(**kwargs)
device = kwargs["device"]
+ noise = kwargs["noise"]
cross_attn = kwargs.get("cross_attn", None)
if cross_attn is not None:
@@ -1571,15 +1572,19 @@ class ACEStep15(BaseModel):
1.4844e-01, 9.4727e-02, 3.8477e-01, -1.2578e+00, -3.3203e-01,
-8.5547e-01, 4.3359e-01, 4.2383e-01, -8.9453e-01, -5.0391e-01,
-5.6152e-02, -2.9219e+00, -2.4658e-02, 5.0391e-01, 9.8438e-01,
- 7.2754e-02, -2.1582e-01, 6.3672e-01, 1.0000e+00]]], device=device).movedim(-1, 1).repeat(1, 1, 750)
+ 7.2754e-02, -2.1582e-01, 6.3672e-01, 1.0000e+00]]], device=device).movedim(-1, 1).repeat(1, 1, noise.shape[2])
+ pass_audio_codes = True
else:
- refer_audio = refer_audio[-1]
+ refer_audio = refer_audio[-1][:, :, :noise.shape[2]]
+ pass_audio_codes = False
+
+ if pass_audio_codes:
+ audio_codes = kwargs.get("audio_codes", None)
+ if audio_codes is not None:
+ out['audio_codes'] = comfy.conds.CONDRegular(torch.tensor(audio_codes, device=device))
+ refer_audio = refer_audio[:, :, :750]
+
out['refer_audio'] = comfy.conds.CONDRegular(refer_audio)
-
- audio_codes = kwargs.get("audio_codes", None)
- if audio_codes is not None:
- out['audio_codes'] = comfy.conds.CONDRegular(torch.tensor(audio_codes, device=device))
-
return out
class Omnigen2(BaseModel):
diff --git a/comfy/text_encoders/ace15.py b/comfy/text_encoders/ace15.py
index fce2b67ce..74e62733e 100644
--- a/comfy/text_encoders/ace15.py
+++ b/comfy/text_encoders/ace15.py
@@ -101,9 +101,7 @@ def sample_manual_loop_no_classes(
return output_audio_codes
-def generate_audio_codes(model, positive, negative, min_tokens=1, max_tokens=1024, seed=0):
- cfg_scale = 2.0
-
+def generate_audio_codes(model, positive, negative, min_tokens=1, max_tokens=1024, seed=0, cfg_scale=2.0, temperature=0.85, top_p=0.9, top_k=0):
positive = [[token for token, _ in inner_list] for inner_list in positive]
negative = [[token for token, _ in inner_list] for inner_list in negative]
positive = positive[0]
@@ -120,7 +118,7 @@ def generate_audio_codes(model, positive, negative, min_tokens=1, max_tokens=102
positive = [model.special_tokens["pad"]] * pos_pad + positive
paddings = [pos_pad, neg_pad]
- return sample_manual_loop_no_classes(model, [positive, negative], paddings, cfg_scale=cfg_scale, seed=seed, min_tokens=min_tokens, max_new_tokens=max_tokens)
+ return sample_manual_loop_no_classes(model, [positive, negative], paddings, cfg_scale=cfg_scale, temperature=temperature, top_p=top_p, top_k=top_k, seed=seed, min_tokens=min_tokens, max_new_tokens=max_tokens)
class ACE15Tokenizer(sd1_clip.SD1Tokenizer):
@@ -137,6 +135,12 @@ class ACE15Tokenizer(sd1_clip.SD1Tokenizer):
language = kwargs.get("language", "en")
seed = kwargs.get("seed", 0)
+ generate_audio_codes = kwargs.get("generate_audio_codes", True)
+ cfg_scale = kwargs.get("cfg_scale", 2.0)
+ temperature = kwargs.get("temperature", 0.85)
+ top_p = kwargs.get("top_p", 0.9)
+ top_k = kwargs.get("top_k", 0.0)
+
duration = math.ceil(duration)
meta_lm = 'bpm: {}\nduration: {}\nkeyscale: {}\ntimesignature: {}'.format(bpm, duration, keyscale, timesignature)
