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20 篇（不包含 AI 创作的文章）\n5.不接受商业性或包含侵入性广告的站点\n6.不接受违反中华人民共和国法律法规的站点\n7.友链的添加结果以管理员审核为准\n",6,1440,[33],{"id":34,"createdAt":35,"updatedAt":36,"name":37,"url":38,"logo":39,"description":40,"rssUrl":41,"contactEmail":42,"categoryId":43,"status":44,"source":45,"isPinned":28,"isFeatured":28,"sortOrder":46,"healthStatus":47,"consecutiveFailures":46,"healthCheckCooldownUntil":48,"lastCheckedAt":49,"lastErrorMessage":50,"lastHttpStatus":4,"applicationId":50,"createdById":51,"updatedById":51,"category":52},"6735b175f7c048d8","2026-03-10T08:03:36.010Z","2026-07-13T14:04:46.826Z","草梅友仁的博客","https:\u002F\u002Fblog.cmyr.ltd\u002F","https:\u002F\u002Foss.cmyr.dev\u002Fmomei-files\u002Fimage\u002F20260310080323739-m6c6b5k.svg","草梅友仁为自己写的博客。","https:\u002F\u002Fblog.cmyr.ltd\u002Fatom.xml","caomeiyouren@qq.com","6735b0f050804976","active","manual",0,"healthy","2026-07-14T14:04:46.810Z","2026-07-13T14:04:46.810Z",null,"66cf4cf532804a53",{"id":43,"createdAt":53,"updatedAt":53,"name":54,"slug":55,"description":56,"sortOrder":46,"isEnabled":28},"2026-03-10T08:01:19.153Z","技术博客","tech-blog","和编程、技术等相关内容的博客",[58],{"category":59,"items":60},{"id":43,"createdAt":53,"updatedAt":53,"name":54,"slug":55,"description":56,"sortOrder":46,"isEnabled":28},[61],{"id":34,"createdAt":35,"updatedAt":36,"name":37,"url":38,"logo":39,"description":40,"rssUrl":41,"contactEmail":42,"categoryId":43,"status":44,"source":45,"isPinned":28,"isFeatured":28,"sortOrder":46,"healthStatus":47,"consecutiveFailures":46,"healthCheckCooldownUntil":48,"lastCheckedAt":49,"lastErrorMessage":50,"lastHttpStatus":4,"applicationId":50,"createdById":51,"updatedById":51,"category":62},{"id":43,"createdAt":53,"updatedAt":53,"name":54,"slug":55,"description":56,"sortOrder":46,"isEnabled":28},{"code":4,"data":64,"locale":73},{"id":65,"createdAt":66,"updatedAt":67,"title":68,"slug":69,"content":70,"summary":71,"coverImage":72,"language":73,"translationId":69,"authorId":51,"categoryId":74,"status":75,"visibility":76,"views":77,"isPinned":11,"copyright":50,"metaVersion":78,"metadata":79,"publishedAt":971,"author":972,"category":974,"tags":978,"audioUrl":85,"audioDuration":86,"audioSize":87,"audioMimeType":88,"publishIntent":1039,"memosId":98,"translations":1040,"previousPost":1050,"nextPost":1057,"relatedPosts":1064,"locked":11},"67c36aaa97c04ecd","2026-06-28T09:58:36.382Z","2026-07-12T00:06:57.571Z","记一次基于 Hermes Agent 的 AI 助手自动化深度使用体验","hermes-agent-docker-deployment-deepseek-v4-feishu","> **摘要**：本文记录了将 Hermes Agent 部署到 Docker、接入飞书、配置 tinyfish-mcp 搜索、搭配 DeepSeek V4 Flash 低成本方案，以及两周深度使用的真实体验。