refactor: 重构 Seedance 节点，三合一并修复轮询 Bug

- 将 SeedanceT2V / SeedanceI2V / SeedanceFlipFlop 合并为单一 Seedance 节点
- 通过图片输入自动判断模式：无图=文生视频，首帧=图生视频，首尾帧=首尾帧模式
- 修复轮询状态字段取值路径错误导致的无限循环问题
- 修复视频 URL / 末帧 URL 取值路径（result.data.content.video_url）
- 新增末帧图片 IMAGE 输出端，支持 return_last_frame 功能
- 删除水印、服务等级前端参数，移除 1.0/1.5 旧模型，去掉 1080p 分辨率
- 关闭 DEBUG 原始响应日志，仅保留用户可见进度日志

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, SeedanceT2V, SeedanceI2V, SeedanceFlipFlop
+from .nodes import NanoBananaPro, BatchNanoBananaPro, GoogleGemini, LoadFile, ImageStitchPro, SaveCleanImage, BatchCleanMetadata, VideoPreview, GoogleVeo, FluxImageEdit, UniversalLLMChat, KlingVideo, KlingFirstLastFrame, KlingMotionControlTest, QuanNengShengTu, BatchQuanNengShengTu, AspectRatioPreset, MultiResPreview, BatchImagesO1key, Seedance
 
 # 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。"
@@ -79,9 +79,7 @@ NODE_CLASS_MAPPINGS = {
     "AspectRatioPreset": AspectRatioPreset,
     "MultiResPreview": MultiResPreview,
     "BatchImagesO1key": BatchImagesO1key,
-    "SeedanceT2V": SeedanceT2V,
+    "Seedance": Seedance,
-    "SeedanceI2V": SeedanceI2V,
-    "SeedanceFlipFlop": SeedanceFlipFlop,
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
@@ -104,9 +102,7 @@ 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",
+    "Seedance": "Seedance 视频生成",
-    "SeedanceI2V": "Seedance 图生视频",
-    "SeedanceFlipFlop": "Seedance 首尾帧生视频",
 }
 
 WEB_DIRECTORY = "./web"

clients/seedance_client.py

@@ -92,37 +92,47 @@ class SeedanceClient:
                     raise RuntimeError(f"状态查询失败 ({resp.status}): {msg}")
                 result = json.loads(text)
 
-            status = (result.get("status") or "").lower()
+            # new-api 包装格式：真实数据在 result["data"] 里
+            inner = result.get("data") or result
 
-            # 调试：打印原始响应（排查状态字段问题后可删除）
+            status = (inner.get("status") or "").lower()
-            print(f"[Seedance][DEBUG] 原始响应: {result}")
 
             # 解析进度
-            progress_raw = result.get("progress", "0")
+            progress_raw = inner.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})")
+            print(f"[Seedance] 生成中 {progress_pct}%")
             if on_progress:
                 on_progress(progress_pct)
 
             if status in self.SUCCESS_STATUSES:
-                # 取视频 URL：url / metadata.url / output.video_url
+                # 响应结构：result["data"] = inner，inner["data"] = platform_data
+                # 视频 URL 在 inner["result_url"] 或 inner["data"]["content"]["video_url"]
+                platform_data = inner.get("data") or {}
+                content = platform_data.get("content") or {}
                 video_url = (
-                    result.get("url")
+                    inner.get("result_url")
-                    or (result.get("output") or {}).get("video_url")
+                    or content.get("video_url")
-                    or (result.get("metadata") or {}).get("url")
+                    or platform_data.get("video_url")
+                    or inner.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
+                # 末帧图片 URL 在 inner["data"]["content"]["last_frame_url"]
+                last_frame_url = (
+                    content.get("last_frame_url")
+                    or platform_data.get("last_frame_url")
+                    or inner.get("last_frame_url")
+                )
+                return video_url, last_frame_url
 
