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Party：将LLM与图片工作流集成，图片、语音、文本、视觉一体！（graphRAG、ollama）</span></div></div><div class="mod-article-content"><div class="mod-header"><div class="mod-header__top"><div class="mod-header__title"><h1 class="title-text">ComfyUI Party：将LLM与图片工作流集成，图片、语音、文本、视觉一体！（graphRAG、ollama）</h1></div></div><div class="mod-article-source header"><div class="mod-article-source__main"><div class="mod-article-source__avatar"><img src="https://developer.qcloudimg.com/http-save/10011/014478f2b75149c90c6c0d48865a5ff0.jpg" alt="作者头像"/></div><div class="mod-article-source__detail"><div class="mod-article-source__name"><span>AI进修生</span></div></div><button class="cdc-btn mod-article-source__operate cdc-btn--primary"><span><i></i>关注</span></button></div></div><div class="mod-header__bottom"><div class="mod-header__detail"><div class="mod-header__date"><span class="date-text">发布于 2024-12-02 19:36:38</span></div><div class="mod-header__date is-mobile"><span class="date-text">发布于 2024-12-02 19:36:38</span></div><div 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class="mod-header__operates"><div class="mod-header__operate"><span class="cdc-svg-icon-con is-operate"><span class="cdc-svg-icon" style="width:16px;height:16px"><svg width="16" height="16" viewBox="0 0 16 16" fill="currentcolor" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M9.21101 2.54545C8.80733 1.81818 7.79814 1.81818 7.39446 2.54545L1.94481 12.3636C1.54113 13.0909 2.04573 14 2.85308 14H13.7524C14.5597 14 15.0643 13.0909 14.6607 12.3636L9.21101 2.54545ZM2.85308 12.9091L8.30273 3.09091L13.7524 12.9091H2.85308ZM8.00037 6H9.00037V10H8.00037V6ZM8.00037 11H9.00037V12H8.00037V11Z" fill="currentcolor"></path></svg></span><span class="cdc-svg-icon-text">举报</span></span></div></div></div><div class="mod-header__special"><div class="cdc-special-guide"><span><i class="cdc-special-guide-icon"></i>文章被收录于专栏：</span><a class="cdc-special-guide-name">AI进修生</a></div></div></div><div class="mod-content"><div class="mod-content__markdown"><div><div class="rno-markdown new-version rno-"><p>🍹 Insight Daily 🪺</p><h6 id="f4sd5" name="Aitrainee-%7C-%E5%85%AC%E4%BC%97%E5%8F%B7%EF%BC%9AAI%E8%BF%9B%E4%BF%AE%E7%94%9F">Aitrainee | 公众号：AI进修生</h6><p>Hi，这里是Aitrainee，欢迎阅读本期新文章。</p><p>我们正在使用一些Agent平台如FastGPT和Dify，他们注重于快速生成文本内容，知识库问答，提供自定义能力和与现有系统的集成性。</p><p>同时，在AI绘画方面，我们原来使用SD，后来使用ComfyUI。虽然ComfyUI被广泛用于将文本转化为图像（文生图），但它实际上是一种生成式AI内容（AIGC）的工具，其功能不仅限于此。它还能够处理文本生成（文生文），因此可以实现多种内容的生成。</p><p>Dify中也有提供ComfyUI的集成工具，他是调用Comfy UI的服务。