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
2026-04-24 00:31:21 +08:00
parent fe3cc65b71
commit 5cf5c6b6d6
3 changed files with 242 additions and 2 deletions
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"""
K26 图生视频节点
"""
import asyncio
import json
import os
import re
import aiohttp
from ..utils.config import get_api_key_or_raise, get_api_base_url
from ..utils.image_utils import tensor_to_pil, encode_image_to_base64
try:
from comfy_api.latest import InputImpl
import folder_paths
_FOLDER_PATHS_OK = True
except ImportError:
_FOLDER_PATHS_OK = False
# 模型基础名,运行时动态拼接完整名称
_MODEL_BASE = "kling-v2-6"
# API 端点
_ENDPOINT_CREATE = "/v1/video/generations"
_ENDPOINT_STATUS = "/v1/video/generations/{task_id}"
_POLL_INIT = 3
_POLL_MAX = 15
def _get_video_dir() -> str:
if _FOLDER_PATHS_OK:
base = folder_paths.get_output_directory()
else:
plugin = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
base = os.path.join(os.path.dirname(os.path.dirname(plugin)), "output")
d = os.path.join(base, "video")
os.makedirs(d, exist_ok=True)
return d
def _next_counter(directory: str, prefix: str) -> int:
pattern = re.compile(rf"^{re.escape(prefix)}_(\d+)")
max_n = 0
if os.path.exists(directory):
for f in os.listdir(directory):
m = pattern.match(f)
if m:
max_n = max(max_n, int(m.group(1)))
return max_n + 1
def _image_to_base64(tensor) -> str:
pil = tensor_to_pil(tensor)
return encode_image_to_base64(pil[0], format="PNG")
class KVideo:
"""K26 图生视频节点"""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"起始帧": ("IMAGE",),
"提示词": ("STRING", {"multiline": True, "default": ""}),
"模式": (["pro"],),
"时长": ([5, 10],),
"生成音频": (["关闭", "打开"], {"default": "关闭"}),
},
"optional": {
"尾帧": ("IMAGE",),
},
}
RETURN_TYPES = ("VIDEO",)
RETURN_NAMES = ("视频",)
FUNCTION = "generate"
CATEGORY = "comfyui_o1key/KVideo"
async def generate(self, 起始帧, 提示词, 模式, 时长, 生成音频="关闭", 尾帧=None):
api_key = get_api_key_or_raise()
base_url = get_api_base_url()
headers = {
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json",
}
# ── 动态拼接模型名 ────────────────────────────────────────────
voice = "voice" if 生成音频 == "打开" else "novoice"
model_name = f"{_MODEL_BASE}-{模式}-{时长}s-{voice}"
# ── 构建请求体 ────────────────────────────────────────────────
body = {
"model": model_name,
"prompt": 提示词.strip(),
"image": _image_to_base64(起始帧),
"mode": 模式,
"duration": 时长,
}
if 生成音频 == "打开":
body["generate_audio"] = True
if 尾帧 is not None:
body["metadata"] = {"image_tail": _image_to_base64(尾帧)}
# ── 进度条 ────────────────────────────────────────────────────
try:
from comfy.utils import ProgressBar
pbar = ProgressBar(100)
except Exception:
pbar = None
def _stage(s: str):
if s == "submitting":
print("[K26 图生视频] 提交中...")
if pbar: pbar.update_absolute(0, 100)
elif s.startswith("submitted:"):
print(f"[K26 图生视频] 任务已提交 → {s.split(':', 1)[1]}")
if pbar: pbar.update_absolute(5, 100)
elif s == "downloading":
print("[K26 图生视频] 下载视频...")
