feat: 接入 Seedance 视频节点并增强图像节点功能

- 新增 Seedance 文生视频、图生视频、首尾帧生视频三个节点
- 新增 seedance_client.py 客户端
- 为 NanoBananaPro、BatchNanoBananaPro、全能生图节点添加「跳过错误」开关，出错时返回占位图以继续队列
- 修复 nano-banana-2-限时特价 动态端点路由（按分辨率选择）
- 统一分辨率选项命名：512 → 512px

Co-Authored-By: Claude Sonnet 4.5 <[email protected]>

__init__.py

@@ -21,7 +21,7 @@ except Exception:
 
 import ssl
 
-from .nodes import NanoBananaPro, BatchNanoBananaPro, GoogleGemini, LoadFile, ImageStitchPro, SaveCleanImage, BatchCleanMetadata, VideoPreview, GoogleVeo, FluxImageEdit, UniversalLLMChat, KlingVideo, KlingFirstLastFrame, KlingMotionControlTest, QuanNengShengTu, BatchQuanNengShengTu, AspectRatioPreset, MultiResPreview, BatchImagesO1key
+from .nodes import NanoBananaPro, BatchNanoBananaPro, GoogleGemini, LoadFile, ImageStitchPro, SaveCleanImage, BatchCleanMetadata, VideoPreview, GoogleVeo, FluxImageEdit, UniversalLLMChat, KlingVideo, KlingFirstLastFrame, KlingMotionControlTest, QuanNengShengTu, BatchQuanNengShengTu, AspectRatioPreset, MultiResPreview, BatchImagesO1key, SeedanceT2V, SeedanceI2V, SeedanceFlipFlop
 
 # 报错弹框友好文案（不修改原节点代码，仅在外层统一处理）
 _MSG_TIMEOUT = "API 请求超时，请稍后重试或检查网络。"
@@ -79,6 +79,9 @@ NODE_CLASS_MAPPINGS = {
     "AspectRatioPreset": AspectRatioPreset,
     "MultiResPreview": MultiResPreview,
     "BatchImagesO1key": BatchImagesO1key,
+    "SeedanceT2V": SeedanceT2V,
+    "SeedanceI2V": SeedanceI2V,
+    "SeedanceFlipFlop": SeedanceFlipFlop,
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
@@ -101,6 +104,9 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "AspectRatioPreset": "图片宽高比预设",
     "MultiResPreview": "预览图像（v2）",
     "BatchImagesO1key": "加载图像（批量）",
+    "SeedanceT2V": "Seedance 文生视频",
+    "SeedanceI2V": "Seedance 图生视频",
+    "SeedanceFlipFlop": "Seedance 首尾帧生视频",
 }
 
 WEB_DIRECTORY = "./web"

clients/gemini_client.py

@@ -62,8 +62,20 @@ class GeminiAPIClient(BaseAPIClient):
             else:
                 return "/v1beta/models/nano-banana-pro-2k:generateContent"
 
+        elif model == "nano-banana-2-限时特价":
+            if resolution == "512px":
+                return "/v1beta/models/nano-banana-2-0.5k:generateContent"
+            elif resolution == "1K":
+                return "/v1beta/models/nano-banana-2-1k:generateContent"
+            elif resolution == "2K":
+                return "/v1beta/models/nano-banana-2-2k:generateContent"
+            elif resolution == "4K":
+                return "/v1beta/models/nano-banana-2-4k:generateContent"
+            else:
+                return "/v1beta/models/nano-banana-2-2k:generateContent"
+
         elif model == "nano-banana-2-官方计费":
-            if resolution == "512":
+            if resolution == "512px":
                 return "/v1beta/models/nano-banana-2-0.5k-official:generateContent"
             elif resolution == "1K":
                 return "/v1beta/models/nano-banana-2-1k-official:generateContent"

