diff --git a/__init__.py b/__init__.py index 061b619..2862d4f 100644 --- a/__init__.py +++ b/__init__.py @@ -3,12 +3,18 @@ __all__ = [ "NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS", - + ] __author__ = """xuyucai""" __email__ = "986327386@qq.com" -__version__ = "53.1.2" +__version__ = "53.2.0" -from .src.Comfyui_Fd_Nodes.nodes import NODE_CLASS_MAPPINGS -from .src.Comfyui_Fd_Nodes.nodes import NODE_DISPLAY_NAME_MAPPINGS +try: + from .src.Comfyui_Fd_Nodes.nodes import NODE_CLASS_MAPPINGS + from .src.Comfyui_Fd_Nodes.nodes import NODE_DISPLAY_NAME_MAPPINGS +except ModuleNotFoundError as exc: + if not exc.name.startswith("comfy"): + raise + NODE_CLASS_MAPPINGS = {} + NODE_DISPLAY_NAME_MAPPINGS = {} diff --git a/pyproject.toml b/pyproject.toml index 205ca1d..0572f57 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta" [project] name = "Comfyui_Fd_Nodes" -version = "53.1.2" # 999开头的版本是debug版 +version = "53.2.0" # 999开头的版本是debug版 description = "Custom nodes for fd project" authors = [ {name = "xuyucai", email = "986327386@qq.com"} diff --git a/remove-bg-by-meitu-refactor-doc.md b/remove-bg-by-meitu-refactor-doc.md new file mode 100644 index 0000000..1847d4d --- /dev/null +++ b/remove-bg-by-meitu-refactor-doc.md @@ -0,0 +1,198 @@ +# 服装退底接口 remove-bg-by-meitu 重构文档 + +## 一、接口概述 + +**业务含义**: 接收一张服装图片 URL，调用外部 AI 服务（美图）进行背景移除（抠图），返回处理后的图片、mask 和红边图片 URL。 + +**当前实现方式**: Spring Cloud OpenFeign 直连外部 AI 服务，Controller 层透传，无额外业务逻辑。 + +**重构目标**: 重新实现请求逻辑（具体目标待确认，以下文档供 Codex 理解现有代码结构）。 + +--- + +## 二、调用链路 + +``` +HTTP 请求 (POST /image-combine/mt/remove-bg-by-meitu) + → ImageCombineMTController.removeBgByMeitu() + → ImageCombineMTServingClient.removeBgByMeitu() [Feign 调用] + → POST {image.detail.url}/image/remove_bg_by_meitu [外部 AI 服务] + ← ClothRemoveBGDTO + ← ApiResult +``` + +--- + +## 三、涉及文件清单（绝对路径） + +### 3.1 Controller 层 + +**文件**: `/Users/chenjunhong/Documents/javaProject/fashion-parent/app-business-clothingAI/src/main/java/com/zhiyi/fashion/clothingai/server/facade/http/controller/ImageCombineMTController.java` + +- 第 74-78 行: `remove-bg-by-meitu` 接口入口 +- 依赖注入: `ImageCombineMTServingClient`, `XinChenManager`, `ImageProcessStatisticsManager` +- 注意: 当前该接口**没有** XinChen 团队判断和统计埋点，但同文件中 `merge-forge-back` 接口（第 108-118 行）有这些逻辑，可作为参考 + +```java +// 第 74-78 行 +@ApiOperation(value = "服装退底", httpMethod = "POST") +@PostMapping("/remove-bg-by-meitu") +public ApiResult removeBgByMeitu(HttpServletRequest request, @RequestBody ClothRemoveBGRequest clothRemoveBGRequest) { + ClothRemoveBGDTO clothRemoveBGDTO = imageCombineMTServingClient.removeBgByMeitu(clothRemoveBGRequest); + return ApiResult.success(clothRemoveBGDTO); +} +``` + +### 3.2 Feign Client 层（HTTP 客户端） + +**文件**: `/Users/chenjunhong/Documents/javaProject/fashion-parent/app-business-clothingAI/src/main/java/com/zhiyi/fashion/clothingai/server/infra/api/ai/ImageCombineMTServingClient.java` + +- 第 51-52 行: `removeBgByMeitu` 方法定义 +- 第 15 行: `@FeignClient` 配置，基础 URL 为 `${image.detail.url}` +- 第 60-61 行: 还有一个 API 版本 `remove_bg_by_api`，接收相同请求/响应 + +```java +// 第 51-52 行 +@PostMapping("/image/remove_bg_by_meitu") +ClothRemoveBGDTO removeBgByMeitu(@RequestBody ClothRemoveBGRequest request); +``` + +### 3.3 Feign 序列化配置 + +**文件**: `/Users/chenjunhong/Documents/javaProject/fashion-parent/app-business-clothingAI/src/main/java/com/zhiyi/fashion/clothingai/server/infra/api/ai/config/FeignSnakeCaseConfig.java` + +- 功能: 将 Java camelCase 字段自动转为 snake_case 发送给下游服务 +- 影响范围: 所有使用此 configuration 的 Feign Client + +### 3.4 请求对象 + +**文件**: `/Users/chenjunhong/Documents/javaProject/fashion-parent/app-business-clothingAI/src/main/java/com/zhiyi/fashion/clothingai/server/infra/api/ai/request/ClothRemoveBGRequest.java` + +```java +@Data +public class ClothRemoveBGRequest { + @ApiModelProperty("图片链接") + private String imageUrl; + + private Integer repaintEdge; + + @ApiModelProperty("红边框粗细，默认40") + private Integer edgeThickness = 40; +} +``` + +经 FeignSnakeCaseConfig 转换后，实际发送给下游的 JSON 格式: +```json +{ + "image_url": "https://xxx/xxx.jpg", + "repaint_edge": 1, + "edge_thickness": 40 +} +``` + +### 3.5 响应对象 + +**基础 DTO 文件**: `/Users/chenjunhong/Documents/javaProject/fashion-parent/app-business-clothingAI/src/main/java/com/zhiyi/fashion/clothingai/server/infra/api/ai/dto/ImageCombineBaseDTO.java` + +```java +@Data +public class ImageCombineBaseDTO implements Serializable { + private Boolean status; + @JsonProperty("cost_time") + private String costTime; + @JsonProperty("server_name") + private String serverName; + private ImageCombineError error; + + @Data + public static class ImageCombineError { + private String code; + private String message; + } +} +``` + +**业务 DTO 文件**: `/Users/chenjunhong/Documents/javaProject/fashion-parent/app-business-clothingAI/src/main/java/com/zhiyi/fashion/clothingai/server/infra/api/ai/dto/ClothRemoveBGDTO.java` + +```java +@Data +public class ClothRemoveBGDTO extends ImageCombineBaseDTO implements Serializable { + private String resultUrl; + private String mainMaskUrl; + private String RedEdgeImageUrl; // 注意: 这里是大写 R 开头，snake_case 转换后为 red_edge_image_url +} +``` + +下游返回的 JSON 格式: +```json +{ + "status": true, + "cost_time": "1.23s", + "server_name": "xxx", + "error": null, + "result_url": "https://xxx/result.jpg", + "main_mask_url": "https://xxx/mask.png", + "red_edge_image_url": "https://xxx/edge.png" +} +``` + +### 3.6 可参考的辅助类（同模块已有逻辑） + +**XinChen 团队处理**: `/Users/chenjunhong/Documents/javaProject/fashion-parent/app-business-clothingAI/src/main/java/com/zhiyi/fashion/clothingai/server/domain/manager/XinChenManager.java` + +**图片处理统计**: `/Users/chenjunhong/Documents/javaProject/fashion-parent/app-business-clothingAI/src/main/java/com/zhiyi/fashion/clothingai/server/domain/manager/ImageProcessStatisticsManager.java` + +--- + +## 四、同文件中可参考的完整业务逻辑（merge-forge-back） + +`ImageCombineMTController.java` 第 106-118 行的 `merge-forge-back` 接口包含了完整的业务处理模式，包含: +1. Feign 调用 +2. XinChen 团队图片转存判断 +3. 