Upload folder using huggingface_hub

Dockerfile

@@ -1,32 +1,24 @@
-# Use a minimal Python base image
-FROM python:3.9-slim
+# Use a minimal base image with Python 3.9 installed
+FROM python:3.9
 
-# Set the working directory
+# Set the working directory inside the container to /app
 WORKDIR /app
 
-# Install system dependencies and create a user first
-RUN apt-get update && apt-get install -y --no-install-recommends \
-    build-essential \
-    && useradd -m -u 1000 user \
-    && rm -rf /var/lib/apt/lists/*
+# Copy all files from the current directory on the host to the container's /app directory
+COPY . .
 
-# Copy all files into /app
-COPY . /app
-
-# Install Python dependencies
-RUN pip install --no-cache-dir --upgrade pip setuptools wheel \
-    && pip install --no-cache-dir -r requirements.txt
-
-# Switch to non-root user
 USER user
 ENV HOME=/home/user \
-    PATH=/home/user/.local/bin:$PATH
+	PATH=/home/user/.local/bin:$PATH
+
+# Install Python dependencies listed in requirements.txt
+RUN pip3 install -r requirements.txt
+
+RUN useradd -m -u 1000 user
 
-# Set working dir for the app
 WORKDIR $HOME/app
 
-# Copy source code again as user (if needed for ownership)
 COPY --chown=