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feat/api-n
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proxy-widg
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|
||||
{"revision": 0, "last_node_id": 13, "last_link_id": 0, "nodes": [{"id": 13, "type": "cf95b747-3e17-46cb-8097-cac60ff9b2e1", "pos": [1120, 330], "size": [240, 58], "flags": {}, "order": 3, "mode": 0, "inputs": [{"localized_name": "video", "name": "video", "type": "VIDEO", "link": null}, {"name": "model_name", "type": "COMBO", "widget": {"name": "model_name"}, "link": null}], "outputs": [{"localized_name": "VIDEO", "name": "VIDEO", "type": "VIDEO", "links": []}], "title": "Video Upscale(GAN x4)", "properties": {"proxyWidgets": [["-1", "model_name"]], "cnr_id": "comfy-core", "ver": "0.14.1"}, "widgets_values": ["RealESRGAN_x4plus.safetensors"]}], "links": [], "version": 0.4, "definitions": {"subgraphs": [{"id": "cf95b747-3e17-46cb-8097-cac60ff9b2e1", "version": 1, "state": {"lastGroupId": 0, "lastNodeId": 13, "lastLinkId": 19, "lastRerouteId": 0}, "revision": 0, "config": {}, "name": "Video Upscale(GAN x4)", "inputNode": {"id": -10, "bounding": [550, 460, 120, 80]}, "outputNode": {"id": -20, "bounding": [1490, 460, 120, 60]}, "inputs": [{"id": "666d633e-93e7-42dc-8d11-2b7b99b0f2a6", "name": "video", "type": "VIDEO", "linkIds": [10], "localized_name": "video", "pos": [650, 480]}, {"id": "2e23a087-caa8-4d65-99e6-662761aa905a", "name": "model_name", "type": "COMBO", "linkIds": [19], "pos": [650, 500]}], "outputs": [{"id": "0c1768ea-3ec2-412f-9af6-8e0fa36dae70", "name": "VIDEO", "type": "VIDEO", "linkIds": [15], "localized_name": "VIDEO", "pos": [1510, 480]}], "widgets": [], "nodes": [{"id": 2, "type": "ImageUpscaleWithModel", "pos": [1110, 450], "size": [320, 46], "flags": {}, "order": 1, "mode": 0, "inputs": [{"localized_name": "upscale_model", "name": "upscale_model", "type": "UPSCALE_MODEL", "link": 1}, {"localized_name": "image", "name": "image", "type": "IMAGE", "link": 14}], "outputs": [{"localized_name": "IMAGE", "name": "IMAGE", "type": "IMAGE", "links": [13]}], "properties": {"cnr_id": "comfy-core", "ver": "0.10.0", "Node name for S&R": "ImageUpscaleWithModel"}}, {"id": 11, "type": "CreateVideo", "pos": [1110, 550], "size": [320, 78], "flags": {}, "order": 3, "mode": 0, "inputs": [{"localized_name": "images", "name": "images", "type": "IMAGE", "link": 13}, {"localized_name": "audio", "name": "audio", "shape": 7, "type": "AUDIO", "link": 16}, {"localized_name": "fps", "name": "fps", "type": "FLOAT", "widget": {"name": "fps"}, "link": 12}], "outputs": [{"localized_name": "VIDEO", "name": "VIDEO", "type": "VIDEO", "links": [15]}], "properties": {"cnr_id": "comfy-core", "ver": "0.10.0", "Node name for S&R": "CreateVideo"}, "widgets_values": [30]}, {"id": 10, "type": "GetVideoComponents", "pos": [1110, 330], "size": [320, 70], "flags": {}, "order": 2, "mode": 0, "inputs": [{"localized_name": "video", "name": "video", "type": "VIDEO", "link": 10}], "outputs": [{"localized_name": "images", "name": "images", "type": "IMAGE", "links": [14]}, {"localized_name": "audio", "name": "audio", "type": "AUDIO", "links": [16]}, {"localized_name": "fps", "name": "fps", "type": "FLOAT", "links": [12]}], "properties": {"cnr_id": "comfy-core", "ver": "0.10.0", "Node name for S&R": "GetVideoComponents"}}, {"id": 1, "type": "UpscaleModelLoader", "pos": [750, 450], "size": [280, 60], "flags": {}, "order": 