适合有一定 Docker 基础、想搭建自部署 AI 助手的读者。\n\n在上期博客 [《Hermes Agent AI 助手与墨梅博客更新 | 2026 年第 24 周草梅周报》](https:\u002F\u002Fmomei.app\u002Fposts\u002F2026-24-caomei-weekly-hermes-agent-momei-weekly) 中简单提了一下 [Hermes Agent](https:\u002F\u002Fgithub.com\u002FNousResearch\u002Fhermes-agent)，这次将结合最近几周的真实使用体验，来给出一个完整的部署和使用报告。\n\n> 官方文档：https:\u002F\u002Fhermes-agent.nousresearch.com\u002Fdocs\u002Fzh-Hans\u002F\n\n## 部署\n\n首先，和 OpenClaw 一样，要想使用 Hermes Agent，先得部署 Hermes Agent。\n\n考虑到此类 AI 助手的所需要的权限非常大，因此非常**不推荐**在个人电脑上部署，如需部署，还是建议优先使用 Docker 这样的容器环境来部署，和主机环境进行隔离，以减少被误删文件和被攻击的风险。\n\n> Docker 容器本身就是安全边界\n\n接下来介绍一下如何通过 Docker 部署 Hermes Agent。\n\n首先进行一些前期准备，包括 Linux 服务器、Docker、LLM 的 API Key。\n\n### 环境要求\n\n- **服务器**：Linux（最好不低于 2 核 4G，否则会有卡死的风险）\n- **Docker**：已安装 docker、docker-compose\n- **API Key**：至少一个 LLM 厂商的密钥（DeepSeek、OpenAI 等）\n- **消息网关**：这里以飞书为例（你可以选择任意一个支持的[消息平台](https:\u002F\u002Fhermes-agent.nousresearch.com\u002Fdocs\u002Fzh-Hans\u002Fuser-guide\u002Fmessaging\u002F)，例如 QQ、企业微信、钉钉等）\n\n### 安装\n\n在服务器合适的目录下写入以下 `docker-compose.yml` 配置文件。\n\n```yml\n# \n# Hermes Agent — Docker Compose 部署\n# 配置: DeepSeek V4 Flash + 飞书 WebSocket\n#\nservices:\n  hermes:\n    image: nousresearch\u002Fhermes-agent:latest\n    container_name: hermes\n    restart: unless-stopped\n    volumes:\n      - .\u002Fhermes_data:\u002Fopt\u002Fdata\n    env_file:\n      - .env\n    environment:\n      # ---- 用户权限 ----\n      - HERMES_UID=${HERMES_UID:-1000}\n      - HERMES_GID=${HERMES_GID:-1000}\n      # ---- DeepSeek Provider ----\n      - DEEPSEEK_API_KEY=${DEEPSEEK_API_KEY}\n      # ---- 飞书渠道 (WebSocket 模式) ----\n      - FEISHU_APP_ID=${FEISHU_APP_ID}\n      - FEISHU_APP_SECRET=${FEISHU_APP_SECRET}\n      - FEISHU_DOMAIN=feishu\n      - FEISHU_CONNECTION_MODE=websocket\n      # ---- 飞书安全白名单 (强烈推荐) ----\n      - FEISHU_ALLOWED_USERS=${FEISHU_ALLOWED_USERS}\n      # ---- 推荐: 设置 home chat 用于 cron\u002F通知 ----\n      - FEISHU_HOME_CHANNEL=${FEISHU_HOME_CHANNEL}\n      # - GATEWAY_ALLOW_ALL_USERS=${GATEWAY_ALLOW_ALL_USERS:-false}\n      - GATEWAY_ALLOWED_USERS=${GATEWAY_ALLOWED_USERS}\n      - OPENCODE_GO_API_KEY=${OPENCODE_GO_API_KEY}\n    command: [\"gateway\", \"run\"]\n\n```\n\n在这里选择用 DeepSeek V4 Flash 作为后端 AI 模型，飞书作为前端交互客户端。在这里不使用 Web dashboard，也就不开放任何端口，所有消息通过飞书发送和接收。所有数据保存到当前目录下的 `hermes_data` 目录（和官方有差异，官方默认是 `~\u002F.hermes\u002F`，我这里用自定义挂载是为了方便备份）。\n\n当然，上述配置还是不完整的，因为没有对应的环境变量。\n\n在同一目录下新建 `.env` 文件，配置参考如下，请注意替换成你的真实值。