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    <a href="https://github.com/fishaudio/fish-speech/blob/main/docs/ar/install.md" title="عدل الصفحة" class="md-content__button md-icon" rel="edit">
      
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  <h1>التثبيت</h1>

<h2 id="_1">المتطلبات</h2>
<ul>
<li>ذاكرة وحدة معالجة الرسومات (GPU): 24 جيجابايت (للاستدلال)</li>
<li>النظام: Linux, WSL</li>
</ul>
<h2 id="_2">إعداد النظام</h2>
<p>يدعم Fish Audio S2 طرق تثبيت متعددة. اختر الطريقة التي تناسب بيئة التطوير الخاصة بك.</p>
<p><strong>المتطلبات الأساسية</strong>: قم بتثبيت تبعيات النظام لمعالجة الصوت:
<div class="language-bash highlight"><pre><span></span><code><span id="__span-0-1"><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a>apt<span class="w"> </span>install<span class="w"> </span>portaudio19-dev<span class="w"> </span>libsox-dev<span class="w"> </span>ffmpeg
</span></code></pre></div></p>
<h3 id="conda">Conda</h3>
<div class="language-bash highlight"><pre><span></span><code><span id="__span-1-1"><a id="__codelineno-1-1" name="__codelineno-1-1" href="#__codelineno-1-1"></a>conda<span class="w"> </span>create<span class="w"> </span>-n<span class="w"> </span>fish-speech<span class="w"> </span><span class="nv">python</span><span class="o">=</span><span class="m">3</span>.12
</span><span id="__span-1-2"><a id="__codelineno-1-2" name="__codelineno-1-2" href="#__codelineno-1-2"></a>conda<span class="w"> </span>activate<span class="w"> </span>fish-speech
</span><span id="__span-1-3"><a id="__codelineno-1-3" name="__codelineno-1-3" href="#__codelineno-1-3"></a>
</span><span id="__span-1-4"><a id="__codelineno-1-4" name="__codelineno-1-4" href="#__codelineno-1-4"></a><span class="c1"># تثبيت نسخة GPU (اختر إصدار CUDA الخاص بك: cu126, cu128, cu129)</span>
</span><span id="__span-1-5"><a id="__codelineno-1-5" name="__codelineno-1-5" href="#__codelineno-1-5"></a>pip<span class="w"> </span>install<span class="w"> </span>-e<span class="w"> </span>.<span class="o">[</span>cu129<span class="o">]</span>
</span><span id="__span-1-6"><a id="__codelineno-1-6" name="__codelineno-1-6" href="#__codelineno-1-6"></a>
</span><span id="__span-1-7"><a id="__codelineno-1-7" name="__codelineno-1-7" href="#__codelineno-1-7"></a><span class="c1"># تثبيت نسخة CPU فقط</span>
</span><span id="__span-1-8"><a id="__codelineno-1-8" name="__codelineno-1-8" href="#__codelineno-1-8"></a>pip<span class="w"> </span>install<span class="w"> </span>-e<span class="w"> </span>.<span class="o">[</span>cpu<span class="o">]</span>
</span><span id="__span-1-9"><a id="__codelineno-1-9" name="__codelineno-1-9" href="#__codelineno-1-9"></a>
</span><span id="__span-1-10"><a id="__codelineno-1-10" name="__codelineno-1-10" href="#__codelineno-1-10"></a><span class="c1"># التثبيت الافتراضي (يستخدم فهرس PyTorch الافتراضي)</span>
</span><span id="__span-1-11"><a id="__codelineno-1-11" name="__codelineno-1-11" href="#__codelineno-1-11"></a>pip<span class="w"> </span>install<span class="w"> </span>-e<span class="w"> </span>.
