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magicwang1111-Comfyui-Kling…/examples/generate_examples.py
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import json
from pathlib import Path
ROOT = Path(__file__).resolve().parent
NODE_PREFIX = "Comfyui-Kling-Wrapper"
CLIENT_TYPE = "COMFYUI_KLING_WRAPPER_API_CLIENT"
ELEMENT_TYPE = "COMFYUI_KLING_WRAPPER_ELEMENT"
ELEMENT_LIST_TYPE = "COMFYUI_KLING_WRAPPER_ELEMENT_LIST"
LIPSYNC_INPUT_TYPE = "COMFYUI_KLING_WRAPPER_LIPSYNC_INPUT"
def input_slot(name, type_name, link=None, shape=7):
slot = {"name": name, "type": type_name, "link": link}
if type_name in {"IMAGE", "MASK"}:
slot["shape"] = shape
return slot
def output_slot(name, type_name, links=None, slot_index=None):
slot = {"name": name, "type": type_name, "links": links}
if slot_index is not None:
slot["slot_index"] = slot_index
return slot
def node(node_id, type_name, pos, size, order, widgets_values, inputs=None, outputs=None):
return {
"id": node_id,
"type": type_name,
"pos": pos,
"size": size,
"flags": {},
"order": order,
"mode": 0,
"inputs": inputs or [],
"outputs": outputs or [],
"properties": {"Node name for S&R": type_name},
"widgets_values": widgets_values,
}
def workflow(nodes, links):
return {
"id": "Comfyui-Kling-Wrapper-example",
"revision": 0,
"last_node_id": max(node["id"] for node in nodes),
"last_link_id": max((link[0] for link in links), default=0),
"nodes": nodes,
"links": links,
"groups": [],
"config": {},
"extra": {
"ds": {
"scale": 0.9,
"offset": [0, 0],
},
"frontendVersion": "1.42.8",
},
"version": 0.4,
}
def strip_client_dependency(data):
data = json.loads(json.dumps(data))
client_node_type = f"{NODE_PREFIX} Client"
removed_link_ids = set()
removed_node_ids = set()
input_index_maps = {}
cleaned_nodes = []
for workflow_node in data["nodes"]:
if workflow_node.get("type") == client_node_type:
removed_node_ids.add(workflow_node["id"])
continue
cleaned_inputs = []
input_index_maps[workflow_node["id"]] = {}
for old_index, node_input in enumerate(workflow_node.get("inputs", [])):
if node_input.get("type") == CLIENT_TYPE or node_input.get("name") == "client":
if node_input.get("link") is not None:
removed_link_ids.add(node_input["link"])
continue
input_index_maps[workflow_node["id"]][old_index] = len(cleaned_inputs)
cleaned_inputs.append(node_input)
workflow_node["inputs"] = cleaned_inputs
cleaned_nodes.append(workflow_node)
cleaned_links = []
for workflow_link in data.get("links", []):
link_id, src_node, _, dst_node, _, link_type = workflow_link
if link_type == CLIENT_TYPE or src_node in removed_node_ids or dst_node in removed_node_ids:
removed_link_ids.add(link_id)
continue
cleaned_link = list(workflow_link)
destination_map = input_index_maps.get(dst_node, {})
cleaned_link[4] = destination_map.get(cleaned_link[4], cleaned_link[4])
cleaned_links.append(cleaned_link)
for workflow_node in cleaned_nodes:
for node_input in workflow_node.get("inputs", []):
if node_input.get("link") in removed_link_ids:
node_input["link"] = None
for node_output in workflow_node.get("outputs", []):
links = node_output.get("links")
if isinstance(links, list):
links = [link_id for link_id in links if link_id not in removed_link_ids]
node_output["links"] = links or None
data["nodes"] = cleaned_nodes
data["links"] = cleaned_links
data["last_node_id"] = max((node["id"] for node in cleaned_nodes), default=0)
data["last_link_id"] = max((link[0] for link in cleaned_links), default=0)
return data
def client_node(node_id=1, order=0, area="china"):
type_name = f"{NODE_PREFIX} Client"
return node(
node_id,
type_name,
[40, 60],
[320, 210],
order,
["", "", 1, 30, area],
outputs=[output_slot("client", CLIENT_TYPE, slot_index=0)],
)
def load_image_node(node_id, filename, pos, order):
return node(
node_id,
"LoadImage",
pos,
[290, 340],
order,
[filename, "image"],
outputs=[
output_slot("IMAGE", "IMAGE", slot_index=0),
output_slot("MASK", "MASK", slot_index=1),
],
)
def load_video_node(node_id, filename, pos, order):
return node(
node_id,
"LoadVideo",
pos,
[320, 120],
order,
[filename],
outputs=[output_slot("VIDEO", "VIDEO", slot_index=0)],
)
def load_audio_node(node_id, filename, pos, order):
return node(
node_id,
"LoadAudio",
pos,
[320, 120],
order,
[filename],
outputs=[output_slot("AUDIO", "AUDIO", slot_index=0)],
)
def save_image_node(node_id, filename_prefix, pos, order, link_id):
return node(
node_id,
"SaveImage",
pos,
[320, 100],
order,
[filename_prefix],
inputs=[input_slot("images", "IMAGE", link_id)],
)
def preview_video_node(node_id, pos, order, link_id):
type_name = f"{NODE_PREFIX} Preview Video"
return node(
node_id,
type_name,
pos,
[430, 820],
order,
[],
inputs=[input_slot("video_url", "STRING", link_id)],
outputs=[output_slot("file_path", "STRING", slot_index=0)],
)
def preview_audio_node(node_id, pos, order, link_id):
type_name = f"{NODE_PREFIX} Preview Audio"
return node(
node_id,
type_name,
pos,
[360, 180],
order,
[NODE_PREFIX + "-audio", True],
inputs=[input_slot("audio_url", "STRING", link_id)],
outputs=[
output_slot("audio", "AUDIO", slot_index=0),
output_slot("file_path", "STRING", slot_index=1),
],
)
def image_generator_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} Image Generator"
return node(
node_id,
type_name,
pos,
[430, 370],
order,
[
"kling-v3",
"A fashion editorial portrait of a young woman in soft morning light, realistic skin texture, elegant framing, filmic color grading.",
"",
"None",
0.5,
0.45,
1,
"16:9",
"1k",
],
inputs=[input_slot("client", CLIENT_TYPE)],
outputs=[output_slot("image", "IMAGE", slot_index=0)],
)
def text2video_node(node_id, pos, order, model, prompt, mode="pro", aspect_ratio="16:9", duration="5",
sound="off", voice_preset="None", shot_type="single", reference_video=""):
type_name = f"{NODE_PREFIX} Text2Video"
return node(
node_id,
type_name,
pos,
[430, 520],
order,
[
model,
prompt,
"",
0.5,
mode,
aspect_ratio,
duration,
"None",
"horizontal",
0.5,
sound,
voice_preset,
shot_type,
reference_video,
],
inputs=[input_slot("client", CLIENT_TYPE)],
outputs=[
output_slot("url", "STRING", slot_index=0),
