feat: 新增豆包5.0生图模型节点

- 新增 DoubaoImage 节点，支持豆包 5.0 文生图模型
- 新增 clients/doubao_image_client.py 封装豆包图像生成 API
- 新增 nodes/doubao_image.py 节点逻辑实现
- 注册节点映射及显示名称「豆包生图」

__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, AspectRatioPreset, MultiResPreview, BatchImagesO1key, Seedance, SeedanceMultiModal, StreamPreview
+from .nodes import NanoBananaPro, BatchNanoBananaPro, GoogleGemini, LoadFile, ImageStitchPro, SaveCleanImage, BatchCleanMetadata, VideoPreview, GoogleVeo, FluxImageEdit, UniversalLLMChat, KlingVideo, KlingFirstLastFrame, KlingMotionControlTest, AspectRatioPreset, MultiResPreview, BatchImagesO1key, Seedance, SeedanceMultiModal, StreamPreview, DoubaoImage
 
 # 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。"
@@ -78,6 +78,7 @@ NODE_CLASS_MAPPINGS = {
     "Seedance": Seedance,
     "SeedanceMultiModal": SeedanceMultiModal,
     "StreamPreview": StreamPreview,
+    "DoubaoImage": DoubaoImage,
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
@@ -101,6 +102,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "Seedance": "Seedance 视频生成",
     "SeedanceMultiModal": "Seedance 多模态参考生视频",
     "StreamPreview": "流式文本预览",
+    "DoubaoImage": "豆包生图",
 }
 
 WEB_DIRECTORY = "./web"

