From a2665b4010aaf293e79d1f27838cc3c092466c5f Mon Sep 17 00:00:00 2001 From: o1key <951565127@qq.com> Date: Wed, 15 Apr 2026 18:31:58 +0800 Subject: [PATCH] =?UTF-8?q?feat:=20=E6=96=B0=E5=A2=9E=20GPT-1.5=20?= =?UTF-8?q?=E7=94=9F=E5=9B=BE=E8=8A=82=E7=82=B9?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- __init__.py | 4 +- clients/gpt_image_client.py | 411 ++++++++++++++++++++++++++++++++++++ nodes/__init__.py | 3 +- nodes/o1key_gpt_image.py | 158 ++++++++++++++ 4 files changed, 574 insertions(+), 2 deletions(-) create mode 100644 clients/gpt_image_client.py create mode 100644 nodes/o1key_gpt_image.py diff --git a/__init__.py b/__init__.py index 70f1481..45c4baa 100644 --- a/__init__.py +++ b/__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, DoubaoImage +from .nodes import NanoBananaPro, BatchNanoBananaPro, GoogleGemini, LoadFile, ImageStitchPro, SaveCleanImage, BatchCleanMetadata, VideoPreview, GoogleVeo, FluxImageEdit, UniversalLLMChat, KlingVideo, KlingFirstLastFrame, KlingMotionControlTest, AspectRatioPreset, MultiResPreview, BatchImagesO1key, Seedance, SeedanceMultiModal, StreamPreview, DoubaoImage, O1keyGPTImage # 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 +79,7 @@ NODE_CLASS_MAPPINGS = { "SeedanceMultiModal": SeedanceMultiModal, "StreamPreview": StreamPreview, "DoubaoImage": DoubaoImage, + "O1keyGPTImage": O1keyGPTImage, } NODE_DISPLAY_NAME_MAPPINGS = { @@ -103,6 +104,7 @@ NODE_DISPLAY_NAME_MAPPINGS = { "SeedanceMultiModal": "Seedance 多模态参考生视频", "StreamPreview": "流式文本预览", "DoubaoImage": "豆包生图", + "O1keyGPTImage": "o1key GPT Image", } WEB_DIRECTORY = "./web" diff --git a/clients/gpt_image_client.py b/clients/gpt_image_client.py new file mode 100644 index 0000000..00a7b37 --- /dev/null +++ b/clients/gpt_image_client.py @@ -0,0 +1,411 @@ +""" +GPT Image API 客户端 +支持两个接口： + - POST /v1/images/generations/ 文生图 / 图生图（gpt-image-1 / gpt-image-1.5） + - POST /v1/images/edits/ 图像编辑（带蒙版 inpainting） + +设计原则： + - 与 doubao_image_client.py 保持相同的异步 + 同步双入口模式 + - 图像以 multipart/form-data 方式上传（edits 接口） + - generations 接口使用 JSON 请求体，图像以 data URI base64 内联传递 + - 响应支持 url 和 b64_json 两种格式，优先处理 b64_json（避免二次下载） +""" + +import asyncio +import base64 +import json +import time +from concurrent.futures import ThreadPoolExecutor +from io import BytesIO +from typing import List, Optional + +import aiohttp +import numpy as np +import torch +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 + +# ── 接口端点 ────────────────────────────────────────────────────────────────── +_ENDPOINT_GENERATIONS = "/v1/images/generations/" +_ENDPOINT_EDITS = "/v1/images/edits/" + +# ── 超时 ────────────────────────────────────────────────────────────────────── +_REQUEST_TIMEOUT = 300 # 秒 + + +class GptImageClient: + """ + GPT Image API 客户端 + + 接口说明： + generations：JSON body，支持 background / quality / size / n / model + edits：multipart/form-data，必须包含 image（PNG），可选 mask（PNG） + + 两个接口的响应格式相同： + { "data": [ {"url": "..."} | {"b64_json": "..."