zengli
/
coding-agent


			
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  <h1>1.3 项目环境(mac)</h1>

<h2 id="_1">前置说明<a class="headerlink" href="#_1" title="Permanent link">&para;</a></h2>
<p>本教程介绍如何在 Windows 11 和 M1 芯片的 macOS 系统上使用 Docker 同时部署和运行单机版 Milvus（向量数据库）和 Redis（键值存储数据库）。教程分为两部分，分别针对不同操作系统提供详细步骤。</p>
<ul>
<li>操作系统</li>
<li>macOS</li>
<li>硬件要求</li>
<li>至少 8GB 内存（建议 16GB 或更高）。</li>
<li>至少 20GB 可用磁盘空间（Milvus 和 Redis 数据存储）。</li>
<li>网络要求</li>
<li>稳定的互联网连接，用于拉取 Docker 镜像。</li>
<li>软件版本</li>
<li>Milvus：2.4.4（最新稳定版）。</li>
<li>Redis：7.2（最新稳定版）。</li>
<li>端口要求</li>
<li>Milvus：<code>19530</code>（gRPC）、<code>9091</code>（RESTful API）。</li>
<li>Redis：<code>6379</code>（默认端口）。</li>
<li>确保以上端口未被占用。</li>
</ul>
<hr />
<h2 id="python">一、python虚拟环境<a class="headerlink" href="#python" title="Permanent link">&para;</a></h2>
<h3 id="1">1 创建虚拟环境<a class="headerlink" href="#1" title="Permanent link">&para;</a></h3>
<div class="highlight"><pre><span></span><code><span class="c1"># 创建虚拟环境, 安装3.12版本的python解析器</span>
conda<span class="w"> </span>create<span class="w"> </span>-n<span class="w"> </span>EnterpriseKB-RAG<span class="w"> </span><span class="nv">python</span><span class="o">==</span><span class="m">3</span>.12
<span class="c1"># 切换虚拟环境 </span>
conda<span class="w"> </span>activate<span class="w"> </span>EnterpriseKB-RAG
</code></pre></div>
<h3 id="2">2 找到依赖文件<a class="headerlink" href="#2" title="Permanent link">&para;</a></h3>
<blockquote>
<p>找到支持人员发的requirements.txt文件</p>
</blockquote>
<h3 id="3">3 安装项目依赖包<a class="headerlink" href="#3" title="Permanent link">&para;</a></h3>
<div class="highlight"><pre><span></span><code><span class="c1"># 安装依赖包, 在requirements.txt对应路径下执行以下命令</span>
pip<span class="w"> </span>install<span class="w"> </span>-r<span class="w"> </span>requirements.txt<span class="w"> </span>
</code></pre></div>
<p><img alt="image-20250814174558612" src="%E4%BC%81%E4%B8%9A%E7%9F%A5%E8%AF%86%E5%BA%93RAG%E9%A1%B9%E7%9B%AE%E7%8E%AF%E5%A2%83%E5%AE%89%E8%A3%85%E6%B5%81%E7%A8%8B.assets/image-20250814174558612.png" /></p>
<p>如果不能顺利安装，可执行以下命令逐个安装：</p>
<div class="highlight"><pre><span></span><code><span class="c1"># conda create -n enterprise_kb_rag python==3.12</span>
<span class="c1"># conda activate enterprise_kb_rag</span>

<span class="c1"># Python版本： 3.12</span>
<span class="c1"># 使用方法：先安装python 3.12或者创建一个conda的3.12的环境，并激活。然后运行以下命令</span>

