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外部调用 FastGPT</button><div class=sidebar-submenu><ul><li><a class=sidebar-nested-link href=https://doc.tryfastgpt.ai/docs/use-cases/external-integration/openapi/>通过 API 访问应用</a></li><li><a class=sidebar-nested-link href=https://doc.tryfastgpt.ai/docs/use-cases/external-integration/feishu/>接入飞书机器人教程</a></li><li><a class=sidebar-nested-link href=https://doc.tryfastgpt.ai/docs/use-cases/external-integration/dingtalk/>接入钉钉机器人教程</a></li><li><a class=sidebar-nested-link href=https://doc.tryfastgpt.ai/docs/use-cases/external-integration/official_account/>接入微信公众号教程</a></li><li><a class=sidebar-nested-link href=https://doc.tryfastgpt.ai/docs/use-cases/external-integration/onwechat/>对接 chatgpt-on-wechat</a></li><li><a class=sidebar-nested-link href=https://doc.tryfastgpt.ai/docs/use-cases/external-integration/wechat/>接入微信和企业微信</a></li><li><a class=sidebar-nested-link href=https://doc.tryfastgpt.ai/docs/use-cases/external-integration/iframe_integration/>iframe 接入</a></li></ul></div></li><li class="sidebar-dropdown nested"><button class=btn>
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Table of Contents</button><nav id=toc-mobile><ul class=dropdown-menu><li><ul><li><a href=#安装-ollama>安装 Ollama</a><ul><li><a href=#docker-安装推荐>Docker 安装（推荐）</a></li><li><a href=#主机安装>主机安装</a></li><li><a href=#ollama-拉取模型镜像>Ollama 拉取模型镜像</a></li><li><a href=#测试通信>测试通信</a></li></ul></li><li><a href=#将-ollama-接入-fastgpt>将 Ollama 接入 FastGPT</a><ul><li><a href=#1-查看-ollama-所拥有的模型>1. 查看 Ollama 所拥有的模型</a></li><li><a href=#2-ai-proxy-接入>2. AI Proxy 接入</a></li><li><a href=#3-oneapi-接入>3. OneAPI 接入</a></li><li><a href=#4-直接接入>4. 直接接入</a></li><li><a href=#5-模型添加和使用>5. 模型添加和使用</a></li><li><a href=#6-补充>6. 补充</a></li></ul></li></ul></li></ul></nav></div><div class="docs-content col-12 col-xl-9 mt-0"><div class="mb-0 d-flex"><i class="material-icons title-icon me-2">api</i><h1 class="content-title mb-0">使用 Ollama 接入本地模型</h1></div><p class="lead mb-3">采用 Ollama 部署自己的模型</p><div id=content class=main-content data-bs-spy=scroll data-bs-root-margin="0px 0px -65%" data-bs-target=#toc-mobile><div data-prismjs-copy data-prismjs-copy-success data-prismjs-copy-error><p><a href=https://ollama.com/ rel=external target=_blank>Ollama<svg width="16" height="16" viewBox="0 0 24 24" xmlns="http://www.w3.org/2000/svg"><path fill="currentcolor" d="M14 5c-.552.0-1-.448-1-1s.448-1 1-1h6c.552.0 1 .448 1 1v6c0 .552-.448 1-1 1s-1-.448-1-1V6.414l-7.293 7.293c-.391.39-1.024.39-1.414.0-.391-.391-.391-1.024.0-1.414L17.586 5H14zM5 7c-.552.0-1 .448-1 1v11c0 .552.448 1 1 1h11c.552.0 1-.448 1-1v-4.563c0-.552.448-1 1-1s1 .448 1 1V19c0 1.657-1.343 3-3 3H5c-1.657.0-3-1.343-3-3V8c0-1.657 1.343-3 3-3h4.563c.552.0 1 .448 1 1s-.448 1-1 1H5z"/></svg></a> 是一个开源的AI大模型部署工具，专注于简化大语言模型的部署和使用，支持一键下载和运行各种大模型。