output_slot("video_id", "STRING", slot_index=1),
],
)
def image2video_node(
node_id,
pos,
order,
model,
prompt="",
mode="pro",
duration="5",
shot_type="single",
reference_video="",
sound="off",
voice_preset="None",
):
type_name = f"{NODE_PREFIX} Image2Video"
return node(
node_id,
type_name,
pos,
[430, 520],
order,
[
model,
prompt,
"",
0.5,
mode,
duration,
"None",
"horizontal",
0.5,
sound,
voice_preset,
shot_type,
reference_video,
],
inputs=[
input_slot("client", CLIENT_TYPE),
input_slot("image", "IMAGE"),
input_slot("image_tail", "IMAGE", None),
input_slot("custom_voice_id", "STRING", None),
],
outputs=[
output_slot("url", "STRING", slot_index=0),
output_slot("video_id", "STRING", slot_index=1),
],
)
def multi_images_to_video_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} Multi Images To Video"
return node(
node_id,
type_name,
pos,
[430, 360],
order,
[
"kling-v3",
"Keep the same person identity across the shot while the subject turns toward camera and smiles naturally.",
"",
"pro",
"5",
"16:9",
],
inputs=[
input_slot("client", CLIENT_TYPE),
input_slot("image_list", "IMAGE"),
input_slot("image_tail", "IMAGE", None),
],
outputs=[
output_slot("url", "STRING", slot_index=0),
output_slot("video_id", "STRING", slot_index=1),
],
)
def image_batch_node(node_id, pos, order):
return node(
node_id,
"ImageBatch",
pos,
[320, 120],
order,
[],
inputs=[
input_slot("image1", "IMAGE"),
input_slot("image2", "IMAGE"),
],
outputs=[output_slot("IMAGE", "IMAGE", slot_index=0)],
)
def virtual_try_on_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} Virtual Try On"
return node(
node_id,
type_name,
pos,
[360, 180],
order,
["kolors-virtual-try-on-v1-5"],
inputs=[
input_slot("client", CLIENT_TYPE),
input_slot("human_image", "IMAGE"),
input_slot("cloth_image", "IMAGE"),
],
outputs=[output_slot("image", "IMAGE", slot_index=0)],
)
def clothing_dupe_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} Clothing Dupe"
return node(
node_id,
type_name,
pos,
[430, 420],
order,
[
"Lightweight breathable shirt for a clean commercial product showcase.",
"720p",
"16:9",
"无",
],
inputs=[
input_slot("source_video", "VIDEO"),
input_slot("product_image_1", "IMAGE"),
input_slot("product_image_2", "IMAGE", None),
input_slot("product_image_3", "IMAGE", None),
input_slot("product_image_4", "IMAGE", None),
input_slot("product_image_5", "IMAGE", None),
input_slot("model_image_1", "IMAGE", None),
input_slot("model_image_2", "IMAGE", None),
input_slot("model_image_3", "IMAGE", None),
input_slot("model_image_4", "IMAGE", None),
input_slot("model_image_5", "IMAGE", None),
input_slot("bgm", "AUDIO", None),
],
outputs=[
output_slot("video_url", "STRING", slot_index=0),
output_slot("watermark_video_url", "STRING", slot_index=1),
output_slot("task_id", "STRING", slot_index=2),
output_slot("result_json", "STRING", slot_index=3),
],
)
def image_expander_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} Image Expander"
return node(
node_id,
type_name,
pos,
[360, 260],
order,
[0.25, 0.0, 0.0, 0.0, "Extend the background naturally with coherent lighting and scene details.", 1],
inputs=[
input_slot("client", CLIENT_TYPE),
input_slot("image", "IMAGE"),
],
outputs=[output_slot("image", "IMAGE", slot_index=0)],
)
def video_extender_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} Video Extender"
return node(
node_id,
type_name,
pos,
[360, 180],
order,
["", "Continue the shot naturally for a few more moments, keeping the same scene and motion direction."],
inputs=[
input_slot("client", CLIENT_TYPE),
input_slot("video_id", "STRING"),
],
outputs=[
output_slot("url", "STRING", slot_index=0),
output_slot("video_id", "STRING", slot_index=1),
],
)
def text_to_audio_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} TextToAudio"
return node(
node_id,
type_name,
pos,
[360, 180],
order,
["Generate a calm cinematic ambient track with gentle piano and soft pads.", 6.0],
inputs=[input_slot("client", CLIENT_TYPE)],
outputs=[
output_slot("id", "STRING", slot_index=0),
output_slot("url", "STRING", slot_index=1),
],
)
def custom_voice_create_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} Custom Voice Create"
return node(
node_id,
type_name,
pos,
[390, 260],
order,
["Demo Voice", "", "", "", "", ""],
inputs=[input_slot("audio", "AUDIO")],
outputs=[
output_slot("voice_id", "STRING", slot_index=0),
output_slot("voice_name", "STRING", slot_index=1),
output_slot("trial_url", "STRING", slot_index=2),
output_slot("task_id", "STRING", slot_index=3),
output_slot("voice_json", "STRING", slot_index=4),
],
)
def tts_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} TTS"
return node(
node_id,
type_name,
pos,
[390, 260],
order,
["这是一段用于测试克隆声音效果的短句。", "", "zh", 1.0],
inputs=[input_slot("voice_id", "STRING")],
outputs=[
output_slot("audio_id", "STRING", slot_index=0),
output_slot("audio_url", "STRING", slot_index=1),
output_slot("duration", "STRING", slot_index=2),
output_slot("audio_json", "STRING", slot_index=3),
],
)
def video_to_audio_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} Video2Audio"
return node(
node_id,
type_name,
pos,
[390, 220],
order,
["", "", "Footsteps on stone floor and distant city ambience.", "Cinematic ambient soundtrack with low strings.", False],
inputs=[
input_slot("client", CLIENT_TYPE),
input_slot("video_id", "STRING"),
],
outputs=[
output_slot("videos_id", "STRING", slot_index=0),
output_slot("videos_url", "STRING", slot_index=1),
output_slot("audio_id", "STRING", slot_index=2),
output_slot("audio_url_mp3", "STRING", slot_index=3),
],
)
def lip_sync_text_input_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} Lip Sync Text Input"
return node(
node_id,
type_name,
pos,
[360, 220],
order,
["Welcome to Comfyui Kling Wrapper demo. This is a lip sync example generated from text.", "The Reader", "en", 1.0],
outputs=[output_slot("input", LIPSYNC_INPUT_TYPE, slot_index=0)],
)
def lip_sync_audio_input_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} Lip Sync Audio Input"
return node(
node_id,
type_name,
pos,
[360, 240],
order,
["", "", "", 0, 0],
inputs=[input_slot("audio", "AUDIO")],
