mirror of
https://git.datalinker.icu/comfyanonymous/ComfyUI
synced 2026-09-06 13:57:08 +08:00
[Kling] Add Duration and Video ID outputs (#105)
This commit is contained in:
Christian Byrne
GitHub
parent
1178022a7a
commit
99a6b59cbb
@ -103,7 +103,42 @@ def get_camera_control_input_config(
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return IO.FLOAT, input_config
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class KlingCameraControls(ComfyNodeABC):
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class KlingNodeBase(ComfyNodeABC):
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"""
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Base class for Kling nodes.
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Compatibility Table
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===================
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| Mode | Duration | Model Name | Camera Control | Image Tail |
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|------|----------|------------------|----------------|------------|
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| std | 5 | kling-v1 | No | Yes |
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| std | 5 | kling-v1-5 | No | Yes |
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| std | 5 | kling-v1-6 | No | No |
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| std | 5 | kling-v2-master | No | No |
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| std | 10 | kling-v1 | No | No |
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| std | 10 | kling-v1-5 | No | No |
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| std | 10 | kling-v1-6 | No | No |
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| std | 10 | kling-v2-master | No | No |
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| pro | 5 | kling-v1 | No | Yes |
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| pro | 5 | kling-v1-5 | Yes | Yes |
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| pro | 5 | kling-v1-6 | No | Yes |
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| pro | 5 | kling-v2-master | No | No |
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| pro | 10 | kling-v1 | No | No |
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| pro | 10 | kling-v1-5 | No | Yes |
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| pro | 10 | kling-v1-6 | No | Yes |
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| pro | 10 | kling-v2-master | No | No |
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**Note**: Although the combo of pro mode, kling-v1-5 model, and 5s duration
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supports both camera_control and image_tail, you can only use one feature
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at a time.
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"""
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FUNCTION = "api_call"
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CATEGORY = "api node/video/Kling"
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API_NODE = True
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class KlingCameraControls(KlingNodeBase):
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"""Kling Camera Controls Node"""
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@classmethod
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@ -148,16 +183,16 @@ class KlingCameraControls(ComfyNodeABC):
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RETURN_NAMES = ("camera_control",)
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FUNCTION = "main"
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def main(
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self,
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camera_control_type: str,
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@classmethod
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def VALIDATE_INPUTS(
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cls,
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horizontal_movement: float,
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vertical_movement: float,
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pan: float,
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tilt: float,
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roll: float,
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zoom: float,
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):
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) -> bool | str:
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if not is_valid_camera_control_configs(
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[
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horizontal_movement,
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@ -169,7 +204,18 @@ class KlingCameraControls(ComfyNodeABC):
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]
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):
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return "Invalid camera control configs: at least one of the values must be non-zero"
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return True
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def main(
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self,
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camera_control_type: str,
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horizontal_movement: float,
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vertical_movement: float,
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pan: float,
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tilt: float,
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roll: float,
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zoom: float,
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) -> tuple[CameraControl]:
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return (
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CameraControl(
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type=CameraType(camera_control_type),
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@ -185,18 +231,8 @@ class KlingCameraControls(ComfyNodeABC):
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)
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class KlingNodeBase(ComfyNodeABC):
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"""Base class for Kling nodes."""
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FUNCTION = "api_call"
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CATEGORY = "api node/video/Kling"
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API_NODE = True
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class KlingTextToVideoNode(KlingNodeBase):
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"""
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Kling Text to Video Node.