</p><h2 id=安装-ollama>安装 Ollama <a href=#%e5%ae%89%e8%a3%85-ollama class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h2><p>Ollama 本身支持多种安装方式，但是推荐使用 Docker 拉取镜像部署。如果是个人设备上安装了 Ollama 后续需要解决如何让 Docker 中 FastGPT 容器访问宿主机 Ollama的问题，较为麻烦。</p><h3 id=docker-安装推荐>Docker 安装（推荐） <a href=#docker-%e5%ae%89%e8%a3%85%e6%8e%a8%e8%8d%90 class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h3><p>你可以使用 Ollama 官方的 Docker 镜像来一键安装和启动 Ollama 服务（确保你的机器上已经安装了 Docker），命令如下：</p><div class=prism-codeblock><pre id=d1f4a00 class=language-bash>
|
||
<code>docker pull ollama/ollama
|
||
docker run --rm -d --name ollama -p 11434:11434 ollama/ollama</code>
|
||
</pre></div><p>如果你的 FastGPT 是在 Docker 中进行部署的，建议在拉取 Ollama 镜像时保证和 FastGPT 镜像处于同一网络，否则可能出现 FastGPT 无法访问的问题，命令如下：</p><div class=prism-codeblock><pre id=f71a506 class=language-bash>
|
||
<code>docker run --rm -d --name ollama --network （你的 Fastgpt 容器所在网络） -p 11434:11434 ollama/ollama</code>
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||
</pre></div><h3 id=主机安装>主机安装 <a href=#%e4%b8%bb%e6%9c%ba%e5%ae%89%e8%a3%85 class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h3><p>如果你不想使用 Docker ，也可以采用主机安装，以下是主机安装的一些方式。</p><h4 id=macos>MacOS <a href=#macos class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h4><p>如果你使用的是 macOS，且系统中已经安装了 Homebrew 包管理器，可通过以下命令来安装 Ollama：</p><div class=prism-codeblock><pre id=0a7179b class=language-bash>
|
||
<code>brew install ollama
|
||
ollama serve #安装完成后，使用该命令启动服务</code>
|
||
</pre></div><h4 id=linux>Linux <a href=#linux class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h4><p>在 Linux 系统上，你可以借助包管理器来安装 Ollama。以 Ubuntu 为例，在终端执行以下命令：</p><div class=prism-codeblock><pre id=cc94cbb class=language-bash>
|
||
<code>curl https://ollama.com/install.sh | sh #此命令会从官方网站下载并执行安装脚本。
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ollama serve #安装完成后，同样启动服务</code>
|
||
</pre></div><h4 id=windows>Windows <a href=#windows class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h4><p>在 Windows 系统中，你可以从 Ollama 官方网站 下载 Windows 版本的安装程序。下载完成后，运行安装程序，按照安装向导的提示完成安装。安装完成后，在命令提示符或 PowerShell 中启动服务：</p><div class=prism-codeblock><pre id=f9708e1 class=language-bash>
|
||
<code>ollama serve #安装完成并启动服务后，你可以在浏览器中访问 http://localhost:11434 来验证 Ollama 是否安装成功。</code>
|
||
