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"""
Pika x ComfyUI API Nodes
Pika API docs: https://pika-827374fb.mintlify.app/api-reference
"""
from __future__ import annotations
from io import BytesIO
import logging
from typing import Optional, TypeVar
import torch
from typing_extensions import override
from comfy_api.latest import ComfyExtension, IO
from comfy_api.input_impl.video_types import VideoCodec, VideoContainer, VideoInput
from comfy_api_nodes.apis import pika_defs
from comfy_api_nodes.apis.client import (
ApiEndpoint,
EmptyRequest,
HttpMethod,
PollingOperation,
SynchronousOperation,
)
from comfy_api_nodes.util import validate_string, download_url_to_video_output, tensor_to_bytesio
R = TypeVar("R")
PATH_PIKADDITIONS = "/proxy/pika/generate/pikadditions"
PATH_PIKASWAPS = "/proxy/pika/generate/pikaswaps"
PATH_PIKAFFECTS = "/proxy/pika/generate/pikaffects"
PIKA_API_VERSION = "2.2"
PATH_TEXT_TO_VIDEO = f"/proxy/pika/generate/{PIKA_API_VERSION}/t2v"
PATH_IMAGE_TO_VIDEO = f"/proxy/pika/generate/{PIKA_API_VERSION}/i2v"
PATH_PIKAFRAMES = f"/proxy/pika/generate/{PIKA_API_VERSION}/pikaframes"
PATH_PIKASCENES = f"/proxy/pika/generate/{PIKA_API_VERSION}/pikascenes"
PATH_VIDEO_GET = "/proxy/pika/videos"
async def execute_task(
initial_operation: SynchronousOperation[R, pika_defs.PikaGenerateResponse],
auth_kwargs: Optional[dict[str, str]] = None,
node_id: Optional[str] = None,
) -> IO.NodeOutput:
task_id = (await initial_operation.execute()).video_id
final_response: pika_defs.PikaVideoResponse = await PollingOperation(
poll_endpoint=ApiEndpoint(
path=f"{PATH_VIDEO_GET}/{task_id}",
method=HttpMethod.GET,
request_model=EmptyRequest,
response_model=pika_defs.PikaVideoResponse,
),
completed_statuses=["finished"],
failed_statuses=["failed", "cancelled"],
status_extractor=lambda response: (response.status.value if response.status else None),
progress_extractor=lambda response: (response.progress if hasattr(response, "progress") else None),
auth_kwargs=auth_kwargs,
result_url_extractor=lambda response: (response.url if hasattr(response, "url") else None),
node_id=node_id,
estimated_duration=60,
max_poll_attempts=240,
).execute()
if not final_response.url:
error_msg = f"Pika task {task_id} succeeded but no video data found in response:\n{final_response}"
logging.error(error_msg)
raise Exception(error_msg)
video_url = final_response.url
logging.info("Pika task %s succeeded. Video URL: %s", task_id, video_url)
return IO.NodeOutput(await download_url_to_video_output(video_url))
def get_base_inputs_types() -> list[IO.Input]:
"""Get the base required inputs types common to all Pika nodes."""
return [
IO.String.Input("prompt_text", multiline=True),
IO.String.Input("negative_prompt", multiline=True),
IO.Int.Input("seed", min=0, max=0xFFFFFFFF, control_after_generate=True),
IO.Combo.Input("resolution", options=["1080p", "720p"], default="1080p"),
IO.Combo.Input("duration", options=[5, 10], default=5),
]
class PikaImageToVideo(IO.ComfyNode):
"""Pika 2.2 Image to Video Node."""
