{"type":"session","version":3,"id":"56e36980-a7d4-4b07-b561-95591336c0f2","timestamp":"2026-04-24T13:31:44.876Z","cwd":"/root/.openclaw/workspace/fabu"} {"type":"model_change","id":"c7afd626","parentId":null,"timestamp":"2026-04-24T13:31:44.879Z","provider":"deepseek","modelId":"deepseek-chat"} {"type":"thinking_level_change","id":"a93a8822","parentId":"c7afd626","timestamp":"2026-04-24T13:31:44.879Z","thinkingLevel":"off"} {"type":"custom","customType":"model-snapshot","data":{"timestamp":1777037504900,"provider":"deepseek","modelApi":"openai-completions","modelId":"deepseek-chat"},"id":"45f2684e","parentId":"a93a8822","timestamp":"2026-04-24T13:31:44.900Z"} {"type":"message","id":"425752fe","parentId":"45f2684e","timestamp":"2026-04-24T13:31:44.913Z","message":{"role":"user","content":[{"type":"text","text":"[Fri 2026-04-24 21:31 GMT+8] [Subagent Context] You are running as a subagent (depth 1/1). Results auto-announce to your requester; do not busy-poll for status.\n\n[Subagent Task]: 你是**发布大师**，公众号内容发布专家。\n\n## 任务：发布\"DeepSeek-V4阿里云百炼\"文章\n\n### 文章信息\n- 标题：阿里云百炼首发DeepSeek-V4：价格击穿地板，国产AI从\"找模型\"到\"找平台\"\n- 作者：ai张三疯\n- Markdown位置：/root/.openclaw/agents/文章大师/workspace/DeepSeekV4阿里云百炼-2026-04-24-v1.md\n- 网站HTML：/root/.openclaw/agents/发布大师/workspace/DeepSeekV4阿里云百炼-2026-04-24.html\n\n**注意：** HTML已预处理，`class=\"container\"` 已替换为内联 `max-width:860px`，无需额外处理。\n\n### 公众号发布\n```bash\ncd /root/.openclaw/agents/发布大师/workspace\nWECHAT_APP_ID=wx88b0cf376e0386c4 WECHAT_APP_SECRET=b2d47ee298204c28cf82549d2798192f bun /root/.openclaw/agents/101/workspace/skills/baoyu-post-to-wechat/scripts/wechat-api.ts /root/.openclaw/agents/文章大师/workspace/DeepSeekV4阿里云百炼-2026-04-24-v1.md --theme default --color blue --author \"ai张三疯\"\n```\n缺封面图就从 picsum.photos 下一张。\n\n### 网站发布\n创建 publish-DeepSeekV4百炼.js：\n- 端点：https://weixinsiwei.com/zb_system/xml-rpc/index.php\n- 账号：admin / 135269zxj\n- blogId：68ba1ff10060dd54f1e399b8e332bdba\n- 标签：DeepSeek-V4, 阿里云百炼, API, 大模型, 阿里云, 国产AI\n\n**container移除处理不能少：**\n```javascript\ncontent = content.replace(/
]*>/g, '
');\ncontent = content.replace(/<\\/section>/g, '
');\n```\n\n完成后回复发布总结（公众号media_id + 网站文章ID和链接）。避免重复发布。"}],"timestamp":1777037504905}} {"type":"message","id":"967ebf90","parentId":"425752fe","timestamp":"2026-04-24T13:31:54.615Z","message":{"role":"assistant","content":[{"type":"text","text":"Let me start by reading the article to understand what we're working with, then execute both publishes."},{"type":"toolCall","id":"call_00_kAWZBgww2TmCX1xOw69eWhQT","name":"read","arguments":{"path":"/root/.openclaw/agents/文章大师/workspace/DeepSeekV4阿里云百炼-2026-04-24-v1.md","limit":50}},{"type":"toolCall","id":"call_01_OICuTsEOGXdwgf3Vczzb7lbe","name":"read","arguments":{"path":"/root/.openclaw/agents/发布大师/workspace/DeepSeekV4阿里云百炼-2026-04-24.html","limit":50}},{"type":"toolCall","id":"call_02_xB7dfYTxYpxul5KOm6msPOhx","name":"exec","arguments":{"command":"ls /root/.openclaw/agents/发布大师/workspace/ && ls /root/.openclaw/agents/101/workspace/skills/baoyu-post-to-wechat/scripts/wechat-api.ts 2>/dev/null && echo \"wechat-api exists\" || echo \"wechat-api NOT found\""}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":12605,"output":286,"cacheRead":0,"cacheWrite":0,"totalTokens":12891,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1777037504918,"responseId":"783e13c8-3523-4055-9213-395ae69b90d6"}} {"type":"message","id":"eb81550a","parentId":"967ebf90","timestamp":"2026-04-24T13:31:54.711Z","message":{"role":"toolResult","toolCallId":"call_00_kAWZBgww2TmCX1xOw69eWhQT","toolName":"read","content":[{"type":"text","text":"# 阿里云百炼首发DeepSeek-V4：价格击穿地板，国产AI从\"找模型\"到\"找平台\"\n\n4月24日，阿里云百炼平台宣布首发上线DeepSeek-V4-pro和DeepSeek-V4-flash两款模型，API价格与DeepSeek官网保持一致——百万Tokens输入最低1元，百万Tokens输出最低2元。这不仅是DeepSeek-V4系列首次在云平台落地，更释放了一个清晰的信号：国产AI的竞争，已经从模型的单点突破，进入平台与模型深度绑定的新阶段。\n\n## 阿里云百炼首发DeepSeek-V4意味着什么\n\n放在一年前，\"某云平台首发某模型\"只是行业新闻里的一条普通条目。但今天，当DeepSeek-V4这个级别的模型选择在阿里云百炼\"首发\"而非独立开放API时，事情的性质变了。\n\nDeepSeek-V4是目前国内公认最强的开源大模型系列，它的pro版在多模态推理、长上下文理解和代码生成等维度上已达到国际一线水准。这样一款模型，完全有能力像此前一样自建API渠道、独立运营——但它选择了与阿里云百炼深度绑定。\n\n这意味着什么？意味着模型厂商在算力成本、平台生态和分发效率上做出了理性选择。跑大模型不是写代码，而是烧GPU。搭一套覆盖全国的API分发网络、处理千万级的并发请求、随时应对流量洪峰，这背后是云的硬实力。阿里云作为国内最大的公有云厂商，其基础设施的弹性和成本优势，是任何模型团队自建体系都无法比拟的。\n\n从另一个角度看，云厂商之间正在展开一场\"模型首发争夺战\"。谁能拿下DeepSeek-V4、谁能抢先部署Llama、谁能让用户在自家平台上\"一键调用\"最新模型，谁就能在新的AI开发浪潮中占据入口地位。模型本身，已经成为云平台最核心的卖点之一——这是过去十年任何云服务都不曾有过的事情。\n\n阿里云与DeepSeek的这次联姻，不只是商业合作，更是国产AI基础设施的\"合流\"：最强模型 + 最强云平台，由此开始。\n\n## 价格与官网一致，低价策略的冲击力\n\n百万Tokens输入1元、输出2元——这个价格是什么概念？\n\n做个简单对比。一年前，同等量级的大模型API调用，百万Tokens的输入价格普遍在10-30元区间，输出则更高。即便半年前，性能接近DeepSeek-V4的模型，输出价格也仍在5-10元徘徊。如今直接打到2元以下，等于把推理成本又砍掉了一个数量级。\n\n更关键的是，阿里云百炼这次的价格\"与DeepSeek官网一致\"。这句话看似平常，实则透露了一个重要信号：模型厂商和云平台在定价上达成了共识，以极低的价格共同推动市场扩张。这不是短期补贴，而是基于规模化推理降本后的真实定价。\n\n价格击穿地板，企业是最大的受益者。\n\n过去企业上线一个AI功能，模型调用的TCO（总拥有成本）居高不下。一个日活10万的问答应用，单日推理成本可能就到千元级别。现在价格降到这个水平，中小团队也有了直接用顶级模型做产品的底气。不是\"等便宜的模型出来再尝试\"，而是\"现在就可以开始，成本完全可控\"。\n\n低价策略的另一重意义是——它倒逼整个行业加速降本。DeepSeek-V4以1元/百万Tokens入场的姿态，让所有同类模型都必须直面这个价格锚点。这对开发者和企业而言，是一个前所未有的低成本窗口期。\n\n## 阿里云百炼的生态棋盘\n\n百炼平台并不是只接了DeepSeek。事实上，阿里云百炼早已汇聚了数十款国内外主流大模型，覆盖通义千问、Llama、Qwen、ChatGLM等多个系列。百花齐放的模型生态，让开发者可以在一个平台内横向对比、自由切换，按场景精准选择最合适的模型。\n\n但这次为首发DeepSeek-V4造势的动作，清晰地传递了一个信号：在百炼的模型矩阵中，DeepSeek被赋予了旗舰级的战略地位。\n\n阿里云之所以愿意为DeepSeek-V4\"站台\"，有两层考量。\n\n第一层是技术上的。DeepSeek-V4-pro在复杂推理和编码任务上的表现，代表了当前开源大模型的最高水准。这也是AI开发者群体最看重的部分——一个能打的旗舰模型，是平台吸引高质量开发者入场的关键。\n\n第二层是生态上的。给DeepSeek做首发，本质上是让更多用户\"走进百炼\"的理由。开发者为了用DeepSeek-V4进来，发现百炼还附带了一整套工具链：模型微调服务、RAG知识库搭建、Prompt工程工具、GPU算力弹性调度……从\"为了用模型而来\"到\"为了平台留下\"，这就是生态黏性的价值。\n\n这也是百炼区别于纯API中转站的核心差异。很多平台也能调DeepSeek的接口，但百炼会让你在这里做完一整件事——选择模型 → 搭建应用 → 打通业务系统 → 上线运维，所有环节都在一个平台上闭环。\n\n## 云+模型一体化，基础设施的逻辑变了\n\n这次首发最值得关注的变化，不在于DeepSeek-V4本身有多强，而在于\"它为什么要通过云平台首发\"这个事实。\n\n过去两三年的AI基础设施格局是\"模型归模型，云归云\"。模型团队开源或开放API，开发者自己去搞定算力、部署、运维。但这种割裂正在终结。\n\n\n[26 more lines in file. Use offset=51 to continue.]"}],"isError":false,"timestamp":1777037514711}} {"type":"message","id":"a80c6eb1","parentId":"eb81550a","timestamp":"2026-04-24T13:31:54.711Z","message":{"role":"toolResult","toolCallId":"call_01_OICuTsEOGXdwgf3Vczzb7lbe","toolName":"read","content":[{"type":"text","text":"\n\n\n \n \n 阿里云百炼首发DeepSeek-V4：价格击穿地板，国产AI从\"找模型\"到\"找平台\"\n \n \n \n\n\n
\n

4月24日，阿里云百炼平台宣布首发上线DeepSeek-V4-pro和DeepSeek-V4-flash两款模型，API价格与DeepSeek官网保持一致——百万Tokens输入最低1元，百万Tokens输出最低2元。这不仅是DeepSeek-V4系列首次在云平台落地，更释放了一个清晰的信号：国产AI的竞争，已经从模型的单点突破，进入平台与模型深度绑定的新阶段。

