id: 923f65c5806d42c08d64a9aac69a6866
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title_diff: "[{\"diffs\":[[1,\"无需GPU本地轻松运行AI模型的开源项目LocalAI\"]],\"start1\":0,\"start2\":0,\"length1\":0,\"length2\":27}]"
body_diff: "[{\"diffs\":[[1,\"<html>\\\r\\\n<head>\\\r\\\n  <title>无需GPU本地轻松运行AI模型的开源项目LocalAI</title>\\\r\\\n  <basefont face=\\\"微软雅黑\\\" size=\\\"2\\\" />\\\r\\\n  <meta http-equiv=\\\"Content-Type\\\" content=\\\"text/html;charset=utf-8\\\" />\\\r\\\n  <meta name=\\\"exporter-version\\\" content=\\\"YXBJ Windows/608924 (zh-CN, DDL); Windows/10.0.0 (Win64); EDAMVersion=V2;\\\"/>\\\r\\\n  <meta name=\\\"content-class\\\" content=\\\"yinxiang.peso.superNote\\\"/>\\\r\\\n  <meta name=\\\"application-data:yinxiang.noteLayout\\\" content=\\\"{\\\"lineSpace\\\":\\\"recommend\\\",\\\"paragraphSpace\\\":\\\"recommend\\\"}\\\"/>\\\r\\\n  <style>\\\r\\\n\\tbody, td {\\\r\\\n\\t  font-family: 微软雅黑;\\\r\\\n\\t  font-size: 12pt;\\\r\\\n\\t}\\\r\\\n  </style>\\\r\\\n</head>\\\r\\\n<body>\\\r\\\n<a name=\\\"37228\\\"></a>\\\r\\\n<h1>无需GPU本地轻松运行AI模型的开源项目LocalAI</h1>\\\r\\\n\\\r\\\n<div><span style=\\\"margin:0px;\\\"><div style=\\\"padding:8px 0px;margin:8px auto;max-width:700px;\\\"> <div><span></span></div>\\\n<p></p>\\\n<div style=\\\"--en-blockquote:true;box-sizing: border-box; padding-left: 19px; padding-top: 6px; padding-bottom: 6px; border-left: 3px solid #b4c0cc; background-position: initial initial; background-repeat: initial initial; margin-top: 6px\\\"><div>原文链接: <a href=\\\"http://mp.weixin.qq.com/s?__biz=MzAwNjE5MTE3Mw==&amp;mid=2449816814&amp;idx=1&amp;sn=a764547eb2b843c17e95bc3aa901f8cc&amp;chksm=8d12da23552d9b70dd5288c7bd54e9012310961becd1778e950d35fba9202375ed4905eccb8a&amp;mpshare=1&amp;scene=1&amp;srcid=0117aE2Dq4NxvVeiUZ0exYLx&amp;sharer_shareinfo=85427244b8b9c2adae0b2f5f48d71c2c&amp;sharer_shareinfo_first=85427244b8b9c2adae0b2f5f48d71c2c#rd\\\"><span>http://mp.weixin.qq.com/s?__biz=MzAwNjE5MTE3Mw==&amp;mid=2449816...</span></a></div></div>\\\n<p></p>\\\n<div><span></span></div>\\\n<div style=\\\"-webkit-tap-highlight-color:transparent;\\\"><div style=\\\"-webkit-tap-highlight-color:transparent;\\\"><div style=\\\"-webkit-tap-highlight-color:transparent;\\\"><h1 style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"> 无需GPU本地轻松运行AI模型的开源项目LocalAI </h1><div style=\\\"-webkit-tap-highlight-color:transparent;\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\"> 菲宇 </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><a style=\\\"-webkit-tap-highlight-color:transparent;position:relative\\\"> Python与Django学习 </a></span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><em style=\\\"-webkit-tap-highlight-color:transparent\\\"></em></span></div><div style=\\\"-webkit-tap-highlight-color:transparent;\\\"><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">开发中经常遇到这样的困扰：想用AI提升工作效率，但担心数据泄露风险；想部署私有AI服务，但被高昂的硬件成本劝退。LocalAI提供了一个绝妙的解决方案。</span></p><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">LocalAI 是免费的开源 OpenAI 替代品。LocalAI充当与 OpenAI 兼容的直接替代 REST API（Elevenlabs、Anthropic...本地 AI 推理的 API 规范。它允许您在本地或本地使用消费级硬件运行LLM、生成图像、音频，支持多个型号CPU，不需要 GPU。</span></p><div style=\\\"-webkit-tap-highlight-color:transparent;text-align:center;\\\"><img src=\\\"无需GPU本地轻松运行AI模型的开源项目LocalAI_files/640.png\\\" type=\\\"image/png\\\" data-filename=\\\"640.png\\\" style=\\\"--en-marks:%7B%22align%22%3A%22center%22%7D;-webkit-tap-highlight-color:transparent\\\"/></div><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent;font-weight:bold\\\">核心优势</span></span></p><ul style=\\\"-webkit-tap-highlight-color:transparent;margin:0;list-style-type:disc\\\"><li style=\\\"-webkit-tap-highlight-color:transparent\\\"><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">    支持CPU部署，无需昂贵GPU</span></p></li><li style=\\\"-webkit-tap-highlight-color:transparent\\\"><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">    完整兼容OpenAI API</span></p></li><li style=\\\"-webkit-tap-highlight-color:transparent\\\"><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">    数据本地处理，安全可控</span></p></li><li style=\\\"-webkit-tap-highlight-color:transparent\\\"><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">    支持多种开源模型，扩展性强</span></p></li></ul><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">LocalAI的实现特别巧妙。它把开源语言模型进行了量化压缩，通过ggml、gguf等框架优化，使得模型能在普通CPU上高效运行。我测试后发现，在16GB内存的笔记本上就能流畅运行7B参数量的模型。</span></p><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">除了文本处理，LocalAI还支持以下功能</span></p><ul style=\\\"-webkit-tap-highlight-color:transparent;margin:0;list-style-type:square\\\"><li style=\\\"-webkit-tap-highlight-color:transparent\\\"><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">文本转语音：集成了多个开源语音模型，可以生成自然的语音输出。</span></p></li><li style=\\\"-webkit-tap-highlight-color:transparent\\\"><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">图像生成：支持Stable Diffusion等模型，能够根据文本描述生成图像。</span></p></li><li style=\\\"-webkit-tap-highlight-color:transparent\\\"><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">多模态处理：可以同时处理文本、图像、语音等多种数据类型。</span></p></li></ul><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent;font-weight:bold\\\">部署建议</span></span></p><ul style=\\\"-webkit-tap-highlight-color:transparent;margin:0;list-style-type:disc\\\"><li style=\\\"-webkit-tap-highlight-color:transparent\\\"><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">服务器选型：建议使用16GB以上内存，性能越好响应速度越快。