统计埋点 + +```java +@ApiOperation(value = "背景融合接口", httpMethod = "POST") +@PostMapping("/merge-forge-back") +public ApiResult mergeForgeBack(HttpServletRequest request, @RequestBody MergeForgeBackRequest mergeForgeBackRequest) { + MergeForgeBackDTO mainMaskDTO = imageCombineMTServingClient.mergeForgeBack(mergeForgeBackRequest); + RequestContext requestContext = RequestHelper.formContext(request); + if (xinChenManager.isXinChenTeam(requestContext.getTeamId())) { + mainMaskDTO.setImageUrl(xinChenManager.copy2XinChenImage(mainMaskDTO.getImageUrl())); + mainMaskDTO.setMainMaskUrl(xinChenManager.copy2XinChenImage(mainMaskDTO.getMainMaskUrl())); + mainMaskDTO.setResultUrl(xinChenManager.copy2XinChenImage(mainMaskDTO.getResultUrl())); + } + imageProcessStatisticsManager.saveImageProcessStatistics(mergeForgeBackRequest.getImageUrl(), 5); + return ApiResult.success(mainMaskDTO); +} +``` + +--- + +## 五、项目包结构 + +``` +com.zhiyi.fashion.clothingai.server +├── facade.http.controller → Controller 层 +│ └── ImageCombineMTController.java +├── infra.api.ai → 外部 API 调用层 +│ ├── ImageCombineMTServingClient.java (Feign Client 接口) +│ ├── config/ +│ │ └── FeignSnakeCaseConfig.java (snake_case 序列化配置) +│ ├── request/ +│ │ └── ClothRemoveBGRequest.java (请求体) +│ └── dto/ +│ ├── ImageCombineBaseDTO.java (基础响应) +│ └── ClothRemoveBGDTO.java (业务响应) +└── domain.manager → 业务逻辑层 + ├── XinChenManager.java + └── ImageProcessStatisticsManager.java +``` + +--- + +## 六、关键配置 + +- **外部服务基础 URL**: `${image.detail.url}` — 在 Apollo 或环境变量中配置 +- **Feign 超时**: 在 `bootstrap.yml` 中配置 +- **命名策略**: camelCase → snake_case（双向，请求和响应都自动转换） diff --git a/src/Comfyui_Fd_Nodes/config_manager.py b/src/Comfyui_Fd_Nodes/config_manager.py index 95d4627..0d0d438 100644 --- a/src/Comfyui_Fd_Nodes/config_manager.py +++ b/src/Comfyui_Fd_Nodes/config_manager.py @@ -1,6 +1,3 @@ -import json -import os - from .config import ( FD_LITELLM_API_KEY, FD_LITELLM_BASE_URL, diff --git a/src/Comfyui_Fd_Nodes/gpt_image_edit_node.py b/src/Comfyui_Fd_Nodes/gpt_image_edit_node.py new file mode 100644 index 0000000..ab329b0 --- /dev/null +++ b/src/Comfyui_Fd_Nodes/gpt_image_edit_node.py @@ -0,0 +1,5 @@ +from .gpt_image_node import FD_GTPImage + +GPTImageEditNode = FD_GTPImage + +__all__ = ["GPTImageEditNode"] diff --git a/src/Comfyui_Fd_Nodes/nodes.py b/src/Comfyui_Fd_Nodes/nodes.py index d3e0c98..b0c51e5 100644 --- a/src/Comfyui_Fd_Nodes/nodes.py +++ b/src/Comfyui_Fd_Nodes/nodes.py @@ -2,8 +2,6 @@ import io import json import logging import os -import random -import time import traceback from datetime import datetime from inspect import cleandoc @@ -50,6 +48,7 @@ from .gpt_multi_image_node import FD_GPTMultiImage from .prompt_nodes import EcommercePromptGenerator, PromptListSelector from .zhiyi_text_node import ZhiYiTextGenNode from .zhiyi_image_text_node import ZhiYiImageTextNode +from .zhiyi_image_text_combo_node import ZhiYiImageTextComboNode from .zhiyi_image_to_image_node import ZhiYiImageToImageNode from .toggle import NodeToggleByID from .utils.logging_utils import configure_default_logging @@ -57,6 +56,7 @@ from .zhiyi_image_combo_node import ZhiYiImageComboNode from .zhiyi_image_to_image_combo_node import ZhiYiImageToImageComboNode from .aistudio_image_combo_node import ZhiYiAiStudioImageComboNode from .remove_bg_by_meitu_node import ZhiYiRemoveBgByMeituNode +from .utils.gpt_image_size import resolution_to_edit_size configure_default_logging() logger = logging.getLogger(__name__) @@ -65,6 +65,10 @@ logger = logging.getLogger(__name__) FD_REMOVE_WATERMARK_SERVICE_URL = os.getenv("FD_REMOVE_WATERMARK_SERVICE_URL", "http://localhost:8000/v1/process") +def _resolution_to_edit_size(resolution: str, aspect_ratio: str) -> str: + return resolution_to_edit_size(resolution, aspect_ratio) + + class FD_RemoveWatermark: """ Remove watermark from image using AI inpainting service @@ -883,6 +887,7 @@ NODE_CLASS_MAPPINGS = { "MaoziEcommercePromptGenerator": EcommercePromptGenerator, "MaoziPromptListSelector": PromptListSelector, "ZhiYiImageTextNode": ZhiYiImageTextNode, + "ZhiYiImageTextComboNode": ZhiYiImageTextComboNode, "ZhiYiImageToImageNode": ZhiYiImageToImageNode, "ZhiYiTextGenNode": ZhiYiTextGenNode, "NodeToggleByID": NodeToggleByID, @@ -907,6 +912,7 @@ NODE_DISPLAY_NAME_MAPPINGS = { "MaoziEcommercePromptGenerator": "猫子提示词节点-详情页生成器", "MaoziPromptListSelector": "猫子提示词节点-列表选择器", "ZhiYiImageTextNode": "知衣-图生文", + "ZhiYiImageTextComboNode": "知衣-图生文-combo", "ZhiYiImageToImageNode": "知衣-图生图", "ZhiYiTextGenNode": "知衣-文生文", "NodeToggleByID": "节点开关 (按ID)", diff --git a/src/Comfyui_Fd_Nodes/old_fd_nodes.py b/src/Comfyui_Fd_Nodes/old_fd_nodes.py index 04ff366..0fc540b 100644 --- a/src/Comfyui_Fd_Nodes/old_fd_nodes.py +++ b/src/Comfyui_Fd_Nodes/old_fd_nodes.py @@ -1,5 +1,4 @@ import json -import os import time import oss2 @@ -107,4 +106,4 @@ class FD_imgToText_Doubao: return (data["response"]["Result"],) except Exception as e: print(e) - return (defaultPrompt,) \ No newline at end of file + return (defaultPrompt,) diff --git a/src/Comfyui_Fd_Nodes/utils/gemini_service.py b/src/Comfyui_Fd_Nodes/utils/gemini_service.py index cd9a111..295a3be 100644 --- a/src/Comfyui_Fd_Nodes/utils/gemini_service.py +++ b/src/Comfyui_Fd_Nodes/utils/gemini_service.py @@ -26,6 +26,8 @@ logger = logging.getLogger(__name__) MODEL_NAME_MAP = { "gemini-2.5-flash-image-preview": "google/gemini-2.5-flash-image-preview", "gemini-3-pro-image-preview": "google/gemini-3-pro-image-preview", + "gemini-3-pro-image-preview-aistudio": "google/gemini-3-pro-image-preview-official", + "gemini-3-pro-image-preview-official": "google/gemini-3-pro-image-preview-official", "gemini-3.1-flash-image-preview": "google/gemini-3.1-flash-image-preview", } diff --git a/src/Comfyui_Fd_Nodes/utils/litellm_gemini_image.py b/src/Comfyui_Fd_Nodes/utils/litellm_gemini_image.py index ff22200..85501a1 100644 --- a/src/Comfyui_Fd_Nodes/utils/litellm_gemini_image.py +++ b/src/Comfyui_Fd_Nodes/utils/litellm_gemini_image.py @@ -16,7 +16,6 @@ logger = logging.getLogger(__name__) LITELLM_GEMINI_MODELS = { - "gemini-3-pro-image-preview-aistudio", "gemini-3-pro-image-preview-siphonlab", } diff --git a/src/Comfyui_Fd_Nodes/zhiyi_image_text_combo_node.py b/src/Comfyui_Fd_Nodes/zhiyi_image_text_combo_node.py new file mode 100644 index 0000000..0061814 --- /dev/null +++ b/src/Comfyui_Fd_Nodes/zhiyi_image_text_combo_node.py @@ -0,0 +1,399 @@ +import json +import logging +import time +import traceback +from concurrent.futures import ThreadPoolExecutor, as_completed + +import requests + +from .config_manager import load_config +from .utils.error_utils import normalize_error_message +from .utils.logging_utils import configure_default_logging +from .zhiyi_image_text_node import ZhiYiImageTextNode + +configure_default_logging() +logger = logging.getLogger(__name__) + + +class ZhiYiImageTextComboNode(ZhiYiImageTextNode): + """知衣多图图生文节点 - 接收最多8个图片组合并发调用豆包视觉理解 API。""" + + DEFAULT_PROMPT = "介绍这幅图片" + MODEL = "doubao-seed-2.0-mini" + + @classmethod + def INPUT_TYPES(cls): + return { + "required": { + "max_concurrency": ("INT", { + "default": 8, + "min": 1, + "max": 64, + "step": 1, + "tooltip": "同时发送请求的最大数量，避免触发 API 限流", + }), + "temperature": ("FLOAT", { + "default": 0.7, + "min": 0.0, + "max": 2.0, + "step": 0.05, + }), + "max_tokens": ("INT", { + "default": 2048, + "min": 1, + "max": 8192, + "step": 1, + }), + "retry_count": ("INT", { + "default": 1, + "min": 0, + "max": 3, + "step": 1, + "tooltip": "请求失败后的重试次数。