</p><figure class=""><div class="rno-markdown-img-url" style="text-align:center"><div class="rno-markdown-img-url-inner" style="width:100%"><div style="width:100%"><img src="https://developer.qcloudimg.com/http-save/yehe-9836881/1ece32ccf90e7a2a27a120f605a031f5.jpg" alt="" style="width:100%"/></div></div></div></figure><p>所以，今天我们介绍ComfyUI LLM Party</p><figure class=""><div class="rno-markdown-img-url" style="text-align:center"><div class="rno-markdown-img-url-inner" style="width:100%"><div style="width:100%"><img src="https://developer.qcloudimg.com/http-save/yehe-9836881/48511625e1c400618a3d45d386a22c31.png" alt="" style="width:100%"/></div></div></div></figure><p>这个工具挺酷的，他专注于LLM集成进ComfyUI里面。旨在基于comfyui作为前端，开发一套完整的LLM工作流构建节点，让用户可以快速便捷地构建自己的LLM工作流，并轻松集成到现有的图片工作流中。</p><p>该插件在 ComfyUI 中支持绝大多数大语言模型，兼容 OpenAI 格式的 API 调用，并结合 OneAPI 调用几乎所有 LLM API。支持的模型包括通义千问、智谱清言、DeepSeek 和 Kimi。</p><p>额外功能有：支持 Ollama 本地模型，模型链节点选项（LLM、VLM-GGUF、LLM-GGUF），以及 VLM 模型的图像识别和提示词反推。</p><p>实用工具包括 OpenAI 语音识别与合成、Markdown 转 HTML、HTML 转图片，以及通过飞书机器人发送消息到多个平台。</p><p><strong>项目愿景：</strong></p><p>1、从最基础的 LLM 多工具调用、角色设定快速搭建自己的专属AI助手、到可以行业落地的词向量RAG、GraphRAG来本地化的管理行业内知识库；</p><p>2、从单一的智能体流水线，到复杂的智能体与智能体辐射状交互模式、环形交互模式的构建;</p><p>3、从个人用户需要的接入自己的社交APP(QQ、飞书、Discord)，到流媒体工作者需要的一站式LLM+TTS+ComfyUI工作流；</p><p>4、从普通学生所需要的第一个LLM应用的简单上手起步，到科研工作者们常用的各类参数调试接口，模型适配。</p><p>挺酷的，我们图片生成的工作流，一定有许多地方可以和视觉、语音LLM结合，比如：</p><p>上下文增强：通过LLM获取用户的意图和上下文，优化生成过程，使生成的图像更符合用户需求。</p><p>图像描述生成：使用视觉模型分析生成的图像并自动生成描述，帮助用户理解图像内容，适用于无障碍应用。</p><p>又如官方所说的：</p><blockquote><p>您可以将任何 ComfyUI 工作流封装到 LLM 工具节点中。您可以让您的 LLM 同时控制多个 ComfyUI 工作流。当您希望它完成某些任务时，它可以根据<strong>您的提示选择合适的 ComfyUI 工作流，完成您的任务，并将结果返回给您。</strong></p></blockquote><p>“<strong>您的提示选择合适的 ComfyUI 工作流</strong>”，这在我们Fastgpt、Coze或者Dify 中称为：问题分类或意图识别。</p><figure class=""><div class="rno-markdown-img-url" style="text-align:center"><div class="rno-markdown-img-url-inner" style="width:100%"><div style="width:100%"><img src="https://developer.qcloudimg.com/http-save/yehe-9836881/0d1fbdea9f792a3a9df4e560b3171711.png" alt="" style="width:100%"/></div></div></div></figure><p><strong>还有一些其他的，比如ComfyUI + GraphRAG，这些就是单纯使用ComfyUI前端实现GraphRAG。</strong></p><figure class=""><div class="rno-markdown-img-url" style="text-align:center"><div class="rno-markdown-img-url-inner" style="width:100%"><div style="width:100%"><img src="https://developer.qcloudimg.com/http-save/yehe-9836881/c1adac7862a8a7f267e7571e34ac08fd.png" alt="" style="width:100%"/></div></div></div></figure><p>总之，节点式工作流本身就是千变万化的，给ComfyUI引入LLM的支持，会让它更加适合千变万化的场景，创建更多复杂有趣的应用。</p><p>看看模型支持部分，基本上再配合One-API，市面上的模型都能支持，生产场景建议使用VLLM做模型加速部署，以API形式接入，而不是直接Hugging Face加载下载的模型，多说一句，ollama也不如Vllm，前者多卡部署大模型如70B的，推理会很慢，生成环境下基本不行。</p><figure class=""><div class="rno-markdown-img-url" style="text-align:center"><div class="rno-markdown-img-url-inner" style="width:100%"><div style="width:100%"><img src="https://developer.qcloudimg.com/http-save/yehe-9836881/f9ca2ad916d0429c9def0dd52f5bf1eb.png" alt="" style="width:100%"/></div></div></div></figure><p>这个项目包罗万象，一直在兼容各种东西的路上，简单的项目描述也要写上许多字才能尽善尽美。