outputs=[output_slot("input", LIPSYNC_INPUT_TYPE, slot_index=0)],
)
def lip_sync_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} Lip Sync"
return node(
node_id,
type_name,
pos,
[390, 220],
order,
["", "", "", "", 0, 1.0, 1.0],
inputs=[
input_slot("client", CLIENT_TYPE),
input_slot("input", LIPSYNC_INPUT_TYPE),
input_slot("video_id", "STRING"),
],
outputs=[
output_slot("url", "STRING", slot_index=0),
output_slot("video_id", "STRING", slot_index=1),
],
)
def avatar_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} Avatar"
return node(
node_id,
type_name,
pos,
[420, 320],
order,
["std", "", "", "", "Speak naturally with subtle head movement and a friendly expression."],
inputs=[
input_slot("image", "IMAGE"),
input_slot("audio", "AUDIO"),
],
outputs=[
output_slot("url", "STRING", slot_index=0),
output_slot("video_id", "STRING", slot_index=1),
],
)
def effects_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} Effects"
return node(
node_id,
type_name,
pos,
[390, 220],
order,
["yearbook", "kling-v1-6", "std", "5"],
inputs=[
input_slot("client", CLIENT_TYPE),
input_slot("image0", "IMAGE"),
input_slot("image1", "IMAGE", None),
],
outputs=[
output_slot("url", "STRING", slot_index=0),
output_slot("video_id", "STRING", slot_index=1),
],
)
def advanced_element_create_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} Advanced Element Create"
return node(
node_id,
type_name,
pos,
[390, 278],
order,
[
"image_subject",
"demo_subject",
"A clear portrait of the subject with consistent identity traits for reuse in video generation.",
"",
"",
"",
],
inputs=[
input_slot("client", CLIENT_TYPE),
input_slot("image", "IMAGE"),
input_slot("image_list", "IMAGE", None),
],
outputs=[
output_slot("element", ELEMENT_TYPE, slot_index=0),
output_slot("element_id", "STRING", slot_index=1),
output_slot("element_json", "STRING", slot_index=2),
],
)
def element_list_builder_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} Element List Builder"
return node(
node_id,
type_name,
pos,
[340, 180],
order,
[""],
inputs=[input_slot("element_1", ELEMENT_TYPE)],
outputs=[
output_slot("element_list", ELEMENT_LIST_TYPE, slot_index=0),
output_slot("element_list_json", "STRING", slot_index=1),
],
)
def motion_control_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} Motion Control"
return node(
node_id,
type_name,
pos,
[430, 420],
order,
[
"kling-v2-6",
"",
"Transfer the body motion naturally while keeping the subject stable and realistic.",
"",
"pro",
"auto",
"video",
True,
"",
],
inputs=[
input_slot("reference_image", "IMAGE"),
input_slot("reference_video_input", "VIDEO"),
],
outputs=[
output_slot("url", "STRING", slot_index=0),
output_slot("video_id", "STRING", slot_index=1),
],
)
def multimodal_video_edit_node(node_id, pos, order):
type_name = f"{NODE_PREFIX} Multi Modal Video Edit"
return node(
node_id,
type_name,
pos,
[470, 460],
order,
[
"kling-v3-omni",
"Replace the subject's coat with the garment shown in the reference image while preserving motion and camera movement.",
"https://example.com/base-video.mp4",
"",
"base",
False,
"std",
"3",
"16:9",
"",
],
inputs=[input_slot("image_list", "IMAGE", None)],
outputs=[
output_slot("url", "STRING", slot_index=0),
output_slot("video_id", "STRING", slot_index=1),
],
)
def link(link_id, src_node, src_slot, dst_node, dst_slot, type_name):
return [link_id, src_node, src_slot, dst_node, dst_slot, type_name]
def write_json(name, data):
(ROOT / name).write_text(json.dumps(data, indent=2, ensure_ascii=False) + "\n", encoding="utf-8")
def write_examples_readme():
content = """# Comfyui-Kling-Wrapper Examples
This directory contains importable ComfyUI workflow JSON examples and small Python API snippets for `Comfyui-Kling-Wrapper`.
## Before running the workflows
- Create and fill in `config.local.json` in the repository root before importing the workflows.
- You can copy `config.example.json` in the repository root as a starting template.
- The provider is configured globally in `config.local.json` and is intentionally not exposed as a node widget. Use `"provider_default": "official"` for Kling or `"provider_default": "tencent_vod"` for Tencent VOD.
- For Tencent VOD workflows, set `provider_default` to `tencent_vod` and configure `tencent_secret_id`, `tencent_secret_key`, and `tencent_sub_app_id`, or use the `TENCENTCLOUD_SECRET_ID` and `TENCENTCLOUD_SECRET_KEY` environment variables.
- Replace placeholder filenames such as `example_portrait.png`, `example_subject_front.png`, `example_subject_ref_1.png`, `example_cloth.png`, `example_scene.png`, `example_lipsync_source.mp4`, `example_lipsync_audio.wav`, and `example_voice_reference.mp3` with files that exist in your ComfyUI input directory.
- Replace placeholder URLs such as `https://example.com/reference-motion.mp4` with real URLs when needed.
- Native preset and cloned voices are available for `kling-v2-6`; the active API rejects `voice_list` for `kling-v3`.
- `kling-v3-omni` is visible in the video generation dropdowns for comparison with `kling-v3`; `kling-video-o1` remains hidden until live endpoint support is confirmed.
## Important workflow notes
- `05_comfyui_kling_wrapper_text2video_v26_sound.json` is the native audio example and is built around `kling-v2-6`.
- `06_comfyui_kling_wrapper_advanced_element_subject_to_image2video.json` requires 1 frontal portrait plus 1-3 additional photos of the same subject. Background or scene images do not count as advanced-element reference images.
- If you need both subject binding and speech, generate the bound video first and then add speech with the lip-sync or audio nodes.
- `kling-v3-omni` can combine `custom_voice_id` or `custom_voice_list` with `element_list`; older models still keep stricter local guards.
- `Motion Control` accepts either a direct http(s) reference-video URL or uploaded/local video workflow inputs. For local media, use a video loader node that provides either `VIDEO` or `reference_video_frames` plus `reference_video_info`. Set `duration` to `auto` if you want it to match the uploaded motion reference length.