pip<span class="w"> </span>install<span class="w"> </span><span class="nv">ollama</span><span class="o">==</span><span class="m">0</span>.4.4<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">requests</span><span class="o">==</span><span class="m">2</span>.32.3
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">numexpr</span><span class="o">==</span><span class="m">2</span>.11.0<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">unstructured</span><span class="o">==</span><span class="m">0</span>.11.0<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span>langchain-core<span class="o">==</span><span class="m">1</span>.2.16<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">langchain_community</span><span class="o">==</span><span class="m">0</span>.4.1<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span>langchain-ollama<span class="o">==</span><span class="m">1</span>.0.1<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">langchain_unstructured</span><span class="o">==</span><span class="m">1</span>.0.1
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">langchain_experimental</span><span class="o">==</span><span class="m">0</span>.4.1<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">langchain_chroma</span><span class="o">==</span><span class="m">1</span>.1.0<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span>langchain-text-splitters<span class="o">==</span><span class="m">1</span>.1.1<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">langgraph</span><span class="o">==</span><span class="m">1</span>.0.8<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">nltk</span><span class="o">==</span><span class="m">3</span>.9.1
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">chromadb</span><span class="o">==</span><span class="m">1</span>.3.5
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">wikipedia</span><span class="o">==</span><span class="m">1</span>.4.0<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span>faiss-cpu<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">pymilvus</span><span class="o">==</span><span class="m">2</span>.5.4<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">pandas</span><span class="o">==</span><span class="m">2</span>.3.1
pip<span class="w"> </span>install<span class="w"> </span>jieba
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">rank_bm25</span><span class="o">==</span><span class="m">0</span>.2.2
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">redis</span><span class="o">==</span><span class="m">5</span>.3.1<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">pymysql</span><span class="o">==</span><span class="m">1</span>.1.1
pip<span class="w"> </span>install<span class="w"> </span>opencv-python<span class="o">==</span><span class="m">4</span>.10.0.84<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">PyMuPDF</span><span class="o">==</span><span class="m">1</span>.23.16<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span>python-docx<span class="o">==</span><span class="m">1</span>.1.2<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">pillow</span><span class="o">==</span><span class="m">10</span>.4.0
pip<span class="w"> </span>install<span class="w"> </span>rapidocr-onnxruntime<span class="o">==</span><span class="m">1</span>.3.8
pip<span class="w"> </span>install<span class="w"> </span>python-pptx<span class="o">==</span><span class="m">0</span>.6.23<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">transformers</span><span class="o">==</span><span class="m">4</span>.45.0<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">modelscope</span><span class="o">==</span><span class="m">1</span>.23.0<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">addict</span><span class="o">==</span><span class="m">2</span>.4.0
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">datasets</span><span class="o">==</span><span class="m">3</span>.3.1<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">simplejson</span><span class="o">==</span><span class="m">3</span>.19.2
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">sortedcontainers</span><span class="o">==</span><span class="m">2</span>.4.0
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">markdown</span><span class="o">==</span><span class="m">3</span>.6
pip<span class="w"> </span>install<span class="w"> </span>sentence-transformers<span class="o">==</span><span class="m">3</span>.0.1
pip<span class="w"> </span>install<span class="w"> </span>milvus-model<span class="o">==</span><span class="m">0</span>.2.5<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">tiktoken</span><span class="o">==</span><span class="m">0</span>.7.0<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">sentencepiece</span><span class="o">==</span><span class="m">0</span>.2.0<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">ragas</span><span class="o">==</span><span class="m">0</span>.2.6<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">starlette</span><span class="o">==</span><span class="m">0</span>.46.2<span class="w"> </span>
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">fastapi</span><span class="o">==</span><span class="m">0</span>.115.12
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">FlagEmbedding</span><span class="o">==</span><span class="m">1</span>.3.5
pip<span class="w"> </span>install<span class="w"> </span><span class="nv">peft</span><span class="o">==</span><span class="m">0</span>.18.1
</code></pre></div>
<h2 id="dockerdesktop">二、安装DockerDesktop<a class="headerlink" href="#dockerdesktop" title="Permanent link">&para;</a></h2>
<h3 id="1-wsl">1 安装WSL<a class="headerlink" href="#1-wsl" title="Permanent link">&para;</a></h3>
<p>启用 WSL 2（Windows Subsystem for Linux 2）支持：</p>
<ul>
<li>打开 PowerShell（以管理员身份），运行：</li>
</ul>
<div class="highlight"><pre><span></span><code>wsl<span class="w"> </span>--install
</code></pre></div>
<ul>
<li>安装完成后，重启计算机。</li>
</ul>
<h3 id="2-docker-desktop">2 安装Docker Desktop<a class="headerlink" href="#2-docker-desktop" title="Permanent link">&para;</a></h3>
<ul>
<li>
<p>下载并安装Docker Desktop</p>
</li>
<li>
<p>访问 <a href="https://www.docker.com/products/docker-desktop/">Docker 官方网站</a>，下载适用于 macOS（Apple Silicon）的 Docker Desktop 安装包。</p>
</li>
</ul>
<p><img alt="image-20250822095538468" src="%E4%BC%81%E4%B8%9A%E7%9F%A5%E8%AF%86%E5%BA%93RAG%E9%A1%B9%E7%9B%AE%E7%8E%AF%E5%A2%83%E5%AE%89%E8%A3%85%E6%B5%81%E7%A8%8B.assets/image-20250822095538468.png" /></p>
<p>安装 Docker Desktop</p>
<ul>
<li>双击下载的 <code>.dmg</code> 文件，按照提示拖动安装。</li>
<li>安装完成后，启动 Docker Desktop，并确保其在菜单栏运行。</li>
</ul>
<p>验证 Docker 安装</p>
<ul>
<li>打开终端，运行：</li>
</ul>
<div class="highlight"><pre><span></span><code>docker<span class="w"> </span>--version
docker<span class="w"> </span>compose<span class="w"> </span>version
</code></pre></div>
<ul>
<li>确保输出版本信息，例如 <code>Docker version 27.x.x</code> 和 <code>Docker Compose version v2.x.x</code>。</li>
</ul>
<p>启用 Rosetta（可选）</p>
<ul>
<li>如果遇到兼容性问题，可在 Docker Desktop 设置中启用 Rosetta 模拟：</li>
<li>打开 Docker Desktop -&gt; Settings -&gt; Features in Development -&gt; 勾选 “Use Rosetta for x86/AMD64 emulation on Apple Silicon”。</li>
</ul>
<h2 id="docker-compose">三、配置 Docker Compose 文件<a class="headerlink" href="#docker-compose" title="Permanent link">&para;</a></h2>
<h3 id="1_1">1 创建项目目录<a class="headerlink" href="#1_1" title="Permanent link">&para;</a></h3>
<p>在本地磁盘（例如 C盘）创建一个文件夹，用于存放 Milvus 和 Redis 的配置文件和数据：</p>
<div class="highlight"><pre><span></span><code>mkdir<span class="w"> </span>C:<span class="se">\m</span>ilvus_redis
<span class="nb">cd</span><span class="w"> </span>C:<span class="se">\m</span>ilvus_redis
</code></pre></div>
<h3 id="2-docker-compose">2 创建 Docker Compose 文件<a class="headerlink" href="#2-docker-compose" title="Permanent link">&para;</a></h3>
<div class="highlight"><pre><span></span><code>touch docker-compose.yml
</code></pre></div>
<h3 id="3_1">3 添加内容<a class="headerlink" href="#3_1" title="Permanent link">&para;</a></h3>
<div class="highlight"><pre><span></span><code><span class="nt">version</span><span class="p">:</span><span class="w"> </span><span class="s">&#39;3.5&#39;</span>