@classmethod
def define_schema(cls) -> IO.Schema:
return IO.Schema(
node_id="PikaImageToVideoNode2_2",
display_name="Pika Image to Video",
description="Sends an image and prompt to the Pika API v2.2 to generate a video.",
category="api node/video/Pika",
inputs=[
IO.Image.Input("image", tooltip="The image to convert to video"),
*get_base_inputs_types(),
],
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,
)
@classmethod
async def execute(
cls,
image: torch.Tensor,
prompt_text: str,
negative_prompt: str,
seed: int,
resolution: str,
duration: int,
) -> IO.NodeOutput:
image_bytes_io = tensor_to_bytesio(image)
pika_files = {"image": ("image.png", image_bytes_io, "image/png")}
pika_request_data = pika_defs.PikaBodyGenerate22I2vGenerate22I2vPost(
promptText=prompt_text,
negativePrompt=negative_prompt,
seed=seed,
resolution=resolution,
duration=duration,
)
auth = {
"auth_token": cls.hidden.auth_token_comfy_org,
"comfy_api_key": cls.hidden.api_key_comfy_org,
}
initial_operation = SynchronousOperation(
endpoint=ApiEndpoint(
path=PATH_IMAGE_TO_VIDEO,
method=HttpMethod.POST,
request_model=pika_defs.PikaBodyGenerate22I2vGenerate22I2vPost,
response_model=pika_defs.PikaGenerateResponse,
),
request=pika_request_data,
files=pika_files,
content_type="multipart/form-data",
auth_kwargs=auth,
)
return await execute_task(initial_operation, auth_kwargs=auth, node_id=cls.hidden.unique_id)
class PikaTextToVideoNode(IO.ComfyNode):
"""Pika Text2Video v2.2 Node."""
@classmethod
def define_schema(cls) -> IO.Schema:
return IO.Schema(
node_id="PikaTextToVideoNode2_2",
display_name="Pika Text to Video",
description="Sends a text prompt to the Pika API v2.2 to generate a video.",
category="api node/video/Pika",
inputs=[
*get_base_inputs_types(),
IO.Float.Input(
"aspect_ratio",
step=0.001,
min=0.4,
max=2.5,
default=1.7777777777777777,
tooltip="Aspect ratio (width / height)",
)
],
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,
)
@classmethod
async def execute(
cls,
prompt_text: str,
negative_prompt: str,
seed: int,
resolution: str,
duration: int,
aspect_ratio: float,
) -> IO.NodeOutput:
auth = {
"auth_token": cls.hidden.auth_token_comfy_org,
"comfy_api_key": cls.hidden.api_key_comfy_org,
}
initial_operation = SynchronousOperation(
endpoint=ApiEndpoint(
path=PATH_TEXT_TO_VIDEO,
method=HttpMethod.POST,
request_model=pika_defs.PikaBodyGenerate22T2vGenerate22T2vPost,
response_model=pika_defs.PikaGenerateResponse,
),
request=pika_defs.PikaBodyGenerate22T2vGenerate22T2vPost(
promptText=prompt_text,
negativePrompt=negative_prompt,
seed=seed,
resolution=resolution,
duration=duration,
aspectRatio=aspect_ratio,
),
auth_kwargs=auth,
content_type="application/x-www-form-urlencoded",
)
return await execute_task(initial_operation, auth_kwargs=auth, node_id=cls.hidden.unique_id)
class PikaScenes(IO.ComfyNode):
"""PikaScenes v2.2 Node."""