</span><span id="__span-1-12"><a id="__codelineno-1-12" name="__codelineno-1-12" href="#__codelineno-1-12"></a>
</span><span id="__span-1-13"><a id="__codelineno-1-13" name="__codelineno-1-13" href="#__codelineno-1-13"></a><span class="c1"># إذا واجهت خطأ أثناء التثبيت بسبب pyaudio، ففكر في استخدام الأمر التالي:</span>
</span><span id="__span-1-14"><a id="__codelineno-1-14" name="__codelineno-1-14" href="#__codelineno-1-14"></a><span class="c1"># conda install pyaudio</span>
</span><span id="__span-1-15"><a id="__codelineno-1-15" name="__codelineno-1-15" href="#__codelineno-1-15"></a><span class="c1"># ثم قم بتشغيل pip install -e . مرة أخرى</span>
</span></code></pre></div>
<h3 id="uv">UV</h3>
<p>يوفر UV حلاً أسرع لتثبيت التبعيات:</p>
<div class="language-bash highlight"><pre><span></span><code><span id="__span-2-1"><a id="__codelineno-2-1" name="__codelineno-2-1" href="#__codelineno-2-1"></a><span class="c1"># تثبيت نسخة GPU (اختر إصدار CUDA الخاص بك: cu126, cu128, cu129)</span>
</span><span id="__span-2-2"><a id="__codelineno-2-2" name="__codelineno-2-2" href="#__codelineno-2-2"></a>uv<span class="w"> </span>sync<span class="w"> </span>--python<span class="w"> </span><span class="m">3</span>.12<span class="w"> </span>--extra<span class="w"> </span>cu129
</span><span id="__span-2-3"><a id="__codelineno-2-3" name="__codelineno-2-3" href="#__codelineno-2-3"></a>
</span><span id="__span-2-4"><a id="__codelineno-2-4" name="__codelineno-2-4" href="#__codelineno-2-4"></a><span class="c1"># تثبيت نسخة CPU فقط</span>
</span><span id="__span-2-5"><a id="__codelineno-2-5" name="__codelineno-2-5" href="#__codelineno-2-5"></a>uv<span class="w"> </span>sync<span class="w"> </span>--python<span class="w"> </span><span class="m">3</span>.12<span class="w"> </span>--extra<span class="w"> </span>cpu
</span></code></pre></div>
<h3 id="intel-arc-xpu">دعم Intel Arc XPU</h3>
<p>لمستخدمي وحدات معالجة الرسومات Intel Arc، قم بالتثبيت مع دعم XPU على النحو التالي:</p>
<div class="language-bash highlight"><pre><span></span><code><span id="__span-3-1"><a id="__codelineno-3-1" name="__codelineno-3-1" href="#__codelineno-3-1"></a>conda<span class="w"> </span>create<span class="w"> </span>-n<span class="w"> </span>fish-speech<span class="w"> </span><span class="nv">python</span><span class="o">=</span><span class="m">3</span>.12
</span><span id="__span-3-2"><a id="__codelineno-3-2" name="__codelineno-3-2" href="#__codelineno-3-2"></a>conda<span class="w"> </span>activate<span class="w"> </span>fish-speech
</span><span id="__span-3-3"><a id="__codelineno-3-3" name="__codelineno-3-3" href="#__codelineno-3-3"></a>
</span><span id="__span-3-4"><a id="__codelineno-3-4" name="__codelineno-3-4" href="#__codelineno-3-4"></a><span class="c1"># تثبيت مكتبة C++ القياسية المطلوبة</span>
</span><span id="__span-3-5"><a id="__codelineno-3-5" name="__codelineno-3-5" href="#__codelineno-3-5"></a>conda<span class="w"> </span>install<span class="w"> </span>libstdcxx<span class="w"> </span>-c<span class="w"> </span>conda-forge
</span><span id="__span-3-6"><a id="__codelineno-3-6" name="__codelineno-3-6" href="#__codelineno-3-6"></a>
</span><span id="__span-3-7"><a id="__codelineno-3-7" name="__codelineno-3-7" href="#__codelineno-3-7"></a><span class="c1"># تثبيت PyTorch مع دعم Intel XPU</span>
</span><span id="__span-3-8"><a id="__codelineno-3-8" name="__codelineno-3-8" href="#__codelineno-3-8"></a>pip<span class="w"> </span>install<span class="w"> </span>--pre<span class="w"> </span>torch<span class="w"> </span>torchvision<span class="w"> </span>torchaudio<span class="w"> </span>--index-url<span class="w"> </span>https://download.pytorch.org/whl/nightly/xpu
</span><span id="__span-3-9"><a id="__codelineno-3-9" name="__codelineno-3-9" href="#__codelineno-3-9"></a>
</span><span id="__span-3-10"><a id="__codelineno-3-10" name="__codelineno-3-10" href="#__codelineno-3-10"></a><span class="c1"># تثبيت Fish Speech</span>
</span><span id="__span-3-11"><a id="__codelineno-3-11" name="__codelineno-3-11" href="#__codelineno-3-11"></a>pip<span class="w"> </span>install<span class="w"> </span>-e<span class="w"> </span>.
