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chore(api-nodes): remove non-used; extract model to separate files (#11927)

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* chore(api-nodes): remove non-used; extract model to separate files

* chore(api-nodes): remove non-needed prefix in filenames
This commit is contained in:
Alexander Piskun
2026-01-18 04:52:45 +02:00
committed by GitHub
parent 190c4416cc
commit ac26065e61
40 changed files with 825 additions and 641 deletions
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55
comfy_api_nodes/nodes_topaz.py
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@@ -5,7 +5,24 @@ import aiohttp
from typing_extensions import override
from comfy_api.latest import IO, ComfyExtension, Input
from comfy_api_nodes.apis import topaz_api
from comfy_api_nodes.apis.topaz import (
CreateVideoRequest,
CreateVideoRequestSource,
CreateVideoResponse,
ImageAsyncTaskResponse,
ImageDownloadResponse,
ImageEnhanceRequest,
ImageStatusResponse,
OutputInformationVideo,
Resolution,
VideoAcceptResponse,
VideoCompleteUploadRequest,
VideoCompleteUploadRequestPart,
VideoCompleteUploadResponse,
VideoEnhancementFilter,
VideoFrameInterpolationFilter,
VideoStatusResponse,
)
from comfy_api_nodes.util import (
ApiEndpoint,
download_url_to_image_tensor,
@@ -153,13 +170,13 @@ class TopazImageEnhance(IO.ComfyNode):
if get_number_of_images(image) != 1:
raise ValueError("Only one input image is supported.")
download_url = await upload_images_to_comfyapi(
cls, image, max_images=1, mime_type="image/png", total_pixels=4096*4096
cls, image, max_images=1, mime_type="image/png", total_pixels=4096 * 4096
)
initial_response = await sync_op(
cls,
ApiEndpoint(path="/proxy/topaz/image/v1/enhance-gen/async", method="POST"),
response_model=topaz_api.ImageAsyncTaskResponse,
data=topaz_api.ImageEnhanceRequest(
response_model=ImageAsyncTaskResponse,
data=ImageEnhanceRequest(
model=model,
prompt=prompt,
subject_detection=subject_detection,
@@ -181,7 +198,7 @@ class TopazImageEnhance(IO.ComfyNode):
await poll_op(
cls,
poll_endpoint=ApiEndpoint(path=f"/proxy/topaz/image/v1/status/{initial_response.process_id}"),
response_model=topaz_api.ImageStatusResponse,
response_model=ImageStatusResponse,
status_extractor=lambda x: x.status,
progress_extractor=lambda x: getattr(x, "progress", 0),
price_extractor=lambda x: x.credits * 0.08,
@@ -193,7 +210,7 @@ class TopazImageEnhance(IO.ComfyNode):
results = await sync_op(
cls,
ApiEndpoint(path=f"/proxy/topaz/image/v1/download/{initial_response.process_id}"),
response_model=topaz_api.ImageDownloadResponse,
response_model=ImageDownloadResponse,
monitor_progress=False,
)
return IO.NodeOutput(await download_url_to_image_tensor(results.download_url))
@@ -331,7 +348,7 @@ class TopazVideoEnhance(IO.ComfyNode):
if target_height % 2 != 0:
target_height += 1
filters.append(
topaz_api.VideoEnhancementFilter(
VideoEnhancementFilter(
model=UPSCALER_MODELS_MAP[upscaler_model],
creativity=(upscaler_creativity if UPSCALER_MODELS_MAP[upscaler_model] == "slc-1" else None),
isOptimizedMode=(True if UPSCALER_MODELS_MAP[upscaler_model] == "slc-1" else None),
@@ -340,7 +357,7 @@ class TopazVideoEnhance(IO.ComfyNode):
if interpolation_enabled:
target_frame_rate = interpolation_frame_rate
filters.append(
topaz_api.VideoFrameInterpolationFilter(
VideoFrameInterpolationFilter(
model=interpolation_model,
slowmo=interpolation_slowmo,
fps=interpolation_frame_rate,
@@ -351,19 +368,19 @@ class TopazVideoEnhance(IO.ComfyNode):
initial_res = await sync_op(
cls,
ApiEndpoint(path="/proxy/topaz/video/", method="POST"),
response_model=topaz_api.CreateVideoResponse,
data=topaz_api.CreateVideoRequest(
source=topaz_api.CreateCreateVideoRequestSource(
response_model=CreateVideoResponse,
data=CreateVideoRequest(
source=CreateVideoRequestSource(
container="mp4",
size=get_fs_object_size(src_video_stream),
duration=int(duration_sec),
frameCount=video.get_frame_count(),
frameRate=src_frame_rate,
resolution=topaz_api.Resolution(width=src_width, height=src_height),
resolution=Resolution(width=src_width, height=src_height),
),
filters=filters,
output=topaz_api.OutputInformationVideo(
resolution=topaz_api.Resolution(width=target_width, height=target_height),
output=OutputInformationVideo(
resolution=Resolution(width=target_width, height=target_height),
frameRate=target_frame_rate,
audioCodec="AAC",
audioTransfer="Copy",
@@ -379,7 +396,7 @@ class TopazVideoEnhance(IO.ComfyNode):
path=f"/proxy/topaz/video/{initial_res.requestId}/accept",
method="PATCH",
),
response_model=topaz_api.VideoAcceptResponse,
response_model=VideoAcceptResponse,
wait_label="Preparing upload",
final_label_on_success="Upload started",
)
@@ -402,10 +419,10 @@ class TopazVideoEnhance(IO.ComfyNode):
path=f"/proxy/topaz/video/{initial_res.requestId}/complete-upload",
method="PATCH",
),
response_model=topaz_api.VideoCompleteUploadResponse,
data=topaz_api.VideoCompleteUploadRequest(
response_model=VideoCompleteUploadResponse,
data=VideoCompleteUploadRequest(
uploadResults=[
topaz_api.VideoCompleteUploadRequestPart(
VideoCompleteUploadRequestPart(
partNum=1,
eTag=upload_etag,
),
@@ -417,7 +434,7 @@ class TopazVideoEnhance(IO.ComfyNode):
final_response = await poll_op(
cls,
ApiEndpoint(path=f"/proxy/topaz/video/{initial_res.requestId}/status"),
response_model=topaz_api.VideoStatusResponse,
response_model=VideoStatusResponse,
status_extractor=lambda x: x.status,
progress_extractor=lambda x: getattr(x, "progress", 0),
price_extractor=lambda x: (x.estimates.cost[0] * 0.08 if x.estimates and x.estimates.cost[0] else None),