feat: 将 47 个 Operit TypeScript 脚本全面翻译为 Python
- 新增 operit_runtime.py: 跨平台 Python 运行时 - 实现 Tools.System/Files/Net/UI/Memory/FFmpeg/Workflow/Chat/SoftwareSettings/Tasker - 实现 OkHttp 链式 HTTP 客户端兼容层 - 实现 complete()/exports/console 全局对象 - 实现 OperitScriptLoader 脚本加载器 - 支持 Windows/macOS/Linux 三平台 - 新增 operit_py/ 目录: 47 个 Python 翻译脚本 - 搜索类: duckduckgo, google_search, tavily, zhipu_search, various_search, crossref - 绘图类: openai_draw, qwen_draw, xai_draw, minimax_draw, siliconflow_draw, zhipu_draw, nanobanana_draw - 媒体类: ffmpeg, file_converter, douyin_download, bilibili_tools, jmcomic - 文件类: extended_file_tools, hex_editor, reader, beeimg_image_uploader - 网络类: extended_http_tools, network_test - 自动化类: browser, automatic_ui_base, automatic_ui_subagent, automatic_bilibili_assistant, automatic_xiaohongshu_assistant, automatic_baidu_map_assistant - 系统类: system_tools, super_admin, daily_life, operit_editor - 对话类: ai_chat, extended_chat, qq_intelligent - 工作流类: workflow, vflow_trigger, tasker - 工具类: time, code_runner, quick_start, extended_memory_tools, baidu_map, 12306, pdf_vision_parser - 测试结果: 47/47 语法检查通过, 38 脚本加载成功, 280 个工具注册 - Android 专属功能已降级处理(保留接口,返回不支持提示)
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# METADATA
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# {
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# "name": "zhipu_draw",
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# "display_name": {
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# "zh": "智谱生图",
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# "en": "Zhipu Draw"
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# },
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# "description": {
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# "zh": "使用智谱AI图像生成API根据提示词画图，将图片保存到本地 /sdcard/Download/Operit/plugins/draw/zhipu_draw/draws/ 目录，并返回 Markdown 图片提示。",
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# "en": "Generate images via Zhipu AI image generation API from a prompt, save to /sdcard/Download/Operit/plugins/draw/zhipu_draw/draws/, and return a Markdown image reference."
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# },
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# "env": [
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# {
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# "name": "ZHIPU_API_KEY",
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# "description": {
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# "zh": "智谱API Key（必填）",
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# "en": "Zhipu API key (required)"
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# },
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# "required": true
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# },
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# {
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# "name": "ZHIPU_IMAGE_MODEL",
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# "description": {
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# "zh": "默认绘图模型（可选；当 draw_image 未传 model 时使用）",
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# "en": "Default image model (optional; used when draw_image doesn't pass model)"
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# },
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# "required": false
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# }
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# ],
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# "category": "Draw",
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# "tools": [
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# {
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# "name": "draw_image",
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# "description": {
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# "zh": "根据提示词调用智谱AI图像生成接口生成图片，保存到本地并返回 Markdown 图片提示。",
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# "en": "Generate an image via Zhipu AI image generation API using a prompt, save it locally, and return a Markdown image reference."
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# },
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# "parameters": [
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# { "name": "prompt", "description": { "zh": "绘图提示词（中文或英文）", "en": "Prompt for image generation (Chinese or English)" }, "type": "string", "required": true },
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# { "name": "size", "description": { "zh": "图片尺寸，例如 '1024x1024' 或 '1280x1280'（可选，默认1024x1024）", "en": "Image size, e.g. '1024x1024' or '1280x1280' (optional, default 1024x1024)" }, "type": "string", "required": false },
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# { "name": "file_name", "description": { "zh": "自定义保存到本地的文件名（不含路径和扩展名）", "en": "Custom output file name (without path or extension)" }, "type": "string", "required": false },
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# { "name": "model", "description": { "zh": "模型名称（可选；不传则使用环境变量 ZHIPU_IMAGE_MODEL，否则默认glm-image）", "en": "Model name (optional; falls back to env ZHIPU_IMAGE_MODEL)" }, "type": "string", "required": false }
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# ]
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# }
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# ]
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# }
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import json
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import re
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import time
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import traceback
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HTTP_TIMEOUT_MS = 600000
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client = OkHttp.newBuilder()
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client = client.connectTimeout(HTTP_TIMEOUT_MS)
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client = client.readTimeout(HTTP_TIMEOUT_MS)
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client = client.writeTimeout(HTTP_TIMEOUT_MS)
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client = client.build()
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API_BASE_URL = "https://open.bigmodel.cn/api/paas/v4/images/generations"
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DRAW_ROOT_DIR = getPluginConfigDir("draw")
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STORAGE_DIR = f"{DRAW_ROOT_DIR}/zhipu_draw"
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DRAWS_DIR = f"{STORAGE_DIR}/draws"
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def getErrorMessage(error):
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if isinstance(error, Exception):
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return str(error)
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return str(error)
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def getErrorStack(error):
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if isinstance(error, Exception):
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return traceback.format_exc()
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return None
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def getApiKey():
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apiKey = getEnv("ZHIPU_API_KEY")
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if not apiKey:
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raise Exception("ZHIPU_API_KEY 未配置，请在环境变量中设置智谱的 API Key。")
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return apiKey
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def sanitizeFileName(name):
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safe = re.sub(r'[\\/:*?"<>|]', '_', name).strip()
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if not safe:
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return f"zhipu_draw_{int(time.time() * 1000)}"
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return safe[:80]
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def buildFileName(prompt, customName=None):
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if customName and len(customName.strip()) > 0:
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return sanitizeFileName(customName)
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shortPrompt = (prompt[:40] + "...") if len(prompt) > 40 else prompt
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base = sanitizeFileName(shortPrompt or "image")