</span></code></pre></div>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>خيار <code>compile</code> غير مدعوم على أنظمة Windows و macOS. إذا كنت ترغب في التشغيل مع التجميع، ستحتاج إلى تثبيت Triton بنفسك.</p>
</div>
<h2 id="docker">إعداد Docker</h2>
<p>يوفر نموذج سلسلة Fish Audio S2 خيارات نشر متعددة مع Docker لتلبية الاحتياجات المختلفة. يمكنك استخدام الصور المعدة مسبقًا من Docker Hub، أو البناء محليًا باستخدام Docker Compose، أو بناء صور مخصصة يدويًا.</p>
<p>لقد قدمنا صور Docker لكل من واجهة المستخدم الرسومية (WebUI) وخادم API، لكل من وحدات معالجة الرسومات (GPU) (CUDA 12.6 افتراضيًا) ووحدات المعالجة المركزية (CPU). يمكنك استخدام الصور المعدة مسبقًا من Docker Hub، أو البناء محليًا باستخدام Docker Compose، أو بناء صور مخصصة يدويًا. إذا كنت ترغب في البناء محليًا، فاتبع الإرشادات أدناه. إذا كنت ترغب فقط في استخدام الصور المعدة مسبقًا، فاتبع مباشرةً <a href="../inference/">دليل الاستدلال</a>.</p>
<h3 id="_3">المتطلبات الأساسية</h3>
<ul>
<li>تثبيت Docker و Docker Compose</li>
<li>تثبيت NVIDIA Docker runtime (لدعم GPU)</li>
<li>ذاكرة GPU لا تقل عن 24 جيجابايت للاستدلال باستخدام CUDA</li>
</ul>
<h3 id="docker-compose">استخدام Docker Compose</h3>
<p>للتطوير أو التخصيص، يمكنك استخدام Docker Compose للبناء والتشغيل محليًا:</p>
<div class="language-bash highlight"><pre><span></span><code><span id="__span-4-1"><a id="__codelineno-4-1" name="__codelineno-4-1" href="#__codelineno-4-1"></a><span class="c1"># أولاً، استنسخ المستودع</span>
</span><span id="__span-4-2"><a id="__codelineno-4-2" name="__codelineno-4-2" href="#__codelineno-4-2"></a>git<span class="w"> </span>clone<span class="w"> </span>https://github.com/fishaudio/fish-speech.git
</span><span id="__span-4-3"><a id="__codelineno-4-3" name="__codelineno-4-3" href="#__codelineno-4-3"></a><span class="nb">cd</span><span class="w"> </span>fish-speech
</span><span id="__span-4-4"><a id="__codelineno-4-4" name="__codelineno-4-4" href="#__codelineno-4-4"></a>
</span><span id="__span-4-5"><a id="__codelineno-4-5" name="__codelineno-4-5" href="#__codelineno-4-5"></a><span class="c1"># بدء واجهة المستخدم الرسومية (WebUI) مع CUDA</span>
</span><span id="__span-4-6"><a id="__codelineno-4-6" name="__codelineno-4-6" href="#__codelineno-4-6"></a>docker<span class="w"> </span>compose<span class="w"> </span>--profile<span class="w"> </span>webui<span class="w"> </span>up
</span><span id="__span-4-7"><a id="__codelineno-4-7" name="__codelineno-4-7" href="#__codelineno-4-7"></a>
</span><span id="__span-4-8"><a id="__codelineno-4-8" name="__codelineno-4-8" href="#__codelineno-4-8"></a><span class="c1"># بدء واجهة المستخدم الرسومية (WebUI) مع تحسين التجميع</span>
</span><span id="__span-4-9"><a id="__codelineno-4-9" name="__codelineno-4-9" href="#__codelineno-4-9"></a><span class="nv">COMPILE</span><span class="o">=</span><span class="m">1</span><span class="w"> </span>docker<span class="w"> </span>compose<span class="w"> </span>--profile<span class="w"> </span>webui<span class="w"> </span>up
</span><span id="__span-4-10"><a id="__codelineno-4-10" name="__codelineno-4-10" href="#__codelineno-4-10"></a>
</span><span id="__span-4-11"><a id="__codelineno-4-11" name="__codelineno-4-11" href="#__codelineno-4-11"></a><span class="c1"># بدء خادم API</span>
</span><span id="__span-4-12"><a id="__codelineno-4-12" name="__codelineno-4-12" href="#__codelineno-4-12"></a>docker<span class="w"> </span>compose<span class="w"> </span>--profile<span class="w"> </span>server<span class="w"> </span>up
</span><span id="__span-4-13"><a id="__codelineno-4-13" name="__codelineno-4-13" href="#__codelineno-4-13"></a>
</span><span id="__span-4-14"><a id="__codelineno-4-14" name="__codelineno-4-14" href="#__codelineno-4-14"></a><span class="c1"># بدء خادم API مع تحسين التجميع</span>
</span><span id="__span-4-15"><a id="__codelineno-4-15" name="__codelineno-4-15" href="#__codelineno-4-15"></a><span class="nv">COMPILE</span><span class="o">=</span><span class="m">1</span><span class="w"> </span>docker<span class="w"> </span>compose<span class="w"> </span>--profile<span class="w"> </span>server<span class="w"> </span>up