<span class="c1"># M1/ARM64 Mac Version</span>
<span class="c1"># Redis Password set to: 1234</span>

<span class="nt">services</span><span class="p">:</span>
<span class="w">  </span><span class="nt">etcd</span><span class="p">:</span>
<span class="w">    </span><span class="nt">container_name</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">milvus-etcd</span>
<span class="w">    </span><span class="nt">image</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">quay.io/coreos/etcd:v3.5.5</span>
<span class="w">    </span><span class="nt">environment</span><span class="p">:</span>
<span class="w">      </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">ETCD_AUTO_COMPACTION_MODE=revision</span>
<span class="w">      </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">ETCD_AUTO_COMPACTION_RETENTION=1000</span>
<span class="w">      </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">ETCD_QUOTA_BACKEND_BYTES=4294967296</span>
<span class="w">      </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">ETCD_ENABLE_V2=true</span>
<span class="w">    </span><span class="nt">volumes</span><span class="p">:</span>
<span class="w">      </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">./volumes/etcd:/etcd/data</span>
<span class="w">    </span><span class="nt">command</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">etcd -advertise-client-urls=http://127.0.0.1:2379 -listen-client-urls http://0.0.0.0:2379 --data-dir /etcd/data</span>

<span class="w">  </span><span class="nt">minio</span><span class="p">:</span>
<span class="w">    </span><span class="nt">container_name</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">milvus-minio</span>
<span class="w">    </span><span class="nt">image</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">minio/minio:RELEASE.2023-03-20T20-16-18Z</span>
<span class="w">    </span><span class="nt">environment</span><span class="p">:</span>
<span class="w">      </span><span class="nt">MINIO_ACCESS_KEY</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">minioadmin</span>
<span class="w">      </span><span class="nt">MINIO_SECRET_KEY</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">minioadmin</span>
<span class="w">    </span><span class="nt">volumes</span><span class="p">:</span>
<span class="w">      </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">./volumes/minio:/minio/data</span>
<span class="w">    </span><span class="nt">command</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">minio server /minio/data</span>
<span class="w">    </span><span class="nt">healthcheck</span><span class="p">:</span>
<span class="w">      </span><span class="nt">test</span><span class="p">:</span><span class="w"> </span><span class="p p-Indicator">[</span><span class="s">&quot;CMD&quot;</span><span class="p p-Indicator">,</span><span class="w"> </span><span class="s">&quot;curl&quot;</span><span class="p p-Indicator">,</span><span class="w"> </span><span class="s">&quot;-f&quot;</span><span class="p p-Indicator">,</span><span class="w"> </span><span class="s">&quot;http://localhost:9000/minio/health/live&quot;</span><span class="p p-Indicator">]</span>
<span class="w">      </span><span class="nt">interval</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">30s</span>
<span class="w">      </span><span class="nt">timeout</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">20s</span>
<span class="w">      </span><span class="nt">retries</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">3</span>