0, "mode": 0, "inputs": [{"localized_name": "model_name", "name": "model_name", "type": "COMBO", "widget": {"name": "model_name"}, "link": 19}], "outputs": [{"localized_name": "UPSCALE_MODEL", "name": "UPSCALE_MODEL", "type": "UPSCALE_MODEL", "links": [1]}], "properties": {"cnr_id": "comfy-core", "ver": "0.10.0", "Node name for S&R": "UpscaleModelLoader", "models": [{"name": "RealESRGAN_x4plus.safetensors", "url": "https://huggingface.co/Comfy-Org/Real-ESRGAN_repackaged/resolve/main/RealESRGAN_x4plus.safetensors", "directory": "upscale_models"}]}, "widgets_values": ["RealESRGAN_x4plus.safetensors"]}], "groups": [], "links": [{"id": 1, "origin_id": 1, "origin_slot": 0, "target_id": 2, "target_slot": 0, "type": "UPSCALE_MODEL"}, {"id": 14, "origin_id": 10, "origin_slot": 0, "target_id": 2, "target_slot": 1, "type": "IMAGE"}, {"id": 13, "origin_id": 2, "origin_slot": 0, "target_id": 11, "target_slot": 0, "type": "IMAGE"}, {"id": 16, "origin_id": 10, "origin_slot": 1, "target_id": 11, "target_slot": 1, "type": "AUDIO"}, {"id": 12, "origin_id": 10, "origin_slot": 2, "target_id": 11, "target_slot": 2, "type": "FLOAT"}, {"id": 10, "origin_id": -10, "origin_slot": 0, "target_id": 10, "target_slot": 0, "type": "VIDEO"}, {"id": 15, "origin_id": 11, "origin_slot": 0, "target_id": -20, "target_slot": 0, "type": "VIDEO"}, {"id": 19, "origin_id": -10, "origin_slot": 1, "target_id": 1, "target_slot": 0, "type": "COMBO"}], "extra": {"workflowRendererVersion": "LG"}, "category": "Video generation and editing/Enhance video"}]}, "extra": {}}
|
||||
|
||||
@@ -611,7 +611,6 @@ class AceStepDiTModel(nn.Module):
|
||||
intermediate_size,
|
||||
patch_size,
|
||||
audio_acoustic_hidden_dim,
|
||||
condition_dim=None,
|
||||
layer_types=None,
|
||||
sliding_window=128,
|
||||
rms_norm_eps=1e-6,
|
||||
@@ -641,7 +640,7 @@ class AceStepDiTModel(nn.Module):
|
||||
|
||||
self.time_embed = TimestepEmbedding(256, hidden_size, dtype=dtype, device=device, operations=operations)
|
||||
self.time_embed_r = TimestepEmbedding(256, hidden_size, dtype=dtype, device=device, operations=operations)
|
||||
self.condition_embedder = Linear(condition_dim, hidden_size, dtype=dtype, device=device)
|
||||
self.condition_embedder = Linear(hidden_size, hidden_size, dtype=dtype, device=device)
|
||||
|
||||
if layer_types is None:
|
||||
layer_types = ["full_attention"] * num_layers
|
||||
@@ -1036,9 +1035,6 @@ class AceStepConditionGenerationModel(nn.Module):
|
||||
fsq_dim=2048,
|
||||
fsq_levels=[8, 8, 8, 5, 5, 5],
|
||||
fsq_input_num_quantizers=1,
|
||||
encoder_hidden_size=2048,
|
||||
encoder_intermediate_size=6144,
|
||||
encoder_num_heads=16,
|
||||
audio_model=None,
|
||||
dtype=None,
|
||||
device=None,
|
||||
@@ -1058,24 +1054,24 @@ class AceStepConditionGenerationModel(nn.Module):
|
||||
|
||||
self.decoder = AceStepDiTModel(
|
||||
in_channels, hidden_size, num_dit_layers, num_heads, num_kv_heads, head_dim,
|
||||
intermediate_size, patch_size, audio_acoustic_hidden_dim, condition_dim=encoder_hidden_size,
|
||||
intermediate_size, patch_size, audio_acoustic_hidden_dim,
|
||||
layer_types=layer_types, sliding_window=sliding_window, rms_norm_eps=rms_norm_eps,
|
||||
dtype=dtype, device=device, operations=operations
|
||||
)
|
||||
self.encoder = AceStepConditionEncoder(
|
||||
text_hidden_dim, timbre_hidden_dim, encoder_hidden_size, num_lyric_layers, num_timbre_layers,
|
||||