</p><figure class=""><div class="rno-markdown-img-url" style="text-align:center"><div class="rno-markdown-img-url-inner" style="width:100%"><div style="width:100%"><img src="https://developer.qcloudimg.com/http-save/yehe-9836881/f93d080b3649189f2e9563740d23284d.png" alt="" style="width:100%"/></div></div></div></figure><p>部署方面总共两步吧</p><figure class=""><div class="rno-markdown-img-url" style="text-align:center"><div class="rno-markdown-img-url-inner" style="width:100%"><div style="width:100%"><img src="https://developer.qcloudimg.com/http-save/yehe-9836881/e8ed4716c4bffe227ed01a39713c63c2.png" alt="" style="width:100%"/></div></div></div></figure><p>方法一下载较方便，可在ComfyUI中直接安装该插件，之后环境部署就是给你的ComfyUI再添加一些这个插件需要的环境。</p><p><strong>快速开始</strong></p><figure class=""><div class="rno-markdown-img-url" style="text-align:center"><div class="rno-markdown-img-url-inner" style="width:100%"><div style="width:100%"><img src="https://developer.qcloudimg.com/http-save/yehe-9836881/e9ef718225e66ac0406ba4d0363d8112.png" alt="" style="width:100%"/></div></div></div></figure><p>从教程上来看，上手并不难，但是实际上因为它覆盖的东西非常多，你需要深入的话，相应的你需要掌握很多东西，比如一些搜索引擎啊 searxng、neo4j KG、graphRAG、各种LLM的格式、llama.cpp 啊（这些我都弄过，往期文章有，但不全，有一些并没有去写） </p><figure class=""><div class="rno-markdown-img-url" style="text-align:center"><div class="rno-markdown-img-url-inner" style="width:100%"><div style="width:100%"><img src="https://developer.qcloudimg.com/http-save/yehe-9836881/c10cce6644291cf8efc99822fddb774b.png" alt="" style="width:100%"/></div></div></div></figure><p>具体你可以参考官方介绍。</p><p>此外，如果你不了解 ComfyUI，那么这三个链接会对你很有帮助：</p><h6 id="cu30o" name="%E6%96%B0%E6%89%8B%E5%85%A5%E9%97%A8%E2%80%94%E4%BB%8ESD%E8%BF%87%E5%BA%A6%E5%88%B0ComfyUI%EF%BC%9Ahttps://www.bilibili.com/video/BV1D7421N7xN/?p=1&spm_id_from=pageDriver"><strong>新手入门—从SD过度到ComfyUI：</strong>https://www.bilibili.com/video/BV1D7421N7xN/?p=1&spm_id_from=pageDriver</h6><h6 id="6gokh" name="%E7%A7%8B%E8%91%89aaaki-ComfyUI-Windows-%E6%95%B4%E5%90%88%E5%8C%85%EF%BC%9A-https://www.bilibili.com/video/BV1Ew411776J/?p=1&spm_id_from=pageDriver"><strong>秋葉aaaki ComfyUI Windows 整合包</strong>： https://www.bilibili.com/video/BV1Ew411776J/?p=1&spm_id_from=pageDriver</h6><h6 id="fhbj2" name="ComfyUI-%E5%AE%98%E6%96%B9Github-(%E4%B9%9F%E5%8C%85%E5%90%ABWindows%E4%B8%8B%E4%B8%80%E9%94%AE%E4%BD%BF%E7%94%A8%E5%8C%85)%EF%BC%9Ahttps://github.com/comfyanonymous/ComfyUI?tab=readme-ov-file#installing"><strong>ComfyUI 官方Github </strong>(也包含Windows下一键使用包)：https://github.com/comfyanonymous/ComfyUI?tab=readme-ov-file#installing</h6><p>🌟希望这篇文章对你有帮助，感谢阅读！如果你喜欢这系列文章请以 <strong>点赞 / 分享 / 在看 </strong>的方式告诉我，以便我用来评估创作方向。