项目地址： https://github.com/index-tts/index-tts
本地部署步骤:
git clone https://github.com/index-tts/index-tts.git
-- 虚拟环境
conda create -n index-tts python=3.10
conda activate index-tts
conda install -c conda-forge ffmpeg
conda install -c conda-forge pynini==2.1.6
pip install WeTextProcessing --no-deps
pip install torch torchaudio --index-url https://download.pytorch.org/whl/cu118
pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
-- 魔搭
pip install modelscope -i https://pypi.tuna.tsinghua.edu.cn/simple
-- 下载模型
modelscope download --model IndexTeam/IndexTTS-1.5 --local_dir ./checkpoints
-- 启动
python webui.py --host=0.0.0.0 --port=9999
启动效果:
##################### 构建docker image #####################
1 确定需要用的cuda基础镜像
查询地址: https://hub.docker.com/r/nvidia/cuda/tags?name=11.8
2 确定本地cuda环境
如果
nvidia-smi报错，需先安装 NVIDIA 驱动
# 检查工具包是否安装成功 没有则安装 NVIDIA Container Toolkit rpm -qa | grep nvidia-container
编写脚本 Dockerfile 放 index-tts根目录
基础镜像依赖
FROM nvidia/cuda:11.8.0-base-ubuntu22.04
设置工作目录 类似mkdri + cd
WORKDIR /index-tts
本机内容复制进去 本地部署时包含了模型文件 会一起复制进去
COPY . /index-tts
liunx基本环境
RUN apt-get update
RUN apt-get install -y --no-install-recommends wget curl libgl1 libsm6
RUN apt-get clean
RUN rm -rf /var/lib/apt/lists/*
ENV CONDA_ROOT /opt/conda
ENV PATH CONDA_ROOT/bin:PATH
下载conda
RUN wget -q https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh && bash /tmp/miniconda.sh -b -p $CONDA_ROOT && rm /tmp/miniconda.sh
创建虚拟环境
RUN $CONDA_ROOT/bin/conda create -n index-tts python=3.10 -y
RUN $CONDA_ROOT/bin/conda install -n index-tts -c conda-forge ffmpeg pynini=2.1.6 -y
设置pip镜像
RUN $CONDA_ROOT/envs/index-tts/bin/pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple
cuda
RUN $CONDA_ROOT/envs/index-tts/bin/pip install torch torchaudio --index-url https://download.pytorch.org/whl/cu118
项目依赖
RUN $CONDA_ROOT/envs/index-tts/bin/pip install WeTextProcessing --no-deps
RUN $CONDA_ROOT/envs/index-tts/bin/pip install -r /index-tts/requirements.txt
暴露端口
EXPOSE 9999
一定要监听0.0.0.0 容器网络环境问题
CMD ["/bin/bash", "-c", "source $CONDA_ROOT/bin/activate index-tts && python webui.py --host=0.0.0.0 --port=9999"]
构建日志 下载cuda很久 可以考虑本机下载后直接复制到容器
(base) [root@lsp-home-centos7 index-tts]# docker build -t lspindextts .
+\] Building 3775.5s (19/19) FINISHED docker:default =\> \[internal\] load build definition from Dockerfile 0.0s =\> =\> transferring dockerfile: 1.20kB 0.0s =\> \[internal\] load metadata for docker.io/nvidia/cuda:11.8.0-base-ubuntu22.04 32.1s =\> \[internal\] load .dockerignore 0.0s =\> =\> transferring context: 65B 0.0s =\> \[internal\] load build context 0.0s =\> =\> transferring context: 4.61kB 0.0s =\> \[ 1/14\] FROM docker.io/nvidia/cuda:11.8.0-base-ubuntu22.04@sha256:f895871972c1c91eb6a896eee68468f40289395a1e58c492e1be7929d0f8703b 0.0s =\> CACHED \[ 2/14\] WORKDIR /index-tts 0.0s =\> CACHED \[ 3/14\] RUN apt-get update 0.0s =\> CACHED \[ 4/14\] RUN apt-get install -y --no-install-recommends wget curl libgl1 libsm6 0.0s =\> CACHED \[ 5/14\] RUN apt-get clean 0.0s =\> CACHED \[ 6/14\] RUN rm -rf /var/lib/apt/lists/\* 0.0s =\> CACHED \[ 7/14\] RUN wget -q [https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh](https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh "https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh") -O /tmp/miniconda.sh \&\& bash /tmp/miniconda.sh -b -p /opt/conda \&\& rm /tmp/miniconda.sh 0.0s =\> CACHED \[ 8/14\] RUN /opt/conda/bin/conda