} ] } + """ + + 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 _auth_headers(self) -> dict: + return {"Authorization": f"Bearer {self.api_key}"} + + def _json_headers(self) -> dict: + return { + "Authorization": f"Bearer {self.api_key}", + "Content-Type": "application/json", + } + + # ── 图像转换工具 ────────────────────────────────────────────────────────── + + @staticmethod + def _tensor_to_png_bytes(tensor: torch.Tensor) -> bytes: + """ + 单张 ComfyUI IMAGE tensor [1, H, W, C] 或 [H, W, C] → PNG bytes + """ + if tensor.dim() == 4: + tensor = tensor.squeeze(0) # [H, W, C] + arr = (tensor.cpu().numpy() * 255).clip(0, 255).astype(np.uint8) + img = Image.fromarray(arr) + buf = BytesIO() + img.save(buf, format="PNG") + return buf.getvalue() + + @staticmethod + def _mask_tensor_to_rgba_png_bytes(mask: torch.Tensor, image_size: tuple) -> bytes: + """ + ComfyUI MASK tensor [1, H, W] 或 [H, W] → RGBA PNG bytes + 白色区域（mask=1）→ 透明（alpha=0），即 API 将在此处生成新内容。 + """ + if mask.dim() == 3: + mask = mask.squeeze(0) # [H, W] + + h, w = mask.shape + ih, iw = image_size + + # 尺寸不一致时给出提示（API 侧也会报错） + if (h, w) != (ih, iw): + raise ValueError( + f"蒙版尺寸 ({h}×{w}) 与图像尺寸 ({ih}×{iw}) 不一致，请保持相同尺寸" + ) + + alpha = ((1.0 - mask.cpu().numpy()) * 255).clip(0, 255).astype(np.uint8) + rgba = np.zeros((h, w, 4), dtype=np.uint8) + rgba[:, :, 3] = alpha # 只设 alpha，RGB 全 0 + + buf = BytesIO() + Image.fromarray(rgba, mode="RGBA").save(buf, format="PNG") + return buf.getvalue() + + @staticmethod + 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] + RGBA 自动转换为 RGBA（保留透明通道） + """ + if not images: + placeholder = Image.new("RGBA", (512, 512), (128, 128, 128, 255)) + images = [placeholder] + + tensors = [] + for img in images: + arr = np.array(img.convert("RGBA")).astype(np.float32) / 255.0 + tensors.append(torch.from_numpy(arr)) + + return torch.stack(tensors, dim=0) # [B, H, W, 4] + + # ── 响应解析（通用） ───────────────────────────────────────────────────── + + async def _parse_response( + self, + resp_json: dict, + session: aiohttp.ClientSession, + ) -> List[Image.Image]: + """ + 解析 data 列表，优先取 b64_json，回退到 url 下载 + """ + if "error" in resp_json: + err = resp_json["error"] + msg = ( + err.get("message") or err.get("msg") or json.dumps(err, ensure_ascii=False) + if isinstance(err, dict) + else 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): + b64 = item.get("b64_json", "") + url = item.get("url", "") + + if b64: + # 优先 base64（无需二次下载） + try: + img_bytes = base64.b64decode(b64) + img = Image.open(BytesIO(img_bytes)) + images.append(img) + print(f"[o1key GPT Image] 第 {idx + 1} 张 base64 解码完成 " + f"({img.size[0]}×{img.size[1]})") + except Exception as e: + raise RuntimeError(f"第 {idx + 1} 张 base64 解码失败: {e}") + + elif url and url.startswith("http"): + # 回退：下载 URL + async with session.get(url, allow_redirects=True) as r: + if r.status != 200: + raise RuntimeError( + f"图像下载失败 HTTP {r.status}，URL: {url}" + ) + img_bytes = await r.read() + img = Image.open(BytesIO(img_bytes)) + images.append(img) + print(f"[o1key GPT Image] 第 {idx + 1} 张下载完成 " + f"({img.size[0]}×{img.size[1]})") + else: + print(f"[o1key GPT Image] 警告：第 {idx + 1} 条数据既无 b64_json 也无 url，已跳过") + + return images + + # ── 文生图 / 图生图（generations 接口）─────────────────────────────────── + + async def _generate_async( + self, + prompt: str, + model: str, + quality: str, + background: str, + size: str, + n: int, + seed: int, + image_tensor: Optional[torch.Tensor] = None, + ) -> List[Image.Image]: + """ + 调用 /v1/images/generations/ 接口。 + 当传入 image_tensor 时，以 data URI 格式内联图像（图生图）。 + """ + body: dict = { + "model": model, + "prompt": prompt, + "quality": quality, + "background": background, + "n": n, + "moderation": "low", + } + + # size = "auto" 时不传该字段，让 API 自行决定 + if size and size != "auto": + body["size"] = size + + # seed > 0 时才传递（0 视为不指定） + if seed > 0: + body["seed"] = seed + + # 图生图：将 tensor 转成 data URI 内联 + if image_tensor is not None: + pil_images = tensor_to_pil(image_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}") + body["image"] = data_urls[0] if len(data_urls) == 1 else data_urls + mode = f"图生图（参考图 {len(data_urls)} 张）" + else: + mode = "文生图" + + url = f"{self.base_url}{_ENDPOINT_GENERATIONS}" + print(f"[o1key GPT Image] {mode} | 模型={model} | quality={quality} | " + f"background={background} | size={size} | n={n}") + + connector = aiohttp.TCPConnector(ssl=False, force_close=True) + timeout = aiohttp.ClientTimeout(total=_REQUEST_TIMEOUT) + + async with aiohttp.ClientSession(connector=connector, timeout=timeout) as session: + t0 = time.time() + async with session.post(url, json=body, headers=self._json_headers()) as resp: + elapsed = time.time() - t0 + text = await resp.text() + + if resp.status != 200: + try: + err_json = json.loads(text) + err_obj = err_json.get("error", {}) + msg = ( + err_obj.get("message") or err_obj.get("msg") or text + if isinstance(err_obj, dict) + else 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"[o1key GPT Image] API 响应耗时 {elapsed:.1f}s") + return await self._parse_response(resp_json, session) + + # ── 图像编辑（edits 接口，必须带蒙版）─────────────────────────────────── + + async def _edit_async( + self, + prompt: str, + model: str, + quality: str, + background: str, + size: str, + n: int, + seed: int, + image_tensor: torch.Tensor, + mask_tensor: Optional[torch.Tensor] = None, + ) -> List[Image.Image]: + """ + 调用 /v1/images/edits/ 接口（multipart/form-data）。 + image_tensor 取第一帧（edits 接口仅支持单张输入图）。 + """ + # 取第一张图 + single = image_tensor[:1] if image_tensor.dim() == 4 else image_tensor.unsqueeze(0) + image_png = self._tensor_to_png_bytes(single) + ih, iw = single.shape[1], single.shape[2] + + # 构建 multipart 表单 + form = aiohttp.FormData() + form.add_field("model", model) + form.add_field("prompt", prompt) + form.add_field("quality", quality) + form.add_field("background", background) + form.add_field("n", str(n)) + form.add_field("moderation", "low") + + if size and size != "auto": + form.add_field("size", size) + + if seed > 0: + form.add_field("seed", str(seed)) + + # 主图（PNG） + form.add_field( + "image", + image_png, + filename="image.png", + content_type="image/png", + ) + + # 蒙版（PNG，RGBA 格式，透明区域为待编辑区） + if mask_tensor is not None: + mask_png = self._mask_tensor_to_rgba_png_bytes(mask_tensor, (ih, iw)) + form.add_field( + "mask", + mask_png, + filename="mask.png", + content_type="image/png", + ) + mode = "图像编辑（带蒙版）" + else: + mode = "图像编辑（无蒙版）" + + url = f"{self.base_url}{_ENDPOINT_EDITS}" + print(f"[o1key GPT Image] {mode} | 模型={model} | quality={quality} | " + f"background={background} | size={size} | n={n}") + + connector = aiohttp.TCPConnector(ssl=False, force_close=True) + timeout = aiohttp.ClientTimeout(total=_REQUEST_TIMEOUT) + + async with aiohttp.ClientSession(connector=connector, timeout=timeout) as session: + t0 = time.time() + async with session.post( + url, + data=form, + headers=self._auth_headers(), # Content-Type 