</span></p></li><li style=\\\"-webkit-tap-highlight-color:transparent\\\"><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">模型选择：根据实际需求选择合适大小的模型，不要贪大求全。</span></p></li><li style=\\\"-webkit-tap-highlight-color:transparent\\\"><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">网络配置：如果是内网部署，注意端口开放和访问控制。</span></p></li><li style=\\\"-webkit-tap-highlight-color:transparent\\\"><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">日志监控：建议配置完整的日志系统，方便问题排查。</span></p></li></ul><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">运行安装程序脚本：</span></p><div style=\\\"-webkit-tap-highlight-color:transparent;\\\"><pre style=\\\"-webkit-tap-highlight-color:transparent\\\"><div style=\\\"--en-codeblock:true;--en-meta:{&quot;title&quot;:&quot;&quot;,&quot;lang&quot;:&quot;Plain Text&quot;,&quot;theme&quot;:&quot;default&quot;,&quot;showLine&quot;:true,&quot;lineWrap&quot;:true};box-sizing: border-box; padding: 8px; font-family: Monaco, Menlo, Consolas, &quot;Courier New&quot;, monospace; font-size: 12px; color: rgb(51, 51, 51); border-top-left-radius: 4px; border-top-right-radius: 4px; border-bottom-right-radius: 4px; border-bottom-left-radius: 4px; background-color: rgb(251, 250, 248); border: 1px solid rgba(0, 0, 0, 0.14902); background-position: initial initial; background-repeat: initial initial; margin-top: 6px;\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">curl </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">https</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">:</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">//localai.io/install.sh | sh</span></span></div></pre></div><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">或使用 docker 运行：</span></p><div style=\\\"-webkit-tap-highlight-color:transparent;\\\"><pre style=\\\"-webkit-tap-highlight-color:transparent\\\"><div style=\\\"--en-codeblock:true;--en-meta:{&quot;title&quot;:&quot;&quot;,&quot;lang&quot;:&quot;Plain Text&quot;,&quot;theme&quot;:&quot;default&quot;,&quot;showLine&quot;:true,&quot;lineWrap&quot;:true};box-sizing: border-box; padding: 8px; font-family: Monaco, Menlo, Consolas, &quot;Courier New&quot;, monospace; font-size: 12px; color: rgb(51, 51, 51); border-top-left-radius: 4px; border-top-right-radius: 4px; border-bottom-right-radius: 4px; border-bottom-left-radius: 4px; background-color: rgb(251, 250, 248); border: 1px solid rgba(0, 0, 0, 0.14902); background-position: initial initial; background-repeat: initial initial; margin-top: 6px;\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\"># CPU </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">only</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"> image:</span></span><div><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">docker run </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">-</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">ti </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">--name local-ai -p 8080:8080 localai/localai:latest-cpu</span></span></div><div><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\"># Nvidia GPU:</span></span></div><div><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12</span></span></div><div><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\"># CPU and GPU image (bigger size):</span></span></div><div><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">docker run -ti --name local-ai -p 8080:8080 localai/localai:latest</span></span></div><div><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\"># AIO images (it will pre-download a set of models ready for use, see https://localai.io/basics/container/)</span></span></div><div><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-cpu</span></span></div></div></pre></div><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">要加载模型：</span></p><div style=\\\"-webkit-tap-highlight-color:transparent;\\\"><pre style=\\\"-webkit-tap-highlight-color:transparent\\\"><div style=\\\"--en-codeblock:true;--en-meta:{&quot;title&quot;:&quot;&quot;,&quot;lang&quot;:&quot;Plain Text&quot;,&quot;theme&quot;:&quot;default&quot;,&quot;showLine&quot;:true,&quot;lineWrap&quot;:true};box-sizing: border-box; padding: 8px; font-family: Monaco, Menlo, Consolas, &quot;Courier New&quot;, monospace; font-size: 12px; color: rgb(51, 51, 51); border-top-left-radius: 4px; border-top-right-radius: 4px; border-bottom-right-radius: 4px; border-bottom-left-radius: 4px; background-color: rgb(251, 250, 248); border: 1px solid rgba(0, 0, 0, 0.14902); background-position: initial initial; background-repeat: initial initial; margin-top: 6px;\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\"># </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">From</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"> the model gallery (see available models </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">with</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"> `</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">local</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">-</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">ai models list`, </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">in</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"> the WebUI </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">from</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"> the model tab, </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">or</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"> visiting