<span class="w">  </span><span class="nt">standalone</span><span class="p">:</span>
<span class="w">    </span><span class="nt">container_name</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">milvus-standalone</span>
<span class="w">    </span><span class="c1"># 使用多架构镜像，Docker on M1 会自动拉取 ARM64 版本</span>
<span class="w">    </span><span class="nt">image</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">milvusdb/milvus:v2.4.4</span>
<span class="w">    </span><span class="nt">command</span><span class="p">:</span><span class="w"> </span><span class="p p-Indicator">[</span><span class="s">&quot;milvus&quot;</span><span class="p p-Indicator">,</span><span class="w"> </span><span class="s">&quot;run&quot;</span><span class="p p-Indicator">,</span><span class="w"> </span><span class="s">&quot;standalone&quot;</span><span class="p p-Indicator">]</span>
<span class="w">    </span><span class="nt">environment</span><span class="p">:</span>
<span class="w">      </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">ETCD_ENDPOINTS=etcd:2379</span>
<span class="w">      </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">MINIO_ADDRESS=minio:9000</span>
<span class="w">    </span><span class="nt">volumes</span><span class="p">:</span>
<span class="w">      </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">./volumes/milvus:/var/lib/milvus</span>
<span class="w">    </span><span class="nt">ports</span><span class="p">:</span>
<span class="w">      </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="s">&quot;19530:19530&quot;</span>
<span class="w">      </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="s">&quot;9091:9091&quot;</span>
<span class="w">    </span><span class="nt">depends_on</span><span class="p">:</span>
<span class="w">      </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="s">&quot;etcd&quot;</span>
<span class="w">      </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="s">&quot;minio&quot;</span>

<span class="w">  </span><span class="nt">redis</span><span class="p">:</span>
<span class="w">    </span><span class="nt">container_name</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">milvus-redis</span>
<span class="w">    </span><span class="nt">image</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">redis:latest</span><span class="w"> </span><span class="c1"># Redis 官方镜像同样支持多架构</span>
<span class="w">    </span><span class="nt">restart</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">always</span>
<span class="w">    </span><span class="nt">ports</span><span class="p">:</span>
<span class="w">      </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="s">&quot;6379:6379&quot;</span>
<span class="w">    </span><span class="nt">volumes</span><span class="p">:</span>
<span class="w">      </span><span class="p p-Indicator">-</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">./volumes/redis:/data</span>
<span class="w">    </span><span class="c1"># 设置 Redis 密码为 1234</span>
<span class="w">    </span><span class="nt">command</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">redis-server --requirepass 1234</span>