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"""
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"""Kling Text to Video Node"""
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@staticmethod
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def poll_for_task_status(task_id: str, auth_token: str) -> KlingText2VideoResponse:
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@ -254,13 +290,11 @@ class KlingTextToVideoNode(KlingNodeBase):
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enum_type=AspectRatio,
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),
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},
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"optional": {
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"camera_control": ("CAMERA_CONTROL", {}),
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},
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"hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
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}
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RETURN_TYPES = ("VIDEO",)
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RETURN_TYPES = ("VIDEO", "STRING", "STRING")
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RETURN_NAMES = ("VIDEO", "Kling ID", "Duration (sec)")
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DESCRIPTION = "Kling Text to Video Node"
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def api_call(
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@ -274,7 +308,7 @@ class KlingTextToVideoNode(KlingNodeBase):
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aspect_ratio: str,
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camera_control: Optional[CameraControl] = None,
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auth_token: Optional[str] = None,
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) -> tuple[VideoFromFile]:
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) -> tuple[VideoFromFile, str, str]:
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validate_prompts(prompt, negative_prompt, MAX_PROMPT_LENGTH_T2V)
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initial_operation = SynchronousOperation(
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endpoint=ApiEndpoint(
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@ -311,16 +345,79 @@ class KlingTextToVideoNode(KlingNodeBase):
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logging.error(error_msg)
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raise KlingApiError(error_msg)
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video_url = str(final_response.data.task_result.videos[0].url)
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logging.debug("Kling task %s succeeded. Video URL: %s", task_id, video_url)
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video = final_response.data.task_result.videos[0]
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logging.debug("Kling task %s succeeded. Video URL: %s", task_id, video.url)
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return (
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download_url_to_video_output(video.url),
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str(video.id),
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str(video.duration),
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)
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return (download_url_to_video_output(video_url),)
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class KlingCameraControlT2VNode(KlingTextToVideoNode):
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"""
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Kling Text to Video Camera Control Node. This node is a text to video node, but it supports controlling the camera.
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Duration, mode, and model_name request fields are hard-coded because camera control is only supported in pro mode with the kling-v1-5 model at 5s duration as of 2025-05-02.
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"""
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"prompt": model_field_to_node_input(
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IO.STRING, KlingText2VideoRequest, "prompt", multiline=True
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),
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"negative_prompt": model_field_to_node_input(
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IO.STRING,
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KlingText2VideoRequest,
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"negative_prompt",
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multiline=True,
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),
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"cfg_scale": model_field_to_node_input(
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IO.FLOAT, KlingText2VideoRequest, "cfg_scale"
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),
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"aspect_ratio": model_field_to_node_input(
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IO.COMBO,
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KlingText2VideoRequest,
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"aspect_ratio",
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enum_type=AspectRatio,
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),
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"camera_control": (
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"CAMERA_CONTROL",
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{
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"tooltip": "Can be created using the Kling Camera Controls node. Controls the camera movement and motion during the video generation.",
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},
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),
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},
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"hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
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}
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DESCRIPTION = "Transform text into cinematic videos with professional camera movements that simulate real-world cinematography. Control virtual camera actions including zoom, rotation, pan, tilt, and first-person view, while maintaining focus on your original text."
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def api_call(
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self,
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prompt: str,
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negative_prompt: str,
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cfg_scale: float,
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aspect_ratio: str,
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camera_control: Optional[CameraControl] = None,
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auth_token: Optional[str] = None,
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):
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return super().api_call(
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model_name="kling-v1-5",
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cfg_scale=cfg_scale,
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mode="pro",
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aspect_ratio=aspect_ratio,
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duration="5",
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prompt=prompt,
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negative_prompt=negative_prompt,
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camera_control=camera_control,
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auth_token=auth_token,
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)
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class KlingImage2VideoNode(KlingNodeBase):
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"""
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Kling Image to Video Node.
