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feat(api-nodes): network client v2: async ops, cancellation, downloads, refactor (#10390)

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* feat(api-nodes): implement new API client for V3 nodes

* feat(api-nodes): implement new API client for V3 nodes

* feat(api-nodes): implement new API client for V3 nodes

* converted WAN nodes to use new client; polishing

* fix(auth): do not leak authentification for the absolute urls

* convert BFL API nodes to use new API client; remove deprecated BFL nodes

* converted Google Veo nodes

* fix(Veo3.1 model): take into account "generate_audio" parameter
This commit is contained in:
Alexander Piskun
2025-10-24 08:37:16 +03:00
committed by GitHub
parent 24188b3141
commit 388b306a2b
29 changed files with 2935 additions and 2298 deletions
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199
comfy_api_nodes/nodes_runway.py
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@@ -11,7 +11,7 @@ User Guides:
"""
from typing import Union, Optional, Any
from typing import Union, Optional
from typing_extensions import override
from enum import Enum
@@ -21,7 +21,6 @@ from comfy_api_nodes.apis import (
RunwayImageToVideoRequest,
RunwayImageToVideoResponse,
RunwayTaskStatusResponse as TaskStatusResponse,
RunwayTaskStatusEnum as TaskStatus,
RunwayModelEnum as Model,
RunwayDurationEnum as Duration,
RunwayAspectRatioEnum as AspectRatio,
@@ -33,23 +32,20 @@ from comfy_api_nodes.apis import (
ReferenceImage,
RunwayTextToImageAspectRatioEnum,
)
from comfy_api_nodes.apis.client import (
ApiEndpoint,
HttpMethod,
SynchronousOperation,
PollingOperation,
EmptyRequest,
)
from comfy_api_nodes.apinode_utils import (
upload_images_to_comfyapi,
download_url_to_video_output,
from comfy_api_nodes.util import (
image_tensor_pair_to_batch,
validate_string,
validate_image_dimensions,
validate_image_aspect_ratio,
upload_images_to_comfyapi,
download_url_to_video_output,
download_url_to_image_tensor,
ApiEndpoint,
sync_op,
poll_op,
)
from comfy_api.input_impl import VideoFromFile
from comfy_api.latest import ComfyExtension, IO
from comfy_api_nodes.util.validation_utils import validate_image_dimensions, validate_image_aspect_ratio
PATH_IMAGE_TO_VIDEO = "/proxy/runway/image_to_video"
PATH_TEXT_TO_IMAGE = "/proxy/runway/text_to_image"
@@ -91,31 +87,6 @@ def get_video_url_from_task_status(response: TaskStatusResponse) -> Union[str, N
return None
async def poll_until_finished(
auth_kwargs: dict[str, str],
api_endpoint: ApiEndpoint[Any, TaskStatusResponse],
estimated_duration: Optional[int] = None,
node_id: Optional[str] = None,
) -> TaskStatusResponse:
"""Polls the Runway API endpoint until the task reaches a terminal state, then returns the response."""
return await PollingOperation(
poll_endpoint=api_endpoint,
completed_statuses=[
TaskStatus.SUCCEEDED.value,
],
failed_statuses=[
TaskStatus.FAILED.value,
TaskStatus.CANCELLED.value,
],
status_extractor=lambda response: response.status.value,
auth_kwargs=auth_kwargs,
result_url_extractor=get_video_url_from_task_status,
estimated_duration=estimated_duration,
node_id=node_id,
progress_extractor=extract_progress_from_task_status,
).execute()
def extract_progress_from_task_status(
response: TaskStatusResponse,
) -> Union[float, None]:
@@ -132,42 +103,32 @@ def get_image_url_from_task_status(response: TaskStatusResponse) -> Union[str, N
async def get_response(
task_id: str, auth_kwargs: dict[str, str], node_id: Optional[str] = None, estimated_duration: Optional[int] = None
cls: type[IO.ComfyNode], task_id: str, estimated_duration: Optional[int] = None
) -> TaskStatusResponse:
"""Poll the task status until it is finished then get the response."""
return await poll_until_finished(
auth_kwargs,
ApiEndpoint(
path=f"{PATH_GET_TASK_STATUS}/{task_id}",
method=HttpMethod.GET,
request_model=EmptyRequest,
response_model=TaskStatusResponse,
),
return await poll_op(
cls,
ApiEndpoint(path=f"{PATH_GET_TASK_STATUS}/{task_id}"),
response_model=TaskStatusResponse,
status_extractor=lambda r: r.status.value,
estimated_duration=estimated_duration,
node_id=node_id,
progress_extractor=extract_progress_from_task_status,
)
async def generate_video(
cls: type[IO.ComfyNode],
request: RunwayImageToVideoRequest,
auth_kwargs: dict[str, str],
node_id: Optional[str] = None,
estimated_duration: Optional[int] = None,
) -> VideoFromFile:
initial_operation = SynchronousOperation(