仅重试网络错误、超时、429 和 5xx", + }), + }, + "optional": { + "node_switch": ("INT", { + "default": 0, + "min": 0, + "max": 1, + "step": 1, + "display": "number", + }), + "combo_1": ("ZHIYI_COMBO",), + "combo_2": ("ZHIYI_COMBO",), + "combo_3": ("ZHIYI_COMBO",), + "combo_4": ("ZHIYI_COMBO",), + "combo_5": ("ZHIYI_COMBO",), + "combo_6": ("ZHIYI_COMBO",), + "combo_7": ("ZHIYI_COMBO",), + "combo_8": ("ZHIYI_COMBO",), + "system_prompt": ("STRING", { + "default": "", + "multiline": True, + }), + }, + } + + RETURN_TYPES = ("STRING", "STRING") + RETURN_NAMES = ("text", "log") + FUNCTION = "generate" + CATEGORY = "知衣/图生文" + OUTPUT_NODE = False + + def _expand_images(self, combo_images): + result = [] + for image in combo_images: + if image is None: + continue + if image.ndim == 4: + for i in range(image.shape[0]): + result.append(image[i:i + 1]) + elif image.ndim == 3: + result.append(image.unsqueeze(0)) + else: + raise RuntimeError(f"图片 tensor 维度错误: {image.ndim}") + return result + + def _select_prompt(self, combo): + combo_prompts = combo.get("prompts") + if isinstance(combo_prompts, str): + combo_prompts = [combo_prompts] + if isinstance(combo_prompts, list): + for prompt in combo_prompts: + if isinstance(prompt, str) and prompt.strip(): + return prompt.strip() + + prompt = combo.get("prompt", "") + if isinstance(prompt, str) and prompt.strip(): + return prompt.strip() + return self.DEFAULT_PROMPT + + def _build_messages(self, prompt, data_urls, system_prompt=""): + messages = [] + system_text = (system_prompt or "").strip() + if system_text: + messages.append({ + "role": "system", + "content": [{"type": "text", "text": system_text}], + }) + + content = [{"type": "text", "text": prompt}] + for data_url in data_urls: + content.append({"type": "image_url", "image_url": {"url": data_url}}) + + messages.append({"role": "user", "content": content}) + return messages + + def _extract_text(self, result): + text = result["choices"][0]["message"]["content"] + if isinstance(text, list): + return "".join( + part.get("text", "") for part in text if isinstance(part, dict) + ) + if text is None: + return "" + return str(text) + + def _is_retryable_status(self, status_code): + return status_code == 429 or 500 <= status_code < 600 + + def _is_retryable_exception(self, exc): + if isinstance(exc, (requests.exceptions.Timeout, requests.exceptions.ConnectionError)): + return True + + response = getattr(exc, "response", None) + status_code = getattr(response, "status_code", None) + return status_code is not None and self._is_retryable_status(status_code) + + def _sleep_before_retry(self, attempt_index): + time.sleep(min(2 ** attempt_index, 2)) + + def _single_request(self, url, api_key, messages, temperature, max_tokens, retry_count): + payload = { + "stream": False, + "model": self.MODEL, + "messages": messages, + "temperature": temperature, + "max_tokens": max_tokens, + } + max_attempts = max(1, int(retry_count) + 1) + last_error = None + + for attempt_index in range(max_attempts): + response = None + try: + logger.info( + "Calling ZhiYi image-to-text combo API with payload=%s", + { + "url": url, + "stream": payload["stream"], + "model": payload["model"], + "temperature": payload["temperature"], + "max_tokens": payload["max_tokens"], + "attempt": attempt_index + 1, + "max_attempts": max_attempts, + "messages": self._summarize_messages_for_log(messages), + }, + ) + response = requests.post( + url=url, + headers={ + "Authorization": f"Bearer {api_key}", + "Content-Type": "application/json", + }, + data=json.dumps(payload), + timeout=600, + ) + + status_code = getattr(response, "status_code", None) + if status_code is not None and status_code >= 400: + response_text = getattr(response, "text", "")[:1000] + last_error = RuntimeError(f"API 请求失败: {status_code}\n{response_text}") + if self._is_retryable_status(status_code) and attempt_index < max_attempts - 1: + logger.warning( + "ZhiYi image-to-text combo API attempt %s/%s failed with HTTP %s, retrying", + attempt_index + 1, + max_attempts, + status_code, + ) + self._sleep_before_retry(attempt_index) + continue + raise last_error + + response.raise_for_status() + result = response.json() + logger.info( + "ZhiYi image-to-text combo API response summary: %s", + { + "status_code": response.status_code, + **self._summarize_response_for_log(result), + }, + ) + return self._extract_text(result), attempt_index + except (KeyError, IndexError, TypeError, ValueError) as exc: + response_text = response.text[:500] if response is not None else "" + raise RuntimeError(f"解析响应失败: {exc}\n原始响应: {response_text}") from exc + except requests.exceptions.RequestException as exc: + last_error = exc + if self._is_retryable_exception(exc) and attempt_index < max_attempts - 1: + logger.warning( + "ZhiYi image-to-text combo API attempt %s/%s failed, retrying: %s", + attempt_index + 1, + max_attempts, + exc, + ) + self._sleep_before_retry(attempt_index) + continue + raise RuntimeError(f"API 请求失败: {exc}") from exc + + raise RuntimeError(last_error or "API 请求失败") + + def _run_concurrent(self, tasks, max_workers, label="请求"): + results = {} + log_lines = [] + last_error_message = None + workers = min(len(tasks), max(1, int(max_workers))) + with ThreadPoolExecutor(max_workers=workers) as executor: + futures = { + executor.submit(fn, *args): (result_index, combo_slot) + for result_index, combo_slot, fn, args in tasks + } + for future in as_completed(futures): + result_index, combo_slot = futures[future] + try: + text, retry_used = future.result() + results[result_index] = {"ok": True, "text": text} + suffix = f"，重试 {retry_used} 次" if retry_used else "" + log_lines.append(f"[{label} combo_{combo_slot}] 成功{suffix}") + except Exception as exc: + normalized_error = normalize_error_message(exc) + last_error_message = normalized_error + results[result_index] = {"ok": False, "text": f"ERROR: {normalized_error}"} + log_lines.append(f"[{label} combo_{combo_slot}] 失败: {normalized_error}") + print(f"[知衣图生文-combo] combo_{combo_slot} 失败: {normalized_error}") + traceback.print_exc() + return results, log_lines, last_error_message + + def _format_text_output(self, combo_inputs, result_items): + successful = [item for item in result_items if item and item.get("ok")] + if len(combo_inputs) == 1 and len(successful) == 1: + return successful[0]["text"] + + sections = [] + for index, (combo_slot, _combo) in enumerate(combo_inputs): + item = result_items[index] or { + "ok": False, + "text": "ERROR: UNKNOWN: 未执行", + } + sections.append(f"[combo_{combo_slot}]\n{item['text']}") + return "\n\n".join(sections) + + def generate( + self, + max_concurrency=8, + temperature=0.7, + max_tokens=2048, + retry_count=1, + node_switch=0, + combo_1=None, + combo_2=None, + combo_3=None, + combo_4=None, + combo_5=None, + combo_6=None, + combo_7=None, + combo_8=None, + system_prompt="", + ): + if node_switch == 1: + return ("", "node skipped") + + cfg = load_config() + base_url = cfg["base_url"].rstrip("/") + api_key = cfg["api_key"] + url = f"{base_url}/v1/chat/completions" + + combo_inputs = [ + (slot, combo) + for slot, combo in enumerate( + [combo_1, combo_2, combo_3, combo_4, combo_5, combo_6, combo_7, combo_8], + start=1, + ) + if combo is not None + ] + if not combo_inputs: + raise RuntimeError("未提供任何组合输入，请连接至少一个 combo") + + result_items = [None] * len(combo_inputs) + tasks = [] + pre_errors = [] + last_error_message = None + + for result_index, (combo_slot, combo) in enumerate(combo_inputs): + try: + if not isinstance(combo, dict): + raise RuntimeError(f"数据格式错误: 期望 dict，实际 {type(combo).__name__}") + + combo_images = combo.get("images", []) + if not combo_images: + raise RuntimeError("无图片") + + expanded_images = self._expand_images(combo_images) + if not expanded_images: + raise RuntimeError("无有效图片") + + data_urls = [] + for image_index, image in enumerate(expanded_images, start=1): + data_url, image_info = self._image_tensor_to_data_url(image) + logger.info( + "ZhiYi image-to-text combo encoded image: %s", + { + "combo": combo_slot, + "image": image_index, + **image_info, + }, + ) + data_urls.append(data_url) + + prompt = self._select_prompt(combo) + messages = self._build_messages(prompt, data_urls, system_prompt) + tasks.append( + ( + result_index, + combo_slot, + self._single_request, + ( + url, + api_key, + messages, + temperature, + max_tokens, + retry_count, + ), + ) + ) + except Exception as exc: + normalized_error = normalize_error_message(exc) + last_error_message = normalized_error + result_items[result_index] = {"ok": False, "text": f"ERROR: {normalized_error}"} + msg = f"[combo_{combo_slot}] 预处理失败: {normalized_error}" + pre_errors.append(msg) + print(f"[知衣图生文-combo] {msg}") + traceback.print_exc() + + run_results = {} + run_log_lines = [] + if tasks: + print( + f"[知衣图生文-combo] 并发发送 {len(tasks)} 个请求（{len(combo_inputs)} 个组合），" + f"并发上限 {max_concurrency}" + ) + run_results, run_log_lines, run_last_error = self._run_concurrent( + tasks, + max_concurrency, + label="请求", + ) + if run_last_error: + last_error_message = run_last_error + + for result_index, item in run_results.items(): + result_items[result_index] = item + + successful_count = sum(1 for item in result_items if item and item.get("ok")) + header = ( + f"总计: {successful_count}/{len(combo_inputs)} 成功, " + f"url={url}, 并发上限={max_concurrency}, retry_count={retry_count}" + ) + log_lines = [header] + if pre_errors: + log_lines.extend(pre_errors) + log_lines.extend(run_log_lines) + log_text = "\n".join(log_lines) + + if successful_count == 0: + raise RuntimeError( + last_error_message or normalize_error_message(f"所有请求均失败，无文本返回\n{log_text}") + ) + + return (self._format_text_output(combo_inputs, result_items), log_text) diff --git a/src/Comfyui_Fd_Nodes/zhiyi_image_text_node.py b/src/Comfyui_Fd_Nodes/zhiyi_image_text_node.py index 85bc815..fa4948a 100644 --- a/src/Comfyui_Fd_Nodes/zhiyi_image_text_node.py +++ b/src/Comfyui_Fd_Nodes/zhiyi_image_text_node.py @@ -11,6 +11,11 @@ from .utils.logging_utils import configure_default_logging configure_default_logging() logger = logging.getLogger(__name__) +MAX_IMAGE_DATA_URL_BYTES = 10_000_000 +JPEG_QUALITY_STEPS = (85, 80, 75, 70, 65, 60) +MIN_IMAGE_LONG_EDGE = 1024 +IMAGE_RESIZE_FACTOR = 0.8 + class ZhiYiImageTextNode: """知衣图生文节点 - 传入图片，调用 Gemini 模型生成描述文本""" @@ -58,12 +63,66 @@ class ZhiYiImageTextNode: CATEGORY = "知衣/图生文" OUTPUT_NODE = False - def _image_tensor_to_base64(self, image_tensor): - arr = (image_tensor[0].numpy() * 255).clip(0, 255).astype(np.uint8) - pil_img = Image.fromarray(arr) + def _image_tensor_to_pil(self, image_tensor): + if getattr(image_tensor, "ndim", None) == 4: + image_tensor = image_tensor[0] + arr = (image_tensor.detach().cpu().numpy() * 255).clip(0, 255).astype(np.uint8) + return Image.fromarray(arr).convert("RGB") + + def _encode_jpeg_data_url(self, pil_img, quality): buf = io.BytesIO() - pil_img.save(buf, format="PNG") - return base64.b64encode(buf.getvalue()).decode("utf-8") + pil_img.save(buf, format="JPEG", quality=quality, optimize=True) + img_b64 = base64.b64encode(buf.getvalue()).decode("utf-8") + return f"data:image/jpeg;base64,{img_b64}", len(buf.getvalue()) + + def _resize_to_long_edge(self, pil_img, long_edge): + width, height = pil_img.size + current_long_edge = max(width, height) + if current_long_edge <= long_edge: + return pil_img + + scale = long_edge / current_long_edge + new_size = ( + max(1, int(round(width * scale))), + max(1, int(round(height * scale))), + ) + return pil_img.resize(new_size, Image.Resampling.LANCZOS) + + def _image_tensor_to_data_url(self, image_tensor): + original_img = self._image_tensor_to_pil(image_tensor) + original_size = original_img.size + current_long_edge = max(original_size) + best_result = None + + while True: + candidate_img = self._resize_to_long_edge(original_img, current_long_edge) + for quality in JPEG_QUALITY_STEPS: + data_url, image_bytes = self._encode_jpeg_data_url(candidate_img, quality) + data_url_bytes = len(data_url.encode("utf-8")) + info = { + "original_size": original_size, + "final_size": candidate_img.size, + "mime_type": "image/jpeg", + "quality": quality, + "image_bytes": image_bytes, + "data_url_bytes": data_url_bytes, + "max_data_url_bytes": MAX_IMAGE_DATA_URL_BYTES, + "resized": candidate_img.size != original_size, + } + best_result = (data_url, info) + if data_url_bytes <= MAX_IMAGE_DATA_URL_BYTES: + return best_result + + if current_long_edge <= MIN_IMAGE_LONG_EDGE: + break + current_long_edge = max(MIN_IMAGE_LONG_EDGE, int(current_long_edge * IMAGE_RESIZE_FACTOR)) + + _, info = best_result + raise RuntimeError( + "图生文输入图片压缩后仍超过 10MB 传输限制: " + f"{info['data_url_bytes']} bytes > {MAX_IMAGE_DATA_URL_BYTES} bytes; " + "请降低输入图片分辨率后重试" + ) def _summarize_messages_for_log(self, messages): summarized_messages = [] @@ -120,8 +179,8 @@ class ZhiYiImageTextNode: base_url = base_url.rstrip("/") url = f"{base_url}/v1/chat/completions" - img_b64 = self._image_tensor_to_base64(image) - data_url = f"data:image/png;base64,{img_b64}" + data_url, image_info = self._image_tensor_to_data_url(image) + logger.info("ZhiYi image-to-text encoded image: %s", image_info) messages = [] if system_prompt.strip(): diff --git a/src/Comfyui_Fd_Nodes/zhiyi_image_to_image_combo_node.py b/src/Comfyui_Fd_Nodes/zhiyi_image_to_image_combo_node.py index fd8faaa..596df5c 100644 --- a/src/Comfyui_Fd_Nodes/zhiyi_image_to_image_combo_node.py +++ b/src/Comfyui_Fd_Nodes/zhiyi_image_to_image_combo_node.py @@ -22,9 +22,14 @@ class ZhiYiImageToImageComboNode: """知衣图生图节点 - 接收最多8个图片组合并发调用 API""" MODELS = [ + "google/gemini-3-pro-image-preview", + "google/gemini-3.1-flash-image-preview", + "google/gemini-2.5-flash-image-preview", + "google/gemini-3-pro-image-preview-official", "gemini-3-pro-image-preview", "gemini-3.1-flash-image-preview", "gemini-2.5-flash-image-preview", + "gemini-3-pro-image-preview-official", "gemini-3-pro-image-preview-aistudio", "gemini-3-pro-image-preview-siphonlab", ] diff --git a/src/Comfyui_Fd_Nodes/zhiyi_image_to_image_node.py b/src/Comfyui_Fd_Nodes/zhiyi_image_to_image_node.py index c594e46..031b796 100644 --- a/src/Comfyui_Fd_Nodes/zhiyi_image_to_image_node.py +++ b/src/Comfyui_Fd_Nodes/zhiyi_image_to_image_node.py @@ -23,10 +23,16 @@ class ZhiYiImageToImageNode: """知衣图生图节点 - 最多6张输入图片，batch_size 控制重复请求次数，支持提示词列表并发""" MODELS = [ + "google/gemini-3-pro-image-preview", + "google/gemini-3.1-flash-image-preview", + "google/gemini-2.5-flash-image-preview", + "google/gemini-3-pro-image-preview-official", "gemini-3-pro-image-preview", "gemini-3.1-flash-image-preview", "gemini-2.5-flash-image-preview", + "gemini-3-pro-image-preview-official", "gemini-3-pro-image-preview-aistudio", + "gemini-3-pro-image-preview-siphonlab", ] ASPECT_RATIOS = ["", "1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "16:9", "9:16", "21:9"] diff --git a/tests/conftest.py b/tests/conftest.py index 310609c..5f750ed 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -1,6 +1,52 @@ import os import sys +import types + +os.environ.setdefault("FD_LITELLM_BASE_URL", "https://example.com") +os.environ.setdefault("FD_LITELLM_API_KEY", "test-key") # Add the project root directory to Python path # This allows the tests to import the project sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) + + +def _install_comfy_test_stubs(): + if "comfy.comfy_types.node_typing" in sys.modules: + return + + comfy_module = sys.modules.get("comfy") or types.ModuleType("comfy") + comfy_types_module = types.ModuleType("comfy.comfy_types") + node_typing_module = types.ModuleType("comfy.comfy_types.node_typing") + utils_module = types.ModuleType("comfy.utils") + + class IO: + STRING = "STRING" + COMBO = "COMBO" + INT = "INT" + FLOAT = "FLOAT" + BOOLEAN = "BOOLEAN" + IMAGE = "IMAGE" + + class ComfyNodeABC: + pass + + def common_upscale(samples, width, height, _upscale_method, _crop): + import torch.nn.functional as F + + return F.interpolate(samples, size=(height, width), mode="bilinear", align_corners=False) + + node_typing_module.IO = IO + node_typing_module.ComfyNodeABC = ComfyNodeABC + node_typing_module.InputTypeDict = dict + utils_module.common_upscale = common_upscale + comfy_module.comfy_types = comfy_types_module + comfy_module.utils = utils_module + comfy_types_module.node_typing = node_typing_module + + sys.modules["comfy"] = comfy_module + sys.modules["comfy.comfy_types"] = comfy_types_module + sys.modules["comfy.comfy_types.node_typing"] = node_typing_module + sys.modules["comfy.utils"] = utils_module + + +_install_comfy_test_stubs() diff --git a/tests/test_Comfyui_Fd_Nodes.py b/tests/test_Comfyui_Fd_Nodes.py index f933160..b6410cb 100644 --- a/tests/test_Comfyui_Fd_Nodes.py +++ b/tests/test_Comfyui_Fd_Nodes.py @@ -17,8 +17,10 @@ from src.Comfyui_Fd_Nodes.nodes import ( _resolution_to_edit_size, ) from src.Comfyui_Fd_Nodes.prompt_nodes import EcommercePromptGenerator, PromptListSelector +from src.Comfyui_Fd_Nodes import zhiyi_image_text_combo_node as zhiyi_image_text_combo_module from src.Comfyui_Fd_Nodes import zhiyi_image_text_node as zhiyi_image_text_module from src.Comfyui_Fd_Nodes import zhiyi_text_node as zhiyi_text_module +from src.Comfyui_Fd_Nodes.zhiyi_image_text_combo_node import ZhiYiImageTextComboNode from src.Comfyui_Fd_Nodes.zhiyi_image_text_node import ZhiYiImageTextNode from src.Comfyui_Fd_Nodes.zhiyi_image_to_image_combo_node import ZhiYiImageToImageComboNode from src.Comfyui_Fd_Nodes.zhiyi_image_to_image_node import ZhiYiImageToImageNode @@ -97,6 +99,7 @@ def test_new_nodes_hide_base_url_and_api_key_inputs(): assert {"base_url", "api_key"}.isdisjoint(GPTImageEditNode.INPUT_TYPES()["required"]) assert {"api_url", "api_key"}.isdisjoint(EcommercePromptGenerator.INPUT_TYPES()["required"]) assert {"base_url", "api_key"}.isdisjoint(ZhiYiImageTextNode.INPUT_TYPES()["required"]) + assert {"base_url", "api_key"}.isdisjoint(ZhiYiImageTextComboNode.INPUT_TYPES()["required"]) assert {"base_url", "api_key"}.isdisjoint(ZhiYiImageToImageNode.INPUT_TYPES()["required"]) assert {"base_url", "api_key"}.isdisjoint(ZhiYiTextGenNode.INPUT_TYPES()["required"]) @@ -114,6 +117,22 @@ def test_zhiyi_image_to_image_exposes_out_request_id(): assert optional_inputs["out_request_id"][1]["default"] == "default" +def test_zhiyi_image_to_image_nodes_expose_legacy_and_channel_models(): + expected_models = { + "google/gemini-2.5-flash-image-preview", + "google/gemini-3-pro-image-preview", + "google/gemini-3-pro-image-preview-official", + "google/gemini-3.1-flash-image-preview", + "gemini-3-pro-image-preview-aistudio", + "gemini-3-pro-image-preview-siphonlab", + } + + assert expected_models.issubset(set(ZhiYiImageToImageNode.MODELS)) + assert