Dockerfile

# Use an official Python runtime as a parent image
FROM python:3.8-slim

COPY --chown=user --from=stage /home/user/.cache /home/user/.cache

# Set the working directory to /app
WORKDIR /app

# Copy the current directory contents into the container at /app
COPY . /app

RUN apt-get update -y
RUN apt-get install -y python-gdbm
# Install any needed packages specified in requirements.txt
RUN pip install --trusted-host pypi.python.org -r requirements.txt && \
    pip uninstall transformers && \
    pip install transformers==4.29.2

# RUN --mount=type=cache,target=/home/user/.cache/

# Make port 80 available to the world outside this container
EXPOSE 80

# Set the TORTOISE_MODELS_DIR environment variable
# ENV TORTOISE_MODELS_DIR tortoise/models/pretrained_models

# Create the directory for pretrained models
# RUN mkdir -p $TORTOISE_MODELS_DIR

# RUN echo "Downloading models through docker container..."

# # Download all the models
# RUN wget -O $TORTOISE_MODELS_DIR/autoregressive.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/autoregressive.pth && \
#     wget -O $TORTOISE_MODELS_DIR/classifier.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/classifier.pth && \
#     wget -O $TORTOISE_MODELS_DIR/clvp2.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/clvp2.pth && \
#     wget -O $TORTOISE_MODELS_DIR/cvvp.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/cvvp.pth && \
#     wget -O $TORTOISE_MODELS_DIR/diffusion_decoder.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/diffusion_decoder.pth && \
#     wget -O $TORTOISE_MODELS_DIR/vocoder.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/vocoder.pth && \
#     wget -O $TORTOISE_MODELS_DIR/rlg_auto.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/rlg_auto.pth && \
#     wget -O $TORTOISE_MODELS_DIR/rlg_diffuser.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/rlg_diffuser.pth && \
#     wget -O $TORTOISE_MODELS_DIR/bigvgan_base_24khz_100band_g.pth https://drive.google.com/uc?id=1_cKskUDuvxQJUEBwdgjAxKuDTUW6kPdY && \
#     wget -O $TORTOISE_MODELS_DIR/bigvgan_24khz_100band_g.pth https://drive.google.com/uc?id=1wmP_mAs7d00KHVfVEl8B5Gb72Kzpcavp

# RUN echo "Finished downloading models through docker container..."

RUN echo "Current directory contents:"
RUN ls -la


# Run app.py when the container launches
CMD ["streamlit","run", "app.py"]