encoder_num_heads, num_kv_heads, head_dim, encoder_intermediate_size, rms_norm_eps,
|
||||
text_hidden_dim, timbre_hidden_dim, hidden_size, num_lyric_layers, num_timbre_layers,
|
||||
num_heads, num_kv_heads, head_dim, intermediate_size, rms_norm_eps,
|
||||
dtype=dtype, device=device, operations=operations
|
||||
)
|
||||
self.tokenizer = AceStepAudioTokenizer(
|
||||
audio_acoustic_hidden_dim, encoder_hidden_size, pool_window_size, fsq_dim=fsq_dim, fsq_levels=fsq_levels, fsq_input_num_quantizers=fsq_input_num_quantizers, num_layers=num_tokenizer_layers, head_dim=head_dim, rms_norm_eps=rms_norm_eps,
|
||||
audio_acoustic_hidden_dim, hidden_size, pool_window_size, fsq_dim=fsq_dim, fsq_levels=fsq_levels, fsq_input_num_quantizers=fsq_input_num_quantizers, num_layers=num_tokenizer_layers, head_dim=head_dim, rms_norm_eps=rms_norm_eps,
|
||||
dtype=dtype, device=device, operations=operations
|
||||
)
|
||||
self.detokenizer = AudioTokenDetokenizer(
|
||||
encoder_hidden_size, pool_window_size, audio_acoustic_hidden_dim, num_layers=2, head_dim=head_dim,
|
||||
hidden_size, pool_window_size, audio_acoustic_hidden_dim, num_layers=2, head_dim=head_dim,
|
||||
dtype=dtype, device=device, operations=operations
|
||||
)
|
||||
self.null_condition_emb = nn.Parameter(torch.empty(1, 1, encoder_hidden_size, dtype=dtype, device=device))
|
||||
self.null_condition_emb = nn.Parameter(torch.empty(1, 1, hidden_size, dtype=dtype, device=device))
|
||||
|
||||
def prepare_condition(
|
||||
self,
|
||||
|
||||
@@ -155,7 +155,6 @@ class AutoencodingEngineLegacy(AutoencodingEngine):
|
||||
def __init__(self, embed_dim: int, **kwargs):
|
||||
self.max_batch_size = kwargs.pop("max_batch_size", None)
|
||||
ddconfig = kwargs.pop("ddconfig")
|
||||
decoder_ddconfig = kwargs.pop("decoder_ddconfig", ddconfig)
|
||||
super().__init__(
|
||||
encoder_config={
|
||||
"target": "comfy.ldm.modules.diffusionmodules.model.Encoder",
|
||||
@@ -163,7 +162,7 @@ class AutoencodingEngineLegacy(AutoencodingEngine):
|
||||
},
|
||||
decoder_config={
|
||||
"target": "comfy.ldm.modules.diffusionmodules.model.Decoder",
|
||||
"params": decoder_ddconfig,
|
||||
"params": ddconfig,
|
||||
},
|
||||
**kwargs,
|
||||
)
|
||||
|
||||
@@ -696,15 +696,6 @@ def detect_unet_config(state_dict, key_prefix, metadata=None):
|
||||
if '{}encoder.lyric_encoder.layers.0.input_layernorm.weight'.format(key_prefix) in state_dict_keys:
|
||||
dit_config = {}
|
||||
dit_config["audio_model"] = "ace1.5"
|
||||
head_dim = 128
|
||||
dit_config["hidden_size"] = state_dict['{}decoder.layers.0.self_attn_norm.weight'.format(key_prefix)].shape[0]
|
||||
dit_config["intermediate_size"] = state_dict['{}decoder.layers.0.mlp.gate_proj.weight'.format(key_prefix)].shape[0]
|
||||
dit_config["num_heads"] = state_dict['{}decoder.layers.0.self_attn.q_proj.weight'.format(key_prefix)].shape[0] // head_dim
|
||||
|
||||
dit_config["encoder_hidden_size"] = state_dict['{}encoder.lyric_encoder.layers.0.input_layernorm.weight'.format(key_prefix)].shape[0]
|
||||
dit_config["encoder_num_heads"] = state_dict['{}encoder.lyric_encoder.layers.0.self_attn.q_proj.weight'.format(key_prefix)].shape[0] // head_dim
|
||||
dit_config["encoder_intermediate_size"] = state_dict['{}encoder.lyric_encoder.layers.0.mlp.gate_proj.weight'.format(key_prefix)].shape[0]
|
||||
dit_config["num_dit_layers"] = count_blocks(state_dict_keys, '{}decoder.layers.'.format(key_prefix) + '{}.')