@classmethod
def define_schema(cls) -> IO.Schema:
return IO.Schema(
node_id="PikaScenesV2_2",
display_name="Pika Scenes (Video Image Composition)",
description="Combine your images to create a video with the objects in them. Upload multiple images as ingredients and generate a high-quality video that incorporates all of them.",
category="api node/video/Pika",
inputs=[
*get_base_inputs_types(),
IO.Combo.Input(
"ingredients_mode",
options=["creative", "precise"],
default="creative",
),
IO.Float.Input(
"aspect_ratio",
step=0.001,
min=0.4,
max=2.5,
default=1.7777777777777777,
tooltip="Aspect ratio (width / height)",
),
IO.Image.Input(
"image_ingredient_1",
optional=True,
tooltip="Image that will be used as ingredient to create a video.",
),
IO.Image.Input(
"image_ingredient_2",
optional=True,
tooltip="Image that will be used as ingredient to create a video.",
),
IO.Image.Input(
"image_ingredient_3",
optional=True,
tooltip="Image that will be used as ingredient to create a video.",
),
IO.Image.Input(
"image_ingredient_4",
optional=True,
tooltip="Image that will be used as ingredient to create a video.",
),
IO.Image.Input(
"image_ingredient_5",
optional=True,
tooltip="Image that will be used as ingredient to create a video.",
),
],
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,
)
@classmethod
async def execute(
cls,
prompt_text: str,
negative_prompt: str,
seed: int,
resolution: str,
duration: int,
ingredients_mode: str,
aspect_ratio: float,
image_ingredient_1: Optional[torch.Tensor] = None,
image_ingredient_2: Optional[torch.Tensor] = None,
image_ingredient_3: Optional[torch.Tensor] = None,
image_ingredient_4: Optional[torch.Tensor] = None,
image_ingredient_5: Optional[torch.Tensor] = None,
) -> IO.NodeOutput:
all_image_bytes_io = []
for image in [
image_ingredient_1,
image_ingredient_2,
image_ingredient_3,
image_ingredient_4,
image_ingredient_5,
]:
if image is not None:
all_image_bytes_io.append(tensor_to_bytesio(image))
pika_files = [
("images", (f"image_{i}.png", image_bytes_io, "image/png"))
for i, image_bytes_io in enumerate(all_image_bytes_io)
]
pika_request_data = pika_defs.PikaBodyGenerate22C2vGenerate22PikascenesPost(
ingredientsMode=ingredients_mode,
promptText=prompt_text,
negativePrompt=negative_prompt,
seed=seed,
resolution=resolution,
duration=duration,
aspectRatio=aspect_ratio,
)
auth = {
"auth_token": cls.hidden.auth_token_comfy_org,
"comfy_api_key": cls.hidden.api_key_comfy_org,
}
initial_operation = SynchronousOperation(
endpoint=ApiEndpoint(
path=PATH_PIKASCENES,
method=HttpMethod.POST,
request_model=pika_defs.PikaBodyGenerate22C2vGenerate22PikascenesPost,
response_model=pika_defs.PikaGenerateResponse,
),
request=pika_request_data,
files=pika_files,
content_type="multipart/form-data",
auth_kwargs=auth,
)
return await execute_task(initial_operation, auth_kwargs=auth, node_id=cls.hidden.unique_id)
class PikAdditionsNode(IO.ComfyNode):
"""Pika Pikadditions Node. Add an image into a video."""
@classmethod
def define_schema(cls) -> IO.Schema:
return IO.Schema(
node_id="Pikadditions",
display_name="Pikadditions (Video Object Insertion)",
description="Add any object or image into your video. Upload a video and specify what you'd like to add to create a seamlessly integrated result.",
category="api node/video/Pika",
inputs=[
IO.Video.Input("video", tooltip="The video to add an image to."),
IO.Image.Input("image", tooltip="The image to add to the video."),
IO.String.Input("prompt_text", multiline=True),
IO.String.Input("negative_prompt", multiline=True),
IO.Int.Input(
"seed",
min=0,
max=0xFFFFFFFF,
control_after_generate=True,
),
],
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,
)
@classmethod
async def execute(
cls,
video: VideoInput,
image: torch.Tensor,
prompt_text: str,
negative_prompt: str,
seed: int,
) -> IO.NodeOutput:
video_bytes_io = BytesIO()
video.save_to(video_bytes_io, format=VideoContainer.MP4, codec=VideoCodec.H264)
video_bytes_io.seek(0)
image_bytes_io = tensor_to_bytesio(image)
pika_files = {
"video": ("video.mp4", video_bytes_io, "video/mp4"),
"image": ("image.png", image_bytes_io, "image/png"),
}
pika_request_data = pika_defs.PikaBodyGeneratePikadditionsGeneratePikadditionsPost(
promptText=prompt_text,
negativePrompt=negative_prompt,
seed=seed,
)
auth = {
"auth_token": cls.hidden.auth_token_comfy_org,
"comfy_api_key": cls.hidden.api_key_comfy_org,
}
initial_operation = SynchronousOperation(
endpoint=ApiEndpoint(
path=PATH_PIKADDITIONS,
method=HttpMethod.POST,
request_model=pika_defs.PikaBodyGeneratePikadditionsGeneratePikadditionsPost,
response_model=pika_defs.PikaGenerateResponse,
),
request=pika_request_data,
files=pika_files,
content_type="multipart/form-data",
auth_kwargs=auth,
)
return await execute_task(initial_operation, auth_kwargs=auth, node_id=cls.hidden.unique_id)
class PikaSwapsNode(IO.ComfyNode):
"""Pika Pikaswaps Node."""