endpoint=ApiEndpoint(
path=PATH_IMAGE_TO_VIDEO,
method=HttpMethod.POST,
request_model=RunwayImageToVideoRequest,
response_model=RunwayImageToVideoResponse,
),
request=request,
auth_kwargs=auth_kwargs,
initial_response = await sync_op(
cls,
endpoint=ApiEndpoint(path=PATH_IMAGE_TO_VIDEO, method="POST"),
response_model=RunwayImageToVideoResponse,
data=request,
)
initial_response = await initial_operation.execute()
final_response = await get_response(initial_response.id, auth_kwargs, node_id, estimated_duration)
final_response = await get_response(cls, initial_response.id, estimated_duration)
if not final_response.output:
raise RunwayApiError("Runway task succeeded but no video data found in response.")
@@ -184,9 +145,9 @@ class RunwayImageToVideoNodeGen3a(IO.ComfyNode):
display_name="Runway Image to Video (Gen3a Turbo)",
category="api node/video/Runway",
description="Generate a video from a single starting frame using Gen3a Turbo model. "
"Before diving in, review these best practices to ensure that "
"your input selections will set your generation up for success: "
"https://help.runwayml.com/hc/en-us/articles/33927968552339-Creating-with-Act-One-on-Gen-3-Alpha-and-Turbo.",
"Before diving in, review these best practices to ensure that "
"your input selections will set your generation up for success: "
"https://help.runwayml.com/hc/en-us/articles/33927968552339-Creating-with-Act-One-on-Gen-3-Alpha-and-Turbo.",
inputs=[
IO.String.Input(
"prompt",
@@ -241,20 +202,16 @@ class RunwayImageToVideoNodeGen3a(IO.ComfyNode):
validate_image_dimensions(start_frame, max_width=7999, max_height=7999)
validate_image_aspect_ratio(start_frame, min_aspect_ratio=0.5, max_aspect_ratio=2.0)
auth_kwargs = {
"auth_token": cls.hidden.auth_token_comfy_org,
"comfy_api_key": cls.hidden.api_key_comfy_org,
}
download_urls = await upload_images_to_comfyapi(
cls,
start_frame,
max_images=1,
mime_type="image/png",
auth_kwargs=auth_kwargs,
)
return IO.NodeOutput(
await generate_video(
cls,
RunwayImageToVideoRequest(
promptText=prompt,
seed=seed,
@@ -262,15 +219,9 @@ class RunwayImageToVideoNodeGen3a(IO.ComfyNode):
duration=Duration(duration),
ratio=AspectRatio(ratio),
promptImage=RunwayPromptImageObject(
root=[
RunwayPromptImageDetailedObject(
uri=str(download_urls[0]), position="first"
)
]
root=[RunwayPromptImageDetailedObject(uri=str(download_urls[0]), position="first")]
),
),
auth_kwargs=auth_kwargs,
node_id=cls.hidden.unique_id,
)
)
@@ -284,9 +235,9 @@ class RunwayImageToVideoNodeGen4(IO.ComfyNode):
display_name="Runway Image to Video (Gen4 Turbo)",
category="api node/video/Runway",
description="Generate a video from a single starting frame using Gen4 Turbo model. "
"Before diving in, review these best practices to ensure that "
"your input selections will set your generation up for success: "
"https://help.runwayml.com/hc/en-us/articles/37327109429011-Creating-with-Gen-4-Video.",
"Before diving in, review these best practices to ensure that "
"your input selections will set your generation up for success: "
"https://help.runwayml.com/hc/en-us/articles/37327109429011-Creating-with-Gen-4-Video.",
inputs=[
IO.String.Input(
"prompt",
@@ -341,20 +292,16 @@ class RunwayImageToVideoNodeGen4(IO.ComfyNode):
validate_image_dimensions(start_frame, max_width=7999, max_height=7999)
validate_image_aspect_ratio(start_frame, min_aspect_ratio=0.5, max_aspect_ratio=2.0)
auth_kwargs = {
"auth_token": cls.hidden.auth_token_comfy_org,
"comfy_api_key": cls.hidden.api_key_comfy_org,
}
download_urls = await upload_images_to_comfyapi(
cls,
start_frame,
max_images=1,
mime_type="image/png",
auth_kwargs=auth_kwargs,
)
return IO.NodeOutput(
await generate_video(
cls,
RunwayImageToVideoRequest(
promptText=prompt,
seed=seed,
@@ -362,15 +309,9 @@ class RunwayImageToVideoNodeGen4(IO.ComfyNode):
duration=Duration(duration),
ratio=AspectRatio(ratio),
promptImage=RunwayPromptImageObject(
root=[
RunwayPromptImageDetailedObject(
uri=str(download_urls[0]), position="first"
)
]
root=[RunwayPromptImageDetailedObject(uri=str(download_urls[0]), position="first")]
),
),
auth_kwargs=auth_kwargs,
node_id=cls.hidden.unique_id,
estimated_duration=AVERAGE_DURATION_FLF_SECONDS,
)
)
@@ -385,12 +326,12 @@ class RunwayFirstLastFrameNode(IO.ComfyNode):
display_name="Runway First-Last-Frame to Video",
category="api node/video/Runway",
description="Upload first and last keyframes, draft a prompt, and generate a video. "
