feat: 新增 K26 图生视频节点
- 新增 nodes/K_video.py，节点显示名称「K26 图生视频」
- 支持起始帧（必填）、尾帧（可选）图片输入
- 参数：提示词、模式(pro)、时长(5/10s)、生成音频(关闭/打开)
- 模型名按规则动态拼接：kling-v2-6-{mode}-{dur}s-{voice}
- 尾帧有输入时通过 metadata.image_tail 传参
- 走三段式流程：提交 → 轮询 → 下载，带进度条
- 注册至 NODE_CLASS_MAPPINGS / NODE_DISPLAY_NAME_MAPPINGS
This commit is contained in:
Jony
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@@ -21,7 +21,7 @@ except Exception:
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import ssl
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from .nodes import NanoBananaPro, BatchNanoBananaPro, GoogleGemini, LoadFile, ImageStitchPro, SaveCleanImage, BatchCleanMetadata, VideoPreview, GoogleVeo, FluxImageEdit, UniversalLLMChat, KlingVideo, KlingFirstLastFrame, KlingMotionControlTest, AspectRatioPreset, MultiResPreview, BatchImagesO1key, Seedance, SeedanceMultiModal, StreamPreview, DoubaoImage, O1keyGPTImage
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from .nodes import NanoBananaPro, BatchNanoBananaPro, GoogleGemini, LoadFile, ImageStitchPro, SaveCleanImage, BatchCleanMetadata, VideoPreview, GoogleVeo, FluxImageEdit, UniversalLLMChat, KlingVideo, KlingFirstLastFrame, KlingMotionControlTest, AspectRatioPreset, MultiResPreview, BatchImagesO1key, Seedance, SeedanceMultiModal, StreamPreview, DoubaoImage, O1keyGPTImage, KVideo
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# 报错弹框友好文案（不修改原节点代码，仅在外层统一处理）
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_MSG_TIMEOUT = "API 请求超时，请稍后重试或检查网络。"
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@@ -80,6 +80,7 @@ NODE_CLASS_MAPPINGS = {
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"StreamPreview": StreamPreview,
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"DoubaoImage": DoubaoImage,
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"O1keyGPTImage": O1keyGPTImage,
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"KVideo": KVideo,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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@@ -105,6 +106,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
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"StreamPreview": "流式文本预览",
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"DoubaoImage": "豆包生图",
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"O1keyGPTImage": "o1key GPT Image",
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"KVideo": "K26 图生视频",
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}
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WEB_DIRECTORY = "./web"
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@@ -0,0 +1,237 @@
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"""
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K26 图生视频节点
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"""
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import asyncio
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import json
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import os
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import re
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import aiohttp
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from ..utils.config import get_api_key_or_raise, get_api_base_url
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from ..utils.image_utils import tensor_to_pil, encode_image_to_base64
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try:
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from comfy_api.latest import InputImpl
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import folder_paths
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_FOLDER_PATHS_OK = True
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except ImportError:
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_FOLDER_PATHS_OK = False
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# 模型基础名，运行时动态拼接完整名称
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_MODEL_BASE = "kling-v2-6"
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# API 端点
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_ENDPOINT_CREATE = "/v1/video/generations"
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_ENDPOINT_STATUS = "/v1/video/generations/{task_id}"
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_POLL_INIT = 3
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_POLL_MAX = 15
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def _get_video_dir() -> str:
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if _FOLDER_PATHS_OK:
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base = folder_paths.get_output_directory()
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else:
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plugin = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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base = os.path.join(os.path.dirname(os.path.dirname(plugin)), "output")
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d = os.path.join(base, "video")
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os.makedirs(d, exist_ok=True)
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return d
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def _next_counter(directory: str, prefix: str) -> int:
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pattern = re.compile(rf"^{re.escape(prefix)}_(\d+)")
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max_n = 0
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if os.path.exists(directory):
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for f in os.listdir(directory):
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m = pattern.match(f)
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if m:
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max_n = max(max_n, int(m.group(1)))
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return max_n + 1
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def _image_to_base64(tensor) -> str:
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pil = tensor_to_pil(tensor)
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return encode_image_to_base64(pil[0], format="PNG")
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class KVideo:
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"""K26 图生视频节点"""
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"起始帧": ("IMAGE",),
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"提示词": ("STRING", {"multiline": True, "default": ""}),
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"模式": (["pro"],),
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"时长": ([5, 10],),