阿里云百炼首发DeepSeek-V4意味着什么

放在一年前，"某云平台首发某模型"只是行业新闻里的一条普通条目。但今天，当DeepSeek-V4这个级别的模型选择在阿里云百炼"首发"而非独立开放API时，事情的性质变了。

DeepSeek-V4是目前国内公认最强的开源大模型系列，它的pro版在多模态推理、长上下文理解和代码生成等维度上已达到国际一线水准。这样一款模型，完全有能力像此前一样自建API渠道、独立运营——但它选择了与阿里云百炼深度绑定。

这意味着什么？意味着模型厂商在算力成本、平台生态和分发效率上做出了理性选择。跑大模型不是写代码，而是烧GPU。搭一套覆盖全国的API分发网络、处理千万级的并发请求、随时应对流量洪峰，这背后是云的硬实力。阿里云作为国内最大的公有云厂商，其基础设施的弹性和成本优势，是任何模型团队自建体系都无法比拟的。

从另一个角度看，云厂商之间正在展开一场"模型首发争夺战"。谁能拿下DeepSeek-V4、谁能抢先部署Llama、谁能让用户在自家平台上"一键调用"最新模型，谁就能在新的AI开发浪潮中占据入口地位。模型本身，已经成为云平台最核心的卖点之一——这是过去十年任何云服务都不曾有过的事情。

阿里云与DeepSeek的这次联姻，不只是商业合作，更是国产AI基础设施的"合流"：最强模型 + 最强云平台，由此开始。

价格与官网一致，低价策略的冲击力

百万Tokens输入1元、输出2元——这个价格是什么概念？

做个简单对比。一年前，同等量级的大模型API调用，百万Tokens的输入价格普遍在10-30元区间，输出则更高。即便半年前，性能接近DeepSeek-V4的模型，输出价格也仍在5-10元徘徊。如今直接打到2元以下，等于把推理成本又砍掉了一个数量级。

更关键的是，阿里云百炼这次的价格"与DeepSeek官网一致"。这句话看似平常，实则透露了一个重要信号：模型厂商和云平台在定价上达成了共识，以极低的价格共同推动市场扩张。这不是短期补贴，而是基于规模化推理降本后的真实定价。

价格击穿地板，企业是最大的受益者。

过去企业上线一个AI功能，模型调用的TCO（总拥有成本）居高不下。一个日活10万的问答应用，单日推理成本可能就到千元级别。现在价格降到这个水平，中小团队也有了直接用顶级模型做产品的底气。不是"等便宜的模型出来再尝试"，而是"现在就可以开始，成本完全可控"。

低价策略的另一重意义是——它倒逼整个行业加速降本。DeepSeek-V4以1元/百万Tokens入场的姿态，让所有同类模型都必须直面这个价格锚点。这对开发者和企业而言，是一个前所未有的低成本窗口期。

阿里云百炼的生态棋盘

百炼平台并不是只接了DeepSeek。事实上，阿里云百炼早已汇聚了数十款国内外主流大模型，覆盖通义千问、Llama、Qwen、ChatGLM等多个系列。百花齐放的模型生态，让开发者可以在一个平台内横向对比、自由切换，按场景精准选择最合适的模型。

但这次为首发DeepSeek-V4造势的动作，清晰地传递了一个信号：在百炼的模型矩阵中，DeepSeek被赋予了旗舰级的战略地位。

阿里云之所以愿意为DeepSeek-V4"站台"，有两层考量。

第一层是技术上的。DeepSeek-V4-pro在复杂推理和编码任务上的表现，代表了当前开源大模型的最高水准。这也是AI开发者群体最看重的部分——一个能打的旗舰模型，是平台吸引高质量开发者入场的关键。

第二层是生态上的。给DeepSeek做首发，本质上是让更多用户"走进百炼"的理由。开发者为了用DeepSeek-V4进来，发现百炼还附带了一整套工具链：模型微调服务、RAG知识库搭建、Prompt工程工具、GPU算力弹性调度……从"为了用模型而来"到"为了平台留下"，这就是生态黏性的价值。

这也是百炼区别于纯API中转站的核心差异。很多平台也能调DeepSeek的接口，但百炼会让你在这里做完一整件事——选择模型 → 搭建应用 → 打通业务系统 → 上线运维，所有环节都在一个平台上闭环。

云+模型一体化，基础设施的逻辑变了

这次首发最值得关注的变化，不在于DeepSeek-V4本身有多强，而在于"它为什么要通过云平台首发"这个事实。

过去两三年的AI基础设施格局是"模型归模型，云归云"。模型团队开源或开放API，开发者自己去搞定算力、部署、运维。但这种割裂正在终结。

云+模型一体化的趋势在加速。具体来说，它解决的是三个核心问题：

算力调度。大模型推理的算力消耗极大，对GPU集群的调度能力要求极高。云平台多年积累的弹性伸缩和资源池化能力，让模型推理不再是一个"帮机器找位置"的难题。

应用开发链路。从调用API到构建一个可用的AI应用，中间隔着大量的工程工作——数据预处理、Prompt调优、向量数据库、API网关、访问控制。这些能力已经逐步内建在云平台中，开发者不再需要自己去拼积木。

成本透明化。一体化模式下，用户不需要分别谈模型授权费、算力租赁费、带宽费。一个API的调用价格，里面打包了模型、算力和网络，按量计费，清晰透明。

DeepSeek-V4通过阿里云百炼首发，就是这种一体化趋势的最佳注脚。以后"选模型"和"选云平台"可能变成同一个决策——你选择了百炼，就等于选择了DeepSeek-V4及整个生态。反过来也一样。

对开发者和企业的实际影响

价格击穿地板、生态一站式、旗舰模型到位——这三个条件凑在一起，意味着AI应用创新的门槛正在被系统性降低。

对个人开发者而言，以前调一个顶级模型可能需要审批预算、申请GPU配额、做成本预估。现在，随手注册一个百炼账号，花几块钱就能跑完整套原型验证。创业团队可以在几天内做出MVP，上线后按量付费，初期推理成本几乎可以忽略不计。

对企业而言，这意味着"要不要上AI"这个问题，正在变成一个不需要纠结的问题。场景合适的，直接调用；场景复杂的，用百炼的配套工具做定制微调、搭建RAG流程、接入内部业务流程。决策的重心从"成本上能不能承担"转向"业务上值不值得做"——而后者恰恰是正常的商业判断。

更大的趋势是，当模型调用变得像调用云数据库一样简单、便宜时，AI能力会像过去十年的云服务一样渗透到每一个软件产品中。不是"加一个AI功能"，而是"每一个功能都用AI重新做一遍"。

DeepSeek-V4落户阿里云百炼，或许会成为这个浪潮的一个注脚：2026年，国产AI进入"平台+模型"一体化时代，而这是它真正走向大规模应用的开端。

以上分析基于公开信息：阿里云百炼平台于2026年4月24日宣布首发上线DeepSeek-V4-pro和DeepSeek-V4-flash模型，API价格与DeepSeek官网保持一致。

