Simplify docker build. 简化dockerfile

Dockerfile

@@ -1,28 +1,15 @@
 # Use an official NVIDIA runtime with CUDA and Miniconda as a parent image
-FROM nvidia/cuda:12.2.0-base-ubuntu22.04
+FROM pytorch/pytorch:2.1.0-cuda11.8-cudnn8-runtime
 
-# Install Miniconda
-RUN apt-get update && apt-get install -y wget
-RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda.sh
-RUN bash ~/miniconda.sh -b -p $HOME/miniconda
-ENV PATH="/root/miniconda/bin:${PATH}"
-RUN conda init bash
+RUN apt-get update && apt-get install ffmpeg -y
 
 # Set the working directory in the container to /app
 WORKDIR /app
 
 # Add the current directory contents into the container at /app
 ADD . /app
 
-# Create a conda environment with the necessary packages
-RUN conda create -n pvtvzhen python=3.9
-
-# Make RUN commands use the new environment
-SHELL ["conda", "run", "-n", "pvtvzhen", "/bin/bash", "-c"]
-
 # Install dependencies
-RUN apt-get update && apt-get install ffmpeg libsm6 libxext6 -y
-RUN conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
 RUN pip install --upgrade pip
 RUN pip install -r requirements.txt
 
@@ -32,7 +19,7 @@ EXPOSE 8080
 # Define environment variable
 ENV FLASK_RUN_PORT 8080
 ENV FLASK_APP app.py
-ENV FLASK_DEBUG 1
+ENV FLASK_DEBUG 0
 
 # Run app.py when the container launches
-CMD [ "/bin/bash", "-c", "source activate pvtvzhen && python3 -m flask run --host=0.0.0.0" ]
+CMD [ "/bin/bash", "-c", "python -m flask run --host=0.0.0.0" ]

work_space.py

@@ -492,7 +492,6 @@ def srtToVoiceEdge(logger, srtFileNameAndPath, outputDir, character="zh-CN-Xiaoy
     fileMp3Names = []
 
     async def convertSrtToVoiceEdge(text, path):
-        print(f"Start to convert srt to voice into {path}, text: {text}")
         communicate = edge_tts.Communicate(text, character)
         await communicate.save(path)