<span class="nt">networks</span><span class="p">:</span>
<span class="w">  </span><span class="nt">default</span><span class="p">:</span>
<span class="w">    </span><span class="nt">name</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">milvus-network</span>
</code></pre></div>
<ul>
<li>
<p><strong>注意</strong>：Milvus 和 Redis 镜像均支持 ARM64，无需额外配置。</p>
</li>
<li>
<p>Milvus 服务</p>
</li>
<li>
<p><code>image</code>: 使用 Milvus 官方镜像 <code>milvusdb/milvus:v2.4.10</code>。</p>
</li>
<li><code>ports</code>: 映射 gRPC（19530）和 RESTful API（9091）端口。</li>
<li><code>volumes</code>: 数据持久化存储到本地 <code>./volumes/milvus</code> 目录。</li>
<li><code>environment</code>: 配置日志级别和 Etcd 参数。</li>
<li>
<p><code>command</code>: 启动 Milvus 单机模式。</p>
</li>
<li>
<p>Redis 服务</p>
</li>
<li>
<p><code>image</code>: 使用 Redis 官方镜像 <code>redis:7.2</code>。</p>
</li>
<li><code>ports</code>: 映射默认端口 <code>6379</code>。</li>
<li><code>volumes</code>: 数据持久化存储到本地 <code>./volumes/redis</code> 目录。</li>
<li>
<p><code>command</code>: 启用 AOF（Append Only File）持久化模式。</p>
</li>
<li>
<p><code>volumes</code>: 定义持久化存储卷。</p>
</li>
</ul>
<h2 id="milvus-redis">四、启动 Milvus 和 Redis<a class="headerlink" href="#milvus-redis" title="Permanent link">&para;</a></h2>
<h3 id="1_2">1 拉取镜像并启动容器<a class="headerlink" href="#1_2" title="Permanent link">&para;</a></h3>
<ul>
<li>在在 ~/milvus_redis 目录下，运行：</li>
</ul>
<div class="highlight"><pre><span></span><code>docker<span class="w"> </span>compose<span class="w"> </span>up<span class="w"> </span>-d
</code></pre></div>
<ul>
<li><code>-d</code> 表示后台运行容器。</li>
</ul>
<h3 id="2_1">2 验证容器状态<a class="headerlink" href="#2_1" title="Permanent link">&para;</a></h3>
<ul>
<li>检查容器是否正常运行：</li>
</ul>
<div class="highlight"><pre><span></span><code>docker<span class="w"> </span>ps
</code></pre></div>
<ul>
<li>确认 <code>milvus_standalone</code> 和 <code>redis</code> 容器均处于 <code>Up</code> 状态。</li>
</ul>
<h2 id="milvusredis">五、验证Milvus和Redis<a class="headerlink" href="#milvusredis" title="Permanent link">&para;</a></h2>
<h3 id="1-milvus">1 验证 Milvus 服务<a class="headerlink" href="#1-milvus" title="Permanent link">&para;</a></h3>
<ol>
<li>
<p>安装 Milvus Python SDK</p>
</li>
<li>
<p>确保已安装 Python 3.8 或以上版本。</p>
</li>
<li>
<p>在 PowerShell 中安装：</p>
<div class="highlight"><pre><span></span><code>pip<span class="w"> </span>install<span class="w"> </span>pymilvus
</code></pre></div>
</li>
<li>
<p>测试 Milvus 连接</p>
</li>
<li>
<p>创建 Python 脚本（例如 test_milvus.py ），内容如下：</p>
<div class="highlight"><pre><span></span><code><span class="kn">from</span><span class="w"> </span><span class="nn">pymilvus</span><span class="w"> </span><span class="kn">import</span> <span class="n">connections</span><span class="p">,</span> <span class="n">utility</span>

<span class="c1"># 连接到 Milvus</span>
<span class="n">connections</span><span class="o">.</span><span class="n">connect</span><span class="p">(</span><span class="n">host</span><span class="o">=</span><span class="s2">&quot;localhost&quot;</span><span class="p">,</span> <span class="n">port</span><span class="o">=</span><span class="s2">&quot;19530&quot;</span><span class="p">)</span>

<span class="c1"># 检查版本</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Milvus version: </span><span class="si">{</span><span class="n">utility</span><span class="o">.</span><span class="n">get_server_version</span><span class="p">()</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
</code></pre></div>
</li>
<li>
<p>运行脚本：</p>
<div class="highlight"><pre><span></span><code>python<span class="w"> </span>test_milvus.py
</code></pre></div>
</li>
<li>
<p>输出类似 <code>Milvus version: 2.4.10</code> 表示 Milvus 部署成功。</p>
</li>
</ol>
<h3 id="2-redis">2 验证 Redis 服务<a class="headerlink" href="#2-redis" title="Permanent link">&para;</a></h3>
<ol>
<li>
<p>安装 Redis Python 客户端</p>
</li>
<li>
<p>在 PowerShell 中安装：</p>
<div class="highlight"><pre><span></span><code>pip<span class="w"> </span>install<span class="w"> </span>redis
</code></pre></div>
</li>
<li>
<p>测试 Redis 连接</p>
</li>
<li>
<p>创建 Python 脚本（例如 test_redis.py ），内容如下：</p>
<div class="highlight"><pre><span></span><code><span class="kn">import</span><span class="w"> </span><span class="nn">redis</span>