clients/seedance_client.py

@@ -0,0 +1,183 @@
+"""
+Seedance 视频生成客户端
+使用 new-api 原生格式：POST /v1/video/generations → GET /v1/video/generations/{task_id}
+"""
+
+import asyncio
+import json
+import os
+from typing import Any, Callable, Dict, Optional
+
+import aiohttp
+
+from ..utils.config import get_api_key_or_raise, get_api_base_url
+
+
+class SeedanceClient:
+    """Seedance 视频生成客户端（new-api 原生三段式）"""
+
+    # 提交任务
+    CREATE_ENDPOINT = "/v1/video/generations"
+    # 查询任务状态：{task_id} 占位
+    STATUS_ENDPOINT = "/v1/video/generations/{task_id}"
+
+    POLL_INITIAL_INTERVAL = 4   # 首次轮询等待秒数
+    POLL_MAX_INTERVAL = 15      # 最大轮询间隔秒数
+
+    # new-api 返回的成功状态值
+    SUCCESS_STATUSES = {"succeeded", "success", "completed", "done", "finished"}
+    FAILURE_STATUSES = {"failed", "fail", "error", "expired"}
+
+    def __init__(self):
+        self.api_key = get_api_key_or_raise()
+        self.base_url = get_api_base_url()
+
+    def _headers(self) -> Dict[str, str]:
+        return {
+            "Authorization": f"Bearer {self.api_key}",
+            "Content-Type": "application/json",
+        }
+
+    # ── 1. 提交任务 ────────────────────────────────────────────────────
+
+    async def submit_async(
+        self,
+        body: Dict[str, Any],
+        session: aiohttp.ClientSession,
+    ) -> str:
+        """提交视频生成任务，返回 task_id"""
+        url = f"{self.base_url}{self.CREATE_ENDPOINT}"
+        async with session.post(url, json=body, headers=self._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"提交失败 ({resp.status}): {msg}")
+            data = json.loads(text)
+
+        # new-api 返回字段：id / task_id
+        task_id = data.get("id") or data.get("task_id")
+        if not task_id:
+            raise RuntimeError(f"API 未返回任务 ID，响应：{data}")
+        return task_id
+
+    # ── 2. 轮询状态 ────────────────────────────────────────────────────
+
+    async def poll_async(
+        self,
+        task_id: str,
+        session: aiohttp.ClientSession,
+        on_progress: Optional[Callable[[int], None]] = None,
+    ) -> str:
+        """轮询任务状态，成功后返回视频 URL"""
+        url = f"{self.base_url}{self.STATUS_ENDPOINT.format(task_id=task_id)}"
+        interval = self.POLL_INITIAL_INTERVAL
+
+        while True:
+            async with session.get(url, headers=self._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}")
+                result = json.loads(text)
+
+            status = (result.get("status") or "").lower()
+
+            # 调试：打印原始响应（排查状态字段问题后可删除）
+            print(f"[Seedance][DEBUG] 原始响应: {result}")
+
+            # 解析进度
+            progress_raw = result.get("progress", "0")
+            try:
+                progress_pct = int(str(progress_raw).rstrip("%").strip())
+            except (ValueError, AttributeError):
+                progress_pct = 0
+
+            print(f"[Seedance] 生成中 {progress_pct}%  (status={status})")
+            if on_progress:
+                on_progress(progress_pct)
+
+            if status in self.SUCCESS_STATUSES:
+                # 取视频 URL：url / metadata.url / output.video_url
+                video_url = (
+                    result.get("url")
+                    or (result.get("output") or {}).get("video_url")
+                    or (result.get("metadata") or {}).get("url")
+                )
+                if not video_url:
+                    raise RuntimeError(f"任务成功但未找到视频 URL，响应：{result}")
+                return video_url
+
+            if status in self.FAILURE_STATUSES:
+                reason = (
+                    result.get("fail_reason")
+                    or (result.get("error") or {}).get("message")
+                    or "未知错误"
+                )
+                raise RuntimeError(f"视频生成失败：{reason}")
+
+            await asyncio.sleep(interval)
+            interval = min(interval * 1.5, self.POLL_MAX_INTERVAL)
+
+    # ── 3. 下载视频 ────────────────────────────────────────────────────
+
+    async def download_async(
+        self,
+        video_url: str,
+        save_path: str,
+        session: aiohttp.ClientSession,
+    ) -> str:
+        """下载视频到本地，返回本地路径"""
+        print(f"[Seedance] 下载视频...")
+        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)
+        return save_path
+
+    # ── 全流程入口（供节点调用）────────────────────────────────────────
+
+    async def generate_async(
+        self,
+        body: Dict[str, Any],
+        save_path: str,
+        on_stage: Optional[Callable[[str], None]] = None,
+        on_progress: Optional[Callable[[int], None]] = None,
+    ) -> str:
+        """提交 → 轮询 → 下载，返回本地文件路径"""
+        connector = aiohttp.TCPConnector(force_close=True)
+        async with aiohttp.ClientSession(connector=connector) as session:
+
+            # 提交
+            if on_stage:
+                on_stage("submitting")
+            task_id = await self.submit_async(body, session)
+            print(f"[Seedance] 任务已提交 → {task_id}")
+            if on_stage:
+                on_stage(f"submitted:{task_id}")
+
+            # 轮询
+            video_url = await self.poll_async(task_id, session, on_progress=on_progress)
+
+            # 下载
+            if on_stage:
+                on_stage("downloading")
+            path = await self.download_async(video_url, save_path, session)
+
+            if on_stage:
+                on_stage("done")
+            return path