lm_template = "<|im_start|>system\n# Instruction\nGenerate audio semantic tokens based on the given conditions:\n\n<|im_end|>\n<|im_start|>user\n# Caption\n{}\n{}\n<|im_end|>\n<|im_start|>assistant\n\n{}\n\n\n<|im_end|>\n"
@@ -147,7 +151,14 @@ class ACE15Tokenizer(sd1_clip.SD1Tokenizer):
out["lyrics"] = self.qwen3_06b.tokenize_with_weights("# Languages\n{}\n\n# Lyric{}<|endoftext|><|endoftext|>".format(language, lyrics), return_word_ids, disable_weights=True, **kwargs)
out["qwen3_06b"] = self.qwen3_06b.tokenize_with_weights("# Instruction\nGenerate audio semantic tokens based on the given conditions:\n\n# Caption\n{}# Metas\n{}<|endoftext|>\n<|endoftext|>".format(text, meta_cap), return_word_ids, **kwargs)
- out["lm_metadata"] = {"min_tokens": duration * 5, "seed": seed}
+ out["lm_metadata"] = {"min_tokens": duration * 5,
+ "seed": seed,
+ "generate_audio_codes": generate_audio_codes,
+ "cfg_scale": cfg_scale,
+ "temperature": temperature,
+ "top_p": top_p,
+ "top_k": top_k,
+ }
return out
@@ -203,10 +214,14 @@ class ACE15TEModel(torch.nn.Module):
self.qwen3_06b.set_clip_options({"layer": [0]})
lyrics_embeds, _, extra_l = self.qwen3_06b.encode_token_weights(token_weight_pairs_lyrics)
- lm_metadata = token_weight_pairs["lm_metadata"]
- audio_codes = generate_audio_codes(getattr(self, self.lm_model, self.qwen3_06b), token_weight_pairs["lm_prompt"], token_weight_pairs["lm_prompt_negative"], min_tokens=lm_metadata["min_tokens"], max_tokens=lm_metadata["min_tokens"], seed=lm_metadata["seed"])
+ out = {"conditioning_lyrics": lyrics_embeds[:, 0]}
- return base_out, None, {"conditioning_lyrics": lyrics_embeds[:, 0], "audio_codes": [audio_codes]}
+ lm_metadata = token_weight_pairs["lm_metadata"]
+ if lm_metadata["generate_audio_codes"]:
+ audio_codes = generate_audio_codes(getattr(self, self.lm_model, self.qwen3_06b), token_weight_pairs["lm_prompt"], token_weight_pairs["lm_prompt_negative"], min_tokens=lm_metadata["min_tokens"], max_tokens=lm_metadata["min_tokens"], seed=lm_metadata["seed"], cfg_scale=lm_metadata["cfg_scale"], temperature=lm_metadata["temperature"], top_p=lm_metadata["top_p"], top_k=lm_metadata["top_k"])
+ out["audio_codes"] = [audio_codes]
+
+ return base_out, None, out
def set_clip_options(self, options):
self.qwen3_06b.set_clip_options(options)
diff --git a/comfy_extras/nodes_ace.py b/comfy_extras/nodes_ace.py
index 376584e5c..dde5bbd2a 100644
--- a/comfy_extras/nodes_ace.py
+++ b/comfy_extras/nodes_ace.py
@@ -44,13 +44,18 @@ class TextEncodeAceStepAudio15(io.ComfyNode):
io.Combo.Input("timesignature", options=['2', '3', '4', '6']),
io.Combo.Input("language", options=["en", "ja", "zh", "es", "de", "fr", "pt", "ru", "it", "nl", "pl", "tr", "vi", "cs", "fa", "id", "ko", "uk", "hu", "ar", "sv", "ro", "el"]),
io.Combo.Input("keyscale", options=[f"{root} {quality}" for quality in ["major", "minor"] for root in ["C", "C#", "Db", "D", "D#", "Eb", "E", "F", "F#", "Gb", "G", "G#", "Ab", "A", "A#", "Bb", "B"]]),
+ io.Boolean.Input("generate_audio_codes", default=True, tooltip="Enable the LLM that generates audio codes. This can be slow but will increase the quality of the generated audio. Turn this off if you are giving the model an audio reference.", advanced=True),