</span><span id="__span-4-16"><a id="__codelineno-4-16" name="__codelineno-4-16" href="#__codelineno-4-16"></a>
</span><span id="__span-4-17"><a id="__codelineno-4-17" name="__codelineno-4-17" href="#__codelineno-4-17"></a><span class="c1"># النشر باستخدام CPU فقط</span>
</span><span id="__span-4-18"><a id="__codelineno-4-18" name="__codelineno-4-18" href="#__codelineno-4-18"></a><span class="nv">BACKEND</span><span class="o">=</span>cpu<span class="w"> </span>docker<span class="w"> </span>compose<span class="w"> </span>--profile<span class="w"> </span>webui<span class="w"> </span>up
</span></code></pre></div>
<h4 id="docker-compose_1">متغيرات البيئة لـ Docker Compose</h4>
<p>يمكنك تخصيص النشر باستخدام متغيرات البيئة:</p>
<div class="language-bash highlight"><pre><span></span><code><span id="__span-5-1"><a id="__codelineno-5-1" name="__codelineno-5-1" href="#__codelineno-5-1"></a><span class="c1"># مثال على ملف .env</span>
</span><span id="__span-5-2"><a id="__codelineno-5-2" name="__codelineno-5-2" href="#__codelineno-5-2"></a><span class="nv">BACKEND</span><span class="o">=</span>cuda<span class="w">              </span><span class="c1"># أو cpu</span>
</span><span id="__span-5-3"><a id="__codelineno-5-3" name="__codelineno-5-3" href="#__codelineno-5-3"></a><span class="nv">COMPILE</span><span class="o">=</span><span class="m">1</span><span class="w">                 </span><span class="c1"># تمكين تحسين التجميع</span>
</span><span id="__span-5-4"><a id="__codelineno-5-4" name="__codelineno-5-4" href="#__codelineno-5-4"></a><span class="nv">GRADIO_PORT</span><span class="o">=</span><span class="m">7860</span><span class="w">         </span><span class="c1"># منفذ واجهة المستخدم الرسومية (WebUI)</span>
</span><span id="__span-5-5"><a id="__codelineno-5-5" name="__codelineno-5-5" href="#__codelineno-5-5"></a><span class="nv">API_PORT</span><span class="o">=</span><span class="m">8080</span><span class="w">            </span><span class="c1"># منفذ خادم API</span>
</span><span id="__span-5-6"><a id="__codelineno-5-6" name="__codelineno-5-6" href="#__codelineno-5-6"></a><span class="nv">UV_VERSION</span><span class="o">=</span><span class="m">0</span>.8.15<span class="w">        </span><span class="c1"># إصدار مدير الحزم UV</span>
</span></code></pre></div>
<p>سيقوم الأمر ببناء الصورة وتشغيل الحاوية. يمكنك الوصول إلى واجهة المستخدم الرسومية (WebUI) على <code>http://localhost:7860</code> وخادم API على <code>http://localhost:8080</code>.</p>
<h3 id="docker_1">البناء اليدوي باستخدام Docker</h3>
<p>للمستخدمين المتقدمين الذين يرغبون في تخصيص عملية البناء:</p>
<div class="language-bash highlight"><pre><span></span><code><span id="__span-6-1"><a id="__codelineno-6-1" name="__codelineno-6-1" href="#__codelineno-6-1"></a><span class="c1"># بناء صورة واجهة المستخدم الرسومية (WebUI) مع دعم CUDA</span>
</span><span id="__span-6-2"><a id="__codelineno-6-2" name="__codelineno-6-2" href="#__codelineno-6-2"></a>docker<span class="w"> </span>build<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-3"><a id="__codelineno-6-3" name="__codelineno-6-3" href="#__codelineno-6-3"></a><span class="w">    </span>--platform<span class="w"> </span>linux/amd64<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-4"><a id="__codelineno-6-4" name="__codelineno-6-4" href="#__codelineno-6-4"></a><span class="w">    </span>-f<span class="w"> </span>docker/Dockerfile<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-5"><a id="__codelineno-6-5" name="__codelineno-6-5" href="#__codelineno-6-5"></a><span class="w">    </span>--build-arg<span class="w"> </span><span class="nv">BACKEND</span><span class="o">=</span>cuda<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-6"><a id="__codelineno-6-6" name="__codelineno-6-6" href="#__codelineno-6-6"></a><span class="w">    </span>--build-arg<span class="w"> </span><span class="nv">CUDA_VER</span><span class="o">=</span><span class="m">12</span>.6.0<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-7"><a id="__codelineno-6-7" name="__codelineno-6-7" href="#__codelineno-6-7"></a><span class="w">    </span>--build-arg<span class="w"> </span><span class="nv">UV_EXTRA</span><span class="o">=</span>cu126<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-8"><a id="__codelineno-6-8" name="__codelineno-6-8" href="#__codelineno-6-8"></a><span class="w">    </span>--target<span class="w"> </span>webui<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-9"><a id="__codelineno-6-9" name="__codelineno-6-9" href="#__codelineno-6-9"></a><span class="w">    </span>-t<span class="w"> </span>fish-speech-webui:cuda<span class="w"> </span>.