models_config.py

@@ -67,15 +67,15 @@ GEMINI_MODELS = [
     },
     {
         "id": "nano-banana-2-限时特价",
-        "description": "Nano Banana 2 限时特价，固定端点，图像生成模型",
+        "description": "Nano Banana 2 限时特价，根据分辨率自动选择端点 (512px/1K/2K/4K)，图像生成模型",
         "enabled": True,
-        "endpoint_type": "standard",
+        "endpoint_type": "dynamic",
-        "endpoint": "/v1beta/models/nano-banana-2:generateContent",
+        "endpoint": None,  # 动态端点，由代码根据分辨率选择
         "supported_aspect_ratios": [
             "1:1", "1:4", "1:8", "2:3", "3:2", "3:4", "4:1", "4:3", "4:5", "5:4",
             "8:1", "9:16", "16:9", "21:9"
         ],
-        "supported_resolutions": ["512", "1K", "2K", "4K"]
+        "supported_resolutions": ["512px", "1K", "2K", "4K"]
     },
     {
         "id": "nano-banana-2-官方计费",
@@ -87,7 +87,7 @@ GEMINI_MODELS = [
             "1:1", "1:4", "1:8", "2:3", "3:2", "3:4", "4:1", "4:3", "4:5", "5:4",
             "8:1", "9:16", "16:9", "21:9"
         ],
-        "supported_resolutions": ["512", "1K", "2K", "4K"]
+        "supported_resolutions": ["512px", "1K", "2K", "4K"]
     },
     {
         "id": "gemini-3-pro-image-preview",
@@ -110,7 +110,7 @@ GEMINI_MODELS = [
             "1:1", "1:4", "1:8", "2:3", "3:2", "3:4", "4:1", "4:3", "4:5", "5:4",
             "8:1", "9:16", "16:9", "21:9"
         ],
-        "supported_resolutions": ["512", "1K", "2K", "4K"]
+        "supported_resolutions": ["512px", "1K", "2K", "4K"]
     }
 ]
 
@@ -329,7 +329,7 @@ def get_all_supported_resolutions() -> List[str]:
         >>> get_all_supported_resolutions()
         ['512', '1K', '2K', '4K']
     """
-    _ORDER = ["512", "1K", "2K", "4K"]
+    _ORDER = ["512px", "1K", "2K", "4K"]
 
     seen = set()
     for model in GEMINI_MODELS:

nodes/__init__.py

@@ -20,5 +20,6 @@ from .multi_res_preview import MultiResPreview
 from .batch_images_o1key import BatchImagesO1key
 from .nano_banana_v2 import NanaBananaV2
 from .batch_nano_banana_v2 import BatchNanaBananaV2
+from .seedance_video import SeedanceT2V, SeedanceI2V, SeedanceFlipFlop
 
-__all__ = ['NanoBananaPro', 'BatchNanoBananaPro', 'GoogleGemini', 'LoadFile', 'ImageStitchPro', 'SaveCleanImage', 'BatchCleanMetadata', 'VideoPreview', 'KlingVideo', 'KlingFirstLastFrame', 'KlingMotionControlTest', 'AspectRatioPreset', 'GoogleVeo', 'FluxImageEdit', 'UniversalLLMChat', 'QuanNengShengTu', 'BatchQuanNengShengTu', 'MultiResPreview', 'BatchImagesO1key', 'NanaBananaV2', 'BatchNanaBananaV2']
+__all__ = ['NanoBananaPro', 'BatchNanoBananaPro', 'GoogleGemini', 'LoadFile', 'ImageStitchPro', 'SaveCleanImage', 'BatchCleanMetadata', 'VideoPreview', 'KlingVideo', 'KlingFirstLastFrame', 'KlingMotionControlTest', 'AspectRatioPreset', 'GoogleVeo', 'FluxImageEdit', 'UniversalLLMChat', 'QuanNengShengTu', 'BatchQuanNengShengTu', 'MultiResPreview', 'BatchImagesO1key', 'NanaBananaV2', 'BatchNanaBananaV2', 'SeedanceT2V', 'SeedanceI2V', 'SeedanceFlipFlop']

nodes/batch_nano_banana_pro.py

@@ -134,7 +134,7 @@ class BatchNanoBananaPro:
     ]
     
     # 支持的分辨率列表（全量兜底，实际由 get_all_supported_resolutions() 动态生成）
-    RESOLUTIONS = ["512", "1K", "2K", "4K"]
+    RESOLUTIONS = ["512px", "1K", "2K", "4K"]
     