+ io.Float.Input("cfg_scale", default=2.0, min=0.0, max=100.0, step=0.1, advanced=True),
+ io.Float.Input("temperature", default=0.85, min=0.0, max=2.0, step=0.01, advanced=True),
+ io.Float.Input("top_p", default=0.9, min=0.0, max=2000.0, step=0.01, advanced=True),
+ io.Int.Input("top_k", default=0, min=0, max=100, advanced=True),
],
outputs=[io.Conditioning.Output()],
)
@classmethod
- def execute(cls, clip, tags, lyrics, seed, bpm, duration, timesignature, language, keyscale) -> io.NodeOutput:
- tokens = clip.tokenize(tags, lyrics=lyrics, bpm=bpm, duration=duration, timesignature=int(timesignature), language=language, keyscale=keyscale, seed=seed)
+ def execute(cls, clip, tags, lyrics, seed, bpm, duration, timesignature, language, keyscale, generate_audio_codes, cfg_scale, temperature, top_p, top_k) -> io.NodeOutput:
+ tokens = clip.tokenize(tags, lyrics=lyrics, bpm=bpm, duration=duration, timesignature=int(timesignature), language=language, keyscale=keyscale, seed=seed, generate_audio_codes=generate_audio_codes, cfg_scale=cfg_scale, temperature=temperature, top_p=top_p, top_k=top_k)
conditioning = clip.encode_from_tokens_scheduled(tokens)
return io.NodeOutput(conditioning)
@@ -100,14 +105,15 @@ class EmptyAceStep15LatentAudio(io.ComfyNode):
latent = torch.zeros([batch_size, 64, length], device=comfy.model_management.intermediate_device())
return io.NodeOutput({"samples": latent, "type": "audio"})
-class ReferenceTimbreAudio(io.ComfyNode):
+class ReferenceAudio(io.ComfyNode):
@classmethod
def define_schema(cls):
return io.Schema(
node_id="ReferenceTimbreAudio",
+ display_name="Reference Audio",
category="advanced/conditioning/audio",
is_experimental=True,
- description="This node sets the reference audio for timbre (for ace step 1.5)",
+ description="This node sets the reference audio for ace step 1.5",
inputs=[
io.Conditioning.Input("conditioning"),
io.Latent.Input("latent", optional=True),
@@ -131,7 +137,7 @@ class AceExtension(ComfyExtension):
EmptyAceStepLatentAudio,
TextEncodeAceStepAudio15,
EmptyAceStep15LatentAudio,
- ReferenceTimbreAudio,
+ ReferenceAudio,
]
async def comfy_entrypoint() -> AceExtension:
From a50c32d63fe55d073edd7af2242f0536f50b362e Mon Sep 17 00:00:00 2001
From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Date: Wed, 4 Feb 2026 19:15:30 -0800
Subject: [PATCH 05/10] Disable sage attention on ace step 1.5 (#12297)
---
comfy/ldm/ace/ace_step15.py | 2 +-
comfy/ldm/modules/attention.py | 3 +++
2 files changed, 4 insertions(+), 1 deletion(-)
diff --git a/comfy/ldm/ace/ace_step15.py b/comfy/ldm/ace/ace_step15.py
index 17a37e573..f2b130bc1 100644
--- a/comfy/ldm/ace/ace_step15.py
+++ b/comfy/ldm/ace/ace_step15.py
@@ -183,7 +183,7 @@ class AceStepAttention(nn.Module):
else:
attn_bias = window_bias
- attn_output = optimized_attention(query_states, key_states, value_states, self.num_heads, attn_bias, skip_reshape=True)
+ attn_output = optimized_attention(query_states, key_states, value_states, self.num_heads, attn_bias, skip_reshape=True, low_precision_attention=False)