</span><span id="__span-6-10"><a id="__codelineno-6-10" name="__codelineno-6-10" href="#__codelineno-6-10"></a>
</span><span id="__span-6-11"><a id="__codelineno-6-11" name="__codelineno-6-11" href="#__codelineno-6-11"></a><span class="c1"># بناء صورة خادم API مع دعم CUDA</span>
</span><span id="__span-6-12"><a id="__codelineno-6-12" name="__codelineno-6-12" href="#__codelineno-6-12"></a>docker<span class="w"> </span>build<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-13"><a id="__codelineno-6-13" name="__codelineno-6-13" href="#__codelineno-6-13"></a><span class="w">    </span>--platform<span class="w"> </span>linux/amd64<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-14"><a id="__codelineno-6-14" name="__codelineno-6-14" href="#__codelineno-6-14"></a><span class="w">    </span>-f<span class="w"> </span>docker/Dockerfile<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-15"><a id="__codelineno-6-15" name="__codelineno-6-15" href="#__codelineno-6-15"></a><span class="w">    </span>--build-arg<span class="w"> </span><span class="nv">BACKEND</span><span class="o">=</span>cuda<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-16"><a id="__codelineno-6-16" name="__codelineno-6-16" href="#__codelineno-6-16"></a><span class="w">    </span>--build-arg<span class="w"> </span><span class="nv">CUDA_VER</span><span class="o">=</span><span class="m">12</span>.6.0<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-17"><a id="__codelineno-6-17" name="__codelineno-6-17" href="#__codelineno-6-17"></a><span class="w">    </span>--build-arg<span class="w"> </span><span class="nv">UV_EXTRA</span><span class="o">=</span>cu126<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-18"><a id="__codelineno-6-18" name="__codelineno-6-18" href="#__codelineno-6-18"></a><span class="w">    </span>--target<span class="w"> </span>server<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-19"><a id="__codelineno-6-19" name="__codelineno-6-19" href="#__codelineno-6-19"></a><span class="w">    </span>-t<span class="w"> </span>fish-speech-server:cuda<span class="w"> </span>.
</span><span id="__span-6-20"><a id="__codelineno-6-20" name="__codelineno-6-20" href="#__codelineno-6-20"></a>
</span><span id="__span-6-21"><a id="__codelineno-6-21" name="__codelineno-6-21" href="#__codelineno-6-21"></a><span class="c1"># بناء صورة CPU فقط (تدعم منصات متعددة)</span>
</span><span id="__span-6-22"><a id="__codelineno-6-22" name="__codelineno-6-22" href="#__codelineno-6-22"></a>docker<span class="w"> </span>build<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-23"><a id="__codelineno-6-23" name="__codelineno-6-23" href="#__codelineno-6-23"></a><span class="w">    </span>--platform<span class="w"> </span>linux/amd64,linux/arm64<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-24"><a id="__codelineno-6-24" name="__codelineno-6-24" href="#__codelineno-6-24"></a><span class="w">    </span>-f<span class="w"> </span>docker/Dockerfile<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-25"><a id="__codelineno-6-25" name="__codelineno-6-25" href="#__codelineno-6-25"></a><span class="w">    </span>--build-arg<span class="w"> </span><span class="nv">BACKEND</span><span class="o">=</span>cpu<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-26"><a id="__codelineno-6-26" name="__codelineno-6-26" href="#__codelineno-6-26"></a><span class="w">    </span>--target<span class="w"> </span>webui<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-27"><a id="__codelineno-6-27" name="__codelineno-6-27" href="#__codelineno-6-27"></a><span class="w">    </span>-t<span class="w"> </span>fish-speech-webui:cpu<span class="w"> </span>.