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"""
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"""Kling Image to Video Node"""
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@staticmethod
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def poll_for_task_status(task_id: str, auth_token: str) -> KlingImage2VideoResponse:
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@ -347,6 +444,9 @@ class KlingImage2VideoNode(KlingNodeBase):
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def INPUT_TYPES(s):
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return {
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"required": {
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"start_frame": model_field_to_node_input(
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IO.IMAGE, KlingImage2VideoRequest, "image"
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),
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"prompt": model_field_to_node_input(
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IO.STRING, KlingImage2VideoRequest, "prompt", multiline=True
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),
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@ -363,9 +463,6 @@ class KlingImage2VideoNode(KlingNodeBase):
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enum_type=ModelName,
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default="kling-v2-master",
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),
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"start_frame": model_field_to_node_input(
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IO.IMAGE, KlingImage2VideoRequest, "image"
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),
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"cfg_scale": model_field_to_node_input(
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IO.FLOAT, KlingImage2VideoRequest, "cfg_scale"
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),
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@ -382,24 +479,19 @@ class KlingImage2VideoNode(KlingNodeBase):
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IO.COMBO, KlingImage2VideoRequest, "duration", enum_type=Duration
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),
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},
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"optional": {
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"camera_control": ("CAMERA_CONTROL", {}),
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"end_frame": model_field_to_node_input(
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IO.IMAGE, KlingImage2VideoRequest, "image_tail"
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),
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},
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"hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
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}
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RETURN_TYPES = ("VIDEO",)
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RETURN_TYPES = ("VIDEO", "STRING", "STRING")
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RETURN_NAMES = ("VIDEO", "Kling ID", "Duration (sec)")
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DESCRIPTION = "Kling Image to Video Node"
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def api_call(
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self,
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start_frame: torch.Tensor,
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prompt: str,
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negative_prompt: str,
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model_name: str,
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start_frame: torch.Tensor,
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cfg_scale: float,
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mode: str,
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aspect_ratio: str,
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@ -449,20 +541,190 @@ class KlingImage2VideoNode(KlingNodeBase):
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logging.error(error_msg)
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raise KlingApiError(error_msg)
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video_url = str(final_response.data.task_result.videos[0].url)
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logging.info("Attempting to download video from URL: %s", video_url)
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video = final_response.data.task_result.videos[0]
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logging.info("Kling task %s succeeded. Video URL: %s", task_id, video.url)
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return (download_url_to_video_output(video_url),)
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return (
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download_url_to_video_output(video.url),
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str(video.id),
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str(video.duration),
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)
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class KlingCameraControlI2VNode(KlingImage2VideoNode):
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"""
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Kling Image to Video Camera Control Node. This node is a image to video node, but it supports controlling the camera.
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Duration, mode, and model_name request fields are hard-coded because camera control is only supported in pro mode with the kling-v1-5 model at 5s duration as of 2025-05-02.
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"""
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"start_frame": model_field_to_node_input(
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IO.IMAGE, KlingImage2VideoRequest, "image"
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),
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"prompt": model_field_to_node_input(
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IO.STRING, KlingImage2VideoRequest, "prompt", multiline=True
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),
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"negative_prompt": model_field_to_node_input(
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IO.STRING,
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KlingImage2VideoRequest,
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"negative_prompt",
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multiline=True,
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),
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"cfg_scale": model_field_to_node_input(
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IO.FLOAT, KlingImage2VideoRequest, "cfg_scale"
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),
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"aspect_ratio": model_field_to_node_input(
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IO.COMBO,
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KlingImage2VideoRequest,
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"aspect_ratio",
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enum_type=AspectRatio,
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),
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"camera_control": (
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"CAMERA_CONTROL",
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{
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"tooltip": "Can be created using the Kling Camera Controls node. Controls the camera movement and motion during the video generation.",
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},
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),
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},
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"hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
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}
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DESCRIPTION = "Transform still images into cinematic videos with professional camera movements that simulate real-world cinematography. Control virtual camera actions including zoom, rotation, pan, tilt, and first-person view, while maintaining focus on your original image."
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def api_call(
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self,
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start_frame: torch.Tensor,
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prompt: str,
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negative_prompt: str,
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cfg_scale: float,
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aspect_ratio: str,
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camera_control: CameraControl,
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auth_token: Optional[str] = None,
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):
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return super().api_call(
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model_name="kling-v1-5",
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start_frame=start_frame,
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cfg_scale=cfg_scale,
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mode="pro",
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aspect_ratio=aspect_ratio,
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duration="5",
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prompt=prompt,
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negative_prompt=negative_prompt,
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camera_control=camera_control,
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auth_token=auth_token,
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)
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class KlingStartEndFrameNode(KlingImage2VideoNode):
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"""
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Kling First Last Frame Node. This node allows creation of a video from a first and last frame. It calls the normal image to video endpoint, but only allows the subset of input options that support the `image_tail` request field.
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"""
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@staticmethod
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def get_mode_string_mapping() -> dict[str, tuple[str, str, str]]:
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"""
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Returns a mapping of mode strings to their corresponding (mode, duration, model_name) tuples.