@classmethod
def define_schema(cls) -> IO.Schema:
return IO.Schema(
node_id="Pikaswaps",
display_name="Pika Swaps (Video Object Replacement)",
description="Swap out any object or region of your video with a new image or object. Define areas to replace either with a mask or coordinates.",
category="api node/video/Pika",
inputs=[
IO.Video.Input("video", tooltip="The video to swap an object in."),
IO.Image.Input(
"image",
tooltip="The image used to replace the masked object in the video.",
optional=True,
),
IO.Mask.Input(
"mask",
tooltip="Use the mask to define areas in the video to replace.",
optional=True,
),
IO.String.Input("prompt_text", multiline=True, optional=True),
IO.String.Input("negative_prompt", multiline=True, optional=True),
IO.Int.Input("seed", min=0, max=0xFFFFFFFF, control_after_generate=True, optional=True),
IO.String.Input(
"region_to_modify",
multiline=True,
optional=True,
tooltip="Plaintext description of the object / region to modify.",
),
],
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,
)
@classmethod
async def execute(
cls,
video: VideoInput,
image: Optional[torch.Tensor] = None,
mask: Optional[torch.Tensor] = None,
prompt_text: str = "",
negative_prompt: str = "",
seed: int = 0,
region_to_modify: str = "",
) -> IO.NodeOutput:
video_bytes_io = BytesIO()
video.save_to(video_bytes_io, format=VideoContainer.MP4, codec=VideoCodec.H264)
video_bytes_io.seek(0)
pika_files = {
"video": ("video.mp4", video_bytes_io, "video/mp4"),
}
if mask is not None:
pika_files["modifyRegionMask"] = ("mask.png", tensor_to_bytesio(mask), "image/png")
if image is not None:
pika_files["image"] = ("image.png", tensor_to_bytesio(image), "image/png")
pika_request_data = pika_defs.PikaBodyGeneratePikaswapsGeneratePikaswapsPost(
promptText=prompt_text,
negativePrompt=negative_prompt,
seed=seed,
modifyRegionRoi=region_to_modify if region_to_modify else None,
)
auth = {
"auth_token": cls.hidden.auth_token_comfy_org,
"comfy_api_key": cls.hidden.api_key_comfy_org,
}
initial_operation = SynchronousOperation(
endpoint=ApiEndpoint(
path=PATH_PIKASWAPS,
method=HttpMethod.POST,
request_model=pika_defs.PikaBodyGeneratePikaswapsGeneratePikaswapsPost,
response_model=pika_defs.PikaGenerateResponse,
),
request=pika_request_data,
files=pika_files,
content_type="multipart/form-data",
auth_kwargs=auth,
)
return await execute_task(initial_operation, auth_kwargs=auth, node_id=cls.hidden.unique_id)
class PikaffectsNode(IO.ComfyNode):
"""Pika Pikaffects Node."""