\n \n \n \n \n \n
\n
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Files exist and the wechat-api tool is there. Let me check the HTML structure more carefully and look at existing publish scripts for patterns."},{"type":"toolCall","id":"call_00_N1UtVKPPMtzV6tnUAu4qCaiu","name":"read","arguments":{"path":"/root/.openclaw/agents/发布大师/workspace/publish-deepseek-v4.js"}},{"type":"toolCall","id":"call_01_wZ4ieUgsPe90BCOegO8OjTIY","name":"read","arguments":{"path":"/root/.openclaw/agents/发布大师/workspace/publish-DeepSeekV4超算.js"}},{"type":"toolCall","id":"call_02_yRSThSqhDBJuoeMMcbGFfYqI","name":"read","arguments":{"path":"/root/.openclaw/agents/发布大师/workspace/publish-DeepSeekV4黄仁勋.js"}},{"type":"toolCall","id":"call_03_d2IQPttVos8L5osJRGIUJjGf","name":"read","arguments":{"path":"/root/.openclaw/agents/发布大师/workspace/publish-deepseek-v4-log.json"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":6259,"output":250,"cacheRead":12544,"cacheWrite":0,"totalTokens":19053,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1777037514711,"responseId":"554cb81e-3f98-4044-b643-3793573d7849"}} {"type":"message","id":"4a0c2b59","parentId":"62410cbc","timestamp":"2026-04-24T13:31:58.729Z","message":{"role":"toolResult","toolCallId":"call_00_N1UtVKPPMtzV6tnUAu4qCaiu","toolName":"read","content":[{"type":"text","text":"const xmlrpc = require('./openclaw-zblog-markdown-publisher/node_modules/xmlrpc');\nconst fs = require('fs');\n\nconst WEBSITE_CONFIG = {\n endpoint: 'https://weixinsiwei.com/zb_system/xml-rpc/index.php',\n username: 'admin',\n password: '135269zxj',\n blogId: '68ba1ff10060dd54f1e399b8e332bdba'\n};\n\nconst TITLE = 'DeepSeek V4 预览版发布：百万上下文开闸，国产大模型的\"普惠宣言\"';\nconst AUTHOR = 'ai张三疯';\n\nconsole.log('🚀 开始发布《' + TITLE + '》到网站...');\n\n// 读取HTML内容\nconst htmlContent = fs.readFileSync('DeepSeek-V4发布-2026-04-24.html', 'utf-8');\n\n// 提取和清理内容\nconst bodyMatch = htmlContent.match(/]*>([\\s\\S]*)<\\/body>/i);\nlet content = bodyMatch ? bodyMatch[1] : htmlContent;\ncontent = content.replace(/
|<\\/div>/g, '');\ncontent = content.replace(/
]*>|<\\/section>/g, '');\n\nconsole.log('📝 文章标题:', TITLE);\nconsole.log('👤 作者:', AUTHOR);\nconsole.log('📊 内容长度:', content.length, '字符');\nconsole.log('🏷️ 分类: 默认分类, AI人工智能, 大模型');\nconsole.log('🔖 标签: DeepSeek,V4,大模型,AI,国产大模型,百万上下文');\n\nconst client = xmlrpc.createSecureClient(WEBSITE_CONFIG.endpoint);\n\nclient.methodCall('metaWeblog.newPost', [\n WEBSITE_CONFIG.blogId,\n WEBSITE_CONFIG.username,\n WEBSITE_CONFIG.password,\n {\n title: TITLE,\n description: content,\n categories: ['默认分类', 'AI人工智能', '大模型'],\n mt_keywords: 'DeepSeek,V4,大模型,AI,国产大模型,百万上下文,普惠定价'\n },\n true // 立即发布\n], (error, postId) => {\n if (error) {\n console.error('❌ 发布失败:', error.message || error);\n } else {\n console.log('✅ 网站发布成功!');\n console.log('📌 文章ID:', postId);\n console.log('🌐 文章链接: https://weixinsiwei.com/?post=' + postId);\n \n // 记录发布日志\n const logEntry = {\n timestamp: new Date().toISOString(),\n title: TITLE,\n postId: postId,\n platform: 'Z-Blog网站',\n status: 'success',\n categories: ['默认分类', 'AI人工智能', '大模型'],\n tags: ['DeepSeek', 'V4', '大模型', 'AI', '国产大模型', '百万上下文', '普惠定价']\n };\n \n fs.writeFileSync('publish-deepseek-v4-log.json', JSON.stringify(logEntry, null, 2));\n console.log('📋 发布日志已保存到 publish-deepseek-v4-log.json');\n }\n});\n"}],"isError":false,"timestamp":1777037518729}} {"type":"message","id":"85652961","parentId":"4a0c2b59","timestamp":"2026-04-24T13:31:58.729Z","message":{"role":"toolResult","toolCallId":"call_01_wZ4ieUgsPe90BCOegO8OjTIY","toolName":"read","content":[{"type":"text","text":"const xmlrpc = require('xmlrpc');\n\n// Configuration\nconst ENDPOINT = 'https://weixinsiwei.com/zb_system/xml-rpc/index.php';\nconst USERNAME = 'admin';\nconst PASSWORD = '135269zxj';\nconst BLOG_ID = '68ba1ff10060dd54f1e399b8e332bdba';\n\n// Read the HTML content\nconst fs = require('fs');\nconst path = require('path');\nconst htmlPath = path.resolve(__dirname, 'DeepSeek-V4超算互联网-2026-04-24.html');\nconst htmlContent = fs.readFileSync(htmlPath, 'utf-8');\n\n// Extract body content\nconst bodyMatch = htmlContent.match(/]*>([\\s\\S]*?)<\\/body>/i);\nconst bodyHtml = bodyMatch ? bodyMatch[1].trim() : htmlContent;\n\n// Full article HTML\nconst fullHtml = `\n\n\n\n\nDeepSeek-V4牵手国家超算：国产AI基础设施的合纵时刻\n\n\n\n${bodyHtml}\n\n`;\n\n// Create XML-RPC client\nconst client = xmlrpc.createClient({\n url: ENDPOINT,\n headers: {\n 'User-Agent': 'Mozilla/5.0 (compatible; BlogPublish/1.0)'\n }\n});\n\n// First, get categories to find the correct IDs\nclient.methodCall('metaWeblog.getCategories', [BLOG_ID, USERNAME, PASSWORD], (err, categories) => {\n if (err) {\n console.error('Error getting categories:', err);\n return;\n }\n \n console.log('Categories found:', categories.length);\n categories.forEach(c => console.log(` - ${c.categoryName} (ID: ${c.categoryId})`));\n \n // Find AI人工智能 and 大模型 category IDs\n let aiCatId = null;\n let daModelCatId = null;\n \n // Try to find by name, looking for both exact and partial matches\n for (const cat of categories) {\n const name = (cat.categoryName || '').toLowerCase();\n const desc = (cat.description || '').toLowerCase();\n if (name.includes('ai') || name.includes('人工智能') || desc.includes('ai') || desc.includes('人工智能')) {\n aiCatId = cat.categoryId;\n }\n if (name.includes('大模型') || desc.includes('大模型')) {\n daModelCatId = cat.categoryId;\n }\n }\n \n // If we didn't find by name, try parent-child relationships\n if (!aiCatId && !daModelCatId) {\n // Maybe it's a single category with combined name\n for (const cat of categories) {\n const name = cat.categoryName || '';\n if (name.includes('AI') || name.includes('人工智能')) {\n aiCatId = cat.categoryId;\n }\n if (name.includes('大模型')) {\n daModelCatId = cat.categoryId;\n }\n }\n }\n \n // Fallback: use first category or AI-related\n if (!aiCatId && categories.length > 0) {\n aiCatId = categories[0].categoryId;\n console.log(`Falling back to first category: ${categories[0].categoryName} (${aiCatId})`);\n }\n \n const categoryIds = [];\n if (aiCatId) categoryIds.push(aiCatId);\n if (daModelCatId && daModelCatId !== aiCatId) categoryIds.push(daModelCatId);\n \n console.log(`Using category IDs: ${categoryIds.join(', ')}`);\n \n // Categories as strings (some systems use names)\n let catNames = null;\n try {\n // Try parent-child structure \n const parentCats = categories.filter(c => !c.parentId || c.parentId === '0');\n console.log('Parent categories:');\n parentCats.forEach(c => console.log(` - ${c.categoryName} (${c.categoryId})`));\n \n // Check sub-categories\n for (const parent of parentCats) {\n const subCats = categories.filter(c => c.parentId === parent.categoryId);\n if (subCats.length > 0) {\n console.log(` Sub-categories of \"${parent.categoryName}\":`);\n subCats.forEach(c => console.log(` - ${c.categoryName} (${c.categoryId})`));\n }\n }\n } catch(e) {}\n \n // Build the post data - try multiple category formats\n const postData = {\n title: 'DeepSeek-V4牵手国家超算：国产AI基础设施的合纵时刻',\n description: fullHtml,\n mt_excerpt: '金十数据4月24日消息，DeepSeek-V4预览版正式上线国家超算互联网AI社区。当国产最强的开源大模型之一，遇上承载国家算力战略的超算互联网平台，二者联手的背后是国产AI从单点突破走向系统整合的新阶段。',\n mt_keywords: 'DeepSeek-V4, 国家超算互联网, AI基础设施, 万卡集群, 百万上下文',\n categories: categoryIds.length > 0 ? categoryIds : ['AI人工智能'],\n wp_slug: 'deepseek-v4-national-supercomputing',\n mt_allow_comments: 1,\n mt_allow_pings: 1,\n post_status: 'publish',\n dateCreated: new Date('2026-04-24T20:15:00+08:00')\n };\n \n console.log('Publishing post with data:', JSON.stringify({\n title: postData.title,\n mt_keywords: postData.mt_keywords,\n categories: postData.categories\n }));\n \n // Try with hw support first (used by Z-Blog)\n // First try: standard metaWeblog.newPost\n client.methodCall('metaWeblog.newPost', [BLOG_ID, USERNAME, PASSWORD, postData, true], (err, data) => {\n if (err) {\n console.error('metaWeblog.newPost failed:', err.message);\n console.log('Trying blogger.newPost...');\n \n // Second try: blogger.newPost\n client.methodCall('blogger.newPost', [BLOG_ID, USERNAME, PASSWORD, postData.title, fullHtml, true], (err2, data2) => {\n if (err2) {\n console.error('blogger.newPost also failed:', err2.message);\n console.log('Trying mt.publishPost...');\n \n // Third try: Z-Blog specific\n client.methodCall('metaWeblog.newPost', [BLOG_ID, USERNAME, PASSWORD, {\n title: postData.title,\n description: fullHtml,\n mt_keywords: postData.mt_keywords\n }, true], (err3, data3) => {\n if (err3) {\n console.error('All attempts failed.');\n console.error('Last error:', err3.message);\n process.exit(1);\n }\n console.log('SUCCESS! Post ID:', data3);\n console.log('Article URL: https://weixinsiwei.com/post/' + data3);\n process.exit(0);\n });\n } else {\n console.log('SUCCESS! Post ID:', data2);\n console.log('Article URL: https://weixinsiwei.com/post/' + data2);\n process.exit(0);\n }\n });\n } else {\n console.log('SUCCESS! Post ID:', data);\n console.log('Article URL: https://weixinsiwei.com/post/' + data);\n process.exit(0);\n }\n });\n});\n"}],"isError":false,"timestamp":1777037518729}} {"type":"message","id":"459e49e9","parentId":"85652961","timestamp":"2026-04-24T13:31:58.729Z","message":{"role":"toolResult","toolCallId":"call_02_yRSThSqhDBJuoeMMcbGFfYqI","toolName":"read","content":[{"type":"text","text":"// Z-Blog XML-RPC 发布脚本 - DeepSeek-V4国产硬件黄仁勋\nconst http = require('http');\nconst xmlrpcEndpoint = 'https://weixinsiwei.com/zb_system/xml-rpc/index.php';\nconst username = 'admin';\nconst password = '135269zxj';\nconst blogId = '68ba1ff10060dd54f1e399b8e332bdba';\n\nconst tags = ['DeepSeek-V4', '黄仁勋', '华为昇腾', '国产芯片', 'AI自主可控', 'GPU'];\nconst title = '对手的恐惧是最好的赞美：DeepSeek-V4让黄仁勋公开破防了';\nconst categories = ['AI', '国产芯片', '科技'];\n\nconst fs = require('fs');\nconst path = require('path');\nconst https = require('https');\n\n// Read and process HTML - remove container class, replace with inline style\nfunction readAndProcessHtml(filePath) {\n let content = fs.readFileSync(filePath, 'utf-8');\n \n // Extract content from #output div\n const outputMatch = content.match(/
([\\s\\S]*?)<\\/div>\\s*<\\/body>/);\n let bodyContent;\n if (outputMatch) {\n bodyContent = outputMatch[1].trim();\n } else {\n const bodyMatch = content.match(/]*>([\\s\\S]*?)<\\/body>/i);\n bodyContent = bodyMatch ? bodyMatch[1].trim() : content;\n }\n \n // Remove section.container -> inline max-width:860px\n bodyContent = bodyContent.replace(/
]*>/g, '
');\n bodyContent = bodyContent.replace(/<\\/section>/g, '
');\n \n // Build full HTML document\n return `\n\n\n\n\n${title}\n\n\n${bodyContent}\n\n`;\n}\n\nfunction buildXmlRpcRequest(method, params) {\n let xml = `\n\n${method}\n`;\n \n for (const p of params) {\n xml += `${paramToXml(p)}`;\n }\n \n xml += `\n`;\n return xml;\n}\n\nfunction paramToXml(val) {\n if (typeof val === 'string') {\n return `${escapeXml(val)}`;\n } else if (typeof val === 'number') {\n return `${val}`;\n } else if (typeof val === 'boolean') {\n return val ? '1' : '0';\n } else if (val instanceof Date) {\n return `${val.toISOString()}`;\n } else if (Array.isArray(val)) {\n let xml = '';\n for (const item of val) {\n xml += `${paramToXml(item)}`;\n }\n xml += '';\n return xml;\n } else if (typeof val === 'object' && val !== null) {\n let xml = '';\n for (const [key, value] of Object.entries(val)) {\n xml += `${key}${paramToXml(value)}`;\n }\n xml += '';\n return xml;\n }\n return '';\n}\n\nfunction escapeXml(s) {\n return String(s).replace(/&/g, '&').replace(//g, '>').replace(/\"/g, '"').replace(/'/g, ''');\n}\n\nfunction xmlrpcCall(method, params) {\n return new Promise((resolve, reject) => {\n const xml = buildXmlRpcRequest(method, params);\n \n const isHttps = xmlrpcEndpoint.startsWith('https');\n const transport = isHttps ? https : http;\n const url = new URL(xmlrpcEndpoint);\n \n const options = {\n hostname: url.hostname,\n port: url.port || (isHttps ? 443 : 80),\n path: url.pathname,\n method: 'POST',\n headers: {\n 'Content-Type': 'text/xml',\n 'Content-Length': Buffer.byteLength(xml),\n 'User-Agent': 'OpenClaw-Publisher/1.0'\n }\n };\n \n const req = transport.request(options, (res) => {\n let data = '';\n res.on('data', chunk => data += chunk);\n res.on('end', () => {\n // Simple XML parsing - extract first content\n const faultMatch = data.match(/([\\s\\S]*?)<\\/fault>/);\n if (faultMatch) {\n // Try to get faultString\n const fsMatch = data.match(/faultString<\\/name>\\s*\\s*([^<]*)<\\/string>/);\n const fcMatch = data.match(/faultCode<\\/name>\\s*\\s*([^<]*)<\\/int>/);\n reject(new Error(`XML-RPC fault: ${fcMatch ? fcMatch[1] : '?'} - ${fsMatch ? fsMatch[1] : 'Unknown error'}`));\n return;\n }\n resolve(data);\n });\n });\n \n req.on('error', reject);\n req.write(xml);\n req.end();\n });\n}\n\nfunction parseResponseValue(xml) {\n // Extract value from response\n const valueMatch = xml.match(/\\s*(?:([^<]*)<\\/string>|([^<]*)<\\/int>|([^<]*)<\\/boolean>|([^<]*)<\\/double>)/);\n if (valueMatch) {\n return valueMatch[1] || valueMatch[2] || valueMatch[3] || valueMatch[4];\n }\n \n // Try array\n if (xml.includes('')) {\n const items = [...xml.matchAll(/(?:([^<]*)<\\/string>|([^<]*)<\\/int>)<\\/value>/g)];\n if (items.length > 4) {\n // This is likely a struct with many values\n const structMatch = xml.match(/([\\s\\S]*?)<\\/struct>/);\n if (structMatch) {\n const members = [...structMatch[1].matchAll(/([^<]*)<\\/name>\\s*\\s*(?:([^<]*)<\\/string>|([^<]*)<\\/int>)/g)];\n const result = {};\n for (const m of members) {\n result[m[1]] = m[2] || m[3] || '';\n }\n return result;\n }\n }\n return items.map(m => m[1] || m[2]);\n }\n \n // Try struct\n const structMatch = xml.match(/([\\s\\S]*?)<\\/struct>/);\n if (structMatch) {\n const members = [...structMatch[1].matchAll(/([^<]*)<\\/name>\\s*\\s*(?:([^<]*)<\\/string>|([^<]*)<\\/int>)/g)];\n const result = {};\n for (const m of members) {\n result[m[1]] = m[2] || m[3] || '';\n }\n return result;\n }\n \n return xml;\n}\n\nasync function main() {\n console.log('=== Z-Blog XML-RPC 发布 ===');\n console.log(`标题: ${title}`);\n console.log(`标签: ${tags.join(', ')}`);\n console.log(`端点: ${xmlrpcEndpoint}`);\n \n // Step 1: Create category structure (ensure categories exist)\n // We'll just get the blog info first\n console.log('\\n[步骤 0] 验证连接...');\n try {\n const result = await xmlrpcCall('blogger.getUsersBlogs', [\n 'appKey', username, password\n ]);\n console.log('连接成功:', result);\n } catch (e) {\n console.error('连接失败:', e.message);\n process.exit(1);\n }\n \n // Step 1: Get categories from blog\n console.log('\\n[步骤 1] 获取分类列表...');\n let existingCategories = [];\n try {\n const catResult = await xmlrpcCall('metaWeblog.getCategories', [\n blogId, username, password\n ]);\n console.log('分类响应:', catResult.substring(0, 200));\n // Parse categories\n const catMatches = [...catResult.matchAll(/categoryName<\\/name>\\s*\\s*([^<]*)<\\/string>/g)];\n existingCategories = catMatches.map(m => m[1]);\n console.log('已有分类:', existingCategories);\n } catch (e) {\n console.log('获取分类失败（可能没有分类，继续）:', e.message);\n }\n \n // Step 2: Read and process HTML content\n console.log('\\n[步骤 2] 读取并处理HTML...');\n const htmlPath = process.argv[2] || '/root/.openclaw/agents/发布大师/workspace/DeepSeekV4国产硬件黄仁勋-2026-04-24.html';\n const htmlContent = readAndProcessHtml(htmlPath);\n console.log(`HTML内容长度: ${htmlContent.length} 字符`);\n \n // Step 3: Get any existing post fix (wp.newPost doesn't require it for new posts)\n console.log('\\n[步骤 3] 发布新文章...');\n \n // Build post struct\n const postStruct = {\n title: title,\n description: htmlContent,\n dateCreated: new Date(),\n categories: categories,\n mt_keywords: tags.join(', '),\n mt_allow_comments: 1,\n mt_allow_pings: 1,\n wp_slug: 'DeepSeekV4-HuangRenxun-2026',\n post_type: 'post',\n post_status: 'publish'\n };\n \n // Try metaWeblog.newPost first\n const publishResult = await xmlrpcCall('metaWeblog.newPost', [\n blogId, username, password, postStruct, true // true = publish immediately\n ]);\n \n console.log('\\n发布响应原始XML:', publishResult.substring(0, 300));\n \n // Z-Blog returns boolean 1 for success, so we need to query the latest post\n console.log('\\n[步骤 4] 查询最新文章ID...');\n let postId = 'unknown';\n try {\n // Get recent posts (get 5 to find ours)\n const recentResult = await xmlrpcCall('metaWeblog.getRecentPosts', [\n blogId, username, password, 5\n ]);\n console.log('最新文章响应(前300字):', recentResult.substring(0, 300));\n \n // Find our post by title\n const posts = recentResult.split('').slice(1);\n for (const postXml of posts) {\n const tMatch = postXml.match(/title<\\/name>\\s*\\s*([^<]*)<\\/string>/);\n const idMatch = postXml.match(/(?:postid|postId)<\\/name>\\s*\\s*(?:([^<]*)<\\/string>|([^<]*)<\\/int>)/);\n if (tMatch && tMatch[1] === title) {\n postId = idMatch ? (idMatch[1] || idMatch[2]) : 'unknown';\n console.log('找到匹配文章:', tMatch[1], 'ID:', postId);\n break;\n }\n }\n } catch (e) {\n console.log('查询最新文章失败:', e.message);\n }\n \n console.log(`\\n=== 发布成功 ===`);\n console.log(`文章ID: ${postId}`);\n console.log(`文章URL: https://weixinsiwei.com/post/${postId}.html`);\n console.log(`文章标题: ${title}`);\n \n // Output JSON for parsing\n console.log(`\\n---RESULT---`);\n console.log(JSON.stringify({\n success: true,\n post_id: postId,\n url: `https://weixinsiwei.com/post/${postId}.html`,\n title: title\n }));\n}\n\nmain().catch(err => {\n console.error('\\n发布失败:', err.message);\n console.log(`\\n---RESULT---`);\n console.log(JSON.stringify({\n success: false,\n error: err.message\n }));\n process.exit(1);\n});\n"}],"isError":false,"timestamp":1777037518729}} {"type":"message","id":"f6b3aefa","parentId":"459e49e9","timestamp":"2026-04-24T13:31:58.729Z","message":{"role":"toolResult","toolCallId":"call_03_d2IQPttVos8L5osJRGIUJjGf","toolName":"read","content":[{"type":"text","text":"{\n \"timestamp\": \"2026-04-24T05:16:19.792Z\",\n \"title\": \"DeepSeek V4 预览版发布：百万上下文开闸，国产大模型的\\\"普惠宣言\\\"\",\n \"postId\": true,\n \"platform\": \"Z-Blog网站\",\n \"status\": \"success\",\n \"categories\": [\n \"默认分类\",\n \"AI人工智能\",\n \"大模型\"\n ],\n \"tags\": [\n \"DeepSeek\",\n \"V4\",\n \"大模型\",\n \"AI\",\n \"国产大模型\",\n \"百万上下文\",\n \"普惠定价\"\n ]\n}"}],"isError":false,"timestamp":1777037518729}} {"type":"message","id":"50d55007","parentId":"f6b3aefa","timestamp":"2026-04-24T13:32:02.730Z","message":{"role":"assistant","content":[{"type":"text","text":"Good. I see the patterns. The `publish-DeepSeekV4国产硬件黄仁勋.js` is the most robust script — it uses raw XML-RPC without external dependencies. I need to create a similar script for this article. Let me also check that the wechat-api.ts script properly downloads cover images.\n\nLet me first check the existing wechat publish pattern and also look at the HTML file more carefully:"},{"type":"toolCall","id":"call_00_XbtBZ9miNNr2VQN8q3XCsgVs","name":"read","arguments":{"path":"/root/.openclaw/agents/发布大师/workspace/DeepSeekV4阿里云百炼-2026-04-24.html","limit":20}},{"type":"toolCall","id":"call_01_EEdrTeLbGohFU2gXf5WQ5dT0","name":"exec","arguments":{"command":"cd /root/.openclaw/agents/发布大师/workspace && grep -r \"picsum\" . --include=\"*.ts\" --include=\"*.js\" 2>/dev/null | head -10"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":5755,"output":249,"cacheRead":18944,"cacheWrite":0,"totalTokens":24948,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1777037518730,"responseId":"22f5fcb4-5a3d-4da1-849b-46e5196cad82"}} {"type":"message","id":"811a22eb","parentId":"50d55007","timestamp":"2026-04-24T13:32:02.851Z","message":{"role":"toolResult","toolCallId":"call_00_XbtBZ9miNNr2VQN8q3XCsgVs","toolName":"read","content":[{"type":"text","text":"\n\n\n \n \n 阿里云百炼首发DeepSeek-V4：价格击穿地板，国产AI从\"找模型\"到\"找平台\"\n \n \n \n\n\n
\n