</pre></div><h4 id=补充说明>补充说明 <a href=#%e8%a1%a5%e5%85%85%e8%af%b4%e6%98%8e class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h4><p>如果你是采用的主机应用 Ollama 而不是镜像，需要确保你的 Ollama 可以监听0.0.0.0。</p><h5 id=1-linxu-系统>1. Linxu 系统 <a href=#1-linxu-%e7%b3%bb%e7%bb%9f class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h5><p>如果 Ollama 作为 systemd 服务运行，打开终端，编辑 Ollama 的 systemd 服务文件，使用命令sudo systemctl edit ollama.service，在[Service]部分添加Environment=“OLLAMA_HOST=0.0.0.0”。保存并退出编辑器，然后执行sudo systemctl daemon - reload和sudo systemctl restart ollama使配置生效。</p><h5 id=2-macos-系统>2. MacOS 系统 <a href=#2-macos-%e7%b3%bb%e7%bb%9f class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h5><p>打开终端，使用launchctl setenv ollama_host “0.0.0.0"命令设置环境变量，然后重启 Ollama 应用程序以使更改生效。</p><h5 id=3-windows-系统>3. Windows 系统 <a href=#3-windows-%e7%b3%bb%e7%bb%9f class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h5><p>通过 “开始” 菜单或搜索栏打开 “编辑系统环境变量”，在 “系统属性” 窗口中点击 “环境变量”，在 “系统变量” 部分点击 “新建”，创建一个名为OLLAMA_HOST的变量，变量值设置为0.0.0.0，点击 “确定” 保存更改，最后从 “开始” 菜单重启 Ollama 应用程序。</p><h3 id=ollama-拉取模型镜像>Ollama 拉取模型镜像 <a href=#ollama-%e6%8b%89%e5%8f%96%e6%a8%a1%e5%9e%8b%e9%95%9c%e5%83%8f class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h3><p>在安装后 Ollama 后，本地是没有模型镜像的，需要自己去拉取 Ollama 中的模型镜像。命令如下：</p><div class=prism-codeblock><pre id=c725436 class=language-bash>
|
||
<code># Docker 部署需要先进容器，命令为： docker exec -it < Ollama 容器名 > /bin/sh
|
||
ollama pull <模型名></code>
|
||
</pre></div><p><img src=https://cdn.jsdelivr.net/gh/yangchuansheng/fastgpt-imgs@main/imgs/Ollama-pull.png alt loading=lazy class=medium-zoom-image></p><h3 id=测试通信>测试通信 <a href=#%e6%b5%8b%e8%af%95%e9%80%9a%e4%bf%a1 class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h3><p>在安装完成后，需要进行检测测试，首先进入 FastGPT 所在的容器，尝试访问自己的 Ollama ，命令如下：</p><div class=prism-codeblock><pre id=e834756 class=language-bash>
|
||
<code>docker exec -it < FastGPT 所在的容器名 > /bin/sh
|
||
curl http://XXX.XXX.XXX.XXX:11434 #容器部署地址为“http://<容器名>:<端口>”,主机安装地址为"http://<主机IP>:<端口>"，主机IP不可为localhost</code>
|
||
</pre></div><p>看到访问显示自己的 Ollama 服务以及启动，说明可以正常通信。</p><h2 id=将-ollama-接入-fastgpt>将 Ollama 接入 FastGPT <a href=#%e5%b0%86-ollama-%e6%8e%a5%e5%85%a5-fastgpt class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h2><h3 id=1-查看-ollama-所拥有的模型>1. 查看 Ollama 所拥有的模型 <a href=#1-%e6%9f%a5%e7%9c%8b-ollama-%e6%89%80%e6%8b%a5%e6%9c%89%e7%9a%84%e6%a8%a1%e5%9e%8b class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h3><p>首先采用下述命令查看 Ollama 中所拥有的模型，</p><div class=prism-codeblock><pre id=05110b0 class=language-bash>
|
||
<code># Docker 部署 Ollama，需要此命令 docker exec -it < Ollama 容器名 > /bin/sh
|
||
ollama ls</code>
|
||