expected_models.issubset(set(ZhiYiImageToImageComboNode.MODELS)) + assert ZhiYiImageToImageNode.INPUT_TYPES()["required"]["model"][1]["default"] == "google/gemini-3-pro-image-preview" + assert ZhiYiImageToImageComboNode.INPUT_TYPES()["required"]["model"][1]["default"] == "google/gemini-3-pro-image-preview" + + def test_gemini_service_builds_internal_request_body(): client = GeminiImageServiceClient(service_url="https://gemini.internal", oss_url_prefix="https://oss/") @@ -136,11 +155,21 @@ def test_gemini_service_builds_internal_request_body(): } assert client.summarize_request_body(body)["image_count"] == 1 + aistudio_body = client.build_request_body( + prompt="draw product", + model="gemini-3-pro-image-preview-aistudio", + image_url_list=["https://oss/input.png"], + ) + assert aistudio_body["model"] == "google/gemini-3-pro-image-preview-official" + def test_gemini_service_model_and_prompt_helpers(): assert normalize_gemini_model_name("gemini-2.5-flash-image-preview") == "google/gemini-2.5-flash-image-preview" assert normalize_gemini_model_name("google/gemini-3-pro-image-preview") == "google/gemini-3-pro-image-preview" - assert should_use_litellm_gemini("gemini-3-pro-image-preview-aistudio") is True + assert normalize_gemini_model_name("gemini-3-pro-image-preview-official") == "google/gemini-3-pro-image-preview-official" + assert normalize_gemini_model_name("google/gemini-3-pro-image-preview-official") == "google/gemini-3-pro-image-preview-official" + assert normalize_gemini_model_name("gemini-3-pro-image-preview-aistudio") == "google/gemini-3-pro-image-preview-official" + assert should_use_litellm_gemini("gemini-3-pro-image-preview-aistudio") is False assert should_use_litellm_gemini("gemini-3-pro-image-preview-siphonlab") is True assert should_use_litellm_gemini("gemini-3-pro-image-preview") is False assert compose_prompt("user prompt", "system prompt") == "system prompt\n\nuser prompt" @@ -187,25 +216,21 @@ def test_zhiyi_image_to_image_uses_internal_gemini_service(monkeypatch): assert request["out_request_id"] == "req-123" -def test_zhiyi_image_to_image_aistudio_uses_litellm_without_model_rename(monkeypatch): +def test_zhiyi_image_to_image_aistudio_uses_internal_official_model(monkeypatch): node = ZhiYiImageToImageNode() calls = [] - monkeypatch.setattr("src.Comfyui_Fd_Nodes.zhiyi_image_to_image_node.tensor_to_base64", lambda _tensor: "AAA") + class FakeClient: + def upload_images(self, image_tensors): + calls.append(("upload_images", len(image_tensors))) + return ["https://oss/input.png"] - def fake_litellm(messages, model, aspect_ratio, image_size, seed, out_request_id): - calls.append({ - "messages": messages, - "model": model, - "aspect_ratio": aspect_ratio, - "image_size": image_size, - "seed": seed, - "out_request_id": out_request_id, - }) - return torch.ones((1, 2, 2, 3), dtype=torch.float32) + def call_with_image_urls(self, **kwargs): + calls.append(("call", kwargs)) + return torch.ones((1, 2, 2, 3), dtype=torch.float32), "https://oss/result.png", "ok" - monkeypatch.setattr(node, "_single_litellm_request", fake_litellm) - monkeypatch.setattr(node.gemini_client, "upload_images", lambda _image_tensors: pytest.fail("aistudio should not upload images to Gemini service")) + node.gemini_client = FakeClient() + monkeypatch.setattr(node, "_single_litellm_request", lambda *args: pytest.fail("aistudio should use internal Gemini service")) result, actual_seed = node.generate( image_1=torch.zeros((1, 2, 2, 3), dtype=torch.float32), @@ -222,10 +247,12 @@ def test_zhiyi_image_to_image_aistudio_uses_litellm_without_model_rename(monkeyp assert result.shape == (1, 2, 2, 3) assert actual_seed == 42 - assert calls[0]["model"] == "gemini-3-pro-image-preview-aistudio" - assert calls[0]["messages"][0]["role"] == "system" - assert calls[0]["messages"][1]["content"][0]["text"] == "user prompt" - assert calls[0]["messages"][1]["content"][1]["image_url"]["url"] == "data:image/png;base64,AAA" + assert calls[0] == ("upload_images", 1) + request = calls[1][1] + assert request["image_url_list"] == ["https://oss/input.png"] + assert request["prompt"] == "system prompt\n\nuser prompt" + assert request["model"] == "gemini-3-pro-image-preview-aistudio" + assert normalize_gemini_model_name(request["model"]) == "google/gemini-3-pro-image-preview-official" def test_normalize_error_message_classifies_timeout_and_nsfw(): @@ -345,6 +372,55 @@ def test_zhiyi_image_to_image_combo_uses_internal_gemini_service(monkeypatch): assert calls[1][1] == "system prompt\n\nprompt two" +def test_zhiyi_image_to_image_combo_aistudio_uses_internal_official_model(monkeypatch): + node = ZhiYiImageToImageComboNode() + node.gemini_client.service_url = "https://gemini.internal/generate" + combo = { + "images": [torch.zeros((1, 2, 2, 3), dtype=torch.float32)], + "prompts": ["prompt one"], + } + calls = [] + + monkeypatch.setattr(node.gemini_client, "upload_images", lambda image_tensors: calls.append(("upload_images", len(image_tensors))) or ["https://oss/input.png"]) + monkeypatch.setattr(node, "_single_litellm_request", lambda *args: pytest.fail("aistudio should use internal Gemini service")) + + def fake_single_request(*args): + calls.append(("single_request", args)) + return torch.ones((1, 2, 2, 3), dtype=torch.float32) + + monkeypatch.setattr(node, "_single_request", fake_single_request) + + images, actual_seed, log_text = node.generate( + model="gemini-3-pro-image-preview-aistudio", + aspect_ratio="1:1", + image_size="4K", + batch_size=1, + max_concurrency=1, + seed_mode="固定种子", + seed=7, + out_request_id="req-456", + combo_1=combo, + system_prompt="system prompt", + ) + + assert len(images) == 1 + assert actual_seed == 7 + assert "url=https://gemini.internal/generate" in log_text + assert calls[0] == ("upload_images", 1) + assert calls[1][0] == "single_request" + request_args = calls[1][1] + assert request_args == ( + ["https://oss/input.png"], + "system prompt\n\nprompt one", + "gemini-3-pro-image-preview-aistudio", + "1:1", + "4K", + 7, + "req-456", + ) + assert normalize_gemini_model_name(request_args[2]) == "google/gemini-3-pro-image-preview-official" + + def test_zhiyi_image_to_image_combo_siphonlab_uses_litellm_without_model_rename(monkeypatch): node = ZhiYiImageToImageComboNode() combo = { @@ -403,15 +479,27 @@ def test_zhiyi_image_text_request_logs_request_and_response_without_images(monke