\n\n```ini\n# === DeepSeek API ===\n# 在 https:\u002F\u002Fplatform.deepseek.com 申请\nDEEPSEEK_API_KEY=sk-xxxx\n\n# === 飞书应用凭据 ===\n# 在 https:\u002F\u002Fopen.feishu.cn\u002Fapp 申请，具体申请过程参考下文\nFEISHU_APP_ID=cli_xxxx\nFEISHU_APP_SECRET=xxxxx\nFEISHU_DOMAIN=feishu\nFEISHU_CONNECTION_MODE=websocket\n\n# === 飞书安全白名单 (用逗号分隔用户 open_id) ===\nFEISHU_ALLOWED_USERS=ou_xxxx\n\n# === 可选: Home Chat ID (cron job 结果、通知发送到此) ===\n# FEISHU_HOME_CHANNEL=oc_xxx\n# 允许的用户 ID。\n# GATEWAY_ALLOWED_USERS=xxx\n# 第一次使用建议先设置成允许所有用户，不过请确保该应用只有自己使用！\nGATEWAY_ALLOW_ALL_USERS=true \n```\n\n除此之外，你还需要在 `hermes_data` 目录下创建一个 `config.yaml` 文件，内容如下：\n\n```yaml\nmodel:\n  provider: deepseek\n  default: deepseek-v4-flash\n```\n\n> 你也可以使用任何[支持的 AI 提供商](https:\u002F\u002Fhermes-agent.nousresearch.com\u002Fdocs\u002Fzh-Hans\u002Fintegrations\u002Fproviders)。\n\n当然，你也可以通过命令行配置，通过以下命令进入设置向导，向导会提示你输入 API 密钥并将其写入 `.\u002Fhermes_data\u002F.env`\n\n```sh\ndocker run -it --rm \\\n  -v .\u002Fhermes_data:\u002Fopt\u002Fdata \\\n  nousresearch\u002Fhermes-agent setup\n```\n\n### 接入飞书平台\n\n在这里需要一个飞书应用凭据和用户的 open_id，先讲一下飞书智能体应用如何创建。\n\n首先登录[飞书开发者后台](https:\u002F\u002Fopen.feishu.cn\u002Fapp)，可以看到首页已经置顶了 `创建飞书智能体应用` 的入口，如果没有的话也可以点击下面的 `创建企业自建应用` 入口来创建。\n\n![飞书开发者后台 - 创建智能体应用入口](https:\u002F\u002Foss.cmyr.dev\u002Fimages\u002F20260628000643113.png)\n\n然后就可以看到设置头像和名称的页面了，直接点 `立即创建` 就行了。\n\n![飞书开发者后台 - 创建智能体应用](https:\u002F\u002Foss.cmyr.dev\u002Fimages\u002F20260628000617122.png)\n\n然后就能直接看到 App ID 和 App Secret 了，复制到环境变量中。\n\n![image-20260628000747412](https:\u002F\u002Foss.cmyr.dev\u002Fimages\u002F20260628000747468.png)\n\n之后在项目目录下面执行以下命令，启用 Hermes Agent 的 Docker 镜像即可。\n\n```sh\ndocker compose up -d \n```\n\n这时候就可以给机器人发消息来验证接入是否成功了。\n\n![image-20260628001752386](https:\u002F\u002Foss.cmyr.dev\u002Fimages\u002F20260628001752563.png)\n\n如果没有响应，一般是没有配置 `飞书安全白名单` 和 `允许的用户 ID` 的缘故。\n\n这种情况下可以先临时把 `GATEWAY_ALLOW_ALL_USERS` 设置成 `true`，然后直接询问 AI 用户的 `open_id`，并在 `FEISHU_ALLOWED_USERS` 和 `GATEWAY_ALLOWED_USERS` 中填入。\n\n> 也可以直接去看 `logs\u002Fgateway.log` 的日志。\n\n![image-20260628002340001](https:\u002F\u002Foss.cmyr.dev\u002Fimages\u002F20260628002340089.png)\n\n## 使用\n\nAI 能够通过飞书渠道进行回复之后，就可以正式开始使用了。\n\n比如说，您可以先向它自我介绍一下，它就会记下来，以后也会直接引用。\n\n![image-20260628003452887](https:\u002F\u002Foss.cmyr.dev\u002Fimages\u002F20260628003453006.png)\n\n然后是一些使用上的小技巧。\n\n### 部署搜索 MCP\n\n众所周知，没有搜索工具的 AI 大模型依旧是个笨蛋，而在我的真实使用过程中，搜索类工具的触发概率基本上到了 80%~90%，做调研、探索、核实等任务的时候基本上是刚需，因此我选择了接入 [tinyfish-mcp](https:\u002F\u002Fgithub.com\u002FCaoMeiYouRen\u002Ftinyfish-mcp)，可以说非常好用。\n\n> tinyfish-mcp 的部署请参考官方文档。