"More complex transitions, such as cases where the Last frame is completely different "
"from the First frame, may benefit from the longer 10s duration. "
"This would give the generation more time to smoothly transition between the two inputs. "
"Before diving in, review these best practices to ensure that your input selections "
"will set your generation up for success: "
"https://help.runwayml.com/hc/en-us/articles/34170748696595-Creating-with-Keyframes-on-Gen-3.",
"More complex transitions, such as cases where the Last frame is completely different "
"from the First frame, may benefit from the longer 10s duration. "
"This would give the generation more time to smoothly transition between the two inputs. "
"Before diving in, review these best practices to ensure that your input selections "
"will set your generation up for success: "
"https://help.runwayml.com/hc/en-us/articles/34170748696595-Creating-with-Keyframes-on-Gen-3.",
inputs=[
IO.String.Input(
"prompt",
@@ -452,23 +393,19 @@ class RunwayFirstLastFrameNode(IO.ComfyNode):
validate_image_aspect_ratio(start_frame, min_aspect_ratio=0.5, max_aspect_ratio=2.0)
validate_image_aspect_ratio(end_frame, min_aspect_ratio=0.5, max_aspect_ratio=2.0)
auth_kwargs = {
"auth_token": cls.hidden.auth_token_comfy_org,
"comfy_api_key": cls.hidden.api_key_comfy_org,
}
stacked_input_images = image_tensor_pair_to_batch(start_frame, end_frame)
download_urls = await upload_images_to_comfyapi(
cls,
stacked_input_images,
max_images=2,
mime_type="image/png",
auth_kwargs=auth_kwargs,
)
if len(download_urls) != 2:
raise RunwayApiError("Failed to upload one or more images to comfy api.")
return IO.NodeOutput(
await generate_video(
cls,
RunwayImageToVideoRequest(
promptText=prompt,
seed=seed,
@@ -477,17 +414,11 @@ class RunwayFirstLastFrameNode(IO.ComfyNode):
ratio=AspectRatio(ratio),
promptImage=RunwayPromptImageObject(
root=[
RunwayPromptImageDetailedObject(
uri=str(download_urls[0]), position="first"
),
RunwayPromptImageDetailedObject(
uri=str(download_urls[1]), position="last"
),
RunwayPromptImageDetailedObject(uri=str(download_urls[0]), position="first"),
RunwayPromptImageDetailedObject(uri=str(download_urls[1]), position="last"),
]
),
),
auth_kwargs=auth_kwargs,
node_id=cls.hidden.unique_id,
estimated_duration=AVERAGE_DURATION_FLF_SECONDS,
)
)
@@ -502,7 +433,7 @@ class RunwayTextToImageNode(IO.ComfyNode):
display_name="Runway Text to Image",
category="api node/image/Runway",
description="Generate an image from a text prompt using Runway's Gen 4 model. "
"You can also include reference image to guide the generation.",
"You can also include reference image to guide the generation.",
inputs=[
IO.String.Input(
"prompt",
@@ -540,49 +471,34 @@ class RunwayTextToImageNode(IO.ComfyNode):
) -> IO.NodeOutput:
validate_string(prompt, min_length=1)
auth_kwargs = {
"auth_token": cls.hidden.auth_token_comfy_org,
"comfy_api_key": cls.hidden.api_key_comfy_org,
}
# Prepare reference images if provided
reference_images = None
if reference_image is not None:
validate_image_dimensions(reference_image, max_width=7999, max_height=7999)
validate_image_aspect_ratio(reference_image, min_aspect_ratio=0.5, max_aspect_ratio=2.0)
download_urls = await upload_images_to_comfyapi(
cls,
reference_image,
max_images=1,
mime_type="image/png",
auth_kwargs=auth_kwargs,
)
reference_images = [ReferenceImage(uri=str(download_urls[0]))]
request = RunwayTextToImageRequest(
promptText=prompt,
model=Model4.gen4_image,
ratio=ratio,
referenceImages=reference_images,
)
initial_operation = SynchronousOperation(
endpoint=ApiEndpoint(
path=PATH_TEXT_TO_IMAGE,
method=HttpMethod.POST,
request_model=RunwayTextToImageRequest,
response_model=RunwayTextToImageResponse,
initial_response = await sync_op(
cls,
endpoint=ApiEndpoint(path=PATH_TEXT_TO_IMAGE, method="POST"),
response_model=RunwayTextToImageResponse,
data=RunwayTextToImageRequest(
promptText=prompt,
model=Model4.gen4_image,
ratio=ratio,
referenceImages=reference_images,
),
request=request,
auth_kwargs=auth_kwargs,
)
initial_response = await initial_operation.execute()
# Poll for completion
final_response = await get_response(
cls,
initial_response.id,
auth_kwargs=auth_kwargs,
node_id=cls.hidden.unique_id,
estimated_duration=AVERAGE_DURATION_T2I_SECONDS,
)
if not final_response.output:
@@ -601,5 +517,6 @@ class RunwayExtension(ComfyExtension):
RunwayTextToImageNode,
]
async def comfy_entrypoint() -> RunwayExtension:
return RunwayExtension()