Instructions to use mhnakif/comfy2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mhnakif/comfy2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mhnakif/comfy2", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
| from typing_extensions import override | |
| from comfy_api.latest import IO, ComfyExtension, Input | |
| from comfy_api_nodes.apis.wavespeed import ( | |
| FlashVSRRequest, | |
| TaskCreatedResponse, | |
| TaskResultResponse, | |
| SeedVR2ImageRequest, | |
| ) | |
| from comfy_api_nodes.util import ( | |
| ApiEndpoint, | |
| download_url_to_video_output, | |
| poll_op, | |
| sync_op, | |
| upload_video_to_comfyapi, | |
| validate_container_format_is_mp4, | |
| validate_video_duration, | |
| upload_images_to_comfyapi, | |
| get_number_of_images, | |
| download_url_to_image_tensor, | |
| ) | |
| class WavespeedFlashVSRNode(IO.ComfyNode): | |
| def define_schema(cls): | |
| return IO.Schema( | |
| node_id="WavespeedFlashVSRNode", | |
| display_name="FlashVSR Video Upscale", | |
| category="api node/video/WaveSpeed", | |
| description="Fast, high-quality video upscaler that " | |
| "boosts resolution and restores clarity for low-resolution or blurry footage.", | |
| inputs=[ | |
| IO.Video.Input("video"), | |
| IO.Combo.Input("target_resolution", options=["720p", "1080p", "2K", "4K"]), | |
| ], | |
| 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=["target_resolution"]), | |
| expr=""" | |
| ( | |
| $price_for_1sec := {"720p": 0.012, "1080p": 0.018, "2k": 0.024, "4k": 0.032}; | |
| { | |
| "type":"usd", | |
| "usd": $lookup($price_for_1sec, widgets.target_resolution), | |
| "format":{"suffix": "/second", "approximate": true} | |
| } | |
| ) | |
| """, | |
| ), | |
| ) | |
| async def execute( | |
| cls, | |
| video: Input.Video, | |
| target_resolution: str, | |
| ) -> IO.NodeOutput: | |
| validate_container_format_is_mp4(video) | |
| validate_video_duration(video, min_duration=5, max_duration=60 * 10) | |
| initial_res = await sync_op( | |
| cls, | |
| ApiEndpoint(path="/proxy/wavespeed/api/v3/wavespeed-ai/flashvsr", method="POST"), | |
| response_model=TaskCreatedResponse, | |
| data=FlashVSRRequest( | |
| target_resolution=target_resolution.lower(), | |
| video=await upload_video_to_comfyapi(cls, video), | |
| duration=video.get_duration(), | |
| ), | |
| ) | |
| if initial_res.code != 200: | |
| raise ValueError(f"Task creation fails with code={initial_res.code} and message={initial_res.message}") | |
| final_response = await poll_op( | |
| cls, | |
| ApiEndpoint(path=f"/proxy/wavespeed/api/v3/predictions/{initial_res.data.id}/result"), | |
| response_model=TaskResultResponse, | |
| status_extractor=lambda x: "failed" if x.data is None else x.data.status, | |
| poll_interval=10.0, | |
| max_poll_attempts=480, | |
| ) | |
| if final_response.code != 200: | |
| raise ValueError( | |
| f"Task processing failed with code={final_response.code} and message={final_response.message}" | |
| ) | |
| return IO.NodeOutput(await download_url_to_video_output(final_response.data.outputs[0])) | |
| class WavespeedImageUpscaleNode(IO.ComfyNode): | |
| def define_schema(cls): | |
| return IO.Schema( | |
| node_id="WavespeedImageUpscaleNode", | |
| display_name="WaveSpeed Image Upscale", | |
| category="api node/image/WaveSpeed", | |
| description="Boost image resolution and quality, upscaling photos to 4K or 8K for sharp, detailed results.", | |
| inputs=[ | |
| IO.Combo.Input("model", options=["SeedVR2", "Ultimate"]), | |
| IO.Image.Input("image"), | |
| IO.Combo.Input("target_resolution", options=["2K", "4K", "8K"]), | |
| ], | |
| outputs=[ | |
| IO.Image.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"]), | |
| expr=""" | |
| ( | |
| $prices := {"seedvr2": 0.01, "ultimate": 0.06}; | |
| {"type":"usd", "usd": $lookup($prices, widgets.model)} | |
| ) | |
| """, | |
| ), | |
| ) | |
| async def execute( | |
| cls, | |
| model: str, | |
| image: Input.Image, | |
| target_resolution: str, | |
| ) -> IO.NodeOutput: | |
| if get_number_of_images(image) != 1: | |
| raise ValueError("Exactly one input image is required.") | |
| if model == "SeedVR2": | |
| model_path = "seedvr2/image" | |
| else: | |
| model_path = "ultimate-image-upscaler" | |
| initial_res = await sync_op( | |
| cls, | |
| ApiEndpoint(path=f"/proxy/wavespeed/api/v3/wavespeed-ai/{model_path}", method="POST"), | |
| response_model=TaskCreatedResponse, | |
| data=SeedVR2ImageRequest( | |
| target_resolution=target_resolution.lower(), | |
| image=(await upload_images_to_comfyapi(cls, image, max_images=1))[0], | |
| ), | |
| ) | |
| if initial_res.code != 200: | |
| raise ValueError(f"Task creation fails with code={initial_res.code} and message={initial_res.message}") | |
| final_response = await poll_op( | |
| cls, | |
| ApiEndpoint(path=f"/proxy/wavespeed/api/v3/predictions/{initial_res.data.id}/result"), | |
| response_model=TaskResultResponse, | |
| status_extractor=lambda x: "failed" if x.data is None else x.data.status, | |
| poll_interval=10.0, | |
| max_poll_attempts=480, | |
| ) | |
| if final_response.code != 200: | |
| raise ValueError( | |
| f"Task processing failed with code={final_response.code} and message={final_response.message}" | |
| ) | |
| return IO.NodeOutput(await download_url_to_image_tensor(final_response.data.outputs[0])) | |
| class WavespeedExtension(ComfyExtension): | |
| async def get_node_list(self) -> list[type[IO.ComfyNode]]: | |
| return [ | |
| WavespeedFlashVSRNode, | |
| WavespeedImageUpscaleNode, | |
| ] | |
| async def comfy_entrypoint() -> WavespeedExtension: | |
| return WavespeedExtension() | |