4月24日，阿里云百炼平台宣布首发上线DeepSeek-V4-pro和DeepSeek-V4-flash两款模型，API价格与DeepSeek官网保持一致——百万Tokens输入最低1元，百万Tokens输出最低2元。这不仅是DeepSeek-V4系列首次在云平台落地，更释放了一个清晰的信号：国产AI的竞争，已经从模型的单点突破，进入平台与模型深度绑定的新阶段。

阿里云百炼首发DeepSeek-V4意味着什么

放在一年前，"某云平台首发某模型"只是行业新闻里的一条普通条目。但今天，当DeepSeek-V4这个级别的模型选择在阿里云百炼"首发"而非独立开放API时，事情的性质变了。

DeepSeek-V4是目前国内公认最强的开源大模型系列，它的pro版在多模态推理、长上下文理解和代码生成等维度上已达到国际一线水准。这样一款模型，完全有能力像此前一样自建API渠道、独立运营——但它选择了与阿里云百炼深度绑定。

这意味着什么？意味着模型厂商在算力成本、平台生态和分发效率上做出了理性选择。跑大模型不是写代码，而是烧GPU。搭一套覆盖全国的API分发网络、处理千万级的并发请求、随时应对流量洪峰，这背后是云的硬实力。阿里云作为国内最大的公有云厂商，其基础设施的弹性和成本优势，是任何模型团队自建体系都无法比拟的。

从另一个角度看，云厂商之间正在展开一场"模型首发争夺战"。谁能拿下DeepSeek-V4、谁能抢先部署Llama、谁能让用户在自家平台上"一键调用"最新模型，谁就能在新的AI开发浪潮中占据入口地位。模型本身，已经成为云平台最核心的卖点之一——这是过去十年任何云服务都不曾有过的事情。