- `Lip Sync` now calls `identify-face` and `advanced-lip-sync`; leave `face_id` empty to use the first detected face.
- `Avatar` accepts one and only one of `AUDIO`, `audio_id`, `audio_file`, or `audio_url`.
- `Image2Video.custom_voice_id` is the single-custom-voice path. For multiple voices, connect `Custom Voice List Builder.custom_voice_list` to `Image2Video.custom_voice_list`, set `sound=on`, and use ordered markers such as `<<<voice_1>>>` and `<<<voice_2>>>`.
## Included files
- `01_comfyui_kling_wrapper_image_generation_v3.json`: basic image generation with a verified `kling-v3` preset.
- `02_comfyui_kling_wrapper_text2video_v3_intelligence.json`: text-to-video with `kling-v3` intelligent multi-shot mode.
- `03_comfyui_kling_wrapper_image2video_v3.json`: single-image to video using the visible 3.0-era model set.
- `04_comfyui_kling_wrapper_multi_images_to_video_v3.json`: multi-image identity-consistent video generation.
- `05_comfyui_kling_wrapper_text2video_v26_sound.json`: `kling-v2-6` talking-head example with native voice presets.
- `06_comfyui_kling_wrapper_advanced_element_subject_to_image2video.json`: advanced custom element creation plus `element_list` binding in image-to-video.
- `07_comfyui_kling_wrapper_motion_control_v26.json`: motion-control workflow centered on a reference image plus uploaded reference-video inputs.
- `08_comfyui_kling_wrapper_virtual_try_on.json`: virtual try-on image workflow.
- `09_comfyui_kling_wrapper_image_expand.json`: image expansion workflow.
- `10_comfyui_kling_wrapper_video_extend_chain.json`: clip generation followed by video extension.
- `11_comfyui_kling_wrapper_text_to_audio.json`: text-to-audio workflow.
- `12_comfyui_kling_wrapper_video_to_audio.json`: video-to-audio workflow.
- `13_comfyui_kling_wrapper_lip_sync_from_text.json`: lip-sync workflow driven by text input.
- `14_comfyui_kling_wrapper_effects_single_image.json`: single-image effects workflow.
- `15_comfyui_kling_wrapper_advanced_element_subject_with_video2audio_music.json`: advanced subject binding followed by `Video2Audio` to add generated music/ambience to the result.
- `16_comfyui_kling_wrapper_video_character_to_image2video.json`: create a `video_character` element from a public `video_url`, then bind that element into `Image2Video`.
- `17_comfyui_kling_wrapper_lip_sync_from_uploaded_audio_video.json`: advanced lip-sync workflow using direct `LoadAudio` and `LoadVideo` uploads.
- `18_comfyui_kling_wrapper_custom_voice_tts_preview.json`: create a custom voice and preview its returned `trial_url`.
- `19_comfyui_kling_wrapper_avatar_from_uploaded_audio_image.json`: create an Avatar video from one image and uploaded audio.
- `20_comfyui_kling_wrapper_custom_voice_image2video.json`: clone a voice and connect its `voice_id` to Kling v2.6 image-to-video.
- `21_tencent_vod_text2video.json`: minimal Tencent VOD text-to-video workflow.
- `22_tencent_vod_image2video.json`: minimal Tencent VOD image-to-video workflow.
- `23_tencent_vod_multi_images_to_video.json`: Tencent VOD multi-image reference generation.
- `24_tencent_vod_motion_control.json`: Tencent VOD motion-control workflow.
- `25_tencent_vod_multimodal_video_edit.json`: Tencent VOD 3.0-Omni video editing with an image reference.
- `26_tencent_vod_advanced_element_create.json`: Tencent VOD advanced subject creation.
- `27_tencent_vod_custom_voice_create.json`: Tencent VOD custom voice creation and trial preview.
- `28_comfyui_kling_wrapper_clothing_dupe.json`: official Kling Clothing Dupe workflow using uploaded video, product/model images, and BGM audio.
- `api_examples.py`: small Python snippets that mirror the same upgraded API wrappers.
"""
(ROOT / "README.md").write_text(content, encoding="utf-8")
def write_api_examples():
content = '''import base64
import os
from pathlib import Path
from py.api import (
AdvancedLipSync,
AdvancedCustomElements,
Avatar,
Client,
CustomVoiceCreate,
FaceIdentify,
Image2Video,
ImageGenerator,
MotionControl,
MultiImages2Video,
TTS,
Text2Video,
)
def image_to_base64(path: str) -> str:
return base64.b64encode(Path(path).read_bytes()).decode("utf-8")
def build_client(in_china: bool = True) -> Client:
access_key = os.environ["KLING_ACCESS_KEY"]
secret_key = os.environ["KLING_SECRET_KEY"]
return Client(access_key, secret_key, in_china=in_china, timeout=30, poll_interval=2.0)
def example_image_generation(client: Client):
task = ImageGenerator()
task.model_name = "kling-v3"
task.prompt = "A cinematic editorial portrait with elegant framing and realistic skin texture."
task.aspect_ratio = "16:9"
task.resolution = "1k"
return task.run(client)
def example_text2video_v3(client: Client):
task = Text2Video()
task.model_name = "kling-v3"
task.prompt = "A traveler walks through an old alley at dusk with cinematic multi-shot storytelling."
task.mode = "pro"
task.aspect_ratio = "16:9"
task.duration = "5"
task.shot_type = "intelligence"
return task.run(client)
def example_text2video_v26_sound(client: Client):
task = Text2Video()
task.model_name = "kling-v2-6"
task.prompt = "A presenter speaks directly to camera in a clean studio."
task.mode = "pro"
task.aspect_ratio = "16:9"
task.duration = "5"
task.sound = "on"
task.voice_list = [{"voice_id": "reader_en_m-v1"}]
return task.run(client)
def example_create_advanced_element(client: Client, frontal_image_url: str, reference_image_urls: list[str]):
if not 1 <= len(reference_image_urls) <= 3:
raise ValueError("Provide 1-3 additional reference image URLs for the same subject.")
task = AdvancedCustomElements()
task.element_name = "demo_subject"
task.element_description = "A clear portrait of the subject with consistent identity traits for reuse in video generation."
task.reference_type = "image_refer"
task.element_image_list = {
"frontal_image": frontal_image_url,
"refer_images": [{"image_url": url} for url in reference_image_urls],
}
return task.run(client)
def example_image2video_with_element(client: Client, image_path: str, element_id: str):
task = Image2Video()
task.model_name = "kling-v3"
task.image = image_to_base64(image_path)
task.prompt = "Keep the same subject identity while the camera slowly pushes in."