attn_output = self.o_proj(attn_output)
return attn_output
diff --git a/comfy/ldm/modules/attention.py b/comfy/ldm/modules/attention.py
index ccf690945..10d051325 100644
--- a/comfy/ldm/modules/attention.py
+++ b/comfy/ldm/modules/attention.py
@@ -524,6 +524,9 @@ def attention_pytorch(q, k, v, heads, mask=None, attn_precision=None, skip_resha
@wrap_attn
def attention_sage(q, k, v, heads, mask=None, attn_precision=None, skip_reshape=False, skip_output_reshape=False, **kwargs):
+ if kwargs.get("low_precision_attention", True) is False:
+ return attention_pytorch(q, k, v, heads, mask=mask, skip_reshape=skip_reshape, skip_output_reshape=skip_output_reshape, **kwargs)
+
exception_fallback = False
if skip_reshape:
b, _, _, dim_head = q.shape
From a246cc02b274104d5f656b68ce505354c164aef8 Mon Sep 17 00:00:00 2001
From: blepping <157360029+blepping@users.noreply.github.com>
Date: Wed, 4 Feb 2026 22:17:37 -0700
Subject: [PATCH 06/10] Improvements to ACE-Steps 1.5 text encoding (#12283)
---
comfy/text_encoders/ace15.py | 56 +++++++++++++++++++++++++++++-------
1 file changed, 45 insertions(+), 11 deletions(-)
diff --git a/comfy/text_encoders/ace15.py b/comfy/text_encoders/ace15.py
index 74e62733e..00dd5ba90 100644
--- a/comfy/text_encoders/ace15.py
+++ b/comfy/text_encoders/ace15.py
@@ -3,6 +3,7 @@ import comfy.text_encoders.llama
from comfy import sd1_clip
import torch
import math
+import yaml
import comfy.utils
@@ -125,14 +126,43 @@ class ACE15Tokenizer(sd1_clip.SD1Tokenizer):
def __init__(self, embedding_directory=None, tokenizer_data={}):
super().__init__(embedding_directory=embedding_directory, tokenizer_data=tokenizer_data, name="qwen3_06b", tokenizer=Qwen3Tokenizer)
+ def _metas_to_cot(self, *, return_yaml: bool = False, **kwargs) -> str:
+ user_metas = {
+ k: kwargs.pop(k)
+ for k in ("bpm", "duration", "keyscale", "timesignature", "language", "caption")
+ if k in kwargs
+ }
+ timesignature = user_metas.get("timesignature")
+ if isinstance(timesignature, str) and timesignature.endswith("/4"):
+ user_metas["timesignature"] = timesignature.rsplit("/", 1)[0]
+ user_metas = {
+ k: v if not isinstance(v, str) or not v.isdigit() else int(v)
+ for k, v in user_metas.items()
+ if v not in {"unspecified", None}
+ }
+ if len(user_metas):
+ meta_yaml = yaml.dump(user_metas, allow_unicode=True, sort_keys=True).strip()
+ else:
+ meta_yaml = ""
+ return f"\n{meta_yaml}\n" if not return_yaml else meta_yaml
+
+ def _metas_to_cap(self, **kwargs) -> str:
+ use_keys = ("bpm", "duration", "keyscale", "timesignature")
+ user_metas = { k: kwargs.pop(k, "N/A") for k in use_keys }
+ duration = user_metas["duration"]
+ if duration == "N/A":
+ user_metas["duration"] = "30 seconds"
+ elif isinstance(duration, (str, int, float)):
+ user_metas["duration"] = f"{math.ceil(float(duration))} seconds"
+ else:
+ raise TypeError("Unexpected type for duration key, must be str, int or float")
+ return "\n".join(f"- {k}: {user_metas[k]}" for k in use_keys)
+
def tokenize_with_weights(self, text, return_word_ids=False, **kwargs):