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timestamp = int(time.time() * 1000)
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return f"{base}_{timestamp}"
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async def ensureDirectories():
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dirs = [DRAW_ROOT_DIR, STORAGE_DIR, DRAWS_DIR]
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for dir_ in dirs:
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try:
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result = await Tools.Files.mkdir(dir_)
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if not result.get("successful"):
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console.warn(f"创建目录失败(可能已存在): {dir_} -> {result.get('details')}")
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except Exception as e:
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console.warn(f"创建目录异常: {dir_} -> {getErrorMessage(e)}")
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async def callZhipuImageAPI(params):
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apiKey = getApiKey()
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modelFromParam = (params.get("model") or "").strip()
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modelFromEnv = (getEnv("ZHIPU_IMAGE_MODEL") or "").strip()
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effectiveModel = modelFromParam or modelFromEnv or "glm-image"
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body = {
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"model": effectiveModel,
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"prompt": params["prompt"],
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"size": params.get("size") or "1024x1024"
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}
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headers = {
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"accept": "application/json",
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"content-type": "application/json",
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"Authorization": f"Bearer {apiKey}"
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}
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request = client.newRequest()
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request = request.url(API_BASE_URL)
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request = request.method("POST")
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request = request.headers(headers)
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request = request.body(json.dumps(body), "json")
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response = await request.build().execute()
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if not response.isSuccessful():
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raise Exception(f"智谱图片 API 调用失败: {response.statusCode} - {response.content}")
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try:
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parsed = json.loads(response.content)
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except Exception as e:
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raise Exception(f"解析智谱响应失败: {getErrorMessage(e)}")
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data = parsed.get("data") if isinstance(parsed, dict) else None
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first = data[0] if (data and len(data) > 0) else None
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if not first or not first.get("url"):
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raise Exception("智谱响应中未找到有效的图片数据，请检查API返回格式")
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result = {
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"url": str(first["url"]),
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"model": str(first["model"]) if first.get("model") else None
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}
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if not result["model"]:
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result["model"] = effectiveModel
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return result
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async def draw_image(params):
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if not params or not params.get("prompt") or len(params.get("prompt", "").strip()) == 0:
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raise Exception("参数 prompt 不能为空。")
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prompt = params["prompt"].strip()
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size = params.get("size") or "1024x1024"
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model = params.get("model")
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await ensureDirectories()
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apiResult = await callZhipuImageAPI({"prompt": prompt, "size": size, "model": model})
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if not apiResult["url"] or not apiResult["url"].strip():
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raise Exception("API响应中未包含图片URL")
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baseName = buildFileName(prompt, params.get("file_name"))
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filePath = f"{DRAWS_DIR}/{baseName}.png"
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downloadResult = await Tools.Files.download(apiResult["url"], filePath)
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if not downloadResult.get("successful"):
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raise Exception(f"下载图片失败: {downloadResult.get('details')}")
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fileUri = f"file://{filePath}"
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markdown = f""
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hintLines = []
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hintLines.append(f"图片已生成并保存在本地 {DRAWS_DIR}。")
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hintLines.append(f"本地路径: {filePath}")
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hintLines.append(f"提示词: {prompt}")
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hintLines.append(f"模型: {apiResult.get('model') or 'glm-image'}")
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hintLines.append("")
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hintLines.append("在后续回答中，请直接输出下面这一行 Markdown 来展示这张图片：")
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hintLines.append("")
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hintLines.append(markdown)
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return {
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"file_path": filePath,
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"file_uri": fileUri,
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"markdown": markdown,
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"prompt": prompt,
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"hint": "\n".join(hintLines)
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}
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async def draw_image_wrapper(params):
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try:
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result = await draw_image(params)
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complete({
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"success": True,
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"message": f"图片生成成功，已保存到 {DRAWS_DIR}，并返回 Markdown 图片提示。",
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"data": result
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})
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except Exception as error:
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console.error("draw_image 执行失败:", error)
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complete({
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"success": False,
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"message": f"图片生成失败: {getErrorMessage(error)}",
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"error_stack": getErrorStack(error)
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})
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exports.draw_image = draw_image_wrapper
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