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Only includes config combos that support the `image_tail` request field.
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"""
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return {
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"standard mode / 5s duration / kling-v1": ("std", "5", "kling-v1"),
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"standard mode / 5s duration / kling-v1-5": ("std", "5", "kling-v1-5"),
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"pro mode / 5s duration / kling-v1": ("pro", "5", "kling-v1"),
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"pro mode / 5s duration / kling-v1-5": ("pro", "5", "kling-v1-5"),
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"pro mode / 5s duration / kling-v1-6": ("pro", "5", "kling-v1-6"),
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"pro mode / 10s duration / kling-v1-5": ("pro", "10", "kling-v1-5"),
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"pro mode / 10s duration / kling-v1-6": ("pro", "10", "kling-v1-6"),
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}
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@classmethod
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def INPUT_TYPES(s):
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modes = list(KlingStartEndFrameNode.get_mode_string_mapping().keys())
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return {
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"required": {
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"start_frame": model_field_to_node_input(
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IO.IMAGE, KlingImage2VideoRequest, "image"
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),
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"end_frame": model_field_to_node_input(
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IO.IMAGE, KlingImage2VideoRequest, "image_tail"
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),
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"prompt": model_field_to_node_input(
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IO.STRING, KlingImage2VideoRequest, "prompt", multiline=True
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),
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"negative_prompt": model_field_to_node_input(
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IO.STRING,
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KlingImage2VideoRequest,
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"negative_prompt",
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multiline=True,
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),
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"cfg_scale": model_field_to_node_input(
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IO.FLOAT, KlingImage2VideoRequest, "cfg_scale"
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),
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"aspect_ratio": model_field_to_node_input(
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IO.COMBO,
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KlingImage2VideoRequest,
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"aspect_ratio",
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enum_type=AspectRatio,
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),
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"mode": (
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modes,
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{
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"default": modes[2],
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"tooltip": "The configuration to use for the video generation following the format: mode / duration / model_name.",
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},
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),
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},
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"hidden": {"auth_token": "AUTH_TOKEN_COMFY_ORG"},
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}
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DESCRIPTION = "Generate a video sequence that transitions between your provided start and end images. The node creates all frames in between, producing a smooth transformation from the first frame to the last."
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def parse_inputs_from_mode(self, mode: str) -> tuple[str, str, str]:
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"""Parses the mode input into a tuple of (model_name, duration, mode)."""
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return KlingStartEndFrameNode.get_mode_string_mapping()[mode]
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def api_call(
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self,
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start_frame: torch.Tensor,
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end_frame: torch.Tensor,
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prompt: str,
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negative_prompt: str,
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cfg_scale: float,
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aspect_ratio: str,
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mode: str,
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auth_token: Optional[str] = None,
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):
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mode, duration, model_name = self.parse_inputs_from_mode(mode)
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return super().api_call(
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prompt=prompt,
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negative_prompt=negative_prompt,
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model_name=model_name,
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start_frame=start_frame,
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cfg_scale=cfg_scale,
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mode=mode,
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aspect_ratio=aspect_ratio,
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duration=duration,
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end_frame=end_frame,
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auth_token=auth_token,
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)
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NODE_CLASS_MAPPINGS = {
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"KlingCameraControls": KlingCameraControls,
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"KlingTextToVideoNode": KlingTextToVideoNode,
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"KlingImage2VideoNode": KlingImage2VideoNode,
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"KlingCameraControlI2VNode": KlingCameraControlI2VNode,
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"KlingCameraControlT2VNode": KlingCameraControlT2VNode,
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"KlingStartEndFrameNode": KlingStartEndFrameNode,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"KlingCameraControls": "Kling Camera Controls",
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"KlingTextToVideoNode": "Kling Text to Video",
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"KlingImage2VideoNode": "Kling Image to Video",
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"KlingCameraControlI2VNode": "Kling Image to Video (Camera Control)",
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"KlingCameraControlT2VNode": "Kling Text to Video (Camera Control)",
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"KlingStartEndFrameNode": "Kling Start-End Frame to Video",
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}
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