task.mode = "pro"
task.duration = "5"
task.element_list = [{"element_id": element_id}]
return task.run(client)
def example_multi_images_to_video(client: Client, image_paths: list[str]):
if len(image_paths) < 2:
raise ValueError("Provide at least two image paths.")
task = MultiImages2Video()
task.model_name = "kling-v3"
encoded = [image_to_base64(path) for path in image_paths]
task.image = encoded[0]
task.image_list = encoded[1:]
task.prompt = "Maintain the same identity across the shot with natural motion."
task.mode = "pro"
task.duration = "5"
task.aspect_ratio = "16:9"
return task.run(client)
def example_motion_control(client: Client, image_path: str, reference_video_url: str):
task = MotionControl()
task.model_name = "kling-v2-6"
task.reference_image = image_to_base64(image_path)
task.reference_video = reference_video_url
task.prompt = "Transfer the motion naturally while keeping the subject stable and realistic."
task.mode = "pro"
task.duration = "5"
return task.run(client)
def example_create_custom_voice(client: Client, voice_url: str):
task = CustomVoiceCreate()
task.voice_name = "Demo Voice"
task.voice_url = voice_url
return task.run(client)
def example_avatar(client: Client, image_path: str, audio_url: str):
task = Avatar()
task.image = image_to_base64(image_path)
task.sound_file = audio_url
task.prompt = "Speak naturally with subtle head movement and a friendly expression."
task.mode = "std"
return task.run(client)
def example_advanced_lip_sync(client: Client, video_url: str, audio_url: str, audio_duration_ms: int):
identify = FaceIdentify()
identify.video_url = video_url
face_result = identify.run(client)
if not face_result.face_data:
raise ValueError("No face was detected in the source video.")
task = AdvancedLipSync()
task.session_id = face_result.session_id
task.face_choose = [{
"face_id": face_result.face_data[0].face_id,
"sound_file": audio_url,
"sound_start_time": 0,
"sound_end_time": audio_duration_ms,
"sound_insert_time": 0,
"sound_volume": 1.0,
"original_audio_volume": 1.0,
}]
return task.run(client)
def example_image2video_with_custom_voice(
client: Client,
image_path: str,
voice_id: str,
dialogue: str,
):
task = Image2Video()
task.model_name = "kling-v2-6"
task.image = image_to_base64(image_path)
task.prompt = f'Portrait subject <<<voice_1>>> says: "{dialogue}"'
task.mode = "pro"
task.duration = "10"
task.sound = "on"
task.voice_list = [{"voice_id": voice_id}]
return task.run(client)
def example_tts_with_voice_id(client: Client, voice_id: str):
task = TTS()
task.text = "这是一段用于测试克隆声音效果的短句。"
task.voice_id = voice_id
task.voice_language = "zh"
task.voice_speed = 1.0
return task.run(client)
if __name__ == "__main__":
print("Set KLING_ACCESS_KEY and KLING_SECRET_KEY before running these examples.")
print("Import this file and call the helper that matches the workflow you want to test.")
'''
(ROOT / "api_examples.py").write_text(content, encoding="utf-8")
def generate_workflows():
examples = {}
nodes = [
client_node(1, 0),
image_generator_node(2, [430, 40], 1),
save_image_node(3, "Comfyui-Kling-Wrapper-image-generation", [900, 60], 2, 2),
]
links = [
link(1, 1, 0, 2, 0, CLIENT_TYPE),
link(2, 2, 0, 3, 0, "IMAGE"),
]
nodes[1]["inputs"][0]["link"] = 1
nodes[1]["outputs"][0]["links"] = [2]
examples["01_comfyui_kling_wrapper_image_generation_v3.json"] = workflow(nodes, links)
nodes = [
client_node(1, 0),
text2video_node(
2,
[430, 20],
1,
"kling-v3",
"A traveler moves through an old alley at dusk, cinematic atmosphere, natural motion, evolving composition with coherent multi-shot storytelling.",
mode="pro",
shot_type="intelligence",
),
preview_video_node(3, [910, 20], 2, 2),
]
links = [
link(1, 1, 0, 2, 0, CLIENT_TYPE),
link(2, 2, 0, 3, 0, "STRING"),
]
nodes[1]["inputs"][0]["link"] = 1
nodes[1]["outputs"][0]["links"] = [2]
examples["02_comfyui_kling_wrapper_text2video_v3_intelligence.json"] = workflow(nodes, links)
nodes = [
client_node(1, 0),
load_image_node(2, "example_portrait.png", [60, 340], 1),
image2video_node(
3,
[430, 200],
2,
"kling-v3",
"A cinematic close-up portrait. The subject breathes naturally, hair and clothing move subtly in the wind, and the camera slowly pushes in.",
mode="pro",
),
preview_video_node(4, [920, 200], 3, 3),
]
links = [
link(1, 1, 0, 3, 0, CLIENT_TYPE),
link(2, 2, 0, 3, 1, "IMAGE"),
link(3, 3, 0, 4, 0, "STRING"),
]
nodes[2]["inputs"][0]["link"] = 1
nodes[2]["inputs"][1]["link"] = 2
nodes[2]["outputs"][0]["links"] = [3]
examples["03_comfyui_kling_wrapper_image2video_v3.json"] = workflow(nodes, links)
nodes = [
client_node(1, 0),
load_image_node(2, "example_subject_a.png", [40, 330], 1),
load_image_node(3, "example_subject_b.png", [40, 700], 2),
image_batch_node(4, [370, 510], 3),
multi_images_to_video_node(5, [700, 420], 4),
preview_video_node(6, [1180, 420], 5, 5),
]
links = [