|
||||
return dit_config
|
||||
|
||||
if '{}encoder.pan_blocks.1.cv4.conv.weight'.format(key_prefix) in state_dict_keys: # RT-DETR_v4
|
||||
|
||||
11
comfy/sd.py
11
comfy/sd.py
@@ -556,19 +556,12 @@ class VAE:
|
||||
old_memory_used_decode = self.memory_used_decode
|
||||
self.memory_used_decode = lambda shape, dtype: old_memory_used_decode(shape, dtype) * 4.0
|
||||
|
||||
decoder_ch = sd['decoder.conv_in.weight'].shape[0] // ddconfig['ch_mult'][-1]
|
||||
if decoder_ch != ddconfig['ch']:
|
||||
decoder_ddconfig = ddconfig.copy()
|
||||
decoder_ddconfig['ch'] = decoder_ch
|
||||
else:
|
||||
decoder_ddconfig = None
|
||||
|
||||
if 'post_quant_conv.weight' in sd:
|
||||
self.first_stage_model = AutoencoderKL(ddconfig=ddconfig, embed_dim=sd['post_quant_conv.weight'].shape[1], **({"decoder_ddconfig": decoder_ddconfig} if decoder_ddconfig is not None else {}))
|
||||
self.first_stage_model = AutoencoderKL(ddconfig=ddconfig, embed_dim=sd['post_quant_conv.weight'].shape[1])
|
||||
else:
|
||||
self.first_stage_model = AutoencodingEngine(regularizer_config={'target': "comfy.ldm.models.autoencoder.DiagonalGaussianRegularizer"},
|
||||
encoder_config={'target': "comfy.ldm.modules.diffusionmodules.model.Encoder", 'params': ddconfig},
|
||||
decoder_config={'target': "comfy.ldm.modules.diffusionmodules.model.Decoder", 'params': decoder_ddconfig if decoder_ddconfig is not None else ddconfig})
|
||||
decoder_config={'target': "comfy.ldm.modules.diffusionmodules.model.Decoder", 'params': ddconfig})
|
||||
elif "decoder.layers.1.layers.0.beta" in sd:
|
||||
config = {}
|
||||
param_key = None
|
||||
|
||||
@@ -24,9 +24,8 @@ from comfy_api_nodes.util import (
|
||||
AVERAGE_DURATION_VIDEO_GEN = 32
|
||||
MODELS_MAP = {
|
||||
"veo-2.0-generate-001": "veo-2.0-generate-001",
|
||||
"veo-3.1-generate": "veo-3.1-generate-001",
|
||||
"veo-3.1-fast-generate": "veo-3.1-fast-generate-001",
|
||||
"veo-3.1-lite": "veo-3.1-lite-generate-001",
|
||||
"veo-3.1-generate": "veo-3.1-generate-preview",
|
||||
"veo-3.1-fast-generate": "veo-3.1-fast-generate-preview",
|
||||
"veo-3.0-generate-001": "veo-3.0-generate-001",
|
||||
"veo-3.0-fast-generate-001": "veo-3.0-fast-generate-001",
|
||||
}
|
||||
@@ -248,8 +247,17 @@ class VeoVideoGenerationNode(IO.ComfyNode):
|
||||
raise Exception("Video generation completed but no video was returned")
|
||||
|
||||
|
||||
class Veo3VideoGenerationNode(IO.ComfyNode):
|
||||
"""Generates videos from text prompts using Google's Veo 3 API."""
|
||||
class Veo3VideoGenerationNode(VeoVideoGenerationNode):
|
||||
"""
|
||||
Generates videos from text prompts using Google's Veo 3 API.
