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import torch
from pydantic import BaseModel, Field
from typing_extensions import override
from comfy_api.latest import IO, ComfyExtension
from comfy_api_nodes.util import (
ApiEndpoint,
download_url_to_video_output,
get_number_of_images,
poll_op,
sync_op,
tensor_to_bytesio,
)
class Sora2GenerationRequest(BaseModel):
prompt: str = Field(...)
model: str = Field(...)
seconds: str = Field(...)
size: str = Field(...)
class Sora2GenerationResponse(BaseModel):
id: str = Field(...)
error: Optional[dict] = Field(None)
status: Optional[str] = Field(None)
class OpenAIVideoSora2(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="OpenAIVideoSora2",
display_name="OpenAI Sora - Video",
category="api node/video/Sora",
description="OpenAI video and audio generation.",
inputs=[
IO.Combo.Input(
"model",
options=["sora-2", "sora-2-pro"],
default="sora-2",
),
IO.String.Input(
"prompt",
multiline=True,
default="",
tooltip="Guiding text; may be empty if an input image is present.",
),
IO.Combo.Input(
"size",
options=[
"720x1280",
"1280x720",
"1024x1792",
"1792x1024",
],
default="1280x720",
),
IO.Combo.Input(
"duration",
options=[4, 8, 12],
default=8,
),
IO.Image.Input(
"image",
optional=True,
),
IO.Int.Input(
"seed",
default=0,
min=0,
max=2147483647,
step=1,
display_mode=IO.NumberDisplay.number,
control_after_generate=True,
optional=True,
tooltip="Seed to determine if node should re-run; "
"actual results are nondeterministic regardless of seed.",
),
],
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=IO.PriceBadge(
depends_on=IO.PriceBadgeDepends(widgets=["model", "size", "duration"]),
expr="""
(
$m := widgets.model;
$size := widgets.size;
$dur := widgets.duration;
$isPro := $contains($m, "sora-2-pro");
$isSora2 := $contains($m, "sora-2");
$isProSize := ($size = "1024x1792" or $size = "1792x1024");
$perSec :=
$isPro ? ($isProSize ? 0.5 : 0.3) :
$isSora2 ? 0.1 :
($isProSize ? 0.5 : 0.1);
{"type":"usd","usd": $round($perSec * $dur, 2)}
)
""",
),
)
@classmethod
async def execute(
cls,
model: str,
prompt: str,
size: str = "1280x720",
duration: int = 8,
seed: int = 0,
image: Optional[torch.Tensor] = None,
):
if model == "sora-2" and size not in ("720x1280", "1280x720"):
raise ValueError("Invalid size for sora-2 model, only 720x1280 and 1280x720 are supported.")
files_input = None
if image is not None:
if get_number_of_images(image) != 1:
raise ValueError("Currently only one input image is supported.")
files_input = {"input_reference": ("image.png", tensor_to_bytesio(image), "image/png")}
initial_response = await sync_op(
cls,
endpoint=ApiEndpoint(path="/proxy/openai/v1/videos", method="POST"),
data=Sora2GenerationRequest(
model=model,
prompt=prompt,
seconds=str(duration),
size=size,
),
files=files_input,
response_model=Sora2GenerationResponse,
content_type="multipart/form-data",
)
if initial_response.error:
raise Exception(initial_response.error["message"])
model_time_multiplier = 1 if model == "sora-2" else 2
await poll_op(
cls,
poll_endpoint=ApiEndpoint(path=f"/proxy/openai/v1/videos/{initial_response.id}"),
response_model=Sora2GenerationResponse,
status_extractor=lambda x: x.status,
poll_interval=8.0,
estimated_duration=int(45 * (duration / 4) * model_time_multiplier),
)
return IO.NodeOutput(
await download_url_to_video_output(f"/proxy/openai/v1/videos/{initial_response.id}/content", cls=cls),
)
class OpenAISoraExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
return [
OpenAIVideoSora2,
]
async def comfy_entrypoint() -> OpenAISoraExtension:
return OpenAISoraExtension()
|