https:</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">//</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">models.localai.io)</span></span><div><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">local</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">-</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">ai run llama</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">-3.2-1</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">b</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">-</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">instruct:q4_k_m</span></span></div><div><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\"># </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">Start</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"> LocalAI </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">with</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"> the phi</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">-2</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"> model directly </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">from</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"> huggingface</span></span></div><div><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">local</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">-</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">ai run huggingface:</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">//</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">TheBloke</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">/</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">phi</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">-2</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">-</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">GGUF</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">/</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">phi</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">-2.</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">Q8_0.gguf</span></span></div><div><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\"># Install </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">and</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"> run a model </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">from</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"> the Ollama OCI registry</span></span></div><div><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">local</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">-</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">ai run ollama:</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">//</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">gemma:</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">2</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">b</span></span></div><div><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\"># Run a model </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">from</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"> a configuration file</span></span></div><div><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">local</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">-</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">ai run https:</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">//</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">gist.githubusercontent.com</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">/</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">...</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">/</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">phi</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">-2.</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">yaml</span></span></div><div><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\"># Install </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">and</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"> run a model </span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">from</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"> a standard OCI registry (e.g., Docker Hub)</span></span></div><div><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">local</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">-</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">ai run oci:</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">//</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">localai</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">/</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">phi</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">-2</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">:latest</span></span></div></div></pre></div><p style=\\\"-webkit-tap-highlight-color:transparent;margin:0\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">项目地址：</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\"><span style=\\\"-webkit-tap-highlight-color:transparent\\\">https</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">:</span><span style=\\\"-webkit-tap-highlight-color:transparent\\\">//github.com/mudler/LocalAI</span></span></p></div></div></div></div></div></span>\\\n</div></body></html>\\u0000\"]],\"start1\":0,\"start2\":0,\"length1\":0,\"length2\":18258}]"
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