</pre></div><p><img src=https://cdn.jsdelivr.net/gh/yangchuansheng/fastgpt-imgs@main/imgs/Ollama-models1.png alt loading=lazy class=medium-zoom-image></p><h3 id=2-ai-proxy-接入>2. AI Proxy 接入 <a href=#2-ai-proxy-%e6%8e%a5%e5%85%a5 class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h3><p>如果你采用的是 FastGPT 中的默认配置文件部署<a data-bs-delay='{"hide":300,"show":550}' data-bs-html=true data-bs-title="<a href='/docs/development/docker/'><p>开发与部署指南</p><strong>Docker Compose 快速部署</strong><br>使用 Docker Compose 快速部署 FastGPT</a>" data-bs-toggle=tooltip href=/docs/development/docker/>这里</a>，即默认采用 AI Proxy 进行启动。</p><p><img src=https://cdn.jsdelivr.net/gh/yangchuansheng/fastgpt-imgs@main/imgs/Ollama-aiproxy1.png alt loading=lazy class=medium-zoom-image></p><p>以及在确保你的 FastGPT 可以直接访问 Ollama 容器的情况下，无法访问，参考上文<a href=/docs/development/custom-models/ollama/#安装-ollama>点此跳转</a>的安装过程，检测是不是主机不能监测0.0.0.0，或者容器不在同一个网络。</p><p><img src=https://cdn.jsdelivr.net/gh/yangchuansheng/fastgpt-imgs@main/imgs/Ollama-aiproxy2.png alt loading=lazy class=medium-zoom-image></p><p>在 FastGPT 中点击账号->模型提供商->模型配置->新增模型，添加自己的模型即可，添加模型时需要保证模型ID和 OneAPI 中的模型名称一致。详细参考<a data-bs-delay='{"hide":300,"show":550}' data-bs-html=true data-bs-title="<a href='/docs/development/modelconfig/intro/'><p>模型配置方案</p><strong>FastGPT 模型配置说明</strong><br>FastGPT 模型配置说明</a>" data-bs-toggle=tooltip href=/docs/development/modelconfig/intro/>这里</a></p><p><img src=https://cdn.jsdelivr.net/gh/yangchuansheng/fastgpt-imgs@main/imgs/Ollama-models2.png alt loading=lazy class=medium-zoom-image></p><p><img src=https://cdn.jsdelivr.net/gh/yangchuansheng/fastgpt-imgs@main/imgs/Ollama-models3.png alt loading=lazy class=medium-zoom-image></p><p>运行 FastGPT ，在页面中选择账号->模型提供商->模型渠道->新增渠道。之后，在渠道选择中选择 Ollama ，然后加入自己拉取的模型，填入代理地址，如果是容器中安装 Ollama ，代理地址为http://地址:端口，补充：容器部署地址为“http://<容器名>:<端口>”,主机安装地址为"http://<主机IP>:<端口>"，主机IP不可为localhost</p><p><img src=https://cdn.jsdelivr.net/gh/yangchuansheng/fastgpt-imgs@main/imgs/Ollama-aiproxy3.png alt loading=lazy class=medium-zoom-image></p><p>在工作台中创建一个应用，选择自己之前添加的模型，此处模型名称为自己当时设置的别名。注：同一个模型无法多次添加，系统会采取最新添加时设置的别名。</p><p><img src=https://cdn.jsdelivr.net/gh/yangchuansheng/fastgpt-imgs@main/imgs/Ollama-models4.png alt loading=lazy class=medium-zoom-image></p><h3 id=3-oneapi-接入>3. OneAPI 接入 <a href=#3-oneapi-%e6%8e%a5%e5%85%a5 class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h3><p>如果你想使用 OneAPI ，首先需要拉取 OneAPI 镜像，然后将其在 FastGPT 容器的网络中运行。具体命令如下：</p><div class=prism-codeblock><pre id=74a9107 class=language-bash>
|
||
<code># 拉取 oneAPI 镜像
|
||
docker pull intel/oneapi-hpckit
|
||
|
||
# 运行容器并指定自定义网络和容器名
|
||
docker run -it --network < FastGPT 网络 > --name 容器名 intel/oneapi-hpckit /bin/bash</code>
|
||