clients/doubao_image_client.py

@@ -0,0 +1,341 @@
+"""
+豆包生图 API 客户端
+端点：POST /v1/images/generations/
+兼容 new-api 透传格式（OpenAI images/generations 兼容）
+
+设计原则：
+  - 发送完整正确的请求体，new-api 丢弃字段是其侧问题
+  - 响应永远是同步 JSON（new-api 强制 stream=false）
+  - 图像输入以 data:image/png;base64,... 格式内联传递
+"""
+
+import asyncio
+import json
+import time
+from io import BytesIO
+from concurrent.futures import ThreadPoolExecutor
+from typing import List, Optional, Union
+
+import aiohttp
+from PIL import Image
+
+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
+
+
+# ── 固定端点 ──────────────────────────────────────────────────────────────────
+_ENDPOINT = "/v1/images/generations/"
+
+# ── 轮询 / 请求超时 ───────────────────────────────────────────────────────────
+_REQUEST_TIMEOUT = 300   # 单次请求超时秒数（豆包图像生成最长约 60s）
+
+
+class DoubaoImageClient:
+    """
+    豆包生图客户端（new-api 原生 OpenAI 兼容格式）
+
+    new-api 兼容性说明（基于源码分析）：
+      ✅ 透传：model / prompt / size / response_format / watermark / image
+      ❌ 丢弃：seed / sequential_image_generation / sequential_image_generation_options
+              （进入 Extra map，但 MarshalJSON 中合并代码被注释）
+      ❌ 强制：stream 硬编码 false，图像接口无流式处理
+      ❌ 未实现：/v1/files 文件上传（501）
+
+    节点仍发送完整字段，待 new-api 修复后自动生效。
+    """
+
+    def __init__(self):
+        self.api_key = get_api_key_or_raise("O1KEY_API_KEY")
+        self.base_url = get_api_base_url()
+
+    # ── 认证头 ────────────────────────────────────────────────────────────────
+
+    def _headers(self) -> dict:
+        return {
+            "Authorization": f"Bearer {self.api_key}",
+            "Content-Type": "application/json",
+        }
+
+    # ── 图像字段构建 ──────────────────────────────────────────────────────────
+
+    def _tensor_to_image_field(self, tensor) -> Union[str, List[str]]:
+        """
+        ComfyUI IMAGE tensor → API image 字段值
+
+        单张返回字符串，多张返回字符串列表，格式：
+            data:image/png;base64,<base64数据>
+        """
+        pil_images = tensor_to_pil(tensor)
+        data_urls = []
+        for img in pil_images:
+            b64 = encode_image_to_base64(img, format="PNG")
+            data_urls.append(f"data:image/png;base64,{b64}")
+
+        return data_urls[0] if len(data_urls) == 1 else data_urls
+
+    # ── 请求体构建 ────────────────────────────────────────────────────────────
+
+    def _build_body(
+        self,
+        model: str,
+        prompt: str,
+        size: str,
+        seed: int,
+        sequential_image_generation: str,
+        max_images: int,
+        image_field=None,          # str | list[str] | None
+    ) -> dict:
+        """
+        构建完整请求体。
+
+        字段说明（对照官方示例）：
+          - response_format: 固定 "url"（new-api 原样透传给豆包）
+          - watermark: 固定 False（UI 已移除该参数）
+          - stream: 固定 False（new-api 强制非流式，此字段不被读取，仅显式注明）
+          - sequential_image_generation_options: 仅 sequential=auto 时发送
+        """
+        body = {
+            "model": model,
+            "prompt": prompt,
+            "size": size,
+            "response_format": "url",
+            "watermark": False,
+            "seed": seed,
+            "sequential_image_generation": sequential_image_generation,
+        }
+
+        # 仅 auto 模式才发送 max_images 选项
+        if sequential_image_generation == "auto":
+            body["sequential_image_generation_options"] = {
+                "max_images": max_images
+            }
+
+        # 图像输入（图生图）
+        if image_field is not None:
+            body["image"] = image_field
+
+        return body
+
+    # ── 图像下载 ──────────────────────────────────────────────────────────────
+
+    async def _download_image(
+        self,
+        url: str,
+        session: aiohttp.ClientSession,
+    ) -> Image.Image:
+        """从 URL 下载图像，返回 PIL.Image。"""
+        async with session.get(url, allow_redirects=True) as resp:
+            if resp.status != 200:
+                raise RuntimeError(
+                    f"图像下载失败，HTTP {resp.status}，URL: {url}"
+                )
+            data = await resp.read()
+
+        try:
+            img = Image.open(BytesIO(data)).convert("RGB")
+        except Exception as e:
+            raise RuntimeError(f"图像解码失败: {e}")
+        return img
+
+    # ── 响应解析 ──────────────────────────────────────────────────────────────
+
+    async def _parse_response(
+        self,
+        resp_json: dict,
+        session: aiohttp.ClientSession,
+    ) -> List[Image.Image]:
+        """
+        解析 /v1/images/generations 响应，返回 PIL.Image 列表。
+
+        期望格式（new-api 原样透传豆包响应）：
+        {
+            "created": 1234567890,
+            "data": [
+                {"url": "https://..."},
+                {"url": "https://..."}
+            ]
+        }
+
+        兼容 b64_json 字段（豆包理论上也支持）。
+        """
+        # 检查 API 层级错误
+        if "error" in resp_json:
+            err = resp_json["error"]
+            if isinstance(err, dict):
+                msg = err.get("message") or err.get("msg") or json.dumps(err, ensure_ascii=False)
+            else:
+                msg = str(err)
+            raise RuntimeError(f"API 返回错误: {msg}")
+
+        data_list = resp_json.get("data")
+        if not data_list:
+            raise RuntimeError(
+                f"API 响应中未找到 data 字段，完整响应：\n"
+                f"{json.dumps(resp_json, ensure_ascii=False, indent=2)}"
+            )
+
+        images: List[Image.Image] = []
+
+        for idx, item in enumerate(data_list):
+            url = item.get("url", "")
+            b64 = item.get("b64_json", "")
+
