Dockerfile

# First stage: Build and load the dataset
FROM python:3.9 as core

# Set the working directory
WORKDIR /app/core

# Copy and install core requirements
COPY ./core/requirements.txt ./requirements.txt
RUN pip install -r requirements.txt

# Copy the core files
COPY ./core .

# Set the PYTHONPATH to include the /app/core directory
ENV PYTHONPATH="/app/core"

# Run the initialization script to load and serialize the dataset
RUN python initialization.py

# Second stage: Set up the API
FROM python:3.9

# Set the working directory
WORKDIR /app/api

# Copy and install API requirements
COPY ./api/requirements.txt ./requirements.txt
RUN pip install -r requirements.txt

# Copy the API files
COPY ./api .

# Copy the serialized engine from the first stage
COPY --from=core /app/core/engine.pickle /app/api/engine.pickle

# Expose the API port
EXPOSE 9999

# Run the service manager
ENTRYPOINT ["python", "service_manager.py"]

# FROM python:3.9 as core
#
# COPY ./core/requirements.txt ./requirements.txt
# RUN pip install -r requirements.txt
#
# WORKDIR /app/core
#
# COPY ./core .
# RUN python ./initialization.py
#
# FROM python:3.9
#
# COPY ./api/requirements.txt ./requirements.txt
# RUN pip install -r requirements.txt
#
# WORKDIR /app/api
# COPY ./api .
#
# COPY --from=core /app/engine.pickle /app/engine.pickle
#
# EXPOSE 9999
# ENTRYPOINT ["python", "service_manager.py"]

# FROM python:3.9 as build
#
# COPY ./requirements.txt ./requirements.txt
# RUN pip install -r requirements.txt
#
# WORKDIR /app
#
# COPY . .
#
# RUN mkdir -p /app/cache && chmod -R 777 /app/cache
#
# ENV TRANSFORMERS_CACHE=/app/cache
#
# EXPOSE 9999
# ENTRYPOINT ["python", "run.py"]