</pre></div><p>进入 OneAPI 页面，添加新的渠道，类型选择 Ollama ，在模型中填入自己 Ollama 中的模型，需要保证添加的模型名称和 Ollama 中一致，再在下方填入自己的 Ollama 代理地址，默认http://地址:端口，不需要填写/v1。添加成功后在 OneAPI 进行渠道测试，测试成功则说明添加成功。此处演示采用的是 Docker 部署 Ollama 的效果，主机 Ollama需要修改代理地址为http://<主机IP>:<端口></p><p><img src=https://cdn.jsdelivr.net/gh/yangchuansheng/fastgpt-imgs@main/imgs/Ollama-oneapi1.png alt loading=lazy class=medium-zoom-image></p><p>渠道添加成功后，点击令牌，点击添加令牌，填写名称，修改配置。</p><p><img src=https://cdn.jsdelivr.net/gh/yangchuansheng/fastgpt-imgs@main/imgs/Ollama-oneapi2.png alt loading=lazy class=medium-zoom-image></p><p>修改部署 FastGPT 的 docker-compose.yml 文件，在其中将 AI Proxy 的使用注释，在 OPENAI_BASE_URL 中加入自己的 OneAPI 开放地址，默认是http://地址:端口/v1，v1必须填写。KEY 中填写自己在 OneAPI 的令牌。</p><p><img src=https://cdn.jsdelivr.net/gh/yangchuansheng/fastgpt-imgs@main/imgs/Ollama-oneapi3.png alt loading=lazy class=medium-zoom-image></p><p><a href=/docs/development/custom-models/ollama/#5-模型添加和使用>直接跳转5</a>添加模型，并使用。</p><h3 id=4-直接接入>4. 直接接入 <a href=#4-%e7%9b%b4%e6%8e%a5%e6%8e%a5%e5%85%a5 class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h3><p>如果你既不想使用 AI Proxy，也不想使用 OneAPI，也可以选择直接接入，修改部署 FastGPT 的 docker-compose.yml 文件，在其中将 AI Proxy 的使用注释，采用和 OneAPI 的类似配置。注释掉 AIProxy 相关代码，在OPENAI_BASE_URL中加入自己的 Ollama 开放地址，默认是http://地址:端口/v1，强调:v1必须填写。在KEY中随便填入，因为 Ollama 默认没有鉴权，如果开启鉴权，请自行填写。其他操作和在 OneAPI 中加入 Ollama 一致，只需在 FastGPT 中加入自己的模型即可使用。此处演示采用的是 Docker 部署 Ollama 的效果，主机 Ollama需要修改代理地址为http://<主机IP>:<端口></p><p><img src=https://cdn.jsdelivr.net/gh/yangchuansheng/fastgpt-imgs@main/imgs/Ollama-direct1.png alt loading=lazy class=medium-zoom-image></p><p>完成后<a href=/docs/development/custom-models/ollama/#5-模型添加和使用>点击这里</a>进行模型添加并使用。</p><h3 id=5-模型添加和使用>5. 模型添加和使用 <a href=#5-%e6%a8%a1%e5%9e%8b%e6%b7%bb%e5%8a%a0%e5%92%8c%e4%bd%bf%e7%94%a8 class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h3><p>在 FastGPT 中点击账号->模型提供商->模型配置->新增模型，添加自己的模型即可，添加模型时需要保证模型ID和 OneAPI 中的模型名称一致。</p><p><img src=https://cdn.jsdelivr.net/gh/yangchuansheng/fastgpt-imgs@main/imgs/Ollama-models2.png alt loading=lazy class=medium-zoom-image></p><p><img src=https://cdn.jsdelivr.net/gh/yangchuansheng/fastgpt-imgs@main/imgs/Ollama-models3.png alt loading=lazy class=medium-zoom-image></p><p>在工作台中创建一个应用，选择自己之前添加的模型，此处模型名称为自己当时设置的别名。注：同一个模型无法多次添加，系统会采取最新添加时设置的别名。</p><p><img src=https://cdn.jsdelivr.net/gh/yangchuansheng/fastgpt-imgs@main/imgs/Ollama-models4.png alt loading=lazy class=medium-zoom-image></p><h3 id=6-补充>6. 补充 <a href=#6-%e8%a1%a5%e5%85%85 class=anchor aria-hidden=true><i class="material-icons align-middle">link</i></a></h3><p>上述接入 Ollama 的代理地址中，主机安装 Ollama 的地址为“http://<主机IP>:<端口>”，容器部署 Ollama 地址为“http://<容器名>:<端口>”</p></div><div class="gitinfo d-flex flex-wrap justify-content-between align-items-center opacity-85 pt-3"><div id=edit-this-page class=mt-1><a href=https://github.com/labring/FastGPT/blob/main/docSite/content/zh-cn/docs/development/custom-models/ollama.md alt="使用 Ollama 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