ComfyUI/comfy_api_nodes/nodes_quiver.py
2026-03-20 12:23:16 -07:00

292 lines
11 KiB
Python

from io import BytesIO
from typing_extensions import override
from comfy_api.latest import IO, ComfyExtension
from comfy_api_nodes.apis.quiver import (
QuiverImageObject,
QuiverImageToSVGRequest,
QuiverSVGResponse,
QuiverTextToSVGRequest,
)
from comfy_api_nodes.util import (
ApiEndpoint,
sync_op,
upload_image_to_comfyapi,
validate_string,
)
from comfy_extras.nodes_images import SVG
class QuiverTextToSVGNode(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="QuiverTextToSVGNode",
display_name="Quiver Text to SVG",
category="api node/image/Quiver",
description="Generate an SVG from a text prompt using Quiver AI.",
inputs=[
IO.String.Input(
"prompt",
multiline=True,
default="",
tooltip="Text description of the desired SVG output.",
),
IO.String.Input(
"instructions",
multiline=True,
default="",
tooltip="Additional style or formatting guidance.",
optional=True,
),
IO.Autogrow.Input(
"reference_images",
template=IO.Autogrow.TemplatePrefix(
IO.Image.Input("image"),
prefix="ref_",
min=0,
max=4,
),
tooltip="Up to 4 reference images to guide the generation.",
optional=True,
),
IO.DynamicCombo.Input(
"model",
options=[
IO.DynamicCombo.Option(
"arrow-preview",
[
IO.Float.Input(
"temperature",
default=1.0,
min=0.0,
max=2.0,
step=0.1,
display_mode=IO.NumberDisplay.slider,
tooltip="Randomness control. Higher values increase randomness.",
advanced=True,
),
IO.Float.Input(
"top_p",
default=1.0,
min=0.05,
max=1.0,
step=0.05,
display_mode=IO.NumberDisplay.slider,
tooltip="Nucleus sampling parameter.",
advanced=True,
),
IO.Float.Input(
"presence_penalty",
default=0.0,
min=-2.0,
max=2.0,
step=0.1,
display_mode=IO.NumberDisplay.slider,
tooltip="Token presence penalty.",
advanced=True,
),
],
),
],
tooltip="Model to use for SVG generation.",
),
IO.Int.Input(
"seed",
default=0,
min=0,
max=2147483647,
control_after_generate=True,
tooltip="Seed to determine if node should re-run; "
"actual results are nondeterministic regardless of seed.",
),
],
outputs=[
IO.SVG.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(
expr="""{"type":"usd","usd":0.429}""",
),
)
@classmethod
async def execute(
cls,
prompt: str,
model: dict,
seed: int,
instructions: str = None,
reference_images: IO.Autogrow.Type = None,
) -> IO.NodeOutput:
validate_string(prompt, strip_whitespace=False, min_length=1)
references = None
if reference_images:
references = []
for key in reference_images:
url = await upload_image_to_comfyapi(cls, reference_images[key])
references.append(QuiverImageObject(url=url))
if len(references) > 4:
raise ValueError("Maximum 4 reference images are allowed.")
instructions_val = instructions.strip() if instructions else None
if instructions_val == "":
instructions_val = None
response = await sync_op(
cls,
ApiEndpoint(path="/proxy/quiver/v1/svgs/generations", method="POST"),
response_model=QuiverSVGResponse,
data=QuiverTextToSVGRequest(
model=model["model"],
prompt=prompt,
instructions=instructions_val,
references=references,
temperature=model.get("temperature"),
top_p=model.get("top_p"),
presence_penalty=model.get("presence_penalty"),
),
)
svg_data = [BytesIO(item.svg.encode("utf-8")) for item in response.data]
return IO.NodeOutput(SVG(svg_data))
class QuiverImageToSVGNode(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="QuiverImageToSVGNode",
display_name="Quiver Image to SVG",
category="api node/image/Quiver",
description="Vectorize a raster image into SVG using Quiver AI.",
inputs=[
IO.Image.Input(
"image",
tooltip="Input image to vectorize.",
),
IO.Boolean.Input(
"auto_crop",
default=False,
tooltip="Automatically crop to the dominant subject.",
),
IO.DynamicCombo.Input(
"model",
options=[
IO.DynamicCombo.Option(
"arrow-preview",
[
IO.Int.Input(
"target_size",
default=1024,
min=128,
max=4096,
tooltip="Square resize target in pixels.",
),
IO.Float.Input(
"temperature",
default=1.0,
min=0.0,
max=2.0,
step=0.1,
display_mode=IO.NumberDisplay.slider,
tooltip="Randomness control. Higher values increase randomness.",
advanced=True,
),
IO.Float.Input(
"top_p",
default=1.0,
min=0.05,
max=1.0,
step=0.05,
display_mode=IO.NumberDisplay.slider,
tooltip="Nucleus sampling parameter.",
advanced=True,
),
IO.Float.Input(
"presence_penalty",
default=0.0,
min=-2.0,
max=2.0,
step=0.1,
display_mode=IO.NumberDisplay.slider,
tooltip="Token presence penalty.",
advanced=True,
),
],
),
],
tooltip="Model to use for SVG vectorization.",
),
IO.Int.Input(
"seed",
default=0,
min=0,
max=2147483647,
control_after_generate=True,
tooltip="Seed to determine if node should re-run; "
"actual results are nondeterministic regardless of seed.",
),
],
outputs=[
IO.SVG.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(
expr="""{"type":"usd","usd":0.429}""",
),
)
@classmethod
async def execute(
cls,
image,
auto_crop: bool,
model: dict,
seed: int,
) -> IO.NodeOutput:
image_url = await upload_image_to_comfyapi(cls, image)
response = await sync_op(
cls,
ApiEndpoint(path="/proxy/quiver/v1/svgs/vectorizations", method="POST"),
response_model=QuiverSVGResponse,
data=QuiverImageToSVGRequest(
model=model["model"],
image=QuiverImageObject(url=image_url),
auto_crop=auto_crop if auto_crop else None,
target_size=model.get("target_size"),
temperature=model.get("temperature"),
top_p=model.get("top_p"),
presence_penalty=model.get("presence_penalty"),
),
)
svg_data = [BytesIO(item.svg.encode("utf-8")) for item in response.data]
return IO.NodeOutput(SVG(svg_data))
class QuiverExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
return [
QuiverTextToSVGNode,
QuiverImageToSVGNode,
]
async def comfy_entrypoint() -> QuiverExtension:
return QuiverExtension()