</p><p>👽Submission：kristjahmez06@gmail.com</p><p>参考链接： [1] github：https://github.com/heshengtao/comfyui_LLM_party</p></div></div></div><div class="mod-content__source"><div class="mod-content__source-inner"><div class="mod-content__source-title">本文参与 <a href="/developer/support-plan" target="_blank">腾讯云自媒体同步曝光计划</a>，分享自微信公众号。</div><div class="mod-content__source-desc">原始发表：2024-10-07，如有侵权请联系 <a href="mailto:cloudcommunity@tencent.com">cloudcommunity@tencent.com</a> 删除</div></div><div class="mod-content__source-qr"></div></div><div class="mod-statement-m"><div class="cdc-tag__list mod-content__tags" track-click=""><div class="cdc-tag" track-click="" track-exposure=""><a class="cdc-tag__inner" href="/developer/tag/17562" target="_blank">语音</a></div><div class="cdc-tag" track-click="" track-exposure=""><a class="cdc-tag__inner" href="/developer/tag/17917" target="_blank">LLM</a></div><div class="cdc-tag" track-click="" track-exposure=""><a 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src="https://qccommunity-1258344699.cos.ap-guangzhou.myqcloud.com/tc_player/releasev5.1.0/libs/hls.min.1.1.7.js"></script><script src="https://qccommunity-1258344699.cos.ap-guangzhou.myqcloud.com/tc_player/releasev5.1.0/tcplayer.v5.1.0.min.js"></script><script id="__NEXT_DATA__" type="application/json">{"props":{"isMobile":false,"isSupportWebp":false,"currentDomain":"cloud.tencent.com","baseUrl":"https://cloud.tencent.com","reqId":"Fa5ef_Tt2QrXI2fK5Uw71","query":{"articleId":"2472881"},"platform":"other","env":"production","__N_SSP":true,"pageProps":{"fallback":{"#url:\"/api/article/detail\",params:#articleId:2472881,,":{"articleData":{"articleId":2472881,"codeLineNum":0,"readingTime":492,"wordsNum":2256},"articleInfo":{"articleId":2472881,"channel":4,"commentNum":0,"content":{"blocks":[{"key":"2g17u","text":"🍹 Insight Daily 🪺","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"f4sd5","text":"Aitrainee | 公众号：AI进修生","type":"header-five","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{"text":"Aitrainee-%7C-%E5%85%AC%E4%BC%97%E5%8F%B7%EF%BC%9AAI%E8%BF%9B%E4%BF%AE%E7%94%9F"}},{"key":"b4d7g","text":"Hi，这里是Aitrainee，欢迎阅读本期新文章。","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"5tcua","text":"我们正在使用一些Agent平台如FastGPT和Dify，他们注重于快速生成文本内容，知识库问答，提供自定义能力和与现有系统的集成性。","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"c3v92","text":"同时，在AI绘画方面，我们原来使用SD，后来使用ComfyUI。虽然ComfyUI被广泛用于将文本转化为图像（文生图），但它实际上是一种生成式AI内容（AIGC）的工具，其功能不仅限于此。