@classmethod
def define_schema(cls) -> IO.Schema:
return IO.Schema(
node_id="Pikaffects",
display_name="Pikaffects (Video Effects)",
description="Generate a video with a specific Pikaffect. Supported Pikaffects: Cake-ify, Crumble, Crush, Decapitate, Deflate, Dissolve, Explode, Eye-pop, Inflate, Levitate, Melt, Peel, Poke, Squish, Ta-da, Tear",
category="api node/video/Pika",
inputs=[
IO.Image.Input("image", tooltip="The reference image to apply the Pikaffect to."),
IO.Combo.Input(
"pikaffect", options=pika_defs.Pikaffect, default="Cake-ify"
),
IO.String.Input("prompt_text", multiline=True),
IO.String.Input("negative_prompt", multiline=True),
IO.Int.Input("seed", min=0, max=0xFFFFFFFF, control_after_generate=True),
],
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,
)
@classmethod
async def execute(
cls,
image: torch.Tensor,
pikaffect: str,
prompt_text: str,
negative_prompt: str,
seed: int,
) -> IO.NodeOutput:
auth = {
"auth_token": cls.hidden.auth_token_comfy_org,
"comfy_api_key": cls.hidden.api_key_comfy_org,
}
initial_operation = SynchronousOperation(
endpoint=ApiEndpoint(
path=PATH_PIKAFFECTS,
method=HttpMethod.POST,
request_model=pika_defs.PikaBodyGeneratePikaffectsGeneratePikaffectsPost,
response_model=pika_defs.PikaGenerateResponse,
),
request=pika_defs.PikaBodyGeneratePikaffectsGeneratePikaffectsPost(
pikaffect=pikaffect,
promptText=prompt_text,
negativePrompt=negative_prompt,
seed=seed,
),
files={"image": ("image.png", tensor_to_bytesio(image), "image/png")},
content_type="multipart/form-data",
auth_kwargs=auth,
)
return await execute_task(initial_operation, auth_kwargs=auth, node_id=cls.hidden.unique_id)
class PikaStartEndFrameNode(IO.ComfyNode):
"""PikaFrames v2.2 Node."""
@classmethod
def define_schema(cls) -> IO.Schema:
return IO.Schema(
node_id="PikaStartEndFrameNode2_2",
display_name="Pika Start and End Frame to Video",
description="Generate a video by combining your first and last frame. Upload two images to define the start and end points, and let the AI create a smooth transition between them.",
category="api node/video/Pika",
inputs=[
IO.Image.Input("image_start", tooltip="The first image to combine."),
IO.Image.Input("image_end", tooltip="The last image to combine."),
*get_base_inputs_types(),
],
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,
)
@classmethod
async def execute(
cls,
image_start: torch.Tensor,
image_end: torch.Tensor,
prompt_text: str,
negative_prompt: str,
seed: int,
resolution: str,
duration: int,
) -> IO.NodeOutput:
validate_string(prompt_text, field_name="prompt_text", min_length=1)
pika_files = [
("keyFrames", ("image_start.png", tensor_to_bytesio(image_start), "image/png")),
("keyFrames", ("image_end.png", tensor_to_bytesio(image_end), "image/png")),
]
auth = {
"auth_token": cls.hidden.auth_token_comfy_org,
"comfy_api_key": cls.hidden.api_key_comfy_org,
}
initial_operation = SynchronousOperation(
endpoint=ApiEndpoint(
path=PATH_PIKAFRAMES,
method=HttpMethod.POST,
request_model=pika_defs.PikaBodyGenerate22KeyframeGenerate22PikaframesPost,
response_model=pika_defs.PikaGenerateResponse,
),
request=pika_defs.PikaBodyGenerate22KeyframeGenerate22PikaframesPost(
promptText=prompt_text,
negativePrompt=negative_prompt,
seed=seed,
resolution=resolution,
duration=duration,
),
files=pika_files,
content_type="multipart/form-data",
auth_kwargs=auth,
)
return await execute_task(initial_operation, auth_kwargs=auth, node_id=cls.hidden.unique_id)
class PikaApiNodesExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
return [
PikaImageToVideo,
PikaTextToVideoNode,
PikaScenes,
PikAdditionsNode,
PikaSwapsNode,
PikaffectsNode,
PikaStartEndFrameNode,
]
async def comfy_entrypoint() -> PikaApiNodesExtension:
return PikaApiNodesExtension()
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