link(1, 1, 0, 5, 0, CLIENT_TYPE),
link(2, 2, 0, 4, 0, "IMAGE"),
link(3, 3, 0, 4, 1, "IMAGE"),
link(4, 4, 0, 5, 1, "IMAGE"),
link(5, 5, 0, 6, 0, "STRING"),
]
nodes[3]["inputs"][0]["link"] = 2
nodes[3]["inputs"][1]["link"] = 3
nodes[4]["inputs"][0]["link"] = 1
nodes[4]["inputs"][1]["link"] = 4
nodes[4]["outputs"][0]["links"] = [5]
examples["04_comfyui_kling_wrapper_multi_images_to_video_v3.json"] = workflow(nodes, links)
nodes = [
client_node(1, 0),
text2video_node(
2,
[430, 20],
1,
"kling-v2-6",
"A presenter speaks directly to camera in a clean studio, natural gestures, subtle head motion, clear talking-head composition.",
mode="pro",
sound="on",
voice_preset="The Reader | reader_en_m-v1",
),
preview_video_node(3, [910, 20], 2, 2),
]
links = [
link(1, 1, 0, 2, 0, CLIENT_TYPE),
link(2, 2, 0, 3, 0, "STRING"),
]
nodes[1]["inputs"][0]["link"] = 1
nodes[1]["outputs"][0]["links"] = [2]
examples["05_comfyui_kling_wrapper_text2video_v26_sound.json"] = workflow(nodes, links)
nodes = [
client_node(1, 0),
load_image_node(2, "example_subject_front.png", [30, 100], 1),
load_image_node(3, "example_subject_ref_1.png", [30, 470], 2),
load_image_node(4, "example_subject_ref_2.png", [30, 840], 3),
image_batch_node(5, [360, 640], 4),
load_image_node(6, "example_scene.png", [360, 980], 5),
advanced_element_create_node(7, [720, 180], 6),
element_list_builder_node(8, [1160, 180], 7),
image2video_node(
9,
[1160, 500],
8,
"kling-v3",
"Keep the same subject identity while the camera slowly moves and the background remains coherent.",
mode="pro",
),
preview_video_node(10, [1640, 500], 9, 10),
]
links = [
link(1, 1, 0, 7, 0, CLIENT_TYPE),
link(2, 2, 0, 7, 1, "IMAGE"),
link(3, 3, 0, 5, 0, "IMAGE"),
link(4, 4, 0, 5, 1, "IMAGE"),
link(5, 5, 0, 7, 2, "IMAGE"),
link(6, 7, 0, 8, 0, ELEMENT_TYPE),
link(7, 1, 0, 9, 0, CLIENT_TYPE),
link(8, 6, 0, 9, 1, "IMAGE"),
link(9, 8, 0, 9, 4, ELEMENT_LIST_TYPE),
link(10, 9, 0, 10, 0, "STRING"),
]
nodes[6]["inputs"][0]["link"] = 1
nodes[6]["inputs"][1]["link"] = 2
nodes[6]["inputs"][2]["link"] = 5
nodes[4]["inputs"][0]["link"] = 3
nodes[4]["inputs"][1]["link"] = 4
nodes[7]["inputs"][0]["link"] = 6
nodes[8]["inputs"][0]["link"] = 7
nodes[8]["inputs"][1]["link"] = 8
nodes[8]["inputs"].append(input_slot("element_list", ELEMENT_LIST_TYPE, 9))
nodes[8]["outputs"][0]["links"] = [10]
examples["06_comfyui_kling_wrapper_advanced_element_subject_to_image2video.json"] = workflow(nodes, links)
nodes = [
load_image_node(2, "example_motion_subject.png", [40, 260], 1),
load_video_node(3, "example_motion_reference.mp4", [40, 670], 2),
motion_control_node(4, [460, 220], 3),
preview_video_node(5, [980, 220], 4, 3),
]
links = [
link(1, 2, 0, 4, 0, "IMAGE"),
link(2, 3, 0, 4, 1, "VIDEO"),
link(3, 4, 0, 5, 0, "STRING"),
]
nodes[0]["outputs"][0]["links"] = [1]
nodes[1]["outputs"][0]["links"] = [2]
nodes[2]["inputs"][0]["link"] = 1
nodes[2]["inputs"][1]["link"] = 2
nodes[2]["outputs"][0]["links"] = [3]
examples["07_comfyui_kling_wrapper_motion_control_v26.json"] = workflow(nodes, links)
nodes = [
client_node(1, 0),
load_image_node(2, "example_model.png", [40, 150], 1),
load_image_node(3, "example_cloth.png", [40, 520], 2),
virtual_try_on_node(4, [420, 310], 3),
save_image_node(5, "Comfyui-Kling-Wrapper-virtual-try-on", [860, 320], 4, 4),
]
links = [
link(1, 1, 0, 4, 0, CLIENT_TYPE),
link(2, 2, 0, 4, 1, "IMAGE"),
link(3, 3, 0, 4, 2, "IMAGE"),
link(4, 4, 0, 5, 0, "IMAGE"),
]
nodes[3]["inputs"][0]["link"] = 1
nodes[3]["inputs"][1]["link"] = 2
nodes[3]["inputs"][2]["link"] = 3
nodes[3]["outputs"][0]["links"] = [4]
examples["08_comfyui_kling_wrapper_virtual_try_on.json"] = workflow(nodes, links)
nodes = [
client_node(1, 0),
load_image_node(2, "example_expand.png", [40, 220], 1),
image_expander_node(3, [430, 180], 2),
save_image_node(4, "Comfyui-Kling-Wrapper-image-expand", [860, 190], 3, 3),
]
links = [
link(1, 1, 0, 3, 0, CLIENT_TYPE),
link(2, 2, 0, 3, 1, "IMAGE"),
link(3, 3, 0, 4, 0, "IMAGE"),
]
nodes[2]["inputs"][0]["link"] = 1
nodes[2]["inputs"][1]["link"] = 2
nodes[2]["outputs"][0]["links"] = [3]
examples["09_comfyui_kling_wrapper_image_expand.json"] = workflow(nodes, links)
nodes = [
client_node(1, 0),
text2video_node(
2,
[420, 20],
1,
"kling-v3",
"A quiet street scene at sunrise with subtle camera drift and natural environmental motion.",
mode="pro",
),
video_extender_node(3, [870, 40], 2),
preview_video_node(4, [1290, 40], 3, 4),
]
links = [
link(1, 1, 0, 2, 0, CLIENT_TYPE),
link(2, 1, 0, 3, 0, CLIENT_TYPE),
link(3, 2, 1, 3, 1, "STRING"),
link(4, 3, 0, 4, 0, "STRING"),
]
nodes[1]["inputs"][0]["link"] = 1
nodes[2]["inputs"][0]["link"] = 2
nodes[2]["inputs"][1]["link"] = 3
nodes[2]["outputs"][0]["links"] = [4]
examples["10_comfyui_kling_wrapper_video_extend_chain.json"] = workflow(nodes, links)
nodes = [
client_node(1, 0),
text_to_audio_node(2, [430, 80], 1),