\n\n部署完 tinyfish-mcp 后，在 `config.yaml` 中配置即可。\n\n```yml\nmcp_servers:\n  tinyfish-search:\n    url: \"https:\u002F\u002Ftinyfish.example.com\u002Fmcp\"\n    headers:\n      Authorization: \"Bearer xxxxxx\"\n```\n\n![image-20260628004015611](https:\u002F\u002Foss.cmyr.dev\u002Fimages\u002F20260628004015715.png)\n\n###  配置 Tool Search\n\n如果你配置了多个 MCP 的话，那么就会发现 MCP 的 schema 占用了大量的上下文，因此可以考虑显式启用 `Tool Search` 功能。\n\n在 `config.yaml` 配置中这样设置：\n\n```yml\ntools:\n  tool_search:\n    enabled: true       # 之前是 auto，现在显式启用\n    threshold_pct: 10   # MCP\u002F插件工具超过上下文 10% 时触发\n    search_default_limit: 5\n    max_search_limit: 20\n\n```\n\n由于像 DeepSeek V4 这样的模型是支持 1M 上下文的，所以按照 auto 的 10% 自动触发来计算的话，得要 100k 左右的 MCP schema 上下文占用才会启用，而这个时候 MCP schema 的占用其实已经太大了，所以建议改成显式启用。\n\n### 使用便宜的 AI 模型\n\n虽然也有人通过 Hermes Agent 编程，但大部分情况下还是跟它聊天多，而这种情况下是不需要太好的模型的，加上使用高级模型带来的开支是不容忽视的，所以还是建议大家使用便宜的 AI 模型，比如说高性价比的 DeepSeek V4 Flash，而不是 DeepSeek V4 Pro。如果真的需要编程，再通过调用 Claude Code、OpenCode 等 AI 工具来编程。\n\n在这里个人比较推荐通过 [OpenCode Go](https:\u002F\u002Fopencode.ai\u002Fgo?ref=T6C9392XGM) 来调用 DeepSeek V4 Flash，能比 DeepSeek 官方还优惠一些。\n\n> 以上链接包含我的邀请码，通过此链接注册你和我都能获得一定免费使用额度。\n>\n> OpenCode Go 官方文档：https:\u002F\u002Fopencode.ai\u002Fdocs\u002Fzh-cn\u002Fgo\n\n具体的原理就是 OpenCode Go 只需要 10 美元一个月，但是额度上却有 60 美元。\n\n虽然 OpenCode Go 里面 DeepSeek V4 Pro 目前还没有同步 DeepSeek 官方的 2.5 折优惠，但是 DeepSeek V4 Flash 的价格是一致的，所以确实可以用 10 美元的价格用 60 美元额度的 DeepSeek V4 Flash，在各类 AI 模型中也算性价比最高的那一档了。\n\n此外 OpenCode Go 还可以配合 Qwen3.7 Plus 来解决图像识别的问题，算是性价比最高的 AI 模型套餐之一了。\n\n![image-20260628010217783](https:\u002F\u002Foss.cmyr.dev\u002Fimages\u002F20260628010217867.png)\n\n如果使用 OpenCode Go，在环境变量中的配置项就要对应改成 OpenCode Go 的，比如：\n\n```ini\nOPENCODE_GO_API_KEY=xxxx\n```\n\n并且 `config.yaml` 配置的 `model.provider` 字段也要做如下修改：\n\n```yaml\nmodel:\n  provider: opencode-go\n  default: deepseek-v4-flash\n```\n\n### 配置视觉模型\n\n如果你使用了 DeepSeek V4 系列作为 Hermes Agent 后端的主力 AI 模型，那么会遇到一个问题，那就是 deepseek-v4 目前还不支持识别图像，所以无法识别你发送的图片，影响使用体验。\n\n在 Hermes Agent 中是支持单独设置视觉模型的，所以可以在 `config.yaml` 配置的 `auxiliary.vision.model` 字段中设置了 `qwen3.7-plus` 等支持图像识别的 AI 模型，来弥补 DeepSeek V4 Flash 的不足。\n\n```yml\nauxiliary:\n  vision:\n    provider: opencode-go\n    model: qwen3.7-plus\n```\n\n![image-20260614220340115](https:\u002F\u002Foss.cmyr.dev\u002Fimages\u002F20260614220340272.png)\n\n### 自动化整理记忆\n\nHermes Agent 是支持设置定时任务的，为了强化它的自主学习能力，可以要求它每天凌晨的时候自动扫描过去 24 小时的会话，提取可复用的知识，从而省去了人工要求它复用的工夫。\n\n> 参考 prompt： \"扫描过去 24 小时的所有会话，提取可复用的知识...\"\n\n这里有一个小问题是，在 cron job 中无法直接写入 Memory，也就是说无法直接修改 Agent 记忆，所以只能采用间接方案，用 `file` 工具写入 `reusable-knowledge.json` 作为文件级知识库。