             if status in self.FAILURE_STATUSES:
                 reason = (
-                    result.get("fail_reason")
+                    inner.get("fail_reason")
-                    or (result.get("error") or {}).get("message")
+                    or (inner.get("error") or {}).get("message")
                     or "未知错误"
                 )
                 raise RuntimeError(f"视频生成失败：{reason}")
@@ -157,8 +167,8 @@ class SeedanceClient:
         save_path: str,
         on_stage: Optional[Callable[[str], None]] = None,
         on_progress: Optional[Callable[[int], None]] = None,
-    ) -> str:
+    ) -> tuple:
-        """提交 → 轮询 → 下载，返回本地文件路径"""
+        """提交 → 轮询 → 下载，返回 (本地视频路径, 末帧图片URL或None)"""
         connector = aiohttp.TCPConnector(force_close=True)
         async with aiohttp.ClientSession(connector=connector) as session:
 
@@ -171,7 +181,7 @@ class SeedanceClient:
                 on_stage(f"submitted:{task_id}")
 
             # 轮询
-            video_url = await self.poll_async(task_id, session, on_progress=on_progress)
+            video_url, last_frame_url = await self.poll_async(task_id, session, on_progress=on_progress)
 
             # 下载
             if on_stage:
@@ -180,4 +190,4 @@ class SeedanceClient:
 
             if on_stage:
                 on_stage("done")
-            return path
+            return path, last_frame_url

nodes/__init__.py

@@ -20,6 +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
+from .seedance_video import Seedance
 
-__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']
+__all__ = ['NanoBananaPro', 'BatchNanoBananaPro', 'GoogleGemini', 'LoadFile', 'ImageStitchPro', 'SaveCleanImage', 'BatchCleanMetadata', 'VideoPreview', 'KlingVideo', 'KlingFirstLastFrame', 'KlingMotionControlTest', 'AspectRatioPreset', 'GoogleVeo', 'FluxImageEdit', 'UniversalLLMChat', 'QuanNengShengTu', 'BatchQuanNengShengTu', 'MultiResPreview', 'BatchImagesO1key', 'NanaBananaV2', 'BatchNanaBananaV2', 'Seedance']

nodes/seedance_video.py

@@ -1,17 +1,19 @@
 """
 Seedance 视频生成节点
 节点列表:
-  - SeedanceT2V:       文生视频
+  - Seedance: 文生视频 / 图生视频 / 首尾帧生视频（根据图片输入自动切换模式）
-  - SeedanceI2V:       图生视频（首帧驱动）
-  - SeedanceFlipFlop:  首尾帧生视频
 """
 
+import io
 import os
 import re
 
+import aiohttp
+import torch
+
 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 ..utils.image_utils import tensor_to_pil, encode_image_to_base64, pil_to_tensor
 
 from comfy_api.latest import InputImpl
 
@@ -24,53 +26,19 @@ except ImportError:
 
 # ── 模型列表 ──────────────────────────────────────────────────────────────────
 
-_T2V_MODELS = [
+_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 = [
+_RESOLUTIONS = ["720p", "480p"]
-    "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）"""
+    """2.0 系列不支持固定镜头"""
-    return not _is_v2(model)
+    return False  # 当前仅 2.0 模型，均不支持
-
-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 ──────────────────────────────────────────────────────────────────
@@ -105,6 +73,22 @@ def _tensor_to_base64_url(tensor) -> str:
     return f"data:image/png;base64,{b64}"
 
 
+async def _url_to_tensor(url: str) -> torch.Tensor:
+    """从 URL 下载图片并转为 ComfyUI IMAGE tensor，失败时返回 None"""
+    try:
+        from PIL import Image
+        async with aiohttp.ClientSession() as session:
+            async with session.get(url, allow_redirects=True) as resp:
+                if resp.status != 200:
+                    return None
+                data = await resp.read()
+        img = Image.open(io.BytesIO(data)).convert("RGB")
+        return pil_to_tensor([img])
+    except Exception as e:
+        print(f"[Seedance] 末帧图片下载失败: {e}")
+        return None
+
+
 def _show_balance():
     """完成后打印余额（静默失败）"""
     try:
@@ -124,7 +108,6 @@ def _make_pbar():
 
 
 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...")
@@ -145,310 +128,160 @@ def _make_callbacks(tag: str, pbar):
     return on_stage, on_progress
 
 
-# ── 节点 1：文生视频 ─────────────────────────────────────────────────────────
+# ── 统一节点 ─────────────────────────────────────────────────────────────────
+#
+#   模式由图片输入自动判断：
+#     首帧 = None              → T2V 文生视频   （联网搜索生效）
+#     首帧 = 图片，尾帧 = None → I2V 图生视频   （固定镜头生效，当前 2.0 不支持故忽略）
+#     首帧 = 图片，尾帧 = 图片 → FlipFlop 首尾帧（联网搜索/固定镜头均忽略）
 
-class SeedanceT2V:
+class Seedance:
-    """Seedance 文生视频"""
+    """Seedance 视频生成（文生视频 / 图生视频 / 首尾帧，自动判断模式）"""
 
     @classmethod
     def INPUT_TYPES(cls):
         return {
             "required": {
                 "提示词":           ("STRING", {"multiline": True, "default": ""}),
-                "模型":             (_T2V_MODELS, {"default": "doubao-seedance-2-0-260128"}),
+                "模型":             (_MODELS, {"default": "doubao-seedance-2-0-260128"}),
-                "分辨率":           (["720p", "1080p", "480p"], {"default": "720p"}),
+                "分辨率":           (_RESOLUTIONS, {"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",
             },
-            {
+            "optional": {
-                "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_TYPES = ("VIDEO", "IMAGE")
-    RETURN_NAMES = ("视频",)
+    RETURN_NAMES = ("视频", "末帧图片")
     FUNCTION = "generate"
     CATEGORY = "comfyui_o1key/Seedance"
 
     async def generate(self, **kwargs):
-        first_image  = kwargs["首帧图片"]
+        prompt      = kwargs["提示词"].strip()
-        last_image   = kwargs["尾帧图片"]
+        model       = kwargs["模型"]
-        prompt       = kwargs["提示词"].strip()
+        resolution  = kwargs["分辨率"]
-        model        = kwargs["模型"]
+        ratio       = kwargs["宽高比"]
-        resolution   = kwargs["分辨率"]
+        duration    = kwargs["时长秒(-1=自动)"]
-        ratio        = kwargs["宽高比"]
+        gen_audio   = kwargs["生成音频"] == "打开"
-        duration     = kwargs["时长秒(-1=自动)"]
+        web_search  = kwargs["联网搜索"] == "打开"
-        gen_audio    = kwargs["生成音频"] == "打开"
+        return_last = kwargs["返回末帧图片"] == "打开"
-        watermark    = kwargs["水印"] == "打开"
+        seed        = kwargs.get("seed", 0)
-        return_last  = kwargs["返回末帧图片"] == "打开"
+        first_image = kwargs.get("首帧图片", None)
-        service_tier = kwargs["服务等级"]
+        last_image  = kwargs.get("尾帧图片", None)
-        seed         = kwargs.get("seed", 0)
+
+        # 模式判断
+        if first_image is None and last_image is not None:
+            raise ValueError("请同时接入首帧图片，或仅接入首帧图片。")
+        if first_image is None:
+            mode = "t2v"
+            tag  = "Seedance文生视频"
+            file_prefix = "seedance_t2v"
+        elif last_image is None:
+            mode = "i2v"
+            tag  = "Seedance图生视频"
+            file_prefix = "seedance_i2v"
+        else:
+            mode = "flipflop"
+            tag  = "Seedance首尾帧"
+            file_prefix = "seedance_flip"
 
         if not prompt:
             raise ValueError("提示词不能为空。")
-        if duration == -1 and not _supports_auto_duration(model):
+        if duration == -1 and mode == "t2v":
-            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。")
+            pass  # 2.0 均支持自动时长
-
+        elif duration == -1 and mode != "t2v":
-        first_url = _tensor_to_base64_url(first_image)
+            pass  # 2.0 均支持自动时长
-        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,
+            "watermark":  False,
-            "content":    content,
         }
         if ratio != "adaptive":
             metadata["ratio"] = ratio
         if duration != -1:
             metadata["duration"] = duration
-        if gen_audio and _supports_audio(model):
+        if gen_audio:
             metadata["generate_audio"] = True
         if return_last:
             metadata["return_last_frame"] = True
         if seed != 0:
             metadata["seed"] = seed
 
-        body = {
+        # 模式专属参数
-            "model":        model,
+        if mode == "t2v":
-            "prompt":       prompt,
+            if web_search:
-            "images":       [first_url],   # 供 new-api HasImage() 识别
+                metadata["tools"] = [{"type": "web_search"}]
-            "metadata":     metadata,
+            body = {
-            "service_tier": service_tier,
+                "model":    model,
-        }
+                "prompt":   prompt,
+                "metadata": metadata,
+            }
+
+        elif mode == "i2v":
+            first_url = _tensor_to_base64_url(first_image)
+            metadata["content"] = [
+                {
+                    "type":      "image_url",
+                    "image_url": {"url": first_url},
+                    "role":      "first_frame",
+                },
+                {"type": "text", "text": prompt},
+            ]
+            body = {
+                "model":    model,
+                "prompt":   prompt,
+                "images":   [first_url],
+                "metadata": metadata,
+            }
+
+        else:  # flipflop
+            first_url = _tensor_to_base64_url(first_image)
+            last_url  = _tensor_to_base64_url(last_image)
+            metadata["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},
+            ]
+            body = {
+                "model":    model,
+                "prompt":   prompt,
+                "images":   [first_url],
+                "metadata": metadata,
+            }
 
         video_dir = _get_video_output_dir()
-        counter   = _get_next_counter(video_dir, "seedance_flip")
+        counter   = _get_next_counter(video_dir, file_prefix)
-        save_path = os.path.join(video_dir, f"seedance_flip_{counter:05d}.mp4")
+        save_path = os.path.join(video_dir, f"{file_prefix}_{counter:05d}.mp4")
 
-        client              = SeedanceClient()
+        client            = SeedanceClient()
-        pbar                = _make_pbar()
+        pbar              = _make_pbar()
-        on_stage, on_prog   = _make_callbacks("Seedance首尾帧", pbar)
+        on_stage, on_prog = _make_callbacks(tag, pbar)
 
         try:
-            result_path = await client.generate_async(
+            result_path, last_frame_url = await client.generate_async(
                 body=body, save_path=save_path,
                 on_stage=on_stage, on_progress=on_prog,
             )
-            return (InputImpl.VideoFromFile(result_path),)
+            last_frame_tensor = None
+            if return_last and last_frame_url:
+                last_frame_tensor = await _url_to_tensor(last_frame_url)
+            return (InputImpl.VideoFromFile(result_path), last_frame_tensor)
         finally:
             _show_balance()
 
@@ -456,13 +289,9 @@ class SeedanceFlipFlop:
 # ── 节点注册 ──────────────────────────────────────────────────────────────────
 
 NODE_CLASS_MAPPINGS = {
-    "SeedanceT2V":      SeedanceT2V,
+    "Seedance": Seedance,
-    "SeedanceI2V":      SeedanceI2V,
-    "SeedanceFlipFlop": SeedanceFlipFlop,
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
-    "SeedanceT2V":      "Seedance 文生视频",
+    "Seedance": "Seedance 视频生成",
-    "SeedanceI2V":      "Seedance 图生视频",
-    "SeedanceFlipFlop": "Seedance 首尾帧生视频",
 }