|
||||
|
||||
Supported models:
|
||||
- veo-3.0-generate-001
|
||||
- veo-3.0-fast-generate-001
|
||||
|
||||
This node extends the base Veo node with Veo 3 specific features including
|
||||
audio generation and fixed 8-second duration.
|
||||
"""
|
||||
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
@@ -271,13 +279,6 @@ class Veo3VideoGenerationNode(IO.ComfyNode):
|
||||
default="16:9",
|
||||
tooltip="Aspect ratio of the output video",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"resolution",
|
||||
options=["720p", "1080p", "4k"],
|
||||
default="720p",
|
||||
tooltip="Output video resolution. 4K is not available for veo-3.1-lite and veo-3.0 models.",
|
||||
optional=True,
|
||||
),
|
||||
IO.String.Input(
|
||||
"negative_prompt",
|
||||
multiline=True,
|
||||
@@ -288,11 +289,11 @@ class Veo3VideoGenerationNode(IO.ComfyNode):
|
||||
IO.Int.Input(
|
||||
"duration_seconds",
|
||||
default=8,
|
||||
min=4,
|
||||
min=8,
|
||||
max=8,
|
||||
step=2,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
tooltip="Duration of the output video in seconds",
|
||||
tooltip="Duration of the output video in seconds (Veo 3 only supports 8 seconds)",
|
||||
optional=True,
|
||||
),
|
||||
IO.Boolean.Input(
|
||||
@@ -331,10 +332,10 @@ class Veo3VideoGenerationNode(IO.ComfyNode):
|
||||
options=[
|
||||
"veo-3.1-generate",
|
||||
"veo-3.1-fast-generate",
|
||||
"veo-3.1-lite",
|
||||
"veo-3.0-generate-001",
|
||||
"veo-3.0-fast-generate-001",
|
||||
],
|
||||
default="veo-3.0-generate-001",
|
||||
tooltip="Veo 3 model to use for video generation",
|
||||
optional=True,
|
||||
),
|
||||
@@ -355,111 +356,21 @@ class Veo3VideoGenerationNode(IO.ComfyNode):
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
depends_on=IO.PriceBadgeDepends(widgets=["model", "generate_audio", "resolution", "duration_seconds"]),
|
||||
depends_on=IO.PriceBadgeDepends(widgets=["model", "generate_audio"]),
|
||||
expr="""
|
||||
(
|
||||
$m := widgets.model;
|
||||
$r := widgets.resolution;
|
||||
$a := widgets.generate_audio;
|
||||
$seconds := widgets.duration_seconds;
|
||||
$pps :=
|
||||
$contains($m, "lite")
|
||||
? ($r = "1080p" ? ($a ? 0.08 : 0.05) : ($a ? 0.05 : 0.03))
|
||||
: $contains($m, "3.1-fast")
|
||||
? ($r = "4k" ? ($a ? 0.30 : 0.25) : $r = "1080p" ? ($a ? 0.12 : 0.10) : ($a ? 0.10 : 0.08))
|
||||
: $contains($m, "3.1-generate")
|
||||
? ($r = "4k" ? ($a ? 0.60 : 0.40) : ($a ? 0.40 : 0.20))
|
||||
: $contains($m, "3.0-fast")
|
||||
? ($a ? 0.15 : 0.10)
|
||||
: ($a ? 0.40 : 0.20);
|
||||
{"type":"usd","usd": $pps * $seconds}
|
||||
($contains($m,"veo-3.0-fast-generate-001") or $contains($m,"veo-3.1-fast-generate"))
|
||||
? {"type":"usd","usd": ($a ? 1.2 : 0.8)}
|
||||
: ($contains($m,"veo-3.0-generate-001") or $contains($m,"veo-3.1-generate"))
|
||||
? {"type":"usd","usd": ($a ? 3.2 : 1.6)}
|
||||
: {"type":"range_usd","min_usd":0.8,"max_usd":3.2}
|
||||
)
|
||||
""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
prompt,
|
||||
aspect_ratio="16:9",
|
||||
resolution="720p",
|
||||
negative_prompt="",
|
||||
duration_seconds=8,
|
||||
enhance_prompt=True,
|
||||
person_generation="ALLOW",
|
||||
seed=0,
|
||||
image=None,
|
||||
model="veo-3.0-generate-001",
|
||||
generate_audio=False,
|
||||
):
|
||||
if "lite" in model and resolution == "4k":
|
||||
raise Exception("4K resolution is not supported by the veo-3.1-lite model.")