阿里云与DeepSeek的这次联姻，不只是商业合作，更是国产AI基础设施的"合流"：最强模型 + 最强云平台，由此开始。

价格与官网一致，低价策略的冲击力

百万Tokens输入1元、输出2元——这个价格是什么概念？

做个简单对比。一年前，同等量级的大模型API调用，百万Tokens的输入价格普遍在10-30元区间，输出则更高。即便半年前，性能接近DeepSeek-V4的模型，输出价格也仍在5-10元徘徊。如今直接打到2元以下，等于把推理成本又砍掉了一个数量级。

更关键的是，阿里云百炼这次的价格"与DeepSeek官网一致"。这句话看似平常，实则透露了一个重要信号：模型厂商和云平台在定价上达成了共识，以极低的价格共同推动市场扩张。这不是短期补贴，而是基于规模化推理降本后的真实定价。

价格击穿地板，企业是最大的受益者。

过去企业上线一个AI功能，模型调用的TCO（总拥有成本）居高不下。一个日活10万的问答应用，单日推理成本可能就到千元级别。现在价格降到这个水平，中小团队也有了直接用顶级模型做产品的底气。不是"等便宜的模型出来再尝试"，而是"现在就可以开始，成本完全可控"。

低价策略的另一重意义是——它倒逼整个行业加速降本。DeepSeek-V4以1元/百万Tokens入场的姿态，让所有同类模型都必须直面这个价格锚点。这对开发者和企业而言，是一个前所未有的低成本窗口期。

阿里云百炼的生态棋盘

百炼平台并不是只接了DeepSeek。事实上，阿里云百炼早已汇聚了数十款国内外主流大模型，覆盖通义千问、Llama、Qwen、ChatGLM等多个系列。百花齐放的模型生态，让开发者可以在一个平台内横向对比、自由切换，按场景精准选择最合适的模型。

但这次为首发DeepSeek-V4造势的动作，清晰地传递了一个信号：在百炼的模型矩阵中，DeepSeek被赋予了旗舰级的战略地位。

阿里云之所以愿意为DeepSeek-V4"站台"，有两层考量。

第一层是技术上的。DeepSeek-V4-pro在复杂推理和编码任务上的表现，代表了当前开源大模型的最高水准。这也是AI开发者群体最看重的部分——一个能打的旗舰模型，是平台吸引高质量开发者入场的关键。

第二层是生态上的。给DeepSeek做首发，本质上是让更多用户"走进百炼"的理由。开发者为了用DeepSeek-V4进来，发现百炼还附带了一整套工具链：模型微调服务、RAG知识库搭建、Prompt工程工具、GPU算力弹性调度……从"为了用模型而来"到"为了平台留下"，这就是生态黏性的价值。

这也是百炼区别于纯API中转站的核心差异。很多平台也能调DeepSeek的接口，但百炼会让你在这里做完一整件事——选择模型 → 搭建应用 → 打通业务系统 → 上线运维，所有环节都在一个平台上闭环。

云+模型一体化，基础设施的逻辑变了

这次首发最值得关注的变化，不在于DeepSeek-V4本身有多强，而在于"它为什么要通过云平台首发"这个事实。

过去两三年的AI基础设施格局是"模型归模型，云归云"。模型团队开源或开放API，开发者自己去搞定算力、部署、运维。但这种割裂正在终结。

云+模型一体化的趋势在加速。具体来说，它解决的是三个核心问题：

算力调度。大模型推理的算力消耗极大，对GPU集群的调度能力要求极高。云平台多年积累的弹性伸缩和资源池化能力，让模型推理不再是一个"帮机器找位置"的难题。

应用开发链路。从调用API到构建一个可用的AI应用，中间隔着大量的工程工作——数据预处理、Prompt调优、向量数据库、API网关、访问控制。这些能力已经逐步内建在云平台中，开发者不再需要自己去拼积木。

成本透明化。一体化模式下，用户不需要分别谈模型授权费、算力租赁费、带宽费。一个API的调用价格，里面打包了模型、算力和网络，按量计费，清晰透明。

DeepSeek-V4通过阿里云百炼首发，就是这种一体化趋势的最佳注脚。以后"选模型"和"选云平台"可能变成同一个决策——你选择了百炼，就等于选择了DeepSeek-V4及整个生态。反过来也一样。

对开发者和企业的实际影响

价格击穿地板、生态一站式、旗舰模型到位——这三个条件凑在一起，意味着AI应用创新的门槛正在被系统性降低。

对个人开发者而言，以前调一个顶级模型可能需要审批预算、申请GPU配额、做成本预估。现在，随手注册一个百炼账号，花几块钱就能跑完整套原型验证。创业团队可以在几天内做出MVP，上线后按量付费，初期推理成本几乎可以忽略不计。

对企业而言，这意味着"要不要上AI"这个问题，正在变成一个不需要纠结的问题。场景合适的，直接调用；场景复杂的，用百炼的配套工具做定制微调、搭建RAG流程、接入内部业务流程。决策的重心从"成本上能不能承担"转向"业务上值不值得做"——而后者恰恰是正常的商业判断。

更大的趋势是，当模型调用变得像调用云数据库一样简单、便宜时，AI能力会像过去十年的云服务一样渗透到每一个软件产品中。不是"加一个AI功能"，而是"每一个功能都用AI重新做一遍"。

DeepSeek-V4落户阿里云百炼，或许会成为这个浪潮的一个注脚：2026年，国产AI进入"平台+模型"一体化时代，而这是它真正走向大规模应用的开端。

以上分析基于公开信息：阿里云百炼平台于2026年4月24日宣布首发上线DeepSeek-V4-pro和DeepSeek-V4-flash模型，API价格与DeepSeek官网保持一致。

