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change the app that is going to run

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samiabat 2025-03-24 23:57:43 +03:00
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@ -1,148 +1,42 @@
# # Base CUDA image
# FROM cnstark/pytorch:2.0.1-py3.9.17-cuda11.8.0-ubuntu20.04
# Base CUDA image
FROM cnstark/pytorch:2.0.1-py3.9.17-cuda11.8.0-ubuntu20.04
# LABEL maintainer="breakstring@hotmail.com"
# LABEL version="dev-20240209"
# LABEL description="Docker image for GPT-SoVITS"
LABEL maintainer="breakstring@hotmail.com"
LABEL version="dev-20240209"
LABEL description="Docker image for GPT-SoVITS"
# # Install 3rd party apps
# ENV DEBIAN_FRONTEND=noninteractive
# ENV TZ=Etc/UTC
# RUN apt-get update && \
# apt-get install -y --no-install-recommends tzdata ffmpeg libsox-dev parallel aria2 git git-lfs && \
# git lfs install && \
# rm -rf /var/lib/apt/lists/*
# # Copy only requirements.txt initially to leverage Docker cache
# WORKDIR /workspace
# COPY requirements.txt /workspace/
# RUN pip install --no-cache-dir -r requirements.txt
# # Define a build-time argument for image type
# ARG IMAGE_TYPE=full
# # Conditional logic based on the IMAGE_TYPE argument
# # Always copy the Docker directory, but only use it if IMAGE_TYPE is not "elite"
# COPY ./Docker /workspace/Docker
# # elite 类型的镜像里面不包含额外的模型
# RUN if [ "$IMAGE_TYPE" != "elite" ]; then \
# chmod +x /workspace/Docker/download.sh && \
# /workspace/Docker/download.sh && \
# python -m nltk.downloader averaged_perceptron_tagger cmudict; \
# fi
# # Copy the rest of the application
# COPY . /workspace
# EXPOSE 9871 9872 9873 9874 9880
# CMD ["python", "webui.py"]
# Use official Ubuntu 22.04 as base image
# FROM ubuntu:22.04
# # Set working directory
# WORKDIR /app/GPT-SoVITS
# # Set environment variables
# ENV DEBIAN_FRONTEND=noninteractive
# ENV PATH="/usr/local/bin:${PATH}"
# # Install basic dependencies
# RUN apt-get update && apt-get install -y \
# git \
# wget \
# curl \
# cmake \
# ffmpeg \
# && rm -rf /var/lib/apt/lists/*
# # Install Miniconda
# RUN wget https://repo.anaconda.com/miniconda/Miniconda3-py39_23.11.0-2-Linux-x86_64.sh -O miniconda.sh \
# && bash miniconda.sh -b -p /opt/conda \
# && rm miniconda.sh
# # Add conda to PATH
# ENV PATH="/opt/conda/bin:${PATH}"
# # Copy the current directory contents (GPT-SoVITS) into the container
# COPY . .
# # Install Conda dependencies
# RUN conda install -y -q -c pytorch -c nvidia cudatoolkit \
# && conda install -y -q -c conda-forge gcc gxx ffmpeg cmake -c pytorch -c nvidia
# # Install Python requirements
# RUN pip install -r requirements.txt
# # Install additional Python packages
# RUN pip install ipykernel
# # Modify config.py to enable WebUI
# RUN sed -i '10s/False/True/' config.py
# # Expose port for WebUI
# EXPOSE 5000
# # Set entrypoint to launch WebUI
# CMD ["python", "api.py"]
# Use official Ubuntu 22.04 as base image
FROM ubuntu:22.04
# Set working directory
WORKDIR /app/GPT-SoVITS
# Set environment variables
# Install 3rd party apps
ENV DEBIAN_FRONTEND=noninteractive
ENV PATH="/opt/conda/bin:${PATH}"
ENV TZ=Etc/UTC
RUN apt-get update && \
apt-get install -y --no-install-recommends tzdata ffmpeg libsox-dev parallel aria2 git git-lfs && \
git lfs install && \
rm -rf /var/lib/apt/lists/*
# Install basic dependencies including git-lfs
RUN apt-get update && apt-get install -y \
git \
git-lfs \
wget \
curl \
cmake \
ffmpeg \
&& git lfs install \
&& rm -rf /var/lib/apt/lists/*
# Copy only requirements.txt initially to leverage Docker cache
WORKDIR /workspace
COPY requirements.txt /workspace/
RUN pip install --no-cache-dir -r requirements.txt
# Install Miniconda
RUN wget https://repo.anaconda.com/miniconda/Miniconda3-py39_23.11.0-2-Linux-x86_64.sh -O miniconda.sh \
&& bash miniconda.sh -b -p /opt/conda \
&& rm miniconda.sh
# Define a build-time argument for image type
ARG IMAGE_TYPE=full
# Clone the repository inside the container (Fixes Git LFS issue)
RUN git clone --recursive https://github.com/ivy-consulting/GPT-SoVITS.git /app/GPT-SoVITS \
&& cd /app/GPT-SoVITS \
&& git lfs install \
&& git lfs pull
# Conditional logic based on the IMAGE_TYPE argument
# Always copy the Docker directory, but only use it if IMAGE_TYPE is not "elite"
COPY ./Docker /workspace/Docker
# elite 类型的镜像里面不包含额外的模型
RUN if [ "$IMAGE_TYPE" != "elite" ]; then \
chmod +x /workspace/Docker/download.sh && \
/workspace/Docker/download.sh && \
python /workspace/Docker/download.py && \
python -m nltk.downloader averaged_perceptron_tagger cmudict; \
fi
# Copy local pretrained models (overwrite if necessary)
COPY GPT_SoVITS/pretrained_models/ /app/GPT-SoVITS/GPT_SoVITS/pretrained_models/
# Ensure LFS files are pulled again (to verify all files are present)
RUN cd /app/GPT-SoVITS && git lfs pull
# Copy the rest of the application
COPY . /workspace
# Install Conda dependencies
RUN conda install -y -q -c pytorch -c nvidia cudatoolkit \
&& conda install -y -q -c conda-forge gcc gxx ffmpeg cmake
# Upgrade pip and install Python requirements
RUN pip install --upgrade pip \
&& pip install -r requirements.txt
# Install additional Python packages
RUN pip install ipykernel
# Modify config.py to enable WebUI
RUN sed -i '10s/False/True/' config.py
# Expose port for
EXPOSE 5000
# Set entrypoint to launch
CMD ["python", "api.py"]
CMD ["python", "api.py"]