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#!/bin/bash
# Source the virtual environment
source /app/venv/bin/activate
# Starting server
echo "Starting Ollama server"
ollama serve &
sleep 1
# Try to get the model environment variable
if [ -n "${MODEL}" ]; then
# Split the MODEL variable into an array
IFS=',' read -ra MODELS <<< "${MODEL}"
else
# Use the default list of models
MODELS=(llama3 ) #gemma:2b phi3 mistral
fi
# Splitting the models by comma and pulling each
#IFS=',' read -ra MODELS <<< "$model"
for m in "${MODELS[@]}"; do
echo "Pulling $m"
ollama pull "$m"
sleep 5
done
ollama create aws-path-learning -f ./Modelfile
# Run the Python application
#streamlit run ./src/app.py
# Run the Python application
#streamlit run --server.address 0.0.0.0 ./src/app.py
streamlit run ./src/app.py --server.port 7860 --server.address 0.0.0.0
# Keep the script running to prevent the container from exiting
#wait |