\n \n \n \n \n \n
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` wrapper. Let me just proceed with the cleanest approach.\n\nNow I'll do both tasks simultaneously:\n1. Start the WeChat publish (download cover image first, then run the script)\n2. Create the website publish script"},{"type":"toolCall","id":"call_00_s0NnnbM0FPNpZjYgiz2t0uGn","name":"exec","arguments":{"command":"cd /root/.openclaw/agents/发布大师/workspace && curl -s -L \"https://picsum.photos/seed/deepseekv4/1200/800\" -o /tmp/cover-deepseekv4.jpg && file /tmp/cover-deepseekv4.jpg && ls -la /tmp/cover-deepseekv4.jpg","timeout":30}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":4039,"output":289,"cacheRead":24832,"cacheWrite":0,"totalTokens":29160,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1777037522852,"responseId":"e83e1ff5-b5e0-4df0-afc1-7a45e826d277"}} {"type":"message","id":"5f3207ce","parentId":"498717b0","timestamp":"2026-04-24T13:32:17.449Z","message":{"role":"toolResult","toolCallId":"call_00_s0NnnbM0FPNpZjYgiz2t0uGn","toolName":"exec","content":[{"type":"text","text":"Command still running (session ember-meadow, pid 3112962). Use process (list/poll/log/write/kill/clear/remove) for follow-up."}],"details":{"status":"running","sessionId":"ember-meadow","pid":3112962,"startedAt":1777037527432,"cwd":"/root/.openclaw/workspace/fabu","tail":""},"isError":false,"timestamp":1777037537449}} {"type":"message","id":"d3615b88","parentId":"5f3207ce","timestamp":"2026-04-24T13:32:19.609Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_00_oFaN0kZRoVffJXmTN6oGNmKg","name":"process","arguments":{"action":"poll","sessionId":"ember-meadow","timeout":15000}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":151,"output":79,"cacheRead":29056,"cacheWrite":0,"totalTokens":29286,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1777037537450,"responseId":"8d9aeb58-bd94-4d7b-915c-8a62c6983b8a"}} {"type":"message","id":"dfdb666e","parentId":"d3615b88","timestamp":"2026-04-24T13:32:20.881Z","message":{"role":"toolResult","toolCallId":"call_00_oFaN0kZRoVffJXmTN6oGNmKg","toolName":"process","content":[{"type":"text","text":"/tmp/cover-deepseekv4.jpg: JPEG image data, Exif standard: [TIFF image data, little-endian, direntries=6, orientation=upper-left, xresolution=86, yresolution=94, resolutionunit=2], progressive, precision 8, 1200x800, components 3\n-rw-r--r-- 1 root root 43892 Apr 24 21:32 /tmp/cover-deepseekv4.jpg\n\nProcess exited with code 0."}],"details":{"status":"completed","sessionId":"ember-meadow","exitCode":0,"aggregated":"/tmp/cover-deepseekv4.jpg: JPEG image data, Exif standard: [TIFF image data, little-endian, direntries=6, orientation=upper-left, xresolution=86, yresolution=94, resolutionunit=2], progressive, precision 8, 1200x800, components 3\n-rw-r--r-- 1 root root 43892 Apr 24 21:32 /tmp/cover-deepseekv4.jpg\n","name":"cd /root/.openclaw/agents/发布大师/workspace"},"isError":false,"timestamp":1777037540881}} {"type":"message","id":"b565890d","parentId":"dfdb666e","timestamp":"2026-04-24T13:32:24.670Z","message":{"role":"assistant","content":[{"type":"text","text":"Cover downloaded. Now let me run the WeChat publish. First let me check how the wechat-api.ts works:"},{"type":"toolCall","id":"call_00_Zzm35Ls27KPYIduaqbdg6ta4","name":"read","arguments":{"path":"/root/.openclaw/agents/101/workspace/skills/baoyu-post-to-wechat/scripts/wechat-api.ts","limit":50}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":221,"output":111,"cacheRead":29184,"cacheWrite":0,"totalTokens":29516,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1777037540882,"responseId":"202e0c17-ec55-4b68-9dac-b73f85f179c3"}} {"type":"message","id":"80759136","parentId":"b565890d","timestamp":"2026-04-24T13:32:24.693Z","message":{"role":"toolResult","toolCallId":"call_00_Zzm35Ls27KPYIduaqbdg6ta4","toolName":"read","content":[{"type":"text","text":"import fs from \"node:fs\";\nimport path from \"node:path\";\nimport { spawnSync } from \"node:child_process\";\nimport { fileURLToPath } from \"node:url\";\nimport { loadWechatExtendConfig, resolveAccount, loadCredentials } from \"./wechat-extend-config.ts\";\n\ninterface AccessTokenResponse {\n access_token?: string;\n errcode?: number;\n errmsg?: string;\n}\n\ninterface UploadResponse {\n media_id: string;\n url: string;\n errcode?: number;\n errmsg?: string;\n}\n\ninterface PublishResponse {\n media_id?: string;\n errcode?: number;\n errmsg?: string;\n}\n\ninterface ImageInfo {\n placeholder: string;\n localPath: string;\n originalPath: string;\n}\n\ninterface MarkdownRenderResult {\n title: string;\n author: string;\n summary: string;\n htmlPath: string;\n contentImages: ImageInfo[];\n}\n\ntype ArticleType = \"news\" | \"newspic\";\n\ninterface ArticleOptions {\n title: string;\n author?: string;\n digest?: string;\n content: string;\n thumbMediaId: string;\n articleType: ArticleType;\n imageMediaIds?: string[];\n needOpenComment?: number;\n\n[615 more lines in file. Use offset=51 to continue.]"}],"isError":false,"timestamp":1777037544693}} {"type":"message","id":"fec66dc7","parentId":"80759136","timestamp":"2026-04-24T13:32:28.132Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_00_BNm1oUBgcML6yF2cHlCMBwvi","name":"read","arguments":{"path":"/root/.openclaw/agents/101/workspace/skills/baoyu-post-to-wechat/scripts/wechat-api.ts","offset":51,"limit":100}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":365,"output":104,"cacheRead":29440,"cacheWrite":0,"totalTokens":29909,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1777037544693,"responseId":"f9a2de10-4b6a-4479-bd71-a1aea4222583"}} {"type":"message","id":"564708ab","parentId":"fec66dc7","timestamp":"2026-04-24T13:32:28.156Z","message":{"role":"toolResult","toolCallId":"call_00_BNm1oUBgcML6yF2cHlCMBwvi","toolName":"read","content":[{"type":"text","text":" onlyFansCanComment?: number;\n}\n\nconst TOKEN_URL = \"https://api.weixin.qq.com/cgi-bin/token\";\nconst UPLOAD_URL = \"https://api.weixin.qq.com/cgi-bin/material/add_material\";\nconst DRAFT_URL = \"https://api.weixin.qq.com/cgi-bin/draft/add\";\n\n\nasync function fetchAccessToken(appId: string, appSecret: string): Promise {\n const url = `${TOKEN_URL}?grant_type=client_credential&appid=${appId}&secret=${appSecret}`;\n const res = await fetch(url);\n if (!res.ok) {\n throw new Error(`Failed to fetch access token: ${res.status}`);\n }\n const data = await res.json() as AccessTokenResponse;\n if (data.errcode) {\n throw new Error(`Access token error ${data.errcode}: ${data.errmsg}`);\n }\n if (!data.access_token) {\n throw new Error(\"No access_token in response\");\n }\n return data.access_token;\n}\n\nasync function uploadImage(\n imagePath: string,\n accessToken: string,\n baseDir?: string\n): Promise {\n let fileBuffer: Buffer;\n let filename: string;\n let contentType: string;\n\n if (imagePath.startsWith(\"http://\") || imagePath.startsWith(\"https://\")) {\n const response = await fetch(imagePath);\n if (!response.ok) {\n throw new Error(`Failed to download image: ${imagePath}`);\n }\n const buffer = await response.arrayBuffer();\n if (buffer.byteLength === 0) {\n throw new Error(`Remote image is empty: ${imagePath}`);\n }\n fileBuffer = Buffer.from(buffer);\n const urlPath = imagePath.split(\"?\")[0];\n filename = path.basename(urlPath) || \"image.jpg\";\n contentType = response.headers.get(\"content-type\") || \"image/jpeg\";\n } else {\n const resolvedPath = path.isAbsolute(imagePath)\n ? imagePath\n : path.resolve(baseDir || process.cwd(), imagePath);\n\n if (!fs.existsSync(resolvedPath)) {\n throw new Error(`Image not found: ${resolvedPath}`);\n }\n const stats = fs.statSync(resolvedPath);\n if (stats.size === 0) {\n throw new Error(`Local image is empty: ${resolvedPath}`);\n }\n fileBuffer = fs.readFileSync(resolvedPath);\n filename = path.basename(resolvedPath);\n const ext = path.extname(filename).toLowerCase();\n const mimeTypes: Record = {\n \".jpg\": \"image/jpeg\",\n \".jpeg\": \"image/jpeg\",\n \".png\": \"image/png\",\n \".gif\": \"image/gif\",\n \".webp\": \"image/webp\",\n };\n contentType = mimeTypes[ext] || \"image/jpeg\";\n }\n\n const boundary = `----WebKitFormBoundary${Date.now().toString(16)}`;\n const header = [\n `--${boundary}`,\n `Content-Disposition: form-data; name=\"media\"; filename=\"${filename}\"`,\n `Content-Type: ${contentType}`,\n \"\",\n \"\",\n ].join(\"\\r\\n\");\n const footer = `\\r\\n--${boundary}--\\r\\n`;\n\n const headerBuffer = Buffer.from(header, \"utf-8\");\n const footerBuffer = Buffer.from(footer, \"utf-8\");\n const body = Buffer.concat([headerBuffer, fileBuffer, footerBuffer]);\n\n const url = `${UPLOAD_URL}?access_token=${accessToken}&type=image`;\n const res = await fetch(url, {\n method: \"POST\",\n headers: {\n \"Content-Type\": `multipart/form-data; boundary=${boundary}`,\n },\n body,\n });\n\n const data = await res.json() as UploadResponse;\n if (data.errcode && data.errcode !== 0) {\n throw new Error(`Upload failed ${data.errcode}: ${data.errmsg}`);\n }\n\n if (data.url?.startsWith(\"http://\")) {\n\n[515 more lines in file. Use offset=151 to continue.]"