if pbar: pbar.update_absolute(99, 100)
elif s == "done":
print("[K26 图生视频] 完成")
if pbar: pbar.update_absolute(100, 100)
def _progress(pct: int):
if pbar: pbar.update_absolute(5 + int(pct * 0.94), 100)
# ── 保存路径 ──────────────────────────────────────────────────
video_dir = _get_video_dir()
counter = _next_counter(video_dir, "k26")
save_path = os.path.join(video_dir, f"k26_{counter:05d}.mp4")
connector = aiohttp.TCPConnector(ssl=False, force_close=True)
async with aiohttp.ClientSession(connector=connector) as session:
# 1. 提交
_stage("submitting")
create_url = f"{base_url}{_ENDPOINT_CREATE}"
async with session.post(create_url, json=body, headers=headers) as resp:
text = await resp.text()
if resp.status != 200:
try:
err = json.loads(text)
msg = err.get("error", {}).get("message") or err.get("message") or text
except Exception:
msg = text
raise RuntimeError(f"K26 提交失败 ({resp.status}): {msg}")
create_resp = json.loads(text)
task_id = (
create_resp.get("task_id")
or create_resp.get("id")
or create_resp.get("data", {}).get("task_id")
)
if not task_id:
raise RuntimeError(f"API 未返回任务 ID,响应:{create_resp}")
_stage(f"submitted:{task_id}")
# 2. 轮询
status_url = f"{base_url}{_ENDPOINT_STATUS.format(task_id=task_id)}"
interval = _POLL_INIT
video_url = None
while True:
async with session.get(status_url, headers=headers) as resp:
text = await resp.text()
if resp.status != 200:
try:
err = json.loads(text)
msg = err.get("error", {}).get("message") or err.get("message") or text
except Exception:
msg = text
raise RuntimeError(f"状态查询失败 ({resp.status}): {msg}")
sr = json.loads(text)
data = sr.get("data", sr)
status = (data.get("status") or sr.get("status") or "").lower()
pct_raw = data.get("progress", 0)
try:
pct = int(str(pct_raw).rstrip("%").strip())
except (ValueError, AttributeError):
pct = 0
print(f"[K26 图生视频] 生成中 {pct}%")
_progress(pct)
if status in ("success", "completed", "done", "finished", "succeed"):
# 提取视频 URL
video_url = (
data.get("video_url")
or data.get("result_url")
or data.get("url")
or (data.get("result", {}) or {}).get("url")
or sr.get("video_url")
or sr.get("url")
)
break
if status in ("failed", "fail"):
err_info = data.get("error") or sr.get("error") or {}
err_msg = (err_info.get("message", "未知错误")
if isinstance(err_info, dict) else str(err_info))
raise RuntimeError(f"K26 生成失败:{err_msg}")
await asyncio.sleep(interval)
interval = min(interval * 1.5, _POLL_MAX)
if not video_url:
raise RuntimeError(f"API 未返回视频 URL,响应:{sr}")
# 3. 下载
_stage("downloading")
async with session.get(video_url, allow_redirects=True) as resp:
if resp.status != 200:
raise RuntimeError(f"视频下载失败 ({resp.status})")
os.makedirs(os.path.dirname(save_path), exist_ok=True)
with open(save_path, "wb") as f:
async for chunk in resp.content.iter_chunked(8192):
f.write(chunk)
_stage("done")
if _FOLDER_PATHS_OK:
return (InputImpl.VideoFromFile(save_path),)
return (save_path,)
NODE_CLASS_MAPPINGS = {
"KVideo": KVideo,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"KVideo": "K26 图生视频",
}
+2 -1
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@@ -20,5 +20,6 @@ from .batch_images_o1key import BatchImagesO1key
from .seedance_video import Seedance, SeedanceMultiModal
from .doubao_image import DoubaoImage
from .gpt_image import O1keyGPTImage
from .K_video import KVideo
__all__ = ['NanoBananaPro', 'BatchNanoBananaPro', 'GoogleGemini', 'LoadFile', 'ImageStitchPro', 'SaveCleanImage', 'BatchCleanMetadata', 'VideoPreview', 'KlingVideo', 'KlingFirstLastFrame', 'KlingMotionControlTest', 'AspectRatioPreset', 'GoogleVeo', 'FluxImageEdit', 'UniversalLLMChat', 'MultiResPreview', 'BatchImagesO1key', 'Seedance', 'SeedanceMultiModal', 'StreamPreview', 'DoubaoImage', 'O1keyGPTImage']
__all__ = ['NanoBananaPro', 'BatchNanoBananaPro', 'GoogleGemini', 'LoadFile', 'ImageStitchPro', 'SaveCleanImage', 'BatchCleanMetadata', 'VideoPreview', 'KlingVideo', 'KlingFirstLastFrame', 'KlingMotionControlTest', 'AspectRatioPreset', 'GoogleVeo', 'FluxImageEdit', 'UniversalLLMChat', 'MultiResPreview', 'BatchImagesO1key', 'Seedance', 'SeedanceMultiModal', 'StreamPreview', 'DoubaoImage', 'O1keyGPTImage', 'KVideo']