Jony
35333b296b
- 新增 K3MotionControl / K3MotionVideoCheck 节点并注册 - K3_video: 生成音频参数改为 metadata.sound - r2_uploader: 新增 upload_image 工具函数 - 移除启动时更新检查弹框
369 lines
14 KiB
Python
369 lines
14 KiB
Python
"""
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K3 图生视频 自研节点（图生视频 / 多镜头）
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模型名根据 模式/时长/音频 动态拼接，不暴露在前端。
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起始帧为必填，仅作图生视频；多镜头功能待实现。
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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 Exception:
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_FOLDER_PATHS_OK = False
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# ── 常量 ──────────────────────────────────────────────────────────────────────
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_MODEL_BASE = "kling-v3" # 动态拼接为 kling-v3-{模式}-{时长}s-{voice}
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_MODES = ["标准", "专家", "4K"]
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_MODE_MAP = {"标准": "std", "专家": "pro", "4K": "4k"}
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_MULTI_SHOT_OPTIONS = [
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"禁用",
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"1个故事板",
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"2个故事板",
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"3个故事板",
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"4个故事板",
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"5个故事板",
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"6个故事板",
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]
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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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# ── 工具函数 ───────────────────────────────────────────────────────────────────
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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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def _prepare_image_base64(tensor) -> str:
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"""转换并校验图片，不符合约束时自动等比缩放后返回 base64。"""
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import io
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import base64
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pil_list = tensor_to_pil(tensor)
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img = pil_list[0].convert("RGB")
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w, h = img.size
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# 1. 宽高比校验（无法通过等比缩放修复，直接报错）
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ratio = w / h
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if ratio < 1 / 2.5 or ratio > 2.5:
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raise RuntimeError(
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f"图片宽高比 {w}:{h}（{ratio:.2f}）超出允许范围 1:2.5 ~ 2.5:1，请裁剪后重试。"
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)
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# 2. 最小尺寸：任意边 < 300px 时等比放大
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if w < 300 or h < 300:
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scale = max(300 / w, 300 / h)
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img = img.resize((int(w * scale), int(h * scale)), resample=1) # LANCZOS=1
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# 3. 文件大小：循环等比缩小直到 ≤ 10MB
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MAX_BYTES = 10 * 1024 * 1024
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for _ in range(20): # 最多迭代 20 次，防止死循环
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buf = io.BytesIO()
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img.save(buf, format="PNG")
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if buf.tell() <= MAX_BYTES:
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break
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scale = (MAX_BYTES / buf.tell()) ** 0.5 * 0.95 # 留 5% 余量
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new_w = int(img.width * scale)
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new_h = int(img.height * scale)
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if new_w < 300 or new_h < 300:
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raise RuntimeError(
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f"图片压缩至 10MB 以内后尺寸（{new_w}x{new_h}）低于最小限制 300px，无法同时满足两项约束。"
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)
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img = img.resize((new_w, new_h), resample=1)
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else:
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raise RuntimeError("图片经过 20 次缩放仍超过 10MB，请检查原始图片。")
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buf.seek(0)
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return base64.b64encode(buf.read()).decode("utf-8")
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# ── 节点 ──────────────────────────────────────────────────────────────────────
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class K3Video:
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"""K3 图生视频 自研"""
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@classmethod
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def INPUT_TYPES(cls):
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required = {
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"多镜头": (_MULTI_SHOT_OPTIONS, {
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"default": "禁用",
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"tooltip": "禁用：单段模式；N个故事板：启用 N 段分镜。",
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}),
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"起始帧": ("IMAGE",),
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"提示词": ("STRING", {"multiline": True, "default": ""}),
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"负向提示词": ("STRING", {"multiline": True, "default": ""}),
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"时长": ([5, 10, 15], {"default": 5}),
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"生成音频": (["关闭", "打开"], {"default": "关闭"}),
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"模式": (_MODES, {"default": "标准"}),
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"seed": ("INT", {
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"default": 0, "min": 0, "max": 2147483647,
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"tooltip": "seed 仅控制节点是否重新运行，结果本身不可复现。",
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}),
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}
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for i in range(1, 7):
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required[f"分镜{i}_提示词"] = ("STRING", {
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"multiline": True, "default": "",
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"tooltip": f"第 {i} 段分镜提示词，最多 512 字符。",
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})
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required[f"分镜{i}_时长"] = ("INT", {
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"default": 4, "min": 1, "max": 15,
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"display": "slider",
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"tooltip": f"第 {i} 段分镜时长（秒）。",
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})
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return {"required": required}
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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, 多镜头, 起始帧, 提示词, 负向提示词, 时长, 生成音频, 模式, seed, **kwargs):
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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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is_multi = 多镜头 != "禁用"
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voice = "voice" if 生成音频 == "打开" else "novoice"
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mode_api = _MODE_MAP[模式]
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if mode_api == "4k":
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model_name = f"{_MODEL_BASE}-4k-{时长}s"
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else:
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model_name = f"{_MODEL_BASE}-{mode_api}-{时长}s-{voice}"
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# ── 多镜头模式 ────────────────────────────────────────────────
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if is_multi:
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shot_count = int(多镜头[0]) # "3个故事板" → 3
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# 收集分镜参数
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multi_prompt = []
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for i in range(1, shot_count + 1):
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p = kwargs.get(f"分镜{i}_提示词", "").strip()
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d = kwargs.get(f"分镜{i}_时长", 0)
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if not p:
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raise RuntimeError(f"多镜头模式错误：第 {i} 段分镜提示词不能为空。")
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if d < 1:
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raise RuntimeError(f"多镜头模式错误：第 {i} 段分镜时长不能小于 1 秒。")
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multi_prompt.append({"index": i, "prompt": p, "duration": str(d)})
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# 校验时长总和
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total = sum(int(s["duration"]) for s in multi_prompt)
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if total != 时长:
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raise RuntimeError(
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f"多镜头模式错误：各分镜时长之和（{total}s）必须等于总时长（{时长}s）。"
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)
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metadata: dict = {
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"multi_shot": "true",
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"shot_type": "customize",
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"multi_prompt": multi_prompt,
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}
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if 生成音频 == "打开":
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metadata["sound"] = "on"
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body: dict = {
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"model": model_name,
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"prompt": 提示词.strip() or " ",
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"mode": mode_api,
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"duration": 时长,
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"image": _prepare_image_base64(起始帧),
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"metadata": metadata,
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}
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if 负向提示词.strip():
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body["negative_prompt"] = 负向提示词.strip()
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# ── 单段图生视频模式 ──────────────────────────────────────────
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else:
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if not 提示词.strip():
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raise RuntimeError("单段模式错误：提示词不能为空。")
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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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"mode": mode_api,
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"duration": 时长,
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"image": _prepare_image_base64(起始帧),
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}
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if 负向提示词.strip():
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body["negative_prompt"] = 负向提示词.strip()
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if 生成音频 == "打开":
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body["metadata"] = {"sound": "on"}
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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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tag = "多镜头" if is_multi else "图生视频"
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def _stage(s: str):
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if s == "submitting":
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print(f"[K3 {tag}] 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"[K3 {tag}] 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(f"[K3 {tag}] 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(f"[K3 {tag}] 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, "k3")
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save_path = os.path.join(video_dir, f"k3_{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"K3 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"[K3 {tag}] 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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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"K3 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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# ── 节点注册 ──────────────────────────────────────────────────────────────────
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NODE_CLASS_MAPPINGS = {
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"K3Video": K3Video,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"K3Video": "K3 图生视频 自研",
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}
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