}],"isError":false,"timestamp":1777037548156}} {"type":"message","id":"8a095f60","parentId":"564708ab","timestamp":"2026-04-24T13:32:33.989Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_00_saokOHzcL4HYEP2uHn3fDY48","name":"exec","arguments":{"command":"cd /root/.openclaw/agents/发布大师/workspace && WECHAT_APP_ID=wx88b0cf376e0386c4 WECHAT_APP_SECRET=b2d47ee298204c28cf82549d2798192f bun /root/.openclaw/agents/101/workspace/skills/baoyu-post-to-wechat/scripts/wechat-api.ts /root/.openclaw/agents/文章大师/workspace/DeepSeekV4阿里云百炼-2026-04-24-v1.md --theme default --color blue --author \"ai张三疯\" --cover /tmp/cover-deepseekv4.jpg 2>&1","timeout":120,"yieldMs":60000}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":1016,"output":230,"cacheRead":29824,"cacheWrite":0,"totalTokens":31070,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1777037548156,"responseId":"dc673517-972a-4ceb-b52a-f57af37a63c5"}} {"type":"message","id":"abef755f","parentId":"8a095f60","timestamp":"2026-04-24T13:33:13.380Z","message":{"role":"toolResult","toolCallId":"call_00_saokOHzcL4HYEP2uHn3fDY48","toolName":"exec","content":[{"type":"text","text":"[wechat-api] Theme: default, color: blue, citeStatus: true\n[wechat-api] Rendering markdown with placeholders via md-to-wechat: default, color: blue, citeStatus: true\n[wechat-api] HTML generated: /tmp/wechat-article-images-NJm6Qk/temp-article.html\n[wechat-api] Placeholder images: 0\n[wechat-api] Title: 阿里云百炼首发DeepSeek-V4：价格击穿地板，国产AI从\"找模型\"到\"找平台\"\n[wechat-api] Author: ai张三疯\n[wechat-api] Digest: 4月24日，阿里云百炼平台宣布首发上线DeepSeek-V4-pro和DeepSeek-V4-fla...\n[wechat-api] Type: news\n[wechat-api] Account: 创业张三疯 (chuangyezhangsanfeng)\n[wechat-api] Fetching access token...\n[wechat-api] Uploading images...\n[wechat-api] Uploading cover: /tmp/cover-deepseekv4.jpg\n[wechat-api] Publishing to draft...\n{\n \"success\": true,\n \"media_id\": \"imBwNhfy9Uv4ps2luE5gfhQByWCCYdVWdgO2GZYJ_Ob-ZssBIB-3G1Us_ikCsIRu\",\n \"title\": \"阿里云百炼首发DeepSeek-V4：价格击穿地板，国产AI从\\\"找模型\\\"到\\\"找平台\\\"\",\n \"articleType\": \"news\"\n}\n[wechat-api] Published successfully! media_id: imBwNhfy9Uv4ps2luE5gfhQByWCCYdVWdgO2GZYJ_Ob-ZssBIB-3G1Us_ikCsIRu"}],"details":{"status":"completed","exitCode":0,"durationMs":39363,"aggregated":"[wechat-api] Theme: default, color: blue, citeStatus: true\n[wechat-api] Rendering markdown with placeholders via md-to-wechat: default, color: blue, citeStatus: true\n[wechat-api] HTML generated: /tmp/wechat-article-images-NJm6Qk/temp-article.html\n[wechat-api] Placeholder images: 0\n[wechat-api] Title: 阿里云百炼首发DeepSeek-V4：价格击穿地板，国产AI从\"找模型\"到\"找平台\"\n[wechat-api] Author: ai张三疯\n[wechat-api] Digest: 4月24日，阿里云百炼平台宣布首发上线DeepSeek-V4-pro和DeepSeek-V4-fla...\n[wechat-api] Type: news\n[wechat-api] Account: 创业张三疯 (chuangyezhangsanfeng)\n[wechat-api] Fetching access token...\n[wechat-api] Uploading images...\n[wechat-api] Uploading cover: /tmp/cover-deepseekv4.jpg\n[wechat-api] Publishing to draft...\n{\n \"success\": true,\n \"media_id\": \"imBwNhfy9Uv4ps2luE5gfhQByWCCYdVWdgO2GZYJ_Ob-ZssBIB-3G1Us_ikCsIRu\",\n \"title\": \"阿里云百炼首发DeepSeek-V4：价格击穿地板，国产AI从\\\"找模型\\\"到\\\"找平台\\\"\",\n \"articleType\": \"news\"\n}\n[wechat-api] Published successfully! media_id: imBwNhfy9Uv4ps2luE5gfhQByWCCYdVWdgO2GZYJ_Ob-ZssBIB-3G1Us_ikCsIRu","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1777037593380}} {"type":"message","id":"7b668a38","parentId":"abef755f","timestamp":"2026-04-24T13:33:45.375Z","message":{"role":"assistant","content":[{"type":"text","text":"公众号发布成功！现在创建网站发布脚本："},{"type":"toolCall","id":"call_00_gDSF1lEpzuWfVakz4trtXPHJ","name":"write","arguments":{"path":"/root/.openclaw/agents/发布大师/workspace/publish-DeepSeekV4百炼.js","content":"// Z-Blog XML-RPC 发布脚本 - DeepSeek-V4阿里云百炼首发\nconst http = require('http');\nconst https = require('https');\nconst fs = require('fs');\nconst path = require('path');\n\nconst xmlrpcEndpoint = 'https://weixinsiwei.com/zb_system/xml-rpc/index.php';\nconst username = 'admin';\nconst password = '135269zxj';\nconst blogId = '68ba1ff10060dd54f1e399b8e332bdba';\n\nconst title = '阿里云百炼首发DeepSeek-V4：价格击穿地板，国产AI从\"找模型\"到\"找平台\"';\nconst author = 'ai张三疯';\nconst tags = ['DeepSeek-V4', '阿里云百炼', 'API', '大模型', '阿里云', '国产AI'];\nconst categories = ['默认分类', 'AI人工智能', '大模型'];\nconst slug = 'DeepSeekV4-Aliyun-Bailian-2026';\n\n// Read and process HTML - remove container class, replace with inline style\nfunction readAndProcessHtml(filePath) {\n let content = fs.readFileSync(filePath, 'utf-8');\n\n // Extract content from #output div\n const outputMatch = content.match(/
([\\s\\S]*?)<\\/div>\\s*<\\/body>/);\n let bodyContent;\n if (outputMatch) {\n bodyContent = outputMatch[1].trim();\n } else {\n const bodyMatch = content.match(/]*>([\\s\\S]*?)<\\/body>/i);\n bodyContent = bodyMatch ? bodyMatch[1].trim() : content;\n }\n\n // Remove section.container -> inline max-width:860px\n bodyContent = bodyContent.replace(/
]*>/g, '
');\n bodyContent = bodyContent.replace(/<\\/section>/g, '
');\n\n // Build full HTML document\n return `\n\n\n\n\n${title.replace(/\"/g, '"')}\n\n\n${bodyContent}\n\n`;\n}\n\nfunction escapeXml(s) {\n return String(s).replace(/&/g, '&').replace(//g, '>').replace(/\"/g, '"').replace(/'/g, ''');\n}\n\nfunction paramToXml(val) {\n if (typeof val === 'string') {\n return `${escapeXml(val)}`;\n } else if (typeof val === 'number') {\n return `${val}`;\n } else if (typeof val === 'boolean') {\n return val ? '1' : '0';\n } else if (val instanceof Date) {\n return `${val.toISOString()}`;\n } else if (Array.isArray(val)) {\n let xml = '';\n for (const item of val) {\n xml += `${paramToXml(item)}`;\n }\n xml += '';\n return xml;\n } else if (typeof val === 'object' && val !== null) {\n let xml = '';\n for (const [key, value] of Object.entries(val)) {\n xml += `${key}${paramToXml(value)}`;\n }\n xml += '';\n return xml;\n }\n return '';\n}\n\nfunction buildXmlRpcRequest(method, params) {\n let xml = `\n\n${method}\n`;\n for (const p of params) {\n xml += `${paramToXml(p)}`;\n }\n xml += `\n`;\n return xml;\n}\n\nfunction xmlrpcCall(method, params) {\n return new Promise((resolve, reject) => {\n const xml = buildXmlRpcRequest(method, params);\n const isHttps = xmlrpcEndpoint.startsWith('https');\n const transport = isHttps ? https : http;\n const url = new URL(xmlrpcEndpoint);\n\n const options = {\n hostname: url.hostname,\n port: url.port || (isHttps ? 443 : 80),\n path: url.pathname,\n method: 'POST',\n headers: {\n 'Content-Type': 'text/xml',\n 'Content-Length': Buffer.byteLength(xml),\n 'User-Agent': 'OpenClaw-Publisher/1.0'\n }\n };\n\n const req = transport.request(options, (res) => {\n let data = '';\n res.on('data', chunk => data += chunk);\n res.on('end', () => {\n const faultMatch = data.match(/([\\s\\S]*?)<\\/fault>/);\n if (faultMatch) {\n const fsMatch = data.match(/faultString<\\/name>\\s*\\s*([^<]*)<\\/string>/);\n const fcMatch = data.match(/faultCode<\\/name>\\s*\\s*([^<]*)<\\/int>/);\n reject(new Error(`XML-RPC fault: ${fcMatch ? fcMatch[1] : '?'} - ${fsMatch ? fsMatch[1] : 'Unknown error'}`));\n return;\n }\n resolve(data);\n });\n });\n\n req.on('error', reject);\n req.write(xml);\n req.end();\n });\n}\n\nasync function main() {\n console.log('=== Z-Blog XML-RPC 发布 ===');\n console.log(`标题: ${title}`);\n console.log(`标签: ${tags.join(', ')}`);\n console.log(`端点: ${xmlrpcEndpoint}`);\n\n // Step 0: Verify connection\n console.log('\\n[步骤 0] 验证连接...');\n try {\n const result = await xmlrpcCall('blogger.getUsersBlogs', ['appKey', username, password]);\n console.log('连接成功');\n } catch (e) {\n console.error('连接失败:', e.message);\n process.exit(1);\n }\n\n // Step 1: Get categories\n console.log('\\n[步骤 1] 获取分类列表...');\n let existingCategories = [];\n try {\n const catResult = await xmlrpcCall('metaWeblog.getCategories', [blogId, username, password]);\n const catMatches = [...catResult.matchAll(/categoryName<\\/name>\\s*\\s*([^<]*)<\\/string>/g)];\n existingCategories = catMatches.map(m => m[1]);\n console.log('已有分类:', existingCategories);\n } catch (e) {\n console.log('获取分类失败（继续）:', e.message);\n }\n\n // Step 2: Read and process HTML\n console.log('\\n[步骤 2] 读取并处理HTML...');\n const htmlPath = path.resolve(__dirname, 'DeepSeekV4阿里云百炼-2026-04-24.html');\n const htmlContent = readAndProcessHtml(htmlPath);\n console.log(`HTML内容长度: ${htmlContent.length} 字符`);\n\n // Step 3: Publish new post\n console.log('\\n[步骤 3] 发布新文章...');\n\n const postStruct = {\n title: title,\n description: htmlContent,\n dateCreated: new Date(),\n categories: categories,\n mt_keywords: tags.join(', '),\n mt_allow_comments: 1,\n mt_allow_pings: 1,\n wp_slug: slug,\n post_type: 'post',\n post_status: 'publish'\n };\n\n const publishResult = await xmlrpcCall('metaWeblog.newPost', [\n blogId, username, password, postStruct, true\n ]);\n\n console.log('发布响应:', publishResult.substring(0, 300));\n\n // Step 4: Get post ID from recent posts\n console.log('\\n[步骤 4] 查询最新文章ID...');\n let postId = 'unknown';\n try {\n const recentResult = await xmlrpcCall('metaWeblog.getRecentPosts', [blogId, username, password, 5]);\n const posts = recentResult.split('').slice(1);\n for (const postXml of posts) {\n const tMatch = postXml.match(/title<\\/name>\\s*\\s*([^<]*)<\\/string>/);\n const idMatch = postXml.match(/(?:postid|postId)<\\/name>\\s*\\s*(?:([^<]*)<\\/string>|([^<]*)<\\/int>)/);\n if (tMatch && tMatch[1] === title) {\n postId = idMatch ? (idMatch[1] || idMatch[2]) : 'unknown';\n console.log('找到匹配文章:', tMatch[1], 'ID:', postId);\n break;\n }\n }\n } catch (e) {\n console.log('查询最新文章失败:', e.message);\n }\n\n console.log(`\\n=== 发布成功 ===`);\n console.log(`文章ID: ${postId}`);\n console.log(`文章URL: https://weixinsiwei.com/post/${postId}.html`);\n console.log(`文章标题: ${title}`);\n\n // Save log\n const logEntry = {\n timestamp: new Date().toISOString(),\n title: title,\n postId: postId,\n platform: 'Z-Blog网站',\n status: 'success',\n categories: categories,\n tags: tags\n };\n fs.writeFileSync('publish-DeepSeekV4百炼-log.json', JSON.stringify(logEntry, null, 2));\n console.log('📋 发布日志已保存到 publish-DeepSeekV4百炼-log.json');\n\n console.log(`\\n---RESULT---`);\n console.log(JSON.stringify({\n success: true,\n post_id: postId,\n url: `https://weixinsiwei.com/post/${postId}.html`,\n title: title\n }));\n}\n\nmain().catch(err => {\n console.error('\\n发布失败:', err.message);\n console.log(`\\n---RESULT---`);\n console.log(JSON.stringify({ success: false, error: err.message }));\n process.exit(1);\n});\n"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":510,"output":2561,"cacheRead":30976,"cacheWrite":0,"totalTokens":34047,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1777037593382,"responseId":"4cea8379-d025-4648-aadc-c49039cd9f86"}} {"type":"message","id":"f6d87481","parentId":"7b668a38","timestamp":"2026-04-24T13:33:45.409Z","message":{"role":"toolResult","toolCallId":"call_00_gDSF1lEpzuWfVakz4trtXPHJ","toolName":"write","content":[{"type":"text","text":"Successfully wrote 7938 bytes to /root/.openclaw/agents/发布大师/workspace/publish-DeepSeekV4百炼.js"}],"isError":false,"timestamp":1777037625408}} {"type":"message","id":"a710bfe9","parentId":"f6d87481","timestamp":"2026-04-24T13:33:47.906Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_00_d8mMdZV0hpASzhsh5JmzB1gi","name":"exec","arguments":{"command":"cd /root/.openclaw/agents/发布大师/workspace && node publish-DeepSeekV4百炼.js 2>&1","timeout":60,"yieldMs":30000}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":172,"output":108,"cacheRead":33920,"cacheWrite":0,"totalTokens":34200,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1777037625409,"responseId":"6e02a8de-bfdc-40fa-a61c-18b7714ee397"}} {"type":"message","id":"5c9359e2","parentId":"a710bfe9","timestamp":"2026-04-24T13:33:49.129Z","message":{"role":"toolResult","toolCallId":"call_00_d8mMdZV0hpASzhsh5JmzB1gi","toolName":"exec","content":[{"type":"text","text":"=== Z-Blog XML-RPC 发布 ===\n标题: 阿里云百炼首发DeepSeek-V4：价格击穿地板，国产AI从\"找模型\"到\"找平台\"\n标签: DeepSeek-V4, 阿里云百炼, API, 大模型, 阿里云, 国产AI\n端点: https://weixinsiwei.com/zb_system/xml-rpc/index.php\n\n[步骤 0] 验证连接...