它还能够处理文本生成（文生文），因此可以实现多种内容的生成。","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"9olje","text":"Dify中也有提供ComfyUI的集成工具，他是调用Comfy UI的服务。","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"29tdo","text":"\ud83d","type":"atomic","depth":0,"inlineStyleRanges":[],"entityRanges":[{"offset":0,"length":1,"key":0}],"data":{}},{"key":"6ccrp","text":"所以，今天我们介绍ComfyUI LLM Party","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"akvg6","text":"\ud83d","type":"atomic","depth":0,"inlineStyleRanges":[],"entityRanges":[{"offset":0,"length":1,"key":1}],"data":{}},{"key":"b0ec5","text":"这个工具挺酷的，他专注于LLM集成进ComfyUI里面。旨在基于comfyui作为前端，开发一套完整的LLM工作流构建节点，让用户可以快速便捷地构建自己的LLM工作流，并轻松集成到现有的图片工作流中。","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"f2d1i","text":"该插件在 ComfyUI 中支持绝大多数大语言模型，兼容 OpenAI 格式的 API 调用，并结合 OneAPI 调用几乎所有 LLM API。支持的模型包括通义千问、智谱清言、DeepSeek 和 Kimi。","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"ap1bc","text":"额外功能有：支持 Ollama 本地模型，模型链节点选项（LLM、VLM-GGUF、LLM-GGUF），以及 VLM 模型的图像识别和提示词反推。","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"uvt6","text":"实用工具包括 OpenAI 语音识别与合成、Markdown 转 HTML、HTML 转图片，以及通过飞书机器人发送消息到多个平台。","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"63mcl","text":"项目愿景：","type":"unstyled","depth":0,"inlineStyleRanges":[{"offset":0,"length":5,"style":"BOLD"}],"entityRanges":[],"data":{}},{"key":"79chk","text":"1、从最基础的 LLM 多工具调用、角色设定快速搭建自己的专属AI助手、到可以行业落地的词向量RAG、GraphRAG来本地化的管理行业内知识库；","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"f52ul","text":"2、从单一的智能体流水线，到复杂的智能体与智能体辐射状交互模式、环形交互模式的构建;","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"ee38t","text":"3、从个人用户需要的接入自己的社交APP(QQ、飞书、Discord)，到流媒体工作者需要的一站式LLM+TTS+ComfyUI工作流；","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"5na88","text":"4、从普通学生所需要的第一个LLM应用的简单上手起步，到科研工作者们常用的各类参数调试接口，模型适配。","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"dfb7o","text":"挺酷的，我们图片生成的工作流，一定有许多地方可以和视觉、语音LLM结合，比如：","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"d11vq","text":"上下文增强：通过LLM获取用户的意图和上下文，优化生成过程，使生成的图像更符合用户需求。","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"6q1hi","text":"图像描述生成：使用视觉模型分析生成的图像并自动生成描述，帮助用户理解图像内容，适用于无障碍应用。","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"4vu37","text":"又如官方所说的：","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"77l4i","text":"您可以将任何 ComfyUI 工作流封装到 LLM 工具节点中。您可以让您的 LLM 同时控制多个 ComfyUI 工作流。当您希望它完成某些任务时，它可以根据您的提示选择合适的 ComfyUI 工作流，完成您的任务，并将结果返回给您。","type":"blockquote","depth":0,"inlineStyleRanges":[{"offset":80,"length":38,"style":"BOLD"}],"entityRanges":[],"data":{}},{"key":"c60hd","text":"“您的提示选择合适的 ComfyUI 工作流”，这在我们Fastgpt、Coze或者Dify 中称为：问题分类或意图识别。","type":"unstyled","depth":0,"inlineStyleRanges":[{"offset":1,"length":21,"style":"BOLD"}],"entityRanges":[],"data":{}},{"key":"4ubb3","text":"\ud83d","type":"atomic","depth":0,"inlineStyleRanges":[],"entityRanges":[{"offset":0,"length":1,"key":2}],"data":{}},{"key":"e1urg","text":"还有一些其他的，比如ComfyUI + GraphRAG，这些就是单纯使用ComfyUI前端实现GraphRAG。","type":"unstyled","depth":0,"inlineStyleRanges":[{"offset":0,"length":57,"style":"BOLD"}],"entityRanges":[],"data":{}},{"key":"38oog","text":"\ud83d","type":"atomic","depth":0,"inlineStyleRanges":[],"entityRanges":[{"offset":0,"length":1,"key":3}],"data":{}},{"key":"27ps3","text":"总之，节点式工作流本身就是千变万化的，给ComfyUI引入LLM的支持，会让它更加适合千变万化的场景，创建更多复杂有趣的应用。","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"1h7mn","text":"看看模型支持部分，基本上再配合One-API，市面上的模型都能支持，生产场景建议使用VLLM做模型加速部署，以API形式接入，而不是直接Hugging Face加载下载的模型，多说一句，ollama也不如Vllm，前者多卡部署大模型如70B的，推理会很慢，生成环境下基本不行。","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"ta7r","text":"\ud83d","type":"atomic","depth":0,"inlineStyleRanges":[],"entityRanges":[{"offset":0,"length":1,"key":4}],"data":{}},{"key":"b9u6i","text":"这个项目包罗万象，一直在兼容各种东西的路上，简单的项目描述也要写上许多字才能尽善尽美。","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"cdmu3","text":"\ud83d","type":"atomic","depth":0,"inlineStyleRanges":[],"entityRanges":[{"offset":0,"length":1,"key":5}],"data":{}},{"key":"fco1b","text":"部署方面总共两步吧","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"1kqgv","text":"\ud83d","type":"atomic","depth":0,"inlineStyleRanges":[],"entityRanges":[{"offset":0,"length":1,"key":6}],"data":{}},{"key":"29nke","text":"方法一下载较方便，可在ComfyUI中直接安装该插件，之后环境部署就是给你的ComfyUI再添加一些这个插件需要的环境。","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"1pe2o","text":"快速开始","type":"unstyled","depth":0,"inlineStyleRanges":[{"offset":0,"length":4,"style":"BOLD"}],"entityRanges":[],"data":{}},{"key":"5i0gd","text":"\ud83d","type":"atomic","depth":0,"inlineStyleRanges":[],"entityRanges":[{"offset":0,"length":1,"key":7}],"data":{}},{"key":"27uof","text":"从教程上来看，上手并不难，但是实际上因为它覆盖的东西非常多，你需要深入的话，相应的你需要掌握很多东西，比如一些搜索引擎啊 searxng、neo4j KG、graphRAG、各种LLM的格式、llama.cpp 啊（这些我都弄过，往期文章有，但不全，有一些并没有去写）\n","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"9dqcp","text":"\ud83d","type":"atomic","depth":0,"inlineStyleRanges":[],"entityRanges":[{"offset":0,"length":1,"key":8}],"data":{}},{"key":"d4a43","text":"具体你可以参考官方介绍。","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"2tn7m","text":"此外，如果你不了解 ComfyUI，那么这三个链接会对你很有帮助：","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"cu30o","text":"新手入门—从SD过度到ComfyUI：https://www.bilibili.com/video/BV1D7421N7xN/?p=1\u0026spm_id_from=pageDriver","type":"header-five","depth":0,"inlineStyleRanges":[{"offset":0,"length":19,"style":"BOLD"}],"entityRanges":[],"data":{"text":"%E6%96%B0%E6%89%8B%E5%85%A5%E9%97%A8%E2%80%94%E4%BB%8ESD%E8%BF%87%E5%BA%A6%E5%88%B0ComfyUI%EF%BC%9Ahttps://www.bilibili.com/video/BV1D7421N7xN/?p=1\u0026spm_id_from=pageDriver"}},{"key":"6gokh","text":"秋葉aaaki ComfyUI Windows 