<span class="c1"># 连接到 Redis</span>
<span class="n">client</span> <span class="o">=</span> <span class="n">redis</span><span class="o">.</span><span class="n">Redis</span><span class="p">(</span><span class="n">host</span><span class="o">=</span><span class="s2">&quot;localhost&quot;</span><span class="p">,</span> <span class="n">port</span><span class="o">=</span><span class="mi">6379</span><span class="p">,</span> <span class="n">decode_responses</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>

<span class="c1"># 测试读写</span>
<span class="n">client</span><span class="o">.</span><span class="n">set</span><span class="p">(</span><span class="s2">&quot;test_key&quot;</span><span class="p">,</span> <span class="s2">&quot;Hello, Redis!&quot;</span><span class="p">)</span>
<span class="n">value</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;test_key&quot;</span><span class="p">)</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Redis value: </span><span class="si">{</span><span class="n">value</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
</code></pre></div>
</li>
<li>
<p>运行脚本：</p>
<div class="highlight"><pre><span></span><code>python<span class="w"> </span>test_redis.py
</code></pre></div>
</li>
<li>
<p>输出类似 <code>Redis value: Hello, Redis!</code> 表示 Redis 部署成功。</p>
</li>
</ol>
<h2 id="milvusattu">六、安装Milvus可视化工具Attu<a class="headerlink" href="#milvusattu" title="Permanent link">&para;</a></h2>
<h3 id="1_3">1 安装<a class="headerlink" href="#1_3" title="Permanent link">&para;</a></h3>
<p>拉取可视化组件attu</p>
<div class="highlight"><pre><span></span><code>docker<span class="w"> </span>pull<span class="w"> </span>zilliz/attu
</code></pre></div>
<p>运行可视化组件</p>
<div class="highlight"><pre><span></span><code><span class="c1"># 下面的30000就是访问的端口，可以自行修改，确保不要被占用即可</span>
<span class="n">docker</span> <span class="n">run</span> <span class="o">-</span><span class="n">d</span> <span class="o">-</span><span class="n">p</span> <span class="mi">30000</span><span class="p">:</span><span class="mi">3000</span> <span class="n">zilliz</span><span class="o">/</span><span class="n">attu</span>
</code></pre></div>
<p>打开127.0.0.1:30000</p>
<h3 id="2_2">2 连接<a class="headerlink" href="#2_2" title="Permanent link">&para;</a></h3>
<p><img alt="1753668545474" src="assets/1753668545474.png" /></p>
<p><img alt="1753668563908" src="assets/1753668563908.png" /></p>
<hr />
<h2 id="_2">常见问题与解决方法<a class="headerlink" href="#_2" title="Permanent link">&para;</a></h2>
<ol>
<li>
<p>端口冲突</p>
</li>
<li>
<p>如果 <code>19530</code>、<code>9091</code> 或 <code>6379</code> 端口被占用，修改 <code>docker-compose.yml</code> 中的端口映射（例如 <code>19531:19530</code>），并在客户端连接时使用新端口。</p>
</li>
<li>
<p>镜像拉取失败</p>
</li>
<li>
<p>确保网络连接正常，或尝试手动拉取镜像：</p>
<div class="highlight"><pre><span></span><code>docker<span class="w"> </span>pull<span class="w"> </span>milvusdb/milvus:v2.4.10
docker<span class="w"> </span>pull<span class="w"> </span>redis:7.2
</code></pre></div>
</li>
<li>
<p>M1 芯片兼容性问题</p>
</li>
<li>
<p>如果镜像运行失败，检查 Docker Desktop 是否启用了 Rosetta 模拟。</p>
</li>
<li>
<p>连接失败</p>
</li>
<li>
<p>确保容器运行正常，检查防火墙（Windows）或网络设置（macOS）是否阻止了端口。</p>
</li>
<li>
<p>Redis 数据未持久化</p>
</li>
<li>
<p>确保 <code>docker-compose.yml</code> 中启用了 <code>--appendonly yes</code>，且 <code>./redis_data</code> 目录有写权限。</p>
</li>
</ol>
<hr />
<h2 id="_3">参考资源<a class="headerlink" href="#_3" title="Permanent link">&para;</a></h2>
<ul>
<li><a href="https://milvus.io/docs">Milvus 官方文档</a></li>
<li><a href="https://redis.io/documentation">Redis 官方文档</a></li>
<li><a href="https://docs.docker.com/desktop/">Docker Desktop 文档</a></li>
<li><a href="https://hub.docker.com/r/milvusdb/milvus">Milvus Docker 镜像</a></li>
<li><a href="https://hub.docker.com/_/redis">Redis Docker 镜像</a></li>
</ul>


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