out = {}
lyrics = kwargs.get("lyrics", "")
- bpm = kwargs.get("bpm", 120)
duration = kwargs.get("duration", 120)
- keyscale = kwargs.get("keyscale", "C major")
- timesignature = kwargs.get("timesignature", 2)
- language = kwargs.get("language", "en")
+ language = kwargs.get("language")
seed = kwargs.get("seed", 0)
generate_audio_codes = kwargs.get("generate_audio_codes", True)
@@ -141,16 +171,20 @@ class ACE15Tokenizer(sd1_clip.SD1Tokenizer):
top_p = kwargs.get("top_p", 0.9)
top_k = kwargs.get("top_k", 0.0)
+
duration = math.ceil(duration)
- meta_lm = 'bpm: {}\nduration: {}\nkeyscale: {}\ntimesignature: {}'.format(bpm, duration, keyscale, timesignature)
- lm_template = "<|im_start|>system\n# Instruction\nGenerate audio semantic tokens based on the given conditions:\n\n<|im_end|>\n<|im_start|>user\n# Caption\n{}\n{}\n<|im_end|>\n<|im_start|>assistant\n\n{}\n\n\n<|im_end|>\n"
+ kwargs["duration"] = duration
- meta_cap = '- bpm: {}\n- timesignature: {}\n- keyscale: {}\n- duration: {}\n'.format(bpm, timesignature, keyscale, duration)
- out["lm_prompt"] = self.qwen3_06b.tokenize_with_weights(lm_template.format(text, lyrics, meta_lm), disable_weights=True)
- out["lm_prompt_negative"] = self.qwen3_06b.tokenize_with_weights(lm_template.format(text, lyrics, ""), disable_weights=True)
+ cot_text = self._metas_to_cot(caption = text, **kwargs)
+ meta_cap = self._metas_to_cap(**kwargs)
- out["lyrics"] = self.qwen3_06b.tokenize_with_weights("# Languages\n{}\n\n# Lyric{}<|endoftext|><|endoftext|>".format(language, lyrics), return_word_ids, disable_weights=True, **kwargs)
- out["qwen3_06b"] = self.qwen3_06b.tokenize_with_weights("# Instruction\nGenerate audio semantic tokens based on the given conditions:\n\n# Caption\n{}# Metas\n{}<|endoftext|>\n<|endoftext|>".format(text, meta_cap), return_word_ids, **kwargs)
+ lm_template = "<|im_start|>system\n# Instruction\nGenerate audio semantic tokens based on the given conditions:\n\n<|im_end|>\n<|im_start|>user\n# Caption\n{}\n# Lyric\n{}\n<|im_end|>\n<|im_start|>assistant\n{}\n<|im_end|>\n"
+
+ out["lm_prompt"] = self.qwen3_06b.tokenize_with_weights(lm_template.format(text, lyrics, cot_text), disable_weights=True)
+ out["lm_prompt_negative"] = self.qwen3_06b.tokenize_with_weights(lm_template.format(text, lyrics, "\n"), disable_weights=True)
+
+ out["lyrics"] = self.qwen3_06b.tokenize_with_weights("# Languages\n{}\n\n# Lyric\n{}<|endoftext|><|endoftext|>".format(language if language is not None else "", lyrics), return_word_ids, disable_weights=True, **kwargs)
+ out["qwen3_06b"] = self.qwen3_06b.tokenize_with_weights("# Instruction\nGenerate audio semantic tokens based on the given conditions:\n\n# Caption\n{}\n# Metas\n{}\n<|endoftext|>\n<|endoftext|>".format(text, meta_cap), return_word_ids, **kwargs)
out["lm_metadata"] = {"min_tokens": duration * 5,
"seed": seed,
"generate_audio_codes": generate_audio_codes,
From 35183543e004d8b7509c043e7a680bee07171622 Mon Sep 17 00:00:00 2001
From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Date: Wed, 4 Feb 2026 22:12:04 -0800