|
||||
|
||||
model = MODELS_MAP[model]
|
||||
|
||||
instances = [{"prompt": prompt}]
|
||||
if image is not None:
|
||||
image_base64 = tensor_to_base64_string(image)
|
||||
if image_base64:
|
||||
instances[0]["image"] = {"bytesBase64Encoded": image_base64, "mimeType": "image/png"}
|
||||
|
||||
parameters = {
|
||||
"aspectRatio": aspect_ratio,
|
||||
"personGeneration": person_generation,
|
||||
"durationSeconds": duration_seconds,
|
||||
"enhancePrompt": True,
|
||||
"generateAudio": generate_audio,
|
||||
}
|
||||
if negative_prompt:
|
||||
parameters["negativePrompt"] = negative_prompt
|
||||
if seed > 0:
|
||||
parameters["seed"] = seed
|
||||
if "veo-3.1" in model:
|
||||
parameters["resolution"] = resolution
|
||||
|
||||
initial_response = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(path=f"/proxy/veo/{model}/generate", method="POST"),
|
||||
response_model=VeoGenVidResponse,
|
||||
data=VeoGenVidRequest(
|
||||
instances=instances,
|
||||
parameters=parameters,
|
||||
),
|
||||
)
|
||||
|
||||
poll_response = await poll_op(
|
||||
cls,
|
||||
ApiEndpoint(path=f"/proxy/veo/{model}/poll", method="POST"),
|
||||
response_model=VeoGenVidPollResponse,
|
||||
status_extractor=lambda r: "completed" if r.done else "pending",
|
||||
data=VeoGenVidPollRequest(operationName=initial_response.name),
|
||||
poll_interval=5.0,
|
||||
estimated_duration=AVERAGE_DURATION_VIDEO_GEN,
|
||||
)
|
||||
|
||||
if poll_response.error:
|
||||
raise Exception(f"Veo API error: {poll_response.error.message} (code: {poll_response.error.code})")
|
||||
|
||||
response = poll_response.response
|
||||
filtered_count = response.raiMediaFilteredCount
|
||||
if filtered_count:
|
||||
reasons = response.raiMediaFilteredReasons or []
|
||||
reason_part = f": {reasons[0]}" if reasons else ""
|
||||
raise Exception(
|
||||
f"Content blocked by Google's Responsible AI filters{reason_part} "
|
||||
f"({filtered_count} video{'s' if filtered_count != 1 else ''} filtered)."
|
||||
)
|
||||
|
||||
if response.videos:
|
||||
video = response.videos[0]
|
||||
if video.bytesBase64Encoded:
|
||||
return IO.NodeOutput(InputImpl.VideoFromFile(BytesIO(base64.b64decode(video.bytesBase64Encoded))))
|
||||
if video.gcsUri:
|
||||
return IO.NodeOutput(await download_url_to_video_output(video.gcsUri))
|
||||
raise Exception("Video returned but no data or URL was provided")
|
||||
raise Exception("Video generation completed but no video was returned")
|
||||
|
||||
|
||||
class Veo3FirstLastFrameNode(IO.ComfyNode):
|
||||
|
||||
@@ -483,7 +394,7 @@ class Veo3FirstLastFrameNode(IO.ComfyNode):
|
||||
default="",
|
||||
tooltip="Negative text prompt to guide what to avoid in the video",
|
||||
),
|
||||
IO.Combo.Input("resolution", options=["720p", "1080p", "4k"]),
|
||||
IO.Combo.Input("resolution", options=["720p", "1080p"]),
|
||||
IO.Combo.Input(
|
||||
"aspect_ratio",
|
||||
options=["16:9", "9:16"],
|
||||
@@ -513,7 +424,8 @@ class Veo3FirstLastFrameNode(IO.ComfyNode):
|
||||
IO.Image.Input("last_frame", tooltip="End frame"),
|
||||
IO.Combo.Input(
|
||||
"model",
|
||||
options=["veo-3.1-generate", "veo-3.1-fast-generate", "veo-3.1-lite"],
|
||||