     # 配对模式
     PAIRING_MODES = ["按相同图片命名", "1*N", "不配对"]
@@ -298,6 +298,11 @@ class BatchNanoBananaPro:
                 "保存路径": ("STRING", {
                     "default": "",
                     "multiline": False
+                }),
+                "跳过错误": ("BOOLEAN", {
+                    "default": False,
+                    "label_on": "打开",
+                    "label_off": "关闭"
                 })
             },
             "optional": optional_inputs
@@ -775,6 +780,7 @@ class BatchNanoBananaPro:
         模型: str,
         宽高比: str,
         分辨率: str,
+        跳过错误: bool = False,
         保存路径: str = "",
         **kwargs
     ) -> Tuple[torch.Tensor]:
@@ -1089,19 +1095,30 @@ class BatchNanoBananaPro:
                 # 用户输入错误 - 打印完整错误信息
                 error_msg = str(e)
                 print(f"BatchNanoBananaPro: ❌ {error_msg}")
+            if 跳过错误:
+                print("BatchNanoBananaPro: ⚠️ 跳过错误已开启，返回占位图继续执行队列")
+                placeholder = Image.new('RGB', (512, 512), color=(128, 128, 128))
+                return (pil_to_tensor([placeholder]),)
             raise ValueError(error_msg) from None
-        
+
         except RuntimeError as e:
             # 打印完整错误信息
             error_full = str(e)
             print(f"BatchNanoBananaPro: ❌ {error_full}")
+            if 跳过错误:
+                print("BatchNanoBananaPro: ⚠️ 跳过错误已开启，返回占位图继续执行队列")
+                placeholder = Image.new('RGB', (512, 512), color=(128, 128, 128))
+                return (pil_to_tensor([placeholder]),)
             raise RuntimeError(error_full) from None
-        
+
         except Exception as e:
             # 其他未知错误 - 打印完整错误信息
             error_msg = str(e)
             print(f"BatchNanoBananaPro: ❌ {error_msg}")
-            
+            if 跳过错误:
+                print("BatchNanoBananaPro: ⚠️ 跳过错误已开启，返回占位图继续执行队列")
+                placeholder = Image.new('RGB', (512, 512), color=(128, 128, 128))
+                return (pil_to_tensor([placeholder]),)
             raise type(e)(error_msg) from None
         
         finally:

nodes/nano_banana_pro.py

@@ -52,10 +52,10 @@ except ImportError:
 # ============================================================================
 # 是否启用调试日志（打印完整的 API 响应内容）
 # 设置为 True 以启用调试日志，False 以禁用
-DEBUG_LOG_ENABLED = False
+DEBUG_LOG_ENABLED = True
 # 是否启用请求体日志（打印发送给 API 的请求体，base64 图片数据将自动截断）
 # 设置为 True 以启用请求体日志，False 以禁用
-REQUEST_LOG_ENABLED = False
+REQUEST_LOG_ENABLED = True
 # ============================================================================
 
 _NODE = "Nano Banana Pro"
@@ -119,7 +119,7 @@ class NanoBananaPro:
     ]
     
     # 支持的分辨率列表（全量兜底，实际由 get_all_supported_resolutions() 动态生成）
-    RESOLUTIONS = ["512", "1K", "2K", "4K"]
+    RESOLUTIONS = ["512px", "1K", "2K", "4K"]
     
     def __init__(self):
         """初始化节点"""
@@ -199,6 +199,11 @@ class NanoBananaPro:
                     "default": 0,
                     "min": 0,
                     "max": 0xffffffffffffffff
+                }),
+                "跳过错误": ("BOOLEAN", {
+                    "default": False,
+                    "label_on": "打开",
+                    "label_off": "关闭"
                 })
             },
             "optional": optional_inputs
@@ -452,6 +457,7 @@ class NanoBananaPro:
         像素缩放: bool,
         分辨率像素: float,
         seed: int,
+        跳过错误: bool = False,
         **kwargs
     ) -> Tuple[torch.Tensor]:
         """
@@ -873,18 +879,30 @@ class NanoBananaPro:
                 # 用户输入错误 - 打印完整错误信息
                 error_msg = str(e)
                 print(f"Nano Banana Pro: ❌ {error_msg}")
+            if 跳过错误:
+                print("Nano Banana Pro: ⚠️ 跳过错误已开启，返回占位图继续执行队列")
+                placeholder = Image.new('RGB', (512, 512), color=(128, 128, 128))
+                return (pil_to_tensor([placeholder]),)
             raise ValueError(error_msg) from None
-        
+
         except RuntimeError as e:
             # 打印完整错误信息
             error_full = str(e)
             print(f"Nano Banana Pro: ❌ {error_full}")
+            if 跳过错误:
+                print("Nano Banana Pro: ⚠️ 跳过错误已开启，返回占位图继续执行队列")
+                placeholder = Image.new('RGB', (512, 512), color=(128, 128, 128))
+                return (pil_to_tensor([placeholder]),)
             raise RuntimeError(error_full) from None
-        
+
         except Exception as e:
             # 其他未知错误 - 打印完整错误信息
             error_msg = str(e)
             print(f"Nano Banana Pro: ❌ {error_msg}")
+            if 跳过错误:
+                print("Nano Banana Pro: ⚠️ 跳过错误已开启，返回占位图继续执行队列")
+                placeholder = Image.new('RGB', (512, 512), color=(128, 128, 128))
+                return (pil_to_tensor([placeholder]),)
             raise type(e)(error_msg) from None
         
         finally:

nodes/quan_neng_sheng_tu.py

@@ -161,6 +161,11 @@ class QuanNengShengTu:
                     "default": 0,
                     "min": 0,
                     "max": 0xffffffffffffffff
+                }),
+                "跳过错误": ("BOOLEAN", {
+                    "default": False,
+                    "label_on": "打开",
+                    "label_off": "关闭"
                 })
             },
             "optional": optional_inputs
@@ -405,6 +410,7 @@ class QuanNengShengTu:
         像素缩放: bool,
         分辨率像素: float,
         seed: int,
+        跳过错误: bool = False,
         **kwargs
     ) -> Tuple[torch.Tensor]:
         """
@@ -798,16 +804,28 @@ class QuanNengShengTu:
             else:
                 error_msg = str(e)
                 print(f"全能生图: ❌ {error_msg}")
+            if 跳过错误:
+                print("全能生图: ⚠️ 跳过错误已开启，返回占位图继续执行队列")
+                placeholder = Image.new('RGB', (512, 512), color=(128, 128, 128))
+                return (pil_to_tensor([placeholder]),)
             raise ValueError(error_msg) from None
 
         except RuntimeError as e:
             error_full = str(e)
             print(f"全能生图: ❌ {error_full}")
+            if 跳过错误:
+                print("全能生图: ⚠️ 跳过错误已开启，返回占位图继续执行队列")
+                placeholder = Image.new('RGB', (512, 512), color=(128, 128, 128))
+                return (pil_to_tensor([placeholder]),)
             raise RuntimeError(error_full) from None
 
         except Exception as e:
             error_msg = str(e)
             print(f"全能生图: ❌ {error_msg}")
+            if 跳过错误:
+                print("全能生图: ⚠️ 跳过错误已开启，返回占位图继续执行队列")
+                placeholder = Image.new('RGB', (512, 512), color=(128, 128, 128))
+                return (pil_to_tensor([placeholder]),)
             raise type(e)(error_msg) from None
 
         finally:

nodes/seedance_video.py

@@ -0,0 +1,468 @@
+"""
+Seedance 视频生成节点
+节点列表:
+  - SeedanceT2V:       文生视频
+  - SeedanceI2V:       图生视频（首帧驱动）
+  - SeedanceFlipFlop:  首尾帧生视频
+"""
+
+import os
+import re
+
+from ..clients.seedance_client import SeedanceClient
+from ..clients.gemini_client import GeminiAPIClient
+from ..utils.image_utils import tensor_to_pil, encode_image_to_base64
+
+from comfy_api.latest import InputImpl
+
+try:
+    import folder_paths
+    FOLDER_PATHS_AVAILABLE = True
+except ImportError:
+    FOLDER_PATHS_AVAILABLE = False
+
+
+# ── 模型列表 ──────────────────────────────────────────────────────────────────
+
+_T2V_MODELS = [
+    "doubao-seedance-2-0-260128",
+    "doubao-seedance-2-0-fast-260128",
+    "doubao-seedance-1-5-pro-251215",
+    "doubao-seedance-1-0-pro-250528",
+    "doubao-seedance-1-0-lite-t2v",
+]
+
+_I2V_MODELS = [
+    "doubao-seedance-2-0-260128",
+    "doubao-seedance-2-0-fast-260128",
+    "doubao-seedance-1-5-pro-251215",
+    "doubao-seedance-1-0-pro-250528",
+    "doubao-seedance-1-0-lite-i2v",
+]
+
+_FLIPFLOP_MODELS = [
+    "doubao-seedance-2-0-260128",
+    "doubao-seedance-2-0-fast-260128",
+    "doubao-seedance-1-5-pro-251215",
+    "doubao-seedance-1-0-pro-250528",
+]
+
+
+# ── 模型能力判断 ──────────────────────────────────────────────────────────────
+
+def _is_v2(model: str) -> bool:
+    return "seedance-2-0" in model
+
+def _is_v15_pro(model: str) -> bool:
+    return "seedance-1-5-pro" in model
+
+def _supports_audio(model: str) -> bool:
+    """2.0、2.0-fast、1.5-pro 支持生成音频"""
+    return _is_v2(model) or _is_v15_pro(model)
+
+def _supports_auto_duration(model: str) -> bool:
+    """2.0 和 1.5-pro 支持自动时长（duration 不传或传 -1）"""
+    return _is_v2(model) or _is_v15_pro(model)
+
+def _supports_camera_fixed(model: str) -> bool:
+    """仅非 2.0 模型支持固定镜头（2.0 已不支持）"""
+    return not _is_v2(model)
+
+def _supports_web_search(model: str) -> bool:
+    """仅 2.0 系列支持联网搜索"""
+    return _is_v2(model)
+
+
+# ── 工具函数 ──────────────────────────────────────────────────────────────────
+
+def _get_video_output_dir() -> str:
+    if FOLDER_PATHS_AVAILABLE:
+        base = folder_paths.get_output_directory()
+    else:
+        plugin_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+        base = os.path.join(os.path.dirname(os.path.dirname(plugin_dir)), "output")
+    video_dir = os.path.join(base, "video")
+    os.makedirs(video_dir, exist_ok=True)
+    return video_dir
+
+
+def _get_next_counter(directory: str, prefix: str) -> int:
+    if not os.path.exists(directory):
+        return 1
+    pattern = re.compile(rf"^{re.escape(prefix)}_(\d+)")
+    max_counter = 0
+    for f in os.listdir(directory):
+        m = pattern.match(f)
+        if m:
+            max_counter = max(max_counter, int(m.group(1)))
+    return max_counter + 1
+
+
+def _tensor_to_base64_url(tensor) -> str:
+    """ComfyUI IMAGE tensor → data:image/png;base64,xxx"""
+    pil_images = tensor_to_pil(tensor)
+    b64 = encode_image_to_base64(pil_images[0], format="PNG")
+    return f"data:image/png;base64,{b64}"
+
+
+def _show_balance():
+    """完成后打印余额（静默失败）"""
+    try:
+        client = GeminiAPIClient()
+        data = client.query_balance_sync()
+        print(f"Seedance: {client.format_balance_info(data)}")
+    except Exception:
+        pass
+
+
+def _make_pbar():
+    try:
+        from comfy.utils import ProgressBar
+        return ProgressBar(100)
+    except Exception:
+        return None
+
+
+def _make_callbacks(tag: str, pbar):
+    """生成通用的 on_stage / on_progress 回调"""
+    def on_stage(stage: str):
+        if stage == "submitting":
+            print(f"[{tag}] 提交中...")
+            if pbar: pbar.update_absolute(0, 100)
+        elif stage.startswith("submitted:"):
+            print(f"[{tag}] 已提交 → {stage.split(':', 1)[1]}")
+            if pbar: pbar.update_absolute(5, 100)
+        elif stage == "downloading":
+            print(f"[{tag}] 下载视频中...")
+            if pbar: pbar.update_absolute(99, 100)
+        elif stage == "done":
+            print(f"[{tag}] 完成")
+            if pbar: pbar.update_absolute(100, 100)
+
+    def on_progress(pct: int):
+        if pbar: pbar.update_absolute(5 + int(pct * 0.94), 100)
+
+    return on_stage, on_progress
+
+
+# ── 节点 1：文生视频 ─────────────────────────────────────────────────────────
+
+class SeedanceT2V:
+    """Seedance 文生视频"""
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "提示词":           ("STRING", {"multiline": True, "default": ""}),
+                "模型":             (_T2V_MODELS, {"default": "doubao-seedance-2-0-260128"}),
+                "分辨率":           (["720p", "1080p", "480p"], {"default": "720p"}),
+                "宽高比":           (["16:9", "adaptive", "9:16", "1:1", "4:3", "3:4", "21:9"],
+                                     {"default": "16:9"}),
+                "时长秒(-1=自动)":  ("INT", {"default": 5, "min": -1, "max": 30, "step": 1}),
+                "生成音频":         (["关闭", "打开"], {"default": "关闭"}),
+                "水印":             (["关闭", "打开"], {"default": "关闭"}),
+                "返回末帧图片":     (["关闭", "打开"], {"default": "关闭"}),
+                "联网搜索":         (["关闭", "打开"], {"default": "关闭"}),
+                "服务等级":         (["default", "flex"], {"default": "default"}),
+                "seed":             ("INT", {"default": 0, "min": 0, "max": 0xffffffff}),
+            }
+        }
+
+    RETURN_TYPES = ("VIDEO",)