Subject: [PATCH 07/10] Add VAE tiled decode node for audio. (#12299)
---
comfy/sd.py | 2 +-
comfy_extras/nodes_audio.py | 43 +++++++++++++++++++++++++++++++------
2 files changed, 38 insertions(+), 7 deletions(-)
diff --git a/comfy/sd.py b/comfy/sd.py
index bc63d6ced..bc9407405 100644
--- a/comfy/sd.py
+++ b/comfy/sd.py
@@ -976,7 +976,7 @@ class VAE:
if overlap is not None:
args["overlap"] = overlap
- if dims == 1:
+ if dims == 1 or self.extra_1d_channel is not None:
args.pop("tile_y")
output = self.decode_tiled_1d(samples, **args)
elif dims == 2:
diff --git a/comfy_extras/nodes_audio.py b/comfy_extras/nodes_audio.py
index bef723dce..b63dd8e97 100644
--- a/comfy_extras/nodes_audio.py
+++ b/comfy_extras/nodes_audio.py
@@ -94,6 +94,19 @@ class VAEEncodeAudio(IO.ComfyNode):
encode = execute # TODO: remove
+def vae_decode_audio(vae, samples, tile=None, overlap=None):
+ if tile is not None:
+ audio = vae.decode_tiled(samples["samples"], tile_y=tile, overlap=overlap).movedim(-1, 1)
+ else:
+ audio = vae.decode(samples["samples"]).movedim(-1, 1)
+
+ std = torch.std(audio, dim=[1, 2], keepdim=True) * 5.0
+ std[std < 1.0] = 1.0
+ audio /= std
+ vae_sample_rate = getattr(vae, "audio_sample_rate", 44100)
+ return {"waveform": audio, "sample_rate": vae_sample_rate if "sample_rate" not in samples else samples["sample_rate"]}
+
+
class VAEDecodeAudio(IO.ComfyNode):
@classmethod
def define_schema(cls):
@@ -111,16 +124,33 @@ class VAEDecodeAudio(IO.ComfyNode):
@classmethod
def execute(cls, vae, samples) -> IO.NodeOutput:
- audio = vae.decode(samples["samples"]).movedim(-1, 1)
- std = torch.std(audio, dim=[1,2], keepdim=True) * 5.0
- std[std < 1.0] = 1.0
- audio /= std
- vae_sample_rate = getattr(vae, "audio_sample_rate", 44100)
- return IO.NodeOutput({"waveform": audio, "sample_rate": vae_sample_rate if "sample_rate" not in samples else samples["sample_rate"]})
+ return IO.NodeOutput(vae_decode_audio(vae, samples))
decode = execute # TODO: remove
+class VAEDecodeAudioTiled(IO.ComfyNode):
+ @classmethod
+ def define_schema(cls):
+ return IO.Schema(
+ node_id="VAEDecodeAudioTiled",
+ search_aliases=["latent to audio"],
+ display_name="VAE Decode Audio (Tiled)",
+ category="latent/audio",
+ inputs=[
+ IO.Latent.Input("samples"),
+ IO.Vae.Input("vae"),
+ IO.Int.Input("tile_size", default=512, min=32, max=8192, step=8),
+ IO.Int.Input("overlap", default=64, min=0, max=1024, step=8),
+ ],
+ outputs=[IO.Audio.Output()],
+ )
+
+ @classmethod
+ def execute(cls, vae, samples, tile_size, overlap) -> IO.NodeOutput:
+ return IO.NodeOutput(vae_decode_audio(vae, samples, tile_size, overlap))
+
+
class SaveAudio(IO.ComfyNode):
@classmethod
def define_schema(cls):
@@ -675,6 +705,7 @@ class AudioExtension(ComfyExtension):
EmptyLatentAudio,
VAEEncodeAudio,
VAEDecodeAudio,
+ VAEDecodeAudioTiled,
SaveAudio,
SaveAudioMP3,
SaveAudioOpus,
From cb459573c8fa025bbf9ecf312f6af376d659f567 Mon Sep 17 00:00:00 2001
From: comfyanonymous
Date: Thu, 5 Feb 2026 01:13:35 -0500
Subject: [PATCH 08/10] ComfyUI v0.12.3
---
comfyui_version.py | 2 +-
pyproject.toml | 2 +-
