File size: 7,271 Bytes
5de606a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 | from io import BytesIO
from pydantic import BaseModel, Field
from typing_extensions import override
from comfy_api.latest import IO, ComfyExtension, Input, InputImpl
from comfy_api_nodes.util import (
ApiEndpoint,
get_number_of_images,
sync_op_raw,
upload_images_to_comfyapi,
validate_string,
)
MODELS_MAP = {
"LTX-2 (Pro)": "ltx-2-pro",
"LTX-2 (Fast)": "ltx-2-fast",
}
class ExecuteTaskRequest(BaseModel):
prompt: str = Field(...)
model: str = Field(...)
duration: int = Field(...)
resolution: str = Field(...)
fps: int | None = Field(25)
generate_audio: bool | None = Field(True)
image_uri: str | None = Field(None)
PRICE_BADGE = IO.PriceBadge(
depends_on=IO.PriceBadgeDepends(widgets=["model", "duration", "resolution"]),
expr="""
(
$prices := {
"ltx-2 (pro)": {"1920x1080":0.06,"2560x1440":0.12,"3840x2160":0.24},
"ltx-2 (fast)": {"1920x1080":0.04,"2560x1440":0.08,"3840x2160":0.16}
};
$modelPrices := $lookup($prices, $lowercase(widgets.model));
$pps := $lookup($modelPrices, widgets.resolution);
{"type":"usd","usd": $pps * widgets.duration}
)
""",
)
class TextToVideoNode(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="LtxvApiTextToVideo",
display_name="LTXV Text To Video",
category="partner/video/LTXV",
description="Professional-quality videos with customizable duration and resolution.",
inputs=[
IO.Combo.Input("model", options=list(MODELS_MAP.keys())),
IO.String.Input(
"prompt",
multiline=True,
default="",
),
IO.Combo.Input("duration", options=[6, 8, 10, 12, 14, 16, 18, 20], default=8),
IO.Combo.Input(
"resolution",
options=[
"1920x1080",
"2560x1440",
"3840x2160",
],
),
IO.Combo.Input("fps", options=[25, 50], default=25),
IO.Boolean.Input(
"generate_audio",
default=False,
optional=True,
tooltip="When true, the generated video will include AI-generated audio matching the scene.",
advanced=True,
),
],
outputs=[
IO.Video.Output(),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=PRICE_BADGE,
)
@classmethod
async def execute(
cls,
model: str,
prompt: str,
duration: int,
resolution: str,
fps: int = 25,
generate_audio: bool = False,
) -> IO.NodeOutput:
validate_string(prompt, min_length=1, max_length=10000)
if duration > 10 and (model != "LTX-2 (Fast)" or resolution != "1920x1080" or fps != 25):
raise ValueError(
"Durations over 10s are only available for the Fast model at 1920x1080 resolution and 25 FPS."
)
response = await sync_op_raw(
cls,
ApiEndpoint("/proxy/ltx/v1/text-to-video", "POST"),
data=ExecuteTaskRequest(
prompt=prompt,
model=MODELS_MAP[model],
duration=duration,
resolution=resolution,
fps=fps,
generate_audio=generate_audio,
),
as_binary=True,
max_retries=1,
)
return IO.NodeOutput(InputImpl.VideoFromFile(BytesIO(response)))
class ImageToVideoNode(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="LtxvApiImageToVideo",
display_name="LTXV Image To Video",
category="partner/video/LTXV",
description="Professional-quality videos with customizable duration and resolution based on start image.",
inputs=[
IO.Image.Input("image", tooltip="First frame to be used for the video."),
IO.Combo.Input("model", options=list(MODELS_MAP.keys())),
IO.String.Input(
"prompt",
multiline=True,
default="",
),
IO.Combo.Input("duration", options=[6, 8, 10, 12, 14, 16, 18, 20], default=8),
IO.Combo.Input(
"resolution",
options=[
"1920x1080",
"2560x1440",
"3840x2160",
],
),
IO.Combo.Input("fps", options=[25, 50], default=25),
IO.Boolean.Input(
"generate_audio",
default=False,
optional=True,
tooltip="When true, the generated video will include AI-generated audio matching the scene.",
advanced=True,
),
],
outputs=[
IO.Video.Output(),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=PRICE_BADGE,
)
@classmethod
async def execute(
cls,
image: Input.Image,
model: str,
prompt: str,
duration: int,
resolution: str,
fps: int = 25,
generate_audio: bool = False,
) -> IO.NodeOutput:
validate_string(prompt, min_length=1, max_length=10000)
if duration > 10 and (model != "LTX-2 (Fast)" or resolution != "1920x1080" or fps != 25):
raise ValueError(
"Durations over 10s are only available for the Fast model at 1920x1080 resolution and 25 FPS."
)
if get_number_of_images(image) != 1:
raise ValueError("Currently only one input image is supported.")
response = await sync_op_raw(
cls,
ApiEndpoint("/proxy/ltx/v1/image-to-video", "POST"),
data=ExecuteTaskRequest(
image_uri=(await upload_images_to_comfyapi(cls, image, max_images=1, mime_type="image/png"))[0],
prompt=prompt,
model=MODELS_MAP[model],
duration=duration,
resolution=resolution,
fps=fps,
generate_audio=generate_audio,
),
as_binary=True,
max_retries=1,
)
return IO.NodeOutput(InputImpl.VideoFromFile(BytesIO(response)))
class LtxvApiExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
return [
TextToVideoNode,
ImageToVideoNode,
]
async def comfy_entrypoint() -> LtxvApiExtension:
return LtxvApiExtension()
|