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<h2 id="requirements">Requirements</h2>
<ul>
<li>GPU Memory: 24GB (Inference)</li>
<li>System: Linux, WSL</li>
</ul>
<h2 id="system-setup">System Setup</h2>
<p>Fish Audio S2 supports multiple installation methods. Choose the one that best fits your development environment.</p>
<p><strong>Prerequisites</strong>: Install system dependencies for audio processing:
<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"># GPU installation (choose your CUDA version: 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"># CPU-only installation</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"># Default installation (uses PyTorch default index)</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"># If you encounter an error during installation due to pyaudio, consider using the following command:</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"># Then run pip install -e . again</span>
</span></code></pre></div>
<h3 id="uv">UV</h3>
<p>UV provides faster dependency resolution and installation:</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"># GPU installation (choose your CUDA version: 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"># CPU-only installation</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-support">Intel Arc XPU support</h3>
<p>For Intel Arc GPU users, install with XPU support:</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"># Install required C++ standard library</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"># Install PyTorch with Intel XPU support</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"># Install 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>The <code>compile</code> option is not supported on Windows and macOS. If you want to run with compile, you need to install Triton manually.</p>
</div>
<h2 id="docker-setup">Docker Setup</h2>
<p>Fish Audio S2 series model provides multiple Docker deployment options to suit different needs. You can use pre-built images from Docker Hub, build locally with Docker Compose, or manually build custom images.</p>
<p>We provide Docker images for both WebUI and API server on both GPU (CUDA126 by default) and CPU. You can use the pre-built images from Docker Hub, build locally with Docker Compose, or manually build custom images. If you want to build locally, follow the instructions below. If you only want to use pre-built images, follow the <a href="../inference/">inference guide</a>.</p>
<h3 id="prerequisites">Prerequisites</h3>
<ul>
<li>Docker and Docker Compose installed</li>
<li>NVIDIA Docker runtime (for GPU support)</li>
<li>At least 24GB GPU memory for CUDA inference</li>
</ul>
<h1 id="use-docker-compose">Use docker compose</h1>
<p>For development or customization, you can use Docker Compose to build and run locally:</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"># Clone the repository first</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"># Start WebUI with 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"># Start WebUI with compile optimization</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"># Start API server</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"># Start API server with compile optimization  </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"># For CPU-only deployment</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="environment-variables-for-docker-compose">Environment Variables for Docker Compose</h4>
<p>You can customize the deployment using environment variables:</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"># .env file example</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"># or 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"># Enable compile optimization</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"># WebUI port</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"># API server port</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"># UV package manager version</span>
</span><span id="__span-5-7"><a id="__codelineno-5-7" name="__codelineno-5-7" href="#__codelineno-5-7"></a><span class="nv">CUDA_VER</span><span class="o">=</span><span class="m">12</span>.9.0<span class="w">          </span><span class="c1"># CUDA base image version (e.g. 12.6.0 for older drivers)</span>
</span><span id="__span-5-8"><a id="__codelineno-5-8" name="__codelineno-5-8" href="#__codelineno-5-8"></a><span class="nv">UV_EXTRA</span><span class="o">=</span>cu129<span class="w">           </span><span class="c1"># PyTorch CUDA variant (cu126, cu128, cu129) — must match CUDA_VER</span>
</span></code></pre></div>
<p>The command will build the image and run the container. You can access the WebUI at <code>http://localhost:7860</code> and the API server at <code>http://localhost:8080</code>.</p>
<h3 id="manual-docker-build">Manual Docker Build</h3>
<p>For advanced users who want to customize the build process:</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"># Build WebUI image with CUDA support</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>.9.0<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>cu129<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"># Build API server image with CUDA support</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>.9.0<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>cu129<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"># Build CPU-only images (supports multi-platform)</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"># Build development image</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="build-arguments">Build Arguments</h4>
<ul>
<li><code>BACKEND</code>: <code>cuda</code> or <code>cpu</code> (default: <code>cuda</code>)</li>
<li><code>CUDA_VER</code>: CUDA version (default: <code>12.6.0</code>)</li>
<li><code>UV_EXTRA</code>: UV extra for CUDA (default: <code>cu126</code>)</li>
<li><code>UBUNTU_VER</code>: Ubuntu version (default: <code>24.04</code>)</li>
<li><code>PY_VER</code>: Python version (default: <code>3.12</code>)</li>
</ul>
<h3 id="volume-mounts">Volume Mounts</h3>
<p>Both methods require mounting these directories:</p>
<ul>
<li><code>./checkpoints:/app/checkpoints</code> - Model weights directory</li>
<li><code>./references:/app/references</code> - Reference audio files directory</li>
</ul>
<h3 id="environment-variables">Environment Variables</h3>
<ul>
<li><code>COMPILE=1</code> - Enable torch.compile for faster inference (~10x speedup)</li>
<li><code>GRADIO_SERVER_NAME=0.0.0.0</code> - WebUI server host</li>
<li><code>GRADIO_SERVER_PORT=7860</code> - WebUI server port</li>
<li><code>API_SERVER_NAME=0.0.0.0</code> - API server host  </li>
<li><code>API_SERVER_PORT=8080</code> - API server port</li>
</ul>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>The Docker containers expect model weights to be mounted at <code>/app/checkpoints</code>. Make sure to download the required model weights before starting the containers.</p>
</div>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>GPU support requires NVIDIA Docker runtime. For CPU-only deployment, remove the <code>--gpus all</code> flag and use CPU images.</p>
</div>


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