Can I see what your Dockerfile looks like?

```

FROM python:3.11-slim

# Install system dependencies
RUN apt-get update && apt-get install -y \
    build-essential \
    git \
    && rm -rf /var/lib/apt/lists/*

# Set working directory
WORKDIR /app

# Copy requirements first to leverage Docker cache
COPY requirements.txt .

# Install Python dependencies
RUN pip install --no-cache-dir --upgrade pip && \
    pip install --no-cache-dir torch torchvision --index-url https://download.pytorch.org/whl/cpu && \
    pip install --no-cache-dir -r requirements.txt

# Copy the entire application with the correct structure
COPY . .

# Set Python path - this is important because you have nested modules
ENV PYTHONPATH="${PYTHONPATH}:/app"

# Create a non-root user and set proper permissions
RUN useradd -m appuser && \
    chown -R appuser:appuser /app && \
    chmod -R 755 /app

USER appuser

# Expose the port the app runs on
EXPOSE 8000

# Command to run the application
CMD ["uvicorn", "server:app", "--host", "0.0.0.0", "--port", "8000"]```

I can see that its a lot of import errors in the build but I am not able to understand why my local build works but this does not.

Issue might be from the PYTHONPATH. Is setting it that way correct?

Can you try it without setting the PATH?

gotcha lemme get back to you on this once

just tried doing this, still getting the same error, if you see the logs its a path issue which we are not able to recreate locally

Have you been able to build with that Dockerfile locally and then run the image?

I need to know what errors you are getting run it with Dockerfile locally

yes we have been able to build it locally and it works, but not on railway

Can i see a screenshot of it working on Docker locally?

this is the screenshot

any chance we can setup a short call to discuss this once?

Can you try this?

```
FROM python:3.11-slim

RUN apt-get update && apt-get install -y \

build-essential \

git \

&& rm -rf /var/lib/apt/lists/*

WORKDIR /app

COPY requirements.txt .

RUN pip install --no-cache-dir --upgrade pip && \

pip install --no-cache-dir torch torchvision --index-url https://download.pytorch.org/whl/cpu && \

pip install --no-cache-dir -r requirements.txt

COPY . .

ENV PYTHONPATH=/app

EXPOSE 8000

CMD ["uvicorn", "server:app", "--host", "0.0.0.0", "--port", "8000"]

```

still facing the same issue. the docker container is working locally as well

I really don't know what could be wrong here. Is your server.py file in the root of your directory?

I think you should consider using a virtual environment within your Docker container. Here's a blog post I wrote on deploying Django but can be used for yours with a few tweaks. You might consider using gunicorn with unicorn workers. Original post is here but the Dockerfile is:

# Set the python version as a build-time argument

# with Python 3.12 as the default

ARG PYTHON_VERSION=3.12-slim-bullseye

FROM python:${PYTHON_VERSION}

# Create a virtual environment

RUN python -m venv /opt/venv

# Set the virtual environment as the current location

ENV PATH=/opt/venv/bin:$PATH

# Upgrade pip

RUN pip install --upgrade pip

# Set Python-related environment variables

ENV PYTHONDONTWRITEBYTECODE 1

ENV PYTHONUNBUFFERED 1

# Install os dependencies for our mini vm

RUN apt-get update && apt-get install -y \

# for postgres

libpq-dev \

# for Pillow

libjpeg-dev \

# for CairoSVG

libcairo2 \

# other

gcc \

&& rm -rf /var/lib/apt/lists/*

# Create the mini vm's code directory

RUN mkdir -p /code

# Set the working directory to that same code directory

WORKDIR /code

# Copy the requirements file into the container

COPY requirements.txt /tmp/requirements.txt

# copy the project code into the container's working directory

COPY ./src /code

# Install the Python project requirements

RUN pip install -r /tmp/requirements.txt

# database isn't available during build

# run any other commands that do not need the database

# such as:

# RUN python manage.py collectstatic --noinput

# set the Django default project name

ARG PROJ_NAME="cfehome"

# create a bash script to run the Django project

# this script will execute at runtime when

# the container starts and the database is available

RUN printf "#!/bin/bash\n" > ./paracord_runner.sh && \

printf "RUN_PORT=\"\${PORT:-8000}\"\n\n" >> ./paracord_runner.sh && \

printf "python manage.py migrate --no-input\n" >> ./paracord_runner.sh && \

printf "gunicorn ${PROJ_NAME}.wsgi:application --bind \"0.0.0.0:\$RUN_PORT\"\n" >> ./paracord_runner.sh

# make the bash script executable

RUN chmod +x paracord_runner.sh

# Clean up apt cache to reduce image size

RUN apt-get remove --purge -y \

&& apt-get autoremove -y \

&& apt-get clean \

&& rm -rf /var/lib/apt/lists/*

# Run the Django project via the runtime script

# when the container starts

CMD ./paracord_runner.sh

I have found that using a script as your run command yields more consistent results. To make this work, you'd change:

RUN printf "#!/bin/bash\n" > ./paracord_runner.sh && \

printf "RUN_PORT=\"\${PORT:-8000}\"\n\n" >> ./paracord_runner.sh && \

printf "python manage.py migrate --no-input\n" >> ./paracord_runner.sh && \

printf "gunicorn ${PROJ_NAME}.wsgi:application --bind \"0.0.0.0:\$RUN_PORT\"\n" >> ./paracord_runner.sh

To

RUN printf "#!/bin/bash\n" > ./paracord_runner.sh && \

printf "RUN_PORT=\"\${PORT:-8000}\"\n\n" >> ./paracord_runner.sh && \

printf "gunicorn server:app -k uvicorn.workers.UvicornWorker--bind \"0.0.0.0:\$RUN_PORT\"\n" >> ./paracord_runner.sh

Be sure to add guincorn to requirements.txt and/or as another step within the dockerfile. Try this with and without pytorch.

Edit: Sorry for the formatting, multi-line code pasting isn't working for some reason.