preview_audio_node(3, [870, 80], 2, 2),
]
links = [
link(1, 1, 0, 2, 0, CLIENT_TYPE),
link(2, 2, 1, 3, 0, "STRING"),
]
nodes[1]["inputs"][0]["link"] = 1
nodes[1]["outputs"][1]["links"] = [2]
examples["11_comfyui_kling_wrapper_text_to_audio.json"] = workflow(nodes, links)
nodes = [
client_node(1, 0),
text2video_node(
2,
[420, 20],
1,
"kling-v3",
"A person walks through an empty hall with slow cinematic movement.",
mode="pro",
),
video_to_audio_node(3, [880, 30], 2),
preview_audio_node(4, [1330, 30], 3, 4),
]
links = [
link(1, 1, 0, 2, 0, CLIENT_TYPE),
link(2, 1, 0, 3, 0, CLIENT_TYPE),
link(3, 2, 1, 3, 1, "STRING"),
link(4, 3, 3, 4, 0, "STRING"),
]
nodes[1]["inputs"][0]["link"] = 1
nodes[2]["inputs"][0]["link"] = 2
nodes[2]["inputs"][1]["link"] = 3
nodes[2]["outputs"][3]["links"] = [4]
examples["12_comfyui_kling_wrapper_video_to_audio.json"] = workflow(nodes, links)
nodes = [
client_node(1, 0),
text2video_node(
2,
[420, 20],
1,
"kling-v3",
"A portrait subject looks at camera with subtle idle motion.",
mode="pro",
),
lip_sync_text_input_node(3, [420, 420], 2),
lip_sync_node(4, [880, 240], 3),
preview_video_node(5, [1320, 240], 4, 5),
]
links = [
link(1, 1, 0, 2, 0, CLIENT_TYPE),
link(2, 1, 0, 4, 0, CLIENT_TYPE),
link(3, 3, 0, 4, 1, LIPSYNC_INPUT_TYPE),
link(4, 2, 1, 4, 2, "STRING"),
link(5, 4, 0, 5, 0, "STRING"),
]
nodes[1]["inputs"][0]["link"] = 1
nodes[3]["inputs"][0]["link"] = 2
nodes[3]["inputs"][1]["link"] = 3
nodes[3]["inputs"][2]["link"] = 4
nodes[3]["outputs"][0]["links"] = [5]
examples["13_comfyui_kling_wrapper_lip_sync_from_text.json"] = workflow(nodes, links)
nodes = [
client_node(1, 0),
load_image_node(2, "example_effect_input.png", [40, 220], 1),
effects_node(3, [430, 180], 2),
preview_video_node(4, [900, 180], 3, 3),
]
links = [
link(1, 1, 0, 3, 0, CLIENT_TYPE),
link(2, 2, 0, 3, 1, "IMAGE"),
link(3, 3, 0, 4, 0, "STRING"),
]
nodes[2]["inputs"][0]["link"] = 1
nodes[2]["inputs"][1]["link"] = 2
nodes[2]["outputs"][0]["links"] = [3]
examples["14_comfyui_kling_wrapper_effects_single_image.json"] = workflow(nodes, links)
nodes = [
load_audio_node(1, "example_lipsync_audio.wav", [40, 40], 0),
load_video_node(2, "example_lipsync_source.mp4", [40, 300], 1),
lip_sync_audio_input_node(3, [420, 40], 2),
lip_sync_node(4, [860, 180], 3),
preview_video_node(5, [1340, 180], 4, 4),
]
nodes[3]["inputs"] = nodes[3]["inputs"][:2] + [input_slot("video_input", "VIDEO")]
links = [
link(1, 1, 0, 3, 0, "AUDIO"),
link(2, 3, 0, 4, 1, LIPSYNC_INPUT_TYPE),
link(3, 2, 0, 4, 2, "VIDEO"),
link(4, 4, 0, 5, 0, "STRING"),
]
nodes[0]["outputs"][0]["links"] = [1]
nodes[1]["outputs"][0]["links"] = [3]
nodes[2]["inputs"][0]["link"] = 1
nodes[2]["outputs"][0]["links"] = [2]
nodes[3]["inputs"][1]["link"] = 2
nodes[3]["inputs"][2]["link"] = 3
nodes[3]["outputs"][0]["links"] = [4]
examples["17_comfyui_kling_wrapper_lip_sync_from_uploaded_audio_video.json"] = workflow(nodes, links)
nodes = [
load_audio_node(1, "example_voice_reference.mp3", [40, 80], 0),
custom_voice_create_node(2, [420, 80], 1),
preview_audio_node(3, [880, 120], 2, 2),
]
links = [
link(1, 1, 0, 2, 0, "AUDIO"),
link(2, 2, 2, 3, 0, "STRING"),
]
nodes[0]["outputs"][0]["links"] = [1]
nodes[1]["inputs"][0]["link"] = 1
nodes[1]["outputs"][2]["links"] = [2]
nodes[2]["inputs"][0]["link"] = 2
examples["18_comfyui_kling_wrapper_custom_voice_tts_preview.json"] = workflow(nodes, links)
nodes = [
load_image_node(1, "example_avatar_portrait.png", [40, 80], 0),
load_audio_node(2, "example_avatar_speech.wav", [40, 480], 1),
avatar_node(3, [460, 200], 2),
preview_video_node(4, [980, 200], 3, 3),
]
links = [
link(1, 1, 0, 3, 0, "IMAGE"),
link(2, 2, 0, 3, 1, "AUDIO"),
link(3, 3, 0, 4, 0, "STRING"),
]
nodes[0]["outputs"][0]["links"] = [1]
nodes[1]["outputs"][0]["links"] = [2]
nodes[2]["inputs"][0]["link"] = 1
nodes[2]["inputs"][1]["link"] = 2
nodes[2]["outputs"][0]["links"] = [3]
examples["19_comfyui_kling_wrapper_avatar_from_uploaded_audio_image.json"] = workflow(nodes, links)
nodes = [
load_audio_node(1, "example_voice_reference.mp3", [40, 40], 0),
load_image_node(2, "example_talking_portrait.png", [40, 360], 1),
custom_voice_create_node(3, [420, 40], 2),
image2video_node(
4,
[860, 260],
3,
"kling-v2-6",
'The portrait subject <<<voice_1>>> says: "Welcome to this custom voice demonstration."',
mode="pro",
duration="10",
sound="on",
),
preview_video_node(5, [1380, 260], 4, 4),
]
links = [
link(1, 1, 0, 3, 0, "AUDIO"),
link(2, 2, 0, 4, 1, "IMAGE"),
link(3, 3, 0, 4, 3, "STRING"),
link(4, 4, 0, 5, 0, "STRING"),
]
nodes[0]["outputs"][0]["links"] = [1]
nodes[1]["outputs"][0]["links"] = [2]
nodes[2]["inputs"][0]["link"] = 1
nodes[2]["outputs"][0]["links"] = [3]
nodes[3]["inputs"][1]["link"] = 2
nodes[3]["inputs"][3]["link"] = 3
nodes[3]["outputs"][0]["links"] = [4]