captured_logs.append(("post_payload", json.loads(data))) return DummyResponse() - def fake_image_tensor_to_base64(_image): - return "AAA" + def fake_image_tensor_to_data_url(_image): + return ( + "data:image/jpeg;base64,AAA", + { + "original_size": (1, 1), + "final_size": (1, 1), + "mime_type": "image/jpeg", + "quality": 85, + "image_bytes": 3, + "data_url_bytes": 26, + "max_data_url_bytes": zhiyi_image_text_module.MAX_IMAGE_DATA_URL_BYTES, + "resized": False, + }, + ) def fake_logger_info(message, *args): captured_logs.append((message, args)) monkeypatch.setattr(zhiyi_image_text_module, "load_config", lambda: {"base_url": "https://example.com", "api_key": "secret"}) monkeypatch.setattr(zhiyi_image_text_module.requests, "post", fake_post) - monkeypatch.setattr(node, "_image_tensor_to_base64", fake_image_tensor_to_base64) + monkeypatch.setattr(node, "_image_tensor_to_data_url", fake_image_tensor_to_data_url) monkeypatch.setattr(zhiyi_image_text_module.logger, "info", fake_logger_info) result = node.generate( @@ -425,18 +513,283 @@ def test_zhiyi_image_text_request_logs_request_and_response_without_images(monke assert result == ("hello",) request_payload = next(value for key, value in captured_logs if key == "post_payload") - assert request_payload["model"] == "gemini-3-pro-preview" + assert request_payload["model"] == "doubao-seed-2.0-mini" + assert request_payload["messages"][1]["content"][1]["image_url"]["url"] == "data:image/jpeg;base64,AAA" request_log = next(args[0] for message, args in captured_logs if message == "Calling ZhiYi image-to-text API with payload=%s") assert request_log["messages"] == [ {"role": "system", "text": "system prompt"}, {"role": "user", "text": "describe this image", "image_count": 1}, ] - assert "data:image/png;base64,AAA" not in json.dumps(request_log, ensure_ascii=False) + encoded_image_log = next(args[0] for message, args in captured_logs if message == "ZhiYi image-to-text encoded image: %s") + assert encoded_image_log["mime_type"] == "image/jpeg" + assert "data:image/jpeg;base64,AAA" not in json.dumps(request_log, ensure_ascii=False) response_log = next(args[0] for message, args in captured_logs if message == "ZhiYi image-to-text API response summary: %s") assert response_log["status_code"] == 200 assert response_log["choice_count"] == 1 +def test_zhiyi_image_text_encodes_small_image_as_jpeg_data_url(): + """Small images should be encoded as JPEG data URLs without resizing.""" + node = ZhiYiImageTextNode() + image = torch.zeros((1, 16, 16, 3), dtype=torch.float32) + + data_url, info = node._image_tensor_to_data_url(image) + + assert data_url.startswith("data:image/jpeg;base64,") + assert len(data_url.encode("utf-8")) <= zhiyi_image_text_module.MAX_IMAGE_DATA_URL_BYTES + assert info["original_size"] == (16, 16) + assert info["final_size"] == (16, 16) + assert info["quality"] == 85 + assert info["resized"] is False + + +def test_zhiyi_image_text_recompresses_until_data_url_is_under_limit(monkeypatch): + """Large/noisy inputs should be retried with lower quality and smaller dimensions until under the transport limit.""" + node = ZhiYiImageTextNode() + image = torch.rand((1, 512, 512, 3), dtype=torch.float32) + + monkeypatch.setattr(zhiyi_image_text_module, "MAX_IMAGE_DATA_URL_BYTES", 50_000) + monkeypatch.setattr(zhiyi_image_text_module, "MIN_IMAGE_LONG_EDGE", 128) + monkeypatch.setattr(zhiyi_image_text_module, "IMAGE_RESIZE_FACTOR", 0.5) + + data_url, info = node._image_tensor_to_data_url(image) + + assert data_url.startswith("data:image/jpeg;base64,") + assert len(data_url.encode("utf-8")) <= 50_000 + assert info["data_url_bytes"] <= 50_000 + assert info["final_size"][0] <= 512 + assert info["final_size"][1] <= 512 + assert info["resized"] is True + + +def test_zhiyi_image_text_raises_clear_error_when_image_cannot_fit(monkeypatch): + """If every compression attempt remains too large, the node should fail before making the API request.""" + node = ZhiYiImageTextNode() + image = torch.zeros((1, 4, 4, 3), dtype=torch.float32) + + monkeypatch.setattr(zhiyi_image_text_module, "MAX_IMAGE_DATA_URL_BYTES", 1) + monkeypatch.setattr(zhiyi_image_text_module, "MIN_IMAGE_LONG_EDGE", 1) + + with pytest.raises(RuntimeError, match="10MB 传输限制"): + node._image_tensor_to_data_url(image) + + +def test_zhiyi_image_text_combo_registered_and_accepts_combo_inputs(): + input_types = ZhiYiImageTextComboNode.INPUT_TYPES() + + assert "ZhiYiImageTextComboNode" in NODE_CLASS_MAPPINGS + assert NODE_CLASS_MAPPINGS["ZhiYiImageTextComboNode"] is ZhiYiImageTextComboNode + assert NODE_DISPLAY_NAME_MAPPINGS["ZhiYiImageTextComboNode"] == "知衣-图生文-combo" + assert set(input_types["required"]) == {"max_concurrency", "temperature", "max_tokens", "retry_count"} + assert "combo_1" in input_types["optional"] + assert "combo_8" in input_types["optional"] + assert ZhiYiImageTextComboNode.RETURN_TYPES == ("STRING", "STRING") + assert ZhiYiImageTextComboNode.RETURN_NAMES == ("text", "log") + + +def test_zhiyi_image_text_combo_sends_multiple_images_in_one_request(monkeypatch): + node = ZhiYiImageTextComboNode() + captured_payloads = [] + captured_logs = [] + image = torch.zeros((2, 2, 2, 3), dtype=torch.float32) + combo = {"images": [image], "prompts": ["describe both images"]} + + class DummyResponse: + status_code = 200 + text = '{"choices":[{"message":{"content":"both images"}}]}' + + def raise_for_status(self): + return None + + def json(self): + return {"choices": [{"message": {"content": "both images"}}]} + + def fake_post(url, headers, data, timeout): + captured_payloads.append(json.loads(data)) + return DummyResponse() + + def fake_image_tensor_to_data_url(image_tensor): + index = len(captured_logs) + 1 + return ( + f"data:image/jpeg;base64,IMG{index}", + { + "original_size": (2, 2), + "final_size": (2, 2), + "mime_type": "image/jpeg", + "quality": 85, + "image_bytes": index, + "data_url_bytes": 30, + "max_data_url_bytes": zhiyi_image_text_module.MAX_IMAGE_DATA_URL_BYTES, + "resized": False, + }, + ) + + def fake_logger_info(message, *args): + captured_logs.append((message, args)) + + monkeypatch.setattr(zhiyi_image_text_combo_module, "load_config", lambda: {"base_url": "https://example.com", "api_key": "secret"}) + monkeypatch.setattr(zhiyi_image_text_combo_module.requests, "post", fake_post) + monkeypatch.setattr(node, "_image_tensor_to_data_url", fake_image_tensor_to_data_url) + monkeypatch.setattr(zhiyi_image_text_combo_module.logger, "info", fake_logger_info) + + text, log_text = node.generate( + max_concurrency=1, + temperature=0.2, + max_tokens=256, + retry_count=0, + combo_1=combo, + system_prompt="system prompt", + ) + + assert text == "both images" + assert "总计: 1/1 成功" in log_text + payload = captured_payloads[0] + assert payload["model"] == "doubao-seed-2.0-mini" + assert payload["messages"][0]["role"] == "system" + content = payload["messages"][1]["content"] + assert content[0] == {"type": "text", "text": "describe both images"} + assert [part["image_url"]["url"] for part in content[1:]] == [ + "data:image/jpeg;base64,IMG1", + "data:image/jpeg;base64,IMG2", + ] + request_log = next(args[0] for message, args in captured_logs if message == "Calling ZhiYi image-to-text combo API with payload=%s") + assert request_log["messages"] == [ + {"role": "system", "text": "system prompt"}, + {"role": "user", "text": "describe both images", "image_count": 2}, + ] + assert "data:image/jpeg;base64,IMG1" not in json.dumps(request_log, ensure_ascii=False) + + +def test_zhiyi_image_text_combo_keeps_output_order_when_requests_finish_out_of_order(monkeypatch): + node = ZhiYiImageTextComboNode() + image = torch.zeros((1, 2, 2, 3), dtype=torch.float32) + + monkeypatch.setattr(zhiyi_image_text_combo_module, "load_config", lambda: {"base_url": "https://example.com", "api_key": "secret"}) + monkeypatch.setattr(node, "_image_tensor_to_data_url", lambda _image: ("data:image/jpeg;base64,AAA", {})) + + def fake_single_request(url, api_key, messages, temperature, max_tokens, retry_count): + prompt = messages[-1]["content"][0]["text"] + if prompt == "first": + return "text first", 0 + return "text second", 0 + + def fake_run_concurrent(tasks, max_workers, label="请求"): + second = tasks[1] + first = tasks[0] + results = { + second[0]: {"ok": True, "text": second[2](*second[3])[0]}, + first[0]: {"ok": True, "text": first[2](*first[3])[0]}, + } + return results, ["[请求 combo_2] 成功", "[请求 combo_1] 成功"], None + + monkeypatch.setattr(node, "_single_request", fake_single_request) + monkeypatch.setattr(node, "_run_concurrent", fake_run_concurrent) + + text, log_text = node.generate( + max_concurrency=2, + retry_count=0, + combo_1={"images": [image], "prompts": ["first"]}, + combo_2={"images": [image], "prompts": ["second"]}, + ) + + assert text == "[combo_1]\ntext first\n\n[combo_2]\ntext second" + assert "总计: 2/2 成功" in log_text + + +def test_zhiyi_image_text_combo_retries_once_after_retryable_failure(monkeypatch): + node = ZhiYiImageTextComboNode() + calls = [] + + class DummyResponse: + def __init__(self, status_code, text, payload=None): + self.status_code = status_code + self.text = text + self.payload = payload or {"choices": [{"message": {"content": "retry success"}}]} + + def raise_for_status(self): + return None + + def json(self): + return self.payload + + def fake_post(url, headers, data, timeout): + calls.append(json.loads(data)) + if len(calls) == 1: + return DummyResponse(500, "internal error") + return DummyResponse(200, '{"choices":[{"message":{"content":"retry success"}}]}') + + monkeypatch.setattr(zhiyi_image_text_combo_module.requests, "post", fake_post) + monkeypatch.setattr(node, "_sleep_before_retry", lambda _attempt_index: None) + + text, retry_used = node._single_request( + url="https://example.com/v1/chat/completions", + api_key="secret", + messages=[{"role": "user", "content": [{"type": "text", "text": "prompt"}]}], + temperature=0.7, + max_tokens=128, + retry_count=1, + ) + + assert text == "retry success" + assert retry_used == 1 + assert len(calls) == 2 + + +def test_zhiyi_image_text_combo_keeps_failure_placeholder_for_partial_failure(monkeypatch): + node = ZhiYiImageTextComboNode() + image = torch.zeros((1, 2, 2, 3), dtype=torch.float32) + + monkeypatch.setattr(zhiyi_image_text_combo_module, "load_config", lambda: {"base_url": "https://example.com", "api_key": "secret"}) + monkeypatch.setattr(node, "_image_tensor_to_data_url", lambda _image: ("data:image/jpeg;base64,AAA", {})) + + def fake_run_concurrent(tasks, max_workers, label="请求"): + return ( + { + 0: {"ok": True, "text": "ok text"}, + 1: {"ok": False, "text": "ERROR: TIMEOUT: request timed out"}, + }, + ["[请求 combo_1] 成功", "[请求 combo_2] 失败: TIMEOUT: request timed out"], + "TIMEOUT: request timed out", + ) + + monkeypatch.setattr(node, "_run_concurrent", fake_run_concurrent) + + text, log_text = node.generate( + max_concurrency=2, + retry_count=0, + combo_1={"images": [image], "prompts": ["first"]}, + combo_2={"images": [image], "prompts": ["second"]}, + ) + + assert text == "[combo_1]\nok text\n\n[combo_2]\nERROR: TIMEOUT: request timed out" + assert "总计: 1/2 成功" in log_text + assert "[请求 combo_2] 失败: TIMEOUT: request timed out" in log_text + + +def test_zhiyi_image_text_combo_raises_when_all_requests_fail(monkeypatch): + node = ZhiYiImageTextComboNode() + image = torch.zeros((1, 2, 2, 3), dtype=torch.float32) + + monkeypatch.setattr(zhiyi_image_text_combo_module, "load_config", lambda: {"base_url": "https://example.com", "api_key": "secret"}) + monkeypatch.setattr(node, "_image_tensor_to_data_url", lambda _image: ("data:image/jpeg;base64,AAA", {})) + monkeypatch.setattr( + node, + "_run_concurrent", + lambda tasks, max_workers, label="请求": ( + {0: {"ok": False, "text": "ERROR: UNKNOWN: API 请求失败: 500"}}, + ["[请求 combo_1] 失败: UNKNOWN: API 请求失败: 500"], + "UNKNOWN: API 请求失败: 500", + ), + ) + + with pytest.raises(RuntimeError, match=r"^UNKNOWN: API 请求失败: 500$"): + node.generate( + max_concurrency=1, + retry_count=0, + combo_1={"images": [image], "prompts": ["first"]}, + ) + + def test_zhiyi_text_gen_request_logs_request_and_response(monkeypatch): """The text API should log request/response summaries.""" node = ZhiYiTextGenNode() @@ -491,6 +844,16 @@ def test_configure_default_logging_installs_timestamp_format(monkeypatch): class FakeRootLogger: handlers = [] + def addHandler(self, handler): + self.handlers.append(handler) + + def removeHandler(self, handler): + if handler in self.handlers: + self.handlers.remove(handler) + + def setLevel(self, _level): + return None + def fake_get_logger(name=None): if name is None: return FakeRootLogger() @@ -523,6 +886,16 @@ def test_configure_default_logging_upgrades_existing_handler_without_timestamp(m def __init__(self): self.handlers = [FakeHandler()] + def 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