\n\n### 使用 markdown 发送消息\n\n由于飞书的限制，表格在消息中是无法渲染的，所以可以考虑转换成 markdown 文件作为附件进行发送，这样可以解决排版问题，也可以避免消息中出现了不支持的 markdown 排版字符。\n\n> 你可以直接要求 AI 以 markdown 文件格式发送附件，或者要求检测到表格字符后就自动转换成 markdown 附件。\n\n![image-20260614220405355](https:\u002F\u002Foss.cmyr.dev\u002Fimages\u002F20260614220405504.png)\n\n## 一些使用体验\n\n接下来聊聊自己这段时间使用 Hermes Agent 的感受吧。\n\n首先就是非常的强大，非常的好用。\n\n最开始对它的期望也就是个高度定制化的豆包而已，但现在看起来远比豆包好用。\n\n为什么？\n\n豆包不能执行代码、不能操作文件、也不能定时自省——而 Hermes Agent 把这些都集成在了一个界面中，这就是它比豆包好用的地方。\n\n一方面，通过自建的 [tinyfish-mcp](https:\u002F\u002Fgithub.com\u002FCaoMeiYouRen\u002Ftinyfish-mcp) 解决的搜索质量问题，另一方面，通过 [super-search](https:\u002F\u002Fgithub.com\u002FCaoMeiYouRen\u002Fcmyr-skills-agents\u002Ftree\u002Fmaster\u002Fskills\u002Fsuper-search) 解决了调查报告质量的问题，可以说这是超过绝大部分 AI 搜索工具结果质量的基石。\n\n其次则是定时任务系统。\n\n个人也是使用过类似 n8n 这样的可视化低代码平台，虽然说写一个定时任务并不复杂，但手动去写、手动去连线还是有点麻烦，而自己写脚本也是嫌麻烦，而通过 Hermes Agent 一句话就能让它自己写脚本，并且出了问题还能自己修复，这就非常的愉快了。\n\n而这些只是 Hermes Agent 最基础的功能，Hermes Agent 从本质上讲就是个自部署的 AI 助手，是可以轻松加入绝大多数工作流的，把它拉进工作群就是个最简单的使用方式了（不过得记得做好权限控制），剩下的交给时间就行，多互动，就会越来越好用。\n\n即便一时间找不到合适的使用方式，那就真的把它当成一个 AI 聊天工具就行，有什么问题问一下，还能帮你总结经验。\n\n## 写在最后\n\n最后其实也没有要多说的了，从 AI 能够通过飞书渠道进行回复之后，剩下的要做的事情就只剩下多用了，遇到不会的就问 AI，还可以让它自己解决问题，从而跑通整个自动化流程。\n\n可以预见的是，从 OpenClaw 开始的自部署个人 AI Agent 框架爆火并不是偶然，而是一个刚需，未来只会出现更多像 Hermes Agent 这样的项目来满足用户需求。\n\n而基于 Hermes Agent 这样的 AI 助手，能够实现的自动化是超乎想象的，可以说完全能够替代人工操作。而至于是**取代**还是**解放**，就见仁见智了。\n\n我们下期再见，拜拜~\n\n----\n\n您可以通过以下方式订阅草梅博客的更新：\n - **博客**：[草梅友仁的博客](https:\u002F\u002Fblog.cmyr.ltd)\n - **墨梅博客**：[墨梅博客](https:\u002F\u002Fmomei.app)\n - **RSS**：[草梅友仁的博客 RSS](https:\u002F\u002Fblog.cmyr.ltd\u002Fatom.xml)\n - **公众号**：[草梅友仁的后花园](https:\u002F\u002Foss.cmyr.dev\u002Fimages\u002F20241025184516839-21n2ctv.png)\n - **邮箱订阅**：[草梅友仁的博客订阅](https:\u002F\u002Flistmonk.cmyr.dev\u002Fsubscription\u002Fform)\n\n## 往期回顾\n\n- [2026-06-14 Hermes Agent AI 助手与墨梅博客更新 | 2026 年第 24 周草梅周报](https:\u002F\u002Fblog.cmyr.ltd\u002Farchives\u002F2026-24-caomei-weekly-hermes-agent-momei-weekly.html)\n- [2026-06-07 墨梅博客 1.19.0 发布与 Copilot 涨价替代方案 | 2026 年第 23 周草梅周报](https:\u002F\u002Fblog.cmyr.ltd\u002Farchives\u002F2026-23-caomei-weekly-momei-blog-1-19-0-release-copilot-price-increase-alternative.html)\n- [2026-05-31 AI 超级搜索与墨梅博客开源动态 | 2026 年第 22 周草梅周报](https:\u002F\u002Fblog.cmyr.ltd\u002Farchives\u002F2026-22-caomei-weekly-super-search-momei-open-source.html)","从 Docker 部署到实际使用，全面分享基于 Hermes Agent 自部署 AI 助手接入飞书、配置搜索 MCP、低成本调用 DeepSeek V4 Flash 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