</span><span id="__span-6-28"><a id="__codelineno-6-28" name="__codelineno-6-28" href="#__codelineno-6-28"></a>
</span><span id="__span-6-29"><a id="__codelineno-6-29" name="__codelineno-6-29" href="#__codelineno-6-29"></a><span class="c1"># بناء صورة التطوير</span>
</span><span id="__span-6-30"><a id="__codelineno-6-30" name="__codelineno-6-30" href="#__codelineno-6-30"></a>docker<span class="w"> </span>build<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-31"><a id="__codelineno-6-31" name="__codelineno-6-31" href="#__codelineno-6-31"></a><span class="w">    </span>--platform<span class="w"> </span>linux/amd64<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-32"><a id="__codelineno-6-32" name="__codelineno-6-32" href="#__codelineno-6-32"></a><span class="w">    </span>-f<span class="w"> </span>docker/Dockerfile<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-33"><a id="__codelineno-6-33" name="__codelineno-6-33" href="#__codelineno-6-33"></a><span class="w">    </span>--build-arg<span class="w"> </span><span class="nv">BACKEND</span><span class="o">=</span>cuda<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-34"><a id="__codelineno-6-34" name="__codelineno-6-34" href="#__codelineno-6-34"></a><span class="w">    </span>--target<span class="w"> </span>dev<span class="w"> </span><span class="se">\</span>
</span><span id="__span-6-35"><a id="__codelineno-6-35" name="__codelineno-6-35" href="#__codelineno-6-35"></a><span class="w">    </span>-t<span class="w"> </span>fish-speech-dev:cuda<span class="w"> </span>.
</span></code></pre></div>
<h4 id="_4">وسيطات البناء</h4>
<ul>
<li><code>BACKEND</code>: <code>cuda</code> أو <code>cpu</code> (الافتراضي: <code>cuda</code>)</li>
<li><code>CUDA_VER</code>: إصدار CUDA (الافتراضي: <code>12.6.0</code>)</li>
<li><code>UV_EXTRA</code>: حزمة UV إضافية لـ CUDA (الافتراضي: <code>cu126</code>)</li>
<li><code>UBUNTU_VER</code>: إصدار Ubuntu (الافتراضي: <code>24.04</code>)</li>
<li><code>PY_VER</code>: إصدار Python (الافتراضي: <code>3.12</code>)</li>
</ul>
<h3 id="_5">تحميل المجلدات</h3>
<p>تتطلب كلتا الطريقتين تحميل المجلدات التالية:</p>
<ul>
<li><code>./checkpoints:/app/checkpoints</code> - مجلد أوزان النموذج</li>
<li><code>./references:/app/references</code> - مجلد ملفات الصوت المرجعية</li>
</ul>
<h3 id="_6">متغيرات البيئة</h3>
<ul>
<li><code>COMPILE=1</code> - تمكين <code>torch.compile</code> لتسريع الاستدلال (حوالي 10 أضعاف)</li>
<li><code>GRADIO_SERVER_NAME=0.0.0.0</code> - مضيف خادم واجهة المستخدم الرسومية (WebUI)</li>
<li><code>GRADIO_SERVER_PORT=7860</code> - منفذ خادم واجهة المستخدم الرسومية (WebUI)</li>
<li><code>API_SERVER_NAME=0.0.0.0</code> - مضيف خادم API</li>
<li><code>API_SERVER_PORT=8080</code> - منفذ خادم API</li>
</ul>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>تتوقع حاويات Docker أن يتم تحميل أوزان النموذج في <code>/app/checkpoints</code>. تأكد من تنزيل أوزان النموذج المطلوبة قبل بدء الحاويات.</p>
</div>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>يتطلب دعم GPU وجود NVIDIA Docker runtime. للنشر باستخدام CPU فقط، قم بإزالة علامة <code>--gpus all</code> واستخدم صور CPU.</p>
</div>


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