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"生成音频": (["关闭", "打开"], {"default": "关闭"}),
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},
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"optional": {
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"尾帧": ("IMAGE",),
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},
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}
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RETURN_TYPES = ("VIDEO",)
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RETURN_NAMES = ("视频",)
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FUNCTION = "generate"
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CATEGORY = "comfyui_o1key/KVideo"
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async def generate(self, 起始帧, 提示词, 模式, 时长, 生成音频="关闭", 尾帧=None):
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api_key = get_api_key_or_raise()
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base_url = get_api_base_url()
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headers = {
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"Authorization": f"Bearer {api_key}",
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"Content-Type": "application/json",
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}
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# ── 动态拼接模型名 ────────────────────────────────────────────
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voice = "voice" if 生成音频 == "打开" else "novoice"
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model_name = f"{_MODEL_BASE}-{模式}-{时长}s-{voice}"
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# ── 构建请求体 ────────────────────────────────────────────────
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body = {
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"model": model_name,
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"prompt": 提示词.strip(),
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"image": _image_to_base64(起始帧),
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"mode": 模式,
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"duration": 时长,
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}
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if 生成音频 == "打开":
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body["generate_audio"] = True
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if 尾帧 is not None:
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body["metadata"] = {"image_tail": _image_to_base64(尾帧)}
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# ── 进度条 ────────────────────────────────────────────────────
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try:
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from comfy.utils import ProgressBar
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pbar = ProgressBar(100)
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except Exception:
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pbar = None
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def _stage(s: str):
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if s == "submitting":
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print("[K26 图生视频] 提交中...")
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if pbar: pbar.update_absolute(0, 100)
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elif s.startswith("submitted:"):
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print(f"[K26 图生视频] 任务已提交 → {s.split(':', 1)[1]}")
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if pbar: pbar.update_absolute(5, 100)
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elif s == "downloading":
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print("[K26 图生视频] 下载视频...")
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if pbar: pbar.update_absolute(99, 100)
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elif s == "done":
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print("[K26 图生视频] 完成")
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if pbar: pbar.update_absolute(100, 100)
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def _progress(pct: int):
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if pbar: pbar.update_absolute(5 + int(pct * 0.94), 100)
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# ── 保存路径 ──────────────────────────────────────────────────
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video_dir = _get_video_dir()
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counter = _next_counter(video_dir, "k26")
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save_path = os.path.join(video_dir, f"k26_{counter:05d}.mp4")
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connector = aiohttp.TCPConnector(ssl=False, force_close=True)
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async with aiohttp.ClientSession(connector=connector) as session:
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# 1. 提交
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_stage("submitting")
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create_url = f"{base_url}{_ENDPOINT_CREATE}"
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async with session.post(create_url, json=body, headers=headers) as resp:
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text = await resp.text()
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if resp.status != 200:
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try:
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err = json.loads(text)
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msg = err.get("error", {}).get("message") or err.get("message") or text
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except Exception:
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msg = text
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raise RuntimeError(f"K26 提交失败 ({resp.status}): {msg}")
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create_resp = json.loads(text)
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task_id = (
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create_resp.get("task_id")
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or create_resp.get("id")
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or create_resp.get("data", {}).get("task_id")
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)
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if not task_id:
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raise RuntimeError(f"API 未返回任务 ID，响应：{create_resp}")