options=["veo-3.1-generate", "veo-3.1-fast-generate"],
|
||||
default="veo-3.1-fast-generate",
|
||||
),
|
||||
IO.Boolean.Input(
|
||||
"generate_audio",
|
||||
@@ -531,20 +443,26 @@ class Veo3FirstLastFrameNode(IO.ComfyNode):
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
depends_on=IO.PriceBadgeDepends(widgets=["model", "generate_audio", "duration", "resolution"]),
|
||||
depends_on=IO.PriceBadgeDepends(widgets=["model", "generate_audio", "duration"]),
|
||||
expr="""
|
||||
(
|
||||
$prices := {
|
||||
"veo-3.1-fast-generate": { "audio": 0.15, "no_audio": 0.10 },
|
||||
"veo-3.1-generate": { "audio": 0.40, "no_audio": 0.20 }
|
||||
};
|
||||
$m := widgets.model;
|
||||
$r := widgets.resolution;
|
||||
$ga := widgets.generate_audio;
|
||||
$ga := (widgets.generate_audio = "true");
|
||||
$seconds := widgets.duration;
|
||||
$pps :=
|
||||
$contains($m, "lite")
|
||||
? ($r = "1080p" ? ($ga ? 0.08 : 0.05) : ($ga ? 0.05 : 0.03))
|
||||
: $contains($m, "fast")
|
||||
? ($r = "4k" ? ($ga ? 0.30 : 0.25) : $r = "1080p" ? ($ga ? 0.12 : 0.10) : ($ga ? 0.10 : 0.08))
|
||||
: ($r = "4k" ? ($ga ? 0.60 : 0.40) : ($ga ? 0.40 : 0.20));
|
||||
{"type":"usd","usd": $pps * $seconds}
|
||||
$modelKey :=
|
||||
$contains($m, "veo-3.1-fast-generate") ? "veo-3.1-fast-generate" :
|
||||
$contains($m, "veo-3.1-generate") ? "veo-3.1-generate" :
|
||||
"";
|
||||
$audioKey := $ga ? "audio" : "no_audio";
|
||||
$modelPrices := $lookup($prices, $modelKey);
|
||||
$pps := $lookup($modelPrices, $audioKey);
|
||||
($pps != null)
|
||||
? {"type":"usd","usd": $pps * $seconds}
|
||||
: {"type":"range_usd","min_usd": 0.4, "max_usd": 3.2}
|
||||
)
|
||||
""",
|
||||
),
|
||||
@@ -564,9 +482,6 @@ class Veo3FirstLastFrameNode(IO.ComfyNode):
|
||||
model: str,
|
||||
generate_audio: bool,
|
||||
):
|
||||
if "lite" in model and resolution == "4k":
|
||||
raise Exception("4K resolution is not supported by the veo-3.1-lite model.")
|
||||
|
||||
model = MODELS_MAP[model]
|
||||
initial_response = await sync_op(
|
||||
cls,
|
||||
|
||||
@@ -80,7 +80,7 @@ class EmptyAceStepLatentAudio(io.ComfyNode):
|
||||
@classmethod
|
||||
def execute(cls, seconds, batch_size) -> io.NodeOutput:
|
||||
length = int(seconds * 44100 / 512 / 8)
|
||||
latent = torch.zeros([batch_size, 8, 16, length], device=comfy.model_management.intermediate_device(), dtype=comfy.model_management.intermediate_dtype())
|
||||
latent = torch.zeros([batch_size, 8, 16, length], device=comfy.model_management.intermediate_device())
|
||||
return io.NodeOutput({"samples": latent, "type": "audio"})
|
||||
|
||||
|
||||
@@ -103,7 +103,7 @@ class EmptyAceStep15LatentAudio(io.ComfyNode):
|
||||
@classmethod
|
||||
def execute(cls, seconds, batch_size) -> io.NodeOutput:
|
||||
length = round((seconds * 48000 / 1920))
|
||||
latent = torch.zeros([batch_size, 64, length], device=comfy.model_management.intermediate_device(), dtype=comfy.model_management.intermediate_dtype())
|
||||
latent = torch.zeros([batch_size, 64, length], device=comfy.model_management.intermediate_device())
|
||||
return io.NodeOutput({"samples": latent, "type": "audio"})
|
||||
|
||||
class ReferenceAudio(io.ComfyNode):
|
||||
|
||||
Reference in New Issue
Block a user