create -n index-tts python=3.10 -y 0.0s =\> CACHED \[ 9/14\] RUN /opt/conda/bin/conda install -n index-tts -c conda-forge ffmpeg pynini=2.1.6 -y 0.0s =\> \[10/14\] RUN /opt/conda/envs/index-tts/bin/pip install WeTextProcessing --no-deps -i [Simple Index](https://mirrors.aliyun.com/pypi/simple "Simple Index") 3.0s =\> \[11/14\] RUN /opt/conda/envs/index-tts/bin/pip config set global.index-url [Simple Index](https://pypi.tuna.tsinghua.edu.cn/simple "Simple Index") 0.6s =\> \[12/14\] RUN /opt/conda/envs/index-tts/bin/pip install torch torchaudio --index-url [https://download.pytorch.org/whl/cu118](https://download.pytorch.org/whl/cu118 "https://download.pytorch.org/whl/cu118") 3416.4s =\> \[13/14\] COPY . /index-tts 64.6s =\> \[14/14\] RUN /opt/conda/envs/index-tts/bin/pip install -r /index-tts/requirements.txt -i [Simple Index](https://pypi.tuna.tsinghua.edu.cn/simple "Simple Index") 143.9s =\> exporting to image 114.6s =\> =\> exporting layers 114.5s =\> =\> writing image sha256:d27bc73d51d8b4721b60c6bc5c58cc23b2fd226279bc33477317fcb81721d44c 0.0s =\> =\> naming to docker.io/library/lspindextts 0.0s (base) \[root@lsp-home-centos7 index-tts\]# docker images REPOSITORY TAG IMAGE ID CREATED SIZE lspindextts latest d27bc73d51d8 6 hours ago 18GB portainer/portainer-ce latest 2a17f0992b45 7 weeks ago 268MB milvusdb/milvus v2.5.7 9a1923427d52 3 months ago 1.72GB apache/kafka latest 12b98f0f2c1f 3 months ago 425MB zookeeper latest 3111c3ba944e 8 months ago 313MB spoonest/clickhouse-tabix-web-client latest e872c1a905d9 7 years ago 245MB (base) \[root@lsp-home-centos7 index-tts\]# **docker run -it --name lsptts --gpus all -p 9999:9999 lspindextts** \>\> GPT weights restored from: checkpoints/gpt.pth \>\> DeepSpeed加载失败，回退到标准推理: No module named 'deepspeed' See more details [Installation Details - DeepSpeed](https://www.deepspeed.ai/tutorials/advanced-install/ "Installation Details - DeepSpeed") \>\> Failed to load custom CUDA kernel for BigVGAN. Falling back to torch. Ninja is required to load C++ extensions Reinstall with \`pip install -e . --no-deps --no-build-isolation\` to prebuild \`anti_alias_activation_cuda\` kernel. See more details: [https://github.com/index-tts/index-tts/issues/164#issuecomment-2903453206](https://github.com/index-tts/index-tts/issues/164#issuecomment-2903453206 "https://github.com/index-tts/index-tts/issues/164#issuecomment-2903453206") Removing weight norm... \>\> bigvgan weights restored from: checkpoints/bigvgan_generator.pth 2025-07-01 23:29:17,382 WETEXT INFO building fst for zh_normalizer ... 2025-07-01 23:29:52,757 WETEXT INFO done 2025-07-01 23:29:52,758 WETEXT INFO fst path: /index-tts/indextts/utils/tagger_cache/zh_tn_tagger.fst 2025-07-01 23:29:52,758 WETEXT INFO /index-tts/indextts/utils/tagger_cache/zh_tn_verbalizer.fst 2025-07-01 23:29:52,766 WETEXT INFO found existing fst: /opt/conda/envs/index-tts/lib/python3.10/site-packages/tn/en_tn_tagger.fst 2025-07-01 23:29:52,766 WETEXT INFO /opt/conda/envs/index-tts/lib/python3.10/site-packages/tn/en_tn_verbalizer.fst 2025-07-01 23:29:52,766 WETEXT INFO skip building fst for en_normalizer ... \>\> TextNormalizer loaded \>\> bpe model loaded from: checkpoints/bpe.model \* Running on local URL: [http://0.0.0.0:9999](http://0.0.0.0:9999 "http://0.0.0.0:9999") \* To create a public link, set \`share=True\` in \`launch()\`.
##image 可以推送到自己的docker仓库 后续其他环境可以image pull拉取使用 !