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_stage(f"submitted:{task_id}")
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# 2. 轮询
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status_url = f"{base_url}{_ENDPOINT_STATUS.format(task_id=task_id)}"
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interval = _POLL_INIT
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video_url = None
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while True:
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async with session.get(status_url, headers=headers) as resp:
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text = await resp.text()
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if resp.status != 200:
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try:
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err = json.loads(text)
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msg = err.get("error", {}).get("message") or err.get("message") or text
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except Exception:
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msg = text
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raise RuntimeError(f"状态查询失败 ({resp.status}): {msg}")
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sr = json.loads(text)
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data = sr.get("data", sr)
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status = (data.get("status") or sr.get("status") or "").lower()
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pct_raw = data.get("progress", 0)
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try:
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pct = int(str(pct_raw).rstrip("%").strip())
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except (ValueError, AttributeError):
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pct = 0
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print(f"[K26 图生视频] 生成中 {pct}%")
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_progress(pct)
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if status in ("success", "completed", "done", "finished", "succeed"):
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# 提取视频 URL
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video_url = (
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data.get("video_url")
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or data.get("result_url")
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or data.get("url")
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or (data.get("result", {}) or {}).get("url")
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or sr.get("video_url")
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or sr.get("url")
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)
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break
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if status in ("failed", "fail"):
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err_info = data.get("error") or sr.get("error") or {}
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err_msg = (err_info.get("message", "未知错误")
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if isinstance(err_info, dict) else str(err_info))
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raise RuntimeError(f"K26 生成失败：{err_msg}")
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await asyncio.sleep(interval)
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interval = min(interval * 1.5, _POLL_MAX)
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if not video_url:
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raise RuntimeError(f"API 未返回视频 URL，响应：{sr}")
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# 3. 下载
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_stage("downloading")
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async with session.get(video_url, allow_redirects=True) as resp:
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if resp.status != 200:
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raise RuntimeError(f"视频下载失败 ({resp.status})")
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os.makedirs(os.path.dirname(save_path), exist_ok=True)
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with open(save_path, "wb") as f:
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async for chunk in resp.content.iter_chunked(8192):
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f.write(chunk)
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_stage("done")
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if _FOLDER_PATHS_OK:
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return (InputImpl.VideoFromFile(save_path),)
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return (save_path,)
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NODE_CLASS_MAPPINGS = {
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"KVideo": KVideo,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"KVideo": "K26 图生视频",
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}
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+2
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@@ -20,5 +20,6 @@ from .batch_images_o1key import BatchImagesO1key
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from .seedance_video import Seedance, SeedanceMultiModal
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from .doubao_image import DoubaoImage
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from .gpt_image import O1keyGPTImage
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from .K_video import KVideo
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__all__ = ['NanoBananaPro', 'BatchNanoBananaPro', 'GoogleGemini', 'LoadFile', 'ImageStitchPro', 'SaveCleanImage', 'BatchCleanMetadata', 'VideoPreview', 'KlingVideo', 'KlingFirstLastFrame', 'KlingMotionControlTest', 'AspectRatioPreset', 'GoogleVeo', 'FluxImageEdit', 'UniversalLLMChat', 'MultiResPreview', 'BatchImagesO1key', 'Seedance', 'SeedanceMultiModal', 'StreamPreview', 'DoubaoImage', 'O1keyGPTImage']
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__all__ = ['NanoBananaPro', 'BatchNanoBananaPro', 'GoogleGemini', 'LoadFile', 'ImageStitchPro', 'SaveCleanImage', 'BatchCleanMetadata', 'VideoPreview', 'KlingVideo', 'KlingFirstLastFrame', 'KlingMotionControlTest', 'AspectRatioPreset', 'GoogleVeo', 'FluxImageEdit', 'UniversalLLMChat', 'MultiResPreview', 'BatchImagesO1key', 'Seedance', 'SeedanceMultiModal', 'StreamPreview', 'DoubaoImage', 'O1keyGPTImage', 'KVideo']
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