2 files changed, 2 insertions(+), 2 deletions(-)
diff --git a/comfyui_version.py b/comfyui_version.py
index 5d296cd1b..706b37763 100644
--- 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__ = "0.12.2"
+__version__ = "0.12.3"
diff --git a/pyproject.toml b/pyproject.toml
index 1ddcc3596..f7925b92a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
[project]
name = "ComfyUI"
-version = "0.12.2"
+version = "0.12.3"
readme = "README.md"
license = { file = "LICENSE" }
requires-python = ">=3.10"
From 00efcc6cd028206ad81a90dec177c9a470a20a2a Mon Sep 17 00:00:00 2001
From: Comfy Org PR Bot
Date: Thu, 5 Feb 2026 15:17:37 +0900
Subject: [PATCH 09/10] Bump comfyui-frontend-package to 1.38.13 (#12238)
---
requirements.txt | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/requirements.txt b/requirements.txt
index 0c401873a..41cc9174b 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,4 +1,4 @@
-comfyui-frontend-package==1.37.11
+comfyui-frontend-package==1.38.13
comfyui-workflow-templates==0.8.31
comfyui-embedded-docs==0.4.0
torch
From 2b70ab9ad0fd6a38b11546a18c546ce40cc176a1 Mon Sep 17 00:00:00 2001
From: AustinMroz
Date: Wed, 4 Feb 2026 22:18:21 -0800
Subject: [PATCH 10/10] Add a Create List node (#12173)
---
comfy_extras/nodes_toolkit.py | 47 +++++++++++++++++++++++++++++++++++
nodes.py | 3 ++-
2 files changed, 49 insertions(+), 1 deletion(-)
create mode 100644 comfy_extras/nodes_toolkit.py
diff --git a/comfy_extras/nodes_toolkit.py b/comfy_extras/nodes_toolkit.py
new file mode 100644
index 000000000..71faf7226
--- /dev/null
+++ b/comfy_extras/nodes_toolkit.py
@@ -0,0 +1,47 @@
+from __future__ import annotations
+from typing_extensions import override
+from comfy_api.latest import ComfyExtension, io
+
+
+class CreateList(io.ComfyNode):
+ @classmethod
+ def define_schema(cls):
+ template_matchtype = io.MatchType.Template("type")
+ template_autogrow = io.Autogrow.TemplatePrefix(
+ input=io.MatchType.Input("input", template=template_matchtype),
+ prefix="input",
+ )
+ return io.Schema(
+ node_id="CreateList",
+ display_name="Create List",
+ category="logic",
+ is_input_list=True,
+ search_aliases=["Image Iterator", "Text Iterator", "Iterator"],
+ inputs=[io.Autogrow.Input("inputs", template=template_autogrow)],
+ outputs=[
+ io.MatchType.Output(
+ template=template_matchtype,
+ is_output_list=True,
+ display_name="list",
+ ),
+ ],
+ )
+
+ @classmethod
+ def execute(cls, inputs: io.Autogrow.Type) -> io.NodeOutput:
+ output_list = []
+ for input in inputs.values():
+ output_list += input
+ return io.NodeOutput(output_list)
+
+
+class ToolkitExtension(ComfyExtension):
+ @override
+ async def get_node_list(self) -> list[type[io.ComfyNode]]:
+ return [
+ CreateList,
+ ]
+
+
+async def comfy_entrypoint() -> ToolkitExtension:
+ return ToolkitExtension()
diff --git a/nodes.py b/nodes.py
index e11a8ed80..91de7a9d7 100644
--- a/nodes.py
+++ b/nodes.py
@@ -2433,7 +2433,8 @@ async def init_builtin_extra_nodes():
"nodes_image_compare.py",
"nodes_zimage.py",
"nodes_lora_debug.py",
- "nodes_color.py"
+ "nodes_color.py",
+ "nodes_toolkit.py",
]
import_failed = []