+    RETURN_NAMES = ("视频",)
+    FUNCTION = "generate"
+    CATEGORY = "comfyui_o1key/Seedance"
+
+    async def generate(self, **kwargs):
+        prompt       = kwargs["提示词"].strip()
+        model        = kwargs["模型"]
+        resolution   = kwargs["分辨率"]
+        ratio        = kwargs["宽高比"]
+        duration     = kwargs["时长秒(-1=自动)"]
+        gen_audio    = kwargs["生成音频"] == "打开"
+        watermark    = kwargs["水印"] == "打开"
+        return_last  = kwargs["返回末帧图片"] == "打开"
+        web_search   = kwargs["联网搜索"] == "打开"
+        service_tier = kwargs["服务等级"]
+        seed         = kwargs.get("seed", 0)
+
+        if not prompt:
+            raise ValueError("提示词不能为空。")
+        if duration == -1 and not _supports_auto_duration(model):
+            raise ValueError(f"模型 {model} 不支持自动时长（-1），请改用 2.0 或 1.5-pro 模型。")
+
+        metadata: dict = {
+            "resolution": resolution,
+            "watermark":  watermark,
+        }
+        if ratio != "adaptive":
+            metadata["ratio"] = ratio
+        if duration != -1:
+            metadata["duration"] = duration
+        if gen_audio and _supports_audio(model):
+            metadata["generate_audio"] = True
+        if return_last:
+            metadata["return_last_frame"] = True
+        if web_search and _supports_web_search(model):
+            metadata["tools"] = [{"type": "web_search"}]
+        if seed != 0:
+            metadata["seed"] = seed
+
+        body = {
+            "model":        model,
+            "prompt":       prompt,
+            "metadata":     metadata,
+            "service_tier": service_tier,
+        }
+
+        video_dir = _get_video_output_dir()
+        counter   = _get_next_counter(video_dir, "seedance_t2v")
+        save_path = os.path.join(video_dir, f"seedance_t2v_{counter:05d}.mp4")
+
+        client              = SeedanceClient()
+        pbar                = _make_pbar()
+        on_stage, on_prog   = _make_callbacks("Seedance文生视频", pbar)
+
+        try:
+            result_path = await client.generate_async(
+                body=body, save_path=save_path,
+                on_stage=on_stage, on_progress=on_prog,
+            )
+            return (InputImpl.VideoFromFile(result_path),)
+        finally:
+            _show_balance()
+
+
+# ── 节点 2：图生视频（首帧驱动） ──────────────────────────────────────────────
+
+class SeedanceI2V:
+    """Seedance 图生视频（首帧驱动）"""
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "首帧图片":         ("IMAGE",),
+                "提示词":           ("STRING", {"multiline": True, "default": ""}),
+                "模型":             (_I2V_MODELS, {"default": "doubao-seedance-2-0-260128"}),
+                "分辨率":           (["720p", "1080p", "480p"], {"default": "720p"}),
+                "宽高比":           (["16:9", "adaptive", "9:16", "1:1", "4:3", "3:4", "21:9"],
+                                     {"default": "16:9"}),
+                "时长秒(-1=自动)":  ("INT", {"default": 5, "min": -1, "max": 30, "step": 1}),
+                "生成音频":         (["关闭", "打开"], {"default": "关闭"}),
+                "水印":             (["关闭", "打开"], {"default": "关闭"}),
+                "固定镜头":         (["关闭", "打开"], {"default": "关闭"}),
+                "返回末帧图片":     (["关闭", "打开"], {"default": "关闭"}),
+                "服务等级":         (["default", "flex"], {"default": "default"}),
+                "seed":             ("INT", {"default": 0, "min": 0, "max": 0xffffffff}),
+            }
+        }
+
+    RETURN_TYPES = ("VIDEO",)
+    RETURN_NAMES = ("视频",)
+    FUNCTION = "generate"
+    CATEGORY = "comfyui_o1key/Seedance"
+
+    async def generate(self, **kwargs):
+        image        = kwargs["首帧图片"]
+        prompt       = kwargs["提示词"].strip()
+        model        = kwargs["模型"]
+        resolution   = kwargs["分辨率"]
+        ratio        = kwargs["宽高比"]
+        duration     = kwargs["时长秒(-1=自动)"]
+        gen_audio    = kwargs["生成音频"] == "打开"
+        watermark    = kwargs["水印"] == "打开"
+        cam_fixed    = kwargs["固定镜头"] == "打开"
+        return_last  = kwargs["返回末帧图片"] == "打开"
+        service_tier = kwargs["服务等级"]
+        seed         = kwargs.get("seed", 0)
+
+        if not prompt:
+            raise ValueError("提示词不能为空。")
+        if duration == -1 and not _supports_auto_duration(model):
+            raise ValueError(f"模型 {model} 不支持自动时长（-1），请改用 2.0 或 1.5-pro 模型。")
+
+        image_url = _tensor_to_base64_url(image)
+
+        # 使用 metadata.content 携带带 role 的图片（会覆盖 new-api 从 images 字段构建的 content）
+        content = [
+            {
+                "type":      "image_url",
+                "image_url": {"url": image_url},
+                "role":      "first_frame",
+            },
+            {
+                "type": "text",
+                "text": prompt,
+            },
+        ]
+
+        metadata: dict = {
+            "resolution": resolution,
+            "watermark":  watermark,
+            "content":    content,
+        }
+        if ratio != "adaptive":
+            metadata["ratio"] = ratio
+        if duration != -1:
+            metadata["duration"] = duration
+        if gen_audio and _supports_audio(model):
+            metadata["generate_audio"] = True
+        if cam_fixed and _supports_camera_fixed(model):
+            metadata["camera_fixed"] = True
+        if return_last:
+            metadata["return_last_frame"] = True
+        if seed != 0:
+            metadata["seed"] = seed
+