\n连接成功\n\n[步骤 1] 获取分类列表...\n已有分类: [\n '视频号', '企业微信',\n '私域流量', '微信小店',\n '企微SOP', '企业邮箱',\n '腾讯电子签', '腾讯会议',\n '企业服务', '数据资产入表',\n '私车公用'\n]\n\n[步骤 2] 读取并处理HTML...\nHTML内容长度: 7889 字符\n\n[步骤 3] 发布新文章...\n发布响应: 1\n\n[步骤 4] 查询最新文章ID...\n\n=== 发布成功 ===\n文章ID: unknown\n文章URL: https://weixinsiwei.com/post/unknown.html\n文章标题: 阿里云百炼首发DeepSeek-V4：价格击穿地板，国产AI从\"找模型\"到\"找平台\"\n📋 发布日志已保存到 publish-DeepSeekV4百炼-log.json\n\n---RESULT---\n{\"success\":true,\"post_id\":\"unknown\",\"url\":\"https://weixinsiwei.com/post/unknown.html\",\"title\":\"阿里云百炼首发DeepSeek-V4：价格击穿地板，国产AI从\\\"找模型\\\"到\\\"找平台\\\"\"}"}],"details":{"status":"completed","exitCode":0,"durationMs":1198,"aggregated":"=== Z-Blog XML-RPC 发布 ===\n标题: 阿里云百炼首发DeepSeek-V4：价格击穿地板，国产AI从\"找模型\"到\"找平台\"\n标签: DeepSeek-V4, 阿里云百炼, API, 大模型, 阿里云, 国产AI\n端点: https://weixinsiwei.com/zb_system/xml-rpc/index.php\n\n[步骤 0] 验证连接...\n连接成功\n\n[步骤 1] 获取分类列表...\n已有分类: [\n '视频号', '企业微信',\n '私域流量', '微信小店',\n '企微SOP', '企业邮箱',\n '腾讯电子签', '腾讯会议',\n '企业服务', '数据资产入表',\n '私车公用'\n]\n\n[步骤 2] 读取并处理HTML...\nHTML内容长度: 7889 字符\n\n[步骤 3] 发布新文章...\n发布响应: 1\n\n[步骤 4] 查询最新文章ID...\n\n=== 发布成功 ===\n文章ID: unknown\n文章URL: https://weixinsiwei.com/post/unknown.html\n文章标题: 阿里云百炼首发DeepSeek-V4：价格击穿地板，国产AI从\"找模型\"到\"找平台\"\n📋 发布日志已保存到 publish-DeepSeekV4百炼-log.json\n\n---RESULT---\n{\"success\":true,\"post_id\":\"unknown\",\"url\":\"https://weixinsiwei.com/post/unknown.html\",\"title\":\"阿里云百炼首发DeepSeek-V4：价格击穿地板，国产AI从\\\"找模型\\\"到\\\"找平台\\\"\"}","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1777037629129}} {"type":"message","id":"539d8ac7","parentId":"5c9359e2","timestamp":"2026-04-24T13:33:58.555Z","message":{"role":"assistant","content":[{"type":"text","text":"Post seems to have been published (boolean 1 = success), but the ID lookup didn't find it in recent posts (likely because it's returning an HTML-escaped title). Let me try to find the actual post ID with a different approach:"},{"type":"toolCall","id":"call_00_2NTufuRwXKCD57DBErVdemA2","name":"exec","arguments":{"command":"cd /root/.openclaw/agents/发布大师/workspace && node -e \"\nconst https = require('https');\n\nfunction escapeXml(s) {\n return String(s).replace(/&/g, '&').replace(//g, '>').replace(/\\\"/g, '"').replace(/'/g, ''');\n}\n\nfunction paramToXml(val) {\n if (typeof val === 'string') return '' + escapeXml(val) + '';\n if (Array.isArray(val)) {\n let xml = '';\n for (const item of val) xml += '' + paramToXml(item) + '';\n xml += '';\n return xml;\n }\n return '';\n}\n\nconst xml = 'metaWeblog.getRecentPosts68ba1ff10060dd54f1e399b8e332bdbaadmin135269zxj20';\n\nconst req = https.request({\n hostname: 'weixinsiwei.com',\n path: '/zb_system/xml-rpc/index.php',\n method: 'POST',\n headers: { 'Content-Type': 'text/xml', 'Content-Length': Buffer.byteLength(xml) }\n}, (res) => {\n let data = '';\n res.on('data', chunk => data += chunk);\n res.on('end', () => {\n // Find ALL post IDs and titles\n const posts = [];\n const parts = data.split('');\n for (const part of parts) {\n const idMatch = part.match(/(?:postid|postId)<\\/name>\\\\s*\\\\s*([^<]*)<\\/string>/);\n const tMatch = part.match(/title<\\/name>\\\\s*\\\\s*([^<]*)<\\/string>/);\n if (idMatch && tMatch) {\n posts.push({ id: idMatch[1], title: tMatch[1] });\n }\n }\n console.log('All recent posts:');\n posts.forEach(p => console.log(' ID:', p.id, '| Title:', p.title));\n });\n});\nreq.write(xml);\nreq.end();\n\" 2>&1","timeout":15}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":421,"output":688,"cacheRead":34176,"cacheWrite":0,"totalTokens":35285,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1777037629130,"responseId":"e7405375-4bf0-4015-a2d0-1e08dae85e68"}} {"type":"message","id":"ccb7a7fb","parentId":"539d8ac7","timestamp":"2026-04-24T13:34:00.269Z","message":{"role":"toolResult","toolCallId":"call_00_2NTufuRwXKCD57DBErVdemA2","toolName":"exec","content":[{"type":"text","text":"All recent posts:\n ID: 9413 | Title: DeepSeek-V4牵手国家超算：国产AI基础设施的合纵时刻\n ID: 9417 | Title: 阿里云百炼首发DeepSeek-V4：价格击穿地板，国产AI从&quot;找模型&quot;到&quot;找平台&quot;\n ID: 9416 | Title: （已删除）对手的恐惧是最好的赞美\n ID: 9415 | Title: （已删除）对手的恐惧是最好的赞美\n ID: 9414 | Title: 对手的恐惧是最好的赞美：DeepSeek-V4让黄仁勋公开破防了\n ID: 9412 | Title: 飞书、钉钉、企微同时推出CLI：AI智能体办公的春天到了\n ID: 9411 | Title: DeepSeek V4 预览版发布：百万上下文开闸，国产大模型的&quot;普惠宣言&quot;\n ID: 9410 | Title: 百度一年处理144人：互联网大厂反腐，撕开了谁的遮羞布？\n ID: 9409 | Title: 国家电网豪掷100亿采购机器人：AI大规模商业落地的号角已经吹响\n ID: 9408 | Title: 日抛型软件时代来了？从无招的钉钉铁律说起\n ID: 9407 | Title: 干货收藏！人工智能100个高价值应用场景全解析，创业者必看\n ID: 9406 | Title: 干货收藏！人工智能100个高价值应用场景全解析，创业者必看\n ID: 9405 | Title: 全国人工智能应用场景创新100目录深度解析：AI落地的价值密码\n ID: 9404 | Title: 企业微信5.0.8重磅发布：智能文档、AI办公、效率革命三大升级\n ID: 9403 | Title: 2026中国Token服务商TOP50榜单深度解析：Token经济新格局与投资趋势\n ID: 9402 | Title: 国务院重磅发布&quot;人工智能+&quot;行动：大模型采购获支持，2030年服务业剑指100万亿\n ID: 9401 | Title: OpenClaw测试文章\n ID: 9400 | Title: 企业微信落地陪跑实操套餐：4980元，让数字化转型不再迷茫（HTML优化版）\n ID: 9399 | Title: OpenClaw升级血赚！DeepSeek真香，成本直降30倍！（HTML优化版）\n ID: 9398 | Title: 封闭生态的黄昏：苹果腾讯为何集体倒向开放AI？（HTML优化版）"}],"details":{"status":"completed","exitCode":0,"durationMs":1686,"aggregated":"All recent posts:\n ID: 9413 | Title: DeepSeek-V4牵手国家超算：国产AI基础设施的合纵时刻\n ID: 9417 | Title: 阿里云百炼首发DeepSeek-V4：价格击穿地板，国产AI从&quot;找模型&quot;到&quot;找平台&quot;\n ID: 9416 | Title: （已删除）对手的恐惧是最好的赞美\n ID: 9415 | Title: （已删除）对手的恐惧是最好的赞美\n ID: 9414 | Title: 对手的恐惧是最好的赞美：DeepSeek-V4让黄仁勋公开破防了\n ID: 9412 | Title: 飞书、钉钉、企微同时推出CLI：AI智能体办公的春天到了\n ID: 9411 | Title: DeepSeek V4 预览版发布：百万上下文开闸，国产大模型的&quot;普惠宣言&quot;\n ID: 9410 | Title: 百度一年处理144人：互联网大厂反腐，撕开了谁的遮羞布？\n ID: 9409 | Title: 国家电网豪掷100亿采购机器人：AI大规模商业落地的号角已经吹响\n ID: 9408 | Title: 日抛型软件时代来了？从无招的钉钉铁律说起\n ID: 9407 | Title: 干货收藏！人工智能100个高价值应用场景全解析，创业者必看\n ID: 9406 | Title: 干货收藏！人工智能100个高价值应用场景全解析，创业者必看\n ID: 9405 | Title: 全国人工智能应用场景创新100目录深度解析：AI落地的价值密码\n ID: 9404 | Title: 企业微信5.0.8重磅发布：智能文档、AI办公、效率革命三大升级\n ID: 9403 | Title: 2026中国Token服务商TOP50榜单深度解析：Token经济新格局与投资趋势\n ID: 9402 | Title: 国务院重磅发布&quot;人工智能+&quot;行动：大模型采购获支持，2030年服务业剑指100万亿\n ID: 9401 | Title: OpenClaw测试文章\n ID: 9400 | Title: 企业微信落地陪跑实操套餐：4980元，让数字化转型不再迷茫（HTML优化版）\n ID: 9399 | Title: OpenClaw升级血赚！DeepSeek真香，成本直降30倍！（HTML优化版）\n ID: 9398 | Title: 封闭生态的黄昏：苹果腾讯为何集体倒向开放AI？（HTML优化版）","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1777037640269}} {"type":"message","id":"02b894a3","parentId":"ccb7a7fb","timestamp":"2026-04-24T13:34:03.664Z","message":{"role":"assistant","content":[{"type":"text","text":"Found it! Post ID 9417 with title (HTML entities in title but that's Z-Blog behavior). The URL should be `https://weixinsiwei.com/post/9417.html`. Let me verify:"},{"type":"toolCall","id":"call_00_vTBYzaqUO6jjRjbpTu19xuPq","name":"exec","arguments":{"command":"cd /root/.openclaw/agents/发布大师/workspace && node -e \"\nconst log = JSON.parse(require('fs').readFileSync('publish-DeepSeekV4百炼-log.json','utf-8'));\nlog.postId = '9417';\nlog.url = 'https://weixinsiwei.com/post/9417.html';\nrequire('fs').writeFileSync('publish-DeepSeekV4百炼-log.json', JSON.stringify(log, null, 2));\nconsole.log('Updated log with post ID 9417');\n\" 2>&1"}}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":687,"output":208,"cacheRead":35200,"cacheWrite":0,"totalTokens":36095,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1777037640270,"responseId":"225fd578-087c-4a39-b391-fc899c16ea27"}} {"type":"message","id":"5f8b7fbb","parentId":"02b894a3","timestamp":"2026-04-24T13:34:03.744Z","message":{"role":"toolResult","toolCallId":"call_00_vTBYzaqUO6jjRjbpTu19xuPq","toolName":"exec","content":[{"type":"text","text":"Updated log with post ID 9417"}],"details":{"status":"completed","exitCode":0,"durationMs":55,"aggregated":"Updated log with post ID 9417","cwd":"/root/.openclaw/workspace/fabu"},"isError":false,"timestamp":1777037643744}} {"type":"message","id":"7eb46fde","parentId":"5f8b7fbb","timestamp":"2026-04-24T13:34:07.549Z","message":{"role":"assistant","content":[{"type":"text","text":"完美！两个渠道都发布成功了。以下是发布总结：\n\n---\n\n## ✅ 发布总结\n\n**📱 公众号发布**\n- **公众号**：创业张三疯\n- **media_id**：`imBwNhfy9Uv4ps2luE5gfhQByWCCYdVWdgO2GZYJ_Ob-ZssBIB-3G1Us_ikCsIRu`\n- **封面图**：picsum.photos 自动下载\n- **状态**：已发布到草稿箱\n\n**🌐 网站发布**\n- **平台**：思维思维 (weixinsiwei.com)\n- **文章ID**：9417\n- **文章链接**：https://weixinsiwei.com/post/9417.html\n- **标签**：DeepSeek-V4, 阿里云百炼, API, 大模型, 阿里云, 国产AI\n- **状态**：已成功发布"}],"api":"openai-completions","provider":"deepseek","model":"deepseek-chat","usage":{"input":147,"output":203,"cacheRead":35968,"cacheWrite":0,"totalTokens":36318,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1777037643745,"responseId":"9f3f1e57-eb54-46f5-a3cc-3144a3710e19"}}