由 FormData 自动设置 + ) as resp: + elapsed = time.time() - t0 + text = await resp.text() + + if resp.status != 200: + try: + err_json = json.loads(text) + err_obj = err_json.get("error", {}) + msg = ( + err_obj.get("message") or err_obj.get("msg") or text + if isinstance(err_obj, dict) + else 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"[o1key GPT Image] API 响应耗时 {elapsed:.1f}s") + return await self._parse_response(resp_json, session) + + # ── 同步统一入口（供节点调用）──────────────────────────────────────────── + + def run_sync( + self, + prompt: str, + model: str, + quality: str, + background: str, + size: str, + n: int, + seed: int, + image_tensor: Optional[torch.Tensor] = None, + mask_tensor: Optional[torch.Tensor] = None, + ) -> List[Image.Image]: + """ + 同步入口，在独立线程中运行事件循环，避免与 ComfyUI 主循环冲突。 + + 路由逻辑： + - 无 image_tensor → generations 接口（文生图） + - 有 image_tensor，无 mask → generations 接口（图生图，data URI） + - 有 image_tensor，有 mask → edits 接口（图像编辑 + 蒙版） + """ + use_edits = (image_tensor is not None and mask_tensor is not None) + + if use_edits: + coro = self._edit_async( + prompt=prompt, model=model, quality=quality, + background=background, size=size, n=n, seed=seed, + image_tensor=image_tensor, mask_tensor=mask_tensor, + ) + else: + coro = self._generate_async( + prompt=prompt, model=model, quality=quality, + background=background, size=size, n=n, seed=seed, + 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"o1key GPT Image 请求超时（>{_REQUEST_TIMEOUT}s），请检查网络或稍后重试" + ) diff --git a/nodes/__init__.py b/nodes/__init__.py index 831568f..9f3f416 100644 --- a/nodes/__init__.py +++ b/nodes/__init__.py @@ -19,5 +19,6 @@ from .multi_res_preview import MultiResPreview from .batch_images_o1key import BatchImagesO1key from .seedance_video import Seedance, SeedanceMultiModal from .doubao_image import DoubaoImage +from .o1key_gpt_image import O1keyGPTImage -__all__ = ['NanoBananaPro', 'BatchNanoBananaPro', 'GoogleGemini', 'LoadFile', 'ImageStitchPro', 'SaveCleanImage', 'BatchCleanMetadata', 'VideoPreview', 'KlingVideo', 'KlingFirstLastFrame', 'KlingMotionControlTest', 'AspectRatioPreset', 'GoogleVeo', 'FluxImageEdit', 'UniversalLLMChat', 'MultiResPreview', 'BatchImagesO1key', 'Seedance', 'SeedanceMultiModal', 'StreamPreview', 'DoubaoImage'] +__all__ = ['NanoBananaPro', 'BatchNanoBananaPro', 'GoogleGemini', 'LoadFile', 'ImageStitchPro', 'SaveCleanImage', 'BatchCleanMetadata', 'VideoPreview', 'KlingVideo', 'KlingFirstLastFrame', 'KlingMotionControlTest', 'AspectRatioPreset', 'GoogleVeo', 'FluxImageEdit', 'UniversalLLMChat', 'MultiResPreview', 'BatchImagesO1key', 'Seedance', 'SeedanceMultiModal', 'StreamPreview', 'DoubaoImage', 'O1keyGPTImage'] diff --git a/nodes/o1key_gpt_image.py b/nodes/o1key_gpt_image.py new file mode 100644 index 0000000..b52cd42 --- /dev/null +++ b/nodes/o1key_gpt_image.py @@ -0,0 +1,158 @@ +""" +o1key GPT Image 节点 +支持 gpt-image-1 / gpt-image-1.5 模型的文生图、图生图、图像编辑（带蒙版） +""" + +import time +import torch + +from ..clients.gpt_image_client import GptImageClient + + +class O1keyGPTImage: + """ + o1key GPT Image 节点 + + 功能： + - 文生图：仅提供 prompt + - 图生图：提供 prompt + image（无 mask） + - 图像编辑：提供 prompt + image + mask（白色区域将被替换） + + 参数： + - prompt : 文本提示词（多行） + - seed : 随机种子（0 表示不指定） + - quality : 图像质量 low / medium / high + - background : 背景模式 auto / opaque / transparent + - size : 图像尺寸（auto 让 API 自动决定） + - n : 生成数量 1-8 + - image : 可选参考图（用于图生图或编辑） + - mask : 可选蒙版（白色区域将被替换） + - model : 模型选择 gpt-image-1 / gpt-image-1.5 + """ + + @classmethod + def INPUT_TYPES(cls): + return { + "required": { + "prompt": ("STRING", { + "default": "", + "multiline": True, + "tooltip": "Text prompt for GPT Image", + }), + }, + "optional": { + "seed": ("INT", { + "default": 0, + "min": 0, + "max": 2**31 - 1, + "step": 1, + "display": "number", + "control_after_generate": True, + "tooltip": "Random seed (0 = not specified)", + }), + "quality": (["low", "medium", "high"], { + "default": "low", + "tooltip": "Image quality, affects cost and generation time.", + }), + "background": (["auto", "opaque", "transparent"], { + "default": "auto", + "tooltip": "Return image with or without background", + }), + "size": (["auto", "1024x1024", "1024x1536", "1536x1024"], { + "default": "auto", + "tooltip": "Image size (auto = API decides)", + }), + "n": ("INT", { + "default": 1, + "min": 1, + "max": 8, + "step": 1, + "display": "number", + "tooltip": "How many images to generate", + }), + "image": ("IMAGE", { + "tooltip": "Optional reference image for image editing.", + }), + "mask": ("MASK", { + "tooltip": "Optional mask for inpainting (white areas will be replaced)", + }), + "model": (["gpt-image-1", "gpt-image-1.5"], { + "default": "gpt-image-1.5", + }), + }, + } + + RETURN_TYPES = ("IMAGE",) + RETURN_NAMES = ("IMAGE",) + FUNCTION = "generate" + CATEGORY = "o1key/image" + OUTPUT_NODE = False + + def generate( + self, + prompt: str, + seed: int = 0, + quality: str = "low", + background: str = "auto", + size: str = "auto", + n: int = 1, + image=None, + mask=None, + model: str = "gpt-image-1.5", + ): + """ + 生成图像（文生图 / 图生图 / 图像编辑） + + 路由逻辑： + - 无 image → generations 接口（文生图） + - 有 image，无 mask → generations 接口（图生图） + - 有 image，有 mask → edits 接口（图像编辑 + 蒙版） + """ + start_time = time.time() + + # ── 1. 参数校验 ─────────────────────────────────────────────────────── + if not prompt or not prompt.strip(): + raise ValueError("提示词不能为空") + + if mask is not None and image is None: + raise ValueError("提供了蒙版但未提供图像，请同时提供 image 和 mask") + + # ── 2. 创建客户端 ───────────────────────────────────────────────────── + try: + client = GptImageClient() + except ValueError as e: + if str(e) == "未授权！": + print("[o1key GPT Image] 请联系作者授权后方可使用！") + raise ValueError("未授权！") from None + raise + + # ── 3. 调用 API ─────────────────────────────────────────────────────── + try: + pil_images = client.run_sync( + prompt=prompt, + model=model, + quality=quality, + background=background, + size=size, + n=n, + seed=seed, + image_tensor=image, + mask_tensor=mask, + ) + except Exception as e: + error_msg = str(e).split('\n')[0] + print(f"[o1key GPT Image] ❌ {error_msg}") + raise RuntimeError(error_msg) from None + + # ── 4. PIL → tensor ─────────────────────────────────────────────────── + output_tensor = GptImageClient._pil_list_to_tensor(pil_images) + + # ── 5. 完成日志 ─────────────────────────────────────────────────────── + elapsed = time.time() - start_time + print( + f"[o1key GPT Image] 完成！耗时 {elapsed:.1f}s，" + f"输出 {output_tensor.shape[0]} 张 " + f"{output_tensor.shape[2]}×{output_tensor.shape[1]}" + ) + + return (output_tensor,)