+        body = {
+            "model":        model,
+            "prompt":       prompt,
+            "images":       [image_url],   # 供 new-api HasImage() 识别，触发正确计费路径
+            "metadata":     metadata,
+            "service_tier": service_tier,
+        }
+
+        video_dir = _get_video_output_dir()
+        counter   = _get_next_counter(video_dir, "seedance_i2v")
+        save_path = os.path.join(video_dir, f"seedance_i2v_{counter:05d}.mp4")
+
+        client              = SeedanceClient()
+        pbar                = _make_pbar()
+        on_stage, on_prog   = _make_callbacks("Seedance图生视频", pbar)
+
+        try:
+            result_path = await client.generate_async(
+                body=body, save_path=save_path,
+                on_stage=on_stage, on_progress=on_prog,
+            )
+            return (InputImpl.VideoFromFile(result_path),)
+        finally:
+            _show_balance()
+
+
+# ── 节点 3：首尾帧生视频 ─────────────────────────────────────────────────────
+
+class SeedanceFlipFlop:
+    """Seedance 首尾帧生视频（同时指定起始帧与结束帧）"""
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "首帧图片":         ("IMAGE",),
+                "尾帧图片":         ("IMAGE",),
+                "提示词":           ("STRING", {"multiline": True, "default": ""}),
+                "模型":             (_FLIPFLOP_MODELS, {"default": "doubao-seedance-2-0-260128"}),
+                "分辨率":           (["720p", "1080p", "480p"], {"default": "720p"}),
+                "宽高比":           (["16:9", "adaptive", "9:16", "1:1", "4:3", "3:4", "21:9"],
+                                     {"default": "16:9"}),
+                "时长秒(-1=自动)":  ("INT", {"default": 5, "min": -1, "max": 30, "step": 1}),
+                "生成音频":         (["关闭", "打开"], {"default": "关闭"}),
+                "水印":             (["关闭", "打开"], {"default": "关闭"}),
+                "返回末帧图片":     (["关闭", "打开"], {"default": "关闭"}),
+                "服务等级":         (["default", "flex"], {"default": "default"}),
+                "seed":             ("INT", {"default": 0, "min": 0, "max": 0xffffffff}),
+            }
+        }
+
+    RETURN_TYPES = ("VIDEO",)
+    RETURN_NAMES = ("视频",)
+    FUNCTION = "generate"
+    CATEGORY = "comfyui_o1key/Seedance"
+
+    async def generate(self, **kwargs):
+        first_image  = kwargs["首帧图片"]
+        last_image   = kwargs["尾帧图片"]
+        prompt       = kwargs["提示词"].strip()
+        model        = kwargs["模型"]
+        resolution   = kwargs["分辨率"]
+        ratio        = kwargs["宽高比"]
+        duration     = kwargs["时长秒(-1=自动)"]
+        gen_audio    = kwargs["生成音频"] == "打开"
+        watermark    = kwargs["水印"] == "打开"
+        return_last  = kwargs["返回末帧图片"] == "打开"
+        service_tier = kwargs["服务等级"]
+        seed         = kwargs.get("seed", 0)
+
+        if not prompt:
+            raise ValueError("提示词不能为空。")
+        if duration == -1 and not _supports_auto_duration(model):
+            raise ValueError(f"模型 {model} 不支持自动时长（-1），请改用 2.0 或 1.5-pro 模型。")
+
+        first_url = _tensor_to_base64_url(first_image)
+        last_url  = _tensor_to_base64_url(last_image)
+
+        content = [
+            {
+                "type":      "image_url",
+                "image_url": {"url": first_url},
+                "role":      "first_frame",
+            },
+            {
+                "type":      "image_url",
+                "image_url": {"url": last_url},
+                "role":      "last_frame",
+            },
+            {
+                "type": "text",
+                "text": prompt,
+            },
+        ]
+
+        metadata: dict = {
+            "resolution": resolution,
+            "watermark":  watermark,
+            "content":    content,
+        }
+        if ratio != "adaptive":
+            metadata["ratio"] = ratio
+        if duration != -1:
+            metadata["duration"] = duration
+        if gen_audio and _supports_audio(model):
+            metadata["generate_audio"] = True
+        if return_last:
+            metadata["return_last_frame"] = True
+        if seed != 0:
+            metadata["seed"] = seed
+
+        body = {
+            "model":        model,
+            "prompt":       prompt,
+            "images":       [first_url],   # 供 new-api HasImage() 识别
+            "metadata":     metadata,
+            "service_tier": service_tier,
+        }
+
+        video_dir = _get_video_output_dir()
+        counter   = _get_next_counter(video_dir, "seedance_flip")
+        save_path = os.path.join(video_dir, f"seedance_flip_{counter:05d}.mp4")
+
+        client              = SeedanceClient()
+        pbar                = _make_pbar()
+        on_stage, on_prog   = _make_callbacks("Seedance首尾帧", pbar)
+
+        try:
+            result_path = await client.generate_async(
+                body=body, save_path=save_path,
+                on_stage=on_stage, on_progress=on_prog,
+            )
+            return (InputImpl.VideoFromFile(result_path),)
+        finally:
+            _show_balance()
+
+
+# ── 节点注册 ──────────────────────────────────────────────────────────────────
+
+NODE_CLASS_MAPPINGS = {
+    "SeedanceT2V":      SeedanceT2V,
+    "SeedanceI2V":      SeedanceI2V,
+    "SeedanceFlipFlop": SeedanceFlipFlop,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "SeedanceT2V":      "Seedance 文生视频",
+    "SeedanceI2V":      "Seedance 图生视频",
+    "SeedanceFlipFlop": "Seedance 首尾帧生视频",
+}