整合包： https://www.bilibili.com/video/BV1Ew411776J/?p=1\u0026spm_id_from=pageDriver","type":"header-five","depth":0,"inlineStyleRanges":[{"offset":0,"length":27,"style":"BOLD"}],"entityRanges":[],"data":{"text":"%E7%A7%8B%E8%91%89aaaki-ComfyUI-Windows-%E6%95%B4%E5%90%88%E5%8C%85%EF%BC%9A-https://www.bilibili.com/video/BV1Ew411776J/?p=1\u0026spm_id_from=pageDriver"}},{"key":"fhbj2","text":"ComfyUI 官方Github (也包含Windows下一键使用包)：https://github.com/comfyanonymous/ComfyUI?tab=readme-ov-file#installing","type":"header-five","depth":0,"inlineStyleRanges":[{"offset":0,"length":17,"style":"BOLD"}],"entityRanges":[],"data":{"text":"ComfyUI-%E5%AE%98%E6%96%B9Github-(%E4%B9%9F%E5%8C%85%E5%90%ABWindows%E4%B8%8B%E4%B8%80%E9%94%AE%E4%BD%BF%E7%94%A8%E5%8C%85)%EF%BC%9Ahttps://github.com/comfyanonymous/ComfyUI?tab=readme-ov-file#installing"}},{"key":"4q07t","text":"🌟希望这篇文章对你有帮助，感谢阅读！如果你喜欢这系列文章请以点赞 / 分享 / 在看的方式告诉我，以便我用来评估创作方向。","type":"unstyled","depth":0,"inlineStyleRanges":[{"offset":31,"length":13,"style":"BOLD"}],"entityRanges":[],"data":{}},{"key":"3h7d3","text":"👽Submission：kristjahmez06@gmail.com","type":"unstyled","depth":0,"inlineStyleRanges":[],"entityRanges":[],"data":{}},{"key":"eaatj","text":"参考链接：\n[1] 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多工具调用、角色设定快速搭建自己的专属AI助手、到可以行业落地的词向量RAG、GraphRAG来本地化的管理行业内知识库；\n2、从单一的智能体流水线，到复杂的智能体与智能体辐射状交互模式、环形交互模式的构建;\n3、从个人用户需要的接入自己的社交APP(QQ、飞书、Discord)，到流媒体工作者需要的一站式LLM+TTS+ComfyUI工作流；\n4、从普通学生所需要的第一个LLM应用的简单上手起步，到科研工作者们常用的各类参数调试接口，模型适配。\n挺酷的，我们图片生成的工作流，一定有许多地方可以和视觉、语音LLM结合，比如：\n上下文增强：通过LLM获取用户的意图和上下文，优化生成过程，使生成的图像更符合用户需求。\n图像描述生成：使用视觉模型分析生成的图像并自动生成描述，帮助用户理解图像内容，适用于无障碍应用。\n又如官方所说的：\n您可以将任何 ComfyUI 工作流封装到 LLM 工具节点中。您可以让您的 LLM 同时控制多个 ComfyUI 工作流。当您希望它完成某些任务时，它可以根据您的提示选择合适的 ComfyUI 工作流，完成您的任务，并将结果返回给您。\n“您的提示选择合适的 ComfyUI 工作流”，这在我们Fastgpt、Coze或者Dify 中称为：问题分类或意图识别。\n还有一些其他的，比如ComfyUI + GraphRAG，这些就是单纯使用ComfyUI前端实现GraphRAG。\n总之，节点式工作流本身就是千变万化的，给ComfyUI引入LLM的支持，会让它更加适合千变万化的场景，创建更多复杂有趣的应用。\n看看模型支持部分，基本上再配合One-API，市面上的模型都能支持，生产场景建议使用VLLM做模型加速部署，以API形式接入，而不是直接Hugging Face加载下载的模型，多说一句，ollama也不如Vllm，前者多卡部署大模型如70B的，推理会很慢，生成环境下基本不行。\n这个项目包罗万象，一直在兼容各种东西的路上，简单的项目描述也要写上许多字才能尽善尽美。\n部署方面总共两步吧\n方法一下载较方便，可在ComfyUI中直接安装该插件，之后环境部署就是给你的ComfyUI再添加一些这个插件需要的环境。\n快速开始\n从教程上来看，上手并不难，但是实际上因为它覆盖的东西非常多，你需要深入的话，相应的你需要掌握很多东西，比如一些搜索引擎啊 searxng、neo4j KG、graphRAG、各种LLM的格式、llama.cpp 啊（这些我都弄过，往期文章有，但不全，有一些并没有去写）\n\n具体你可以参考官方介绍。\n此外，如果你不了解 ComfyUI，那么这三个链接会对你很有帮助：\n新手入门—从SD过度到ComfyUI：https://www.bilibili.com/video/BV1D7421N7xN/?p=1\u0026spm_id_from=pageDriver\n秋葉aaaki ComfyUI Windows 整合包： https://www.bilibili.com/video/BV1Ew411776J/?p=1\u0026spm_id_from=pageDriver\nComfyUI 官方Github (也包含Windows下一键使用包)：https://github.com/comfyanonymous/ComfyUI?tab=readme-ov-file#installing\n🌟希望这篇文章对你有帮助，感谢阅读！如果你喜欢这系列文章请以点赞 / 分享 / 在看的方式告诉我，以便我用来评估创作方向。\n👽Submission：kristjahmez06@gmail.com\n参考链接：\n[1] 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