examples["20_comfyui_kling_wrapper_custom_voice_image2video.json"] = workflow(nodes, links)
nodes = [
text2video_node(
1,
[60, 60],
0,
"kling-v3",
"A red fox runs through fresh snow, cinematic natural motion.",
mode="std",
duration="3",
),
preview_video_node(2, [580, 60], 1, 1),
]
links = [link(1, 1, 0, 2, 0, "STRING")]
nodes[0]["outputs"][0]["links"] = [1]
examples["21_tencent_vod_text2video.json"] = workflow(nodes, links)
nodes = [
load_image_node(1, "example_portrait.png", [40, 60], 0),
image2video_node(
2,
[390, 60],
1,
"kling-v3",
"The subject turns toward camera while the clothing moves naturally.",
mode="std",
duration="3",
),
preview_video_node(3, [900, 60], 2, 2),
]
links = [
link(1, 1, 0, 2, 1, "IMAGE"),
link(2, 2, 0, 3, 0, "STRING"),
]
nodes[0]["outputs"][0]["links"] = [1]
nodes[1]["inputs"][1]["link"] = 1
nodes[1]["outputs"][0]["links"] = [2]
examples["22_tencent_vod_image2video.json"] = workflow(nodes, links)
nodes = [
load_image_node(1, "example_subject_a.png", [40, 40], 0),
load_image_node(2, "example_subject_b.png", [40, 420], 1),
image_batch_node(3, [390, 230], 2),
multi_images_to_video_node(4, [730, 160], 3),
preview_video_node(5, [1220, 160], 4, 4),
]
links = [
link(1, 1, 0, 3, 0, "IMAGE"),
link(2, 2, 0, 3, 1, "IMAGE"),
link(3, 3, 0, 4, 1, "IMAGE"),
link(4, 4, 0, 5, 0, "STRING"),
]
nodes[0]["outputs"][0]["links"] = [1]
nodes[1]["outputs"][0]["links"] = [2]
nodes[2]["inputs"][0]["link"] = 1
nodes[2]["inputs"][1]["link"] = 2
nodes[2]["outputs"][0]["links"] = [3]
nodes[3]["inputs"][1]["link"] = 3
nodes[3]["outputs"][0]["links"] = [4]
examples["23_tencent_vod_multi_images_to_video.json"] = workflow(nodes, links)
nodes = [
load_image_node(1, "example_portrait.png", [40, 40], 0),
load_video_node(2, "example_motion_reference.mp4", [40, 420], 1),
motion_control_node(3, [430, 170], 2),
preview_video_node(4, [930, 170], 3, 3),
]
links = [
link(1, 1, 0, 3, 0, "IMAGE"),
link(2, 2, 0, 3, 1, "VIDEO"),
link(3, 3, 0, 4, 0, "STRING"),
]
nodes[0]["outputs"][0]["links"] = [1]
nodes[1]["outputs"][0]["links"] = [2]
nodes[2]["inputs"][0]["link"] = 1
nodes[2]["inputs"][1]["link"] = 2
nodes[2]["outputs"][0]["links"] = [3]
examples["24_tencent_vod_motion_control.json"] = workflow(nodes, links)
nodes = [
load_image_node(1, "example_garment_reference.png", [40, 120], 0),
multimodal_video_edit_node(2, [410, 80], 1),
preview_video_node(3, [940, 80], 2, 2),
]
links = [
link(1, 1, 0, 2, 0, "IMAGE"),
link(2, 2, 0, 3, 0, "STRING"),
]
nodes[0]["outputs"][0]["links"] = [1]
nodes[1]["inputs"][0]["link"] = 1
nodes[1]["outputs"][0]["links"] = [2]
examples["25_tencent_vod_multimodal_video_edit.json"] = workflow(nodes, links)
nodes = [
load_image_node(1, "example_subject_front.png", [40, 40], 0),
load_image_node(2, "example_subject_ref_1.png", [40, 420], 1),
image_batch_node(3, [390, 230], 2),
advanced_element_create_node(4, [730, 150], 3),
]
links = [
link(1, 1, 0, 4, 1, "IMAGE"),
link(2, 2, 0, 3, 0, "IMAGE"),
link(3, 3, 0, 4, 2, "IMAGE"),
]
nodes[0]["outputs"][0]["links"] = [1]
nodes[1]["outputs"][0]["links"] = [2]
nodes[2]["inputs"][0]["link"] = 2
nodes[2]["outputs"][0]["links"] = [3]
nodes[3]["inputs"][1]["link"] = 1
nodes[3]["inputs"][2]["link"] = 3
examples["26_tencent_vod_advanced_element_create.json"] = workflow(nodes, links)
nodes = [
load_audio_node(1, "example_voice_reference.mp3", [40, 80], 0),
custom_voice_create_node(2, [420, 80], 1),
preview_audio_node(3, [880, 120], 2, 2),
]
links = [
link(1, 1, 0, 2, 0, "AUDIO"),
link(2, 2, 2, 3, 0, "STRING"),
]
nodes[0]["outputs"][0]["links"] = [1]
nodes[1]["inputs"][0]["link"] = 1
nodes[1]["outputs"][2]["links"] = [2]
nodes[2]["inputs"][0]["link"] = 2
examples["27_tencent_vod_custom_voice_create.json"] = workflow(nodes, links)
nodes = [
load_video_node(1, "example_clothing_reference.mp4", [40, 40], 0),
load_image_node(2, "example_product.png", [40, 250], 1),
load_image_node(3, "example_model.png", [40, 610], 2),
load_audio_node(4, "example_bgm.wav", [40, 980], 3),
clothing_dupe_node(5, [430, 300], 4),
preview_video_node(6, [930, 300], 5, 5),
]
links = [
link(1, 1, 0, 5, 0, "VIDEO"),
link(2, 2, 0, 5, 1, "IMAGE"),
link(3, 3, 0, 5, 6, "IMAGE"),
link(4, 4, 0, 5, 11, "AUDIO"),
link(5, 5, 0, 6, 0, "STRING"),
]
for index, link_id in enumerate((1, 2, 3, 4)):
nodes[index]["outputs"][0]["links"] = [link_id]
nodes[4]["inputs"][0]["link"] = 1
nodes[4]["inputs"][1]["link"] = 2
nodes[4]["inputs"][6]["link"] = 3
nodes[4]["inputs"][11]["link"] = 4
nodes[4]["outputs"][0]["links"] = [5]
examples["28_comfyui_kling_wrapper_clothing_dupe.json"] = workflow(nodes, links)
for name, data in examples.items():
write_json(name, strip_client_dependency(data))
if __name__ == "__main__":
write_examples_readme()
write_api_examples()
generate_workflows()
print(f"Wrote refreshed examples into {ROOT}")
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