+            if url and url.startswith("http"):
+                # 优先使用 URL 模式
+                img = await self._download_image(url, session)
+                images.append(img)
+                print(f"[豆包生图] 第 {idx + 1} 张下载完成 ({img.size[0]}×{img.size[1]})")
+
+            elif b64:
+                # 回退到 base64 模式
+                import base64 as _b64
+                try:
+                    img_data = _b64.b64decode(b64)
+                    img = Image.open(BytesIO(img_data)).convert("RGB")
+                    images.append(img)
+                    print(f"[豆包生图] 第 {idx + 1} 张 base64 解码完成 ({img.size[0]}×{img.size[1]})")
+                except Exception as e:
+                    raise RuntimeError(f"第 {idx + 1} 张 base64 解码失败: {e}")
+
+            else:
+                print(f"[豆包生图] 警告：第 {idx + 1} 条数据既无 url 也无 b64_json，已跳过")
+
+        return images
+
+    # ── 核心异步生成方法 ──────────────────────────────────────────────────────
+
+    async def _generate_async(
+        self,
+        model: str,
+        prompt: str,
+        size: str,
+        seed: int,
+        sequential_image_generation: str,
+        max_images: int,
+        image_tensor=None,
+    ) -> List[Image.Image]:
+        """
+        异步完整流程：构建请求 → POST → 解析 → 下载图像。
+        """
+        # 1. 构建 image 字段
+        image_field = None
+        if image_tensor is not None:
+            image_field = self._tensor_to_image_field(image_tensor)
+            n_imgs = len(image_field) if isinstance(image_field, list) else 1
+            print(f"[豆包生图] 图生图模式，参考图 {n_imgs} 张")
+        else:
+            print(f"[豆包生图] 文生图模式")
+
+        # 2. 构建请求体
+        body = self._build_body(
+            model=model,
+            prompt=prompt,
+            size=size,
+            seed=seed,
+            sequential_image_generation=sequential_image_generation,
+            max_images=max_images,
+            image_field=image_field,
+        )
+
+        url = f"{self.base_url}{_ENDPOINT}"
+        print(f"[豆包生图] 提交请求 → {model} | {size}")
+
+        connector = aiohttp.TCPConnector(ssl=False, force_close=True)
+        timeout = aiohttp.ClientTimeout(total=_REQUEST_TIMEOUT)
+
+        async with aiohttp.ClientSession(connector=connector, timeout=timeout) as session:
+
+            # 3. 发送 POST 请求
+            t0 = time.time()
+            async with session.post(
+                url,
+                json=body,
+                headers=self._headers(),
+            ) as resp:
+                elapsed_req = time.time() - t0
+                text = await resp.text()
+
+                if resp.status != 200:
+                    # 尝试解析错误信息
+                    try:
+                        err_json = json.loads(text)
+                        err_obj = err_json.get("error", {})
+                        if isinstance(err_obj, dict):
+                            msg = (
+                                err_obj.get("message")
+                                or err_obj.get("msg")
+                                or text
+                            )
+                        else:
+                            msg = str(err_obj) or text
+                    except Exception:
+                        msg = text
+                    raise RuntimeError(
+                        f"请求失败 HTTP {resp.status}: {msg}"
+                    )
+
+                try:
+                    resp_json = json.loads(text)
+                except Exception:
+                    raise RuntimeError(f"响应 JSON 解析失败，原始内容：{text[:500]}")
+
+            print(f"[豆包生图] API 响应耗时 {elapsed_req:.1f}s，开始下载图像...")
+
+            # 4. 解析响应 & 下载图像（session 复用）
+            images = await self._parse_response(resp_json, session)
+
+        return images
+
+    # ── 同步入口（供 ComfyUI 节点调用）──────────────────────────────────────
+
+    def generate_sync(
+        self,
+        model: str,
+        prompt: str,
+        size: str,
+        seed: int,
+        sequential_image_generation: str,
+        max_images: int,
+        image_tensor=None,
+    ) -> List[Image.Image]:
+        """
+        同步生成接口（在独立线程中运行事件循环，避免与 ComfyUI 主循环冲突）。
+
+        Args:
+            model:                       模型 ID
+            prompt:                      提示词
+            size:                        尺寸字符串，如 "2048x2048"
+            seed:                        随机种子
+            sequential_image_generation: "disabled" | "auto"
+            max_images:                  最大图片数（auto 模式生效）
+            image_tensor:                ComfyUI IMAGE tensor（可选，图生图用）
+
+        Returns:
+            List[PIL.Image]
+        """
+        coro = self._generate_async(
+            model=model,
+            prompt=prompt,
+            size=size,
+            seed=seed,
+            sequential_image_generation=sequential_image_generation,
+            max_images=max_images,
+            image_tensor=image_tensor,
+        )
+
+        def _run():
+            loop = asyncio.new_event_loop()
+            asyncio.set_event_loop(loop)
+            try:
+                return loop.run_until_complete(coro)
+            finally:
+                loop.close()
+
+        with ThreadPoolExecutor(max_workers=1) as executor:
+            future = executor.submit(_run)
+            try:
+                return future.result(timeout=_REQUEST_TIMEOUT + 30)
+            except TimeoutError:
+                raise RuntimeError(
+                    f"豆包生图超时（>{_REQUEST_TIMEOUT}s），请检查网络或稍后重试"
+                )

nodes/__init__.py

@@ -18,5 +18,6 @@ from .universal_llm import UniversalLLMChat
 from .multi_res_preview import MultiResPreview
 from .batch_images_o1key import BatchImagesO1key
 from .seedance_video import Seedance, SeedanceMultiModal
+from .doubao_image import DoubaoImage
 
-__all__ = ['NanoBananaPro', 'BatchNanoBananaPro', 'GoogleGemini', 'LoadFile', 'ImageStitchPro', 'SaveCleanImage', 'BatchCleanMetadata', 'VideoPreview', 'KlingVideo', 'KlingFirstLastFrame', 'KlingMotionControlTest', 'AspectRatioPreset', 'GoogleVeo', 'FluxImageEdit', 'UniversalLLMChat', 'MultiResPreview', 'BatchImagesO1key', 'Seedance', 'SeedanceMultiModal', 'StreamPreview']
+__all__ = ['NanoBananaPro', 'BatchNanoBananaPro', 'GoogleGemini', 'LoadFile', 'ImageStitchPro', 'SaveCleanImage', 'BatchCleanMetadata', 'VideoPreview', 'KlingVideo', 'KlingFirstLastFrame', 'KlingMotionControlTest', 'AspectRatioPreset', 'GoogleVeo', 'FluxImageEdit', 'UniversalLLMChat', 'MultiResPreview', 'BatchImagesO1key', 'Seedance', 'SeedanceMultiModal', 'StreamPreview', 'DoubaoImage']

nodes/doubao_image.py

@@ -0,0 +1,290 @@
+"""
+豆包生图节点
+1:1 复刻字节跳动 Seedream 4 节点的前端外观（输入/输出/参数/样式）
+后端通过 new-api 兼容层调用豆包官方 API
+"""
+
+import time
+import numpy as np
+import torch
+from PIL import Image
+from typing import List
+
+from ..clients.doubao_image_client import DoubaoImageClient
+from ..utils.image_utils import tensor_to_pil
+
+
+# ── 尺寸预设 ──────────────────────────────────────────────────────────────────
+# (显示名, 宽, 高) —— 宽高用于构造 "WxH" size 字符串
+RECOMMENDED_PRESETS_SEEDREAM_4 = [
+    ("2048×2048 (1:1)",  2048, 2048),
+    ("2304×1728 (4:3)",  2304, 1728),
+    ("1728×2304 (3:4)",  1728, 2304),
+    ("2560×1440 (16:9)", 2560, 1440),
+    ("1440×2560 (9:16)", 1440, 2560),
+    ("2496×1664 (3:2)",  2496, 1664),
+    ("1664×2496 (2:3)",  1664, 2496),
+    ("3024×1296 (21:9)", 3024, 1296),
+    ("3072×3072 (1:1)",  3072, 3072),
+    ("4096×4096 (1:1)",  4096, 4096),
+    ("自定义",           None, None),
+]
+
+_PRESET_LABELS = [label for label, _, _ in RECOMMENDED_PRESETS_SEEDREAM_4]
+
+# ── 模型列表 ──────────────────────────────────────────────────────────────────
+# 节点下拉选项 = new-api 后台配置的模型 ID（直接透传给 API）
+_MODELS = [
+    "doubao-seedream-5-0-260128",
+    "doubao-seedream-4-5-251128",
+]
+
+
+def _pil_list_to_tensor(images: List[Image.Image]) -> torch.Tensor:
+    """
+    PIL Image 列表 → ComfyUI IMAGE tensor [B, H, W, C]，值域 [0, 1]。
+
+    多张尺寸不同时，以最大尺寸为准，较小图像丢弃（与项目其他节点策略一致）。
+    """
+    if not images:
+        placeholder = Image.new("RGB", (512, 512), color=(128, 128, 128))
+        images = [placeholder]
+
+    # 找最大尺寸
+    base_size = max(images, key=lambda img: img.size[0] * img.size[1]).size
+    matched = [img for img in images if img.size == base_size]
+    skipped = len(images) - len(matched)
+    if skipped:
+        print(f"[豆包生图] 丢弃 {skipped} 张非最大尺寸图像，仅输出 {base_size[0]}×{base_size[1]} 的 {len(matched)} 张")
+
+    tensors = []
+    for img in matched:
+        arr = np.array(img.convert("RGB")).astype(np.float32) / 255.0
+        tensors.append(torch.from_numpy(arr))
+
+    return torch.stack(tensors, dim=0)   # [B, H, W, C]
+
+
+class DoubaoImage:
+    """豆包生图 —— 1:1 复刻字节跳动 Seedream 4 节点前端，后端对接豆包官方 API"""
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "模型": (
+                    _MODELS,
+                    {"default": _MODELS[0]},
+                ),
+                "提示词": (
+                    "STRING",
+                    {
+                        "multiline": True,
+                        "default": "",
+                        "tooltip": "用于创建或编辑图像的文本提示",
+                    },
+                ),
+                "尺寸预设": (
+                    _PRESET_LABELS,
+                    {
+                        "default": _PRESET_LABELS[0],
+                        "tooltip": '选择推荐尺寸。选择"自定义"可使用下方的宽度和高度',
+                    },
+                ),
+                "宽度": (
+                    "INT",
+                    {
+                        "default": 2048,
+                        "min": 1024,
+                        "max": 6240,
+                        "step": 64,
+                        "tooltip": '图像的自定义宽度。仅当尺寸预设设置为"自定义"时生效',
+                    },
+                ),
+                "高度": (
+                    "INT",
+                    {
+                        "default": 2048,
+                        "min": 1024,
+                        "max": 4992,
+                        "step": 64,
+                        "tooltip": '图像的自定义高度。仅当尺寸预设设置为"自定义"时生效',
+                    },
+                ),
+                "顺序图像生成": (
+                    ["disabled", "auto"],
+                    {
+                        "default": "disabled",
+                        "tooltip": (
+                            '分组图像生成模式。'
+                            '"disabled"生成单张图像；'
+                            '"auto"让模型决定是否生成多张相关图像（如故事场景、角色变体）'
+                        ),
+                    },
+                ),
+                "最大图片数": (
+                    "INT",
+                    {
+                        "default": 1,
+                        "min": 1,
+                        "max": 15,
+                        "step": 1,
+                        "tooltip": (
+                            "当顺序图像生成='auto'时生成的最大图像数量。"
+                            "总图像数（输入+生成）不能超过15张"
+                        ),
+                    },
+                ),
+                "种子": (
+                    "INT",
+                    {
+                        "default": 0,
+                        "min": 0,
+                        "max": 2147483647,
+                        "step": 1,
+                        "control_after_generate": True,
+                        "tooltip": "用于生成的随机种子",
+                    },
+                ),
+                "部分失败时停止": (
+                    "BOOLEAN",
+                    {
+                        "default": True,
+                        "tooltip": "如果启用，当任何请求的图像缺失或返回错误时将中止执行",
+                    },
+                ),
+            },
+            "optional": {
+                "图像": (
+                    "IMAGE",
+                    {
+                        "tooltip": (
+                            "用于图生图的输入图像。"
+                            "单参考或多参考生成时，可输入1-10张图像列表"
+                        ),
+                    },
+                ),
+            },
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("图像",)
+    FUNCTION = "generate"
+    CATEGORY = "comfyui_o1key/豆包"
+
+    # ── 核心生成方法 ──────────────────────────────────────────────────────────
+
+    def generate(
+        self,
+        模型: str,
+        提示词: str,
+        尺寸预设: str,
+        宽度: int,
+        高度: int,
+        顺序图像生成: str,
+        最大图片数: int,
+        种子: int,
+        部分失败时停止: bool,
+        图像=None,
+    ):
+        start_time = time.time()
+
+        # ── 1. 校验提示词 ─────────────────────────────────────────────────────
+        if not 提示词.strip():
+            raise ValueError("提示词不能为空，请输入图像描述后重试。")
+
+        # ── 2. 解析尺寸 ───────────────────────────────────────────────────────
+        w, h = None, None
+        for label, tw, th in RECOMMENDED_PRESETS_SEEDREAM_4:
+            if label == 尺寸预设:
+                w, h = tw, th
+                break
+
+        if w is None or h is None:
+            # 自定义尺寸
+            w, h = 宽度, 高度
+            print(f"[豆包生图] 自定义尺寸：{w}×{h}")
+
+        size_str = f"{w}x{h}"
+
+        # ── 3. 打印概要 ───────────────────────────────────────────────────────
+        mode_str = "图生图" if 图像 is not None else "文生图"
+        seq_str = f" | 顺序生成=auto(最多{最大图片数}张)" if 顺序图像生成 == "auto" else ""
+        print(
+            f"[豆包生图] {mode_str} | 模型={模型} | 尺寸={size_str}"
+            f" | 种子={种子}{seq_str}"
+        )
+
+        # ── 4. 进度条 ─────────────────────────────────────────────────────────
+        try:
+            from comfy.utils import ProgressBar
+            pbar = ProgressBar(100)
+        except Exception:
+            pbar = None
+
+        def _pb(pct: int):
+            if pbar:
+                pbar.update_absolute(pct, 100)
+
+        _pb(0)
+
+        # ── 5. 调用客户端 ─────────────────────────────────────────────────────
+        try:
+            client = DoubaoImageClient()
+        except ValueError as e:
+            raise ValueError(str(e)) from None
+
+        _pb(5)
+
+        try:
+            pil_images: List[Image.Image] = client.generate_sync(
+                model=模型,
+                prompt=提示词,
+                size=size_str,
+                seed=种子,
+                sequential_image_generation=顺序图像生成,
+                max_images=最大图片数,
+                image_tensor=图像,
+            )
+        except RuntimeError as e:
+            raise RuntimeError(str(e)) from None
+        except Exception as e:
+            raise RuntimeError(f"豆包生图请求失败: {e}") from None
+
+        _pb(90)
+
+        # ── 6. 部分失败判断 ───────────────────────────────────────────────────
+        if 顺序图像生成 == "auto" and 部分失败时停止:
+            if len(pil_images) < 最大图片数:
+                raise RuntimeError(
+                    f"部分图像生成失败：期望 {最大图片数} 张，"
+                    f"实际返回 {len(pil_images)} 张。"
+                    "（可将【部分失败时停止】设为 False 以接受不完整结果）"
+                )
+
+        # ── 7. PIL → tensor ───────────────────────────────────────────────────
+        output_tensor = _pil_list_to_tensor(pil_images)
+
+        _pb(100)
+
+        # ── 8. 完成日志 ───────────────────────────────────────────────────────
+        elapsed = time.time() - start_time
+        time_str = f"{elapsed:.1f}s"
+        print(
+            f"[豆包生图] 完成！耗时 {time_str}，"
+            f"输出 {output_tensor.shape[0]} 张 "
+            f"{output_tensor.shape[2]}×{output_tensor.shape[1]}"
+        )
+
+        return (output_tensor,)
+
+
+# ── 节点注册 ──────────────────────────────────────────────────────────────────
+
+NODE_CLASS_MAPPINGS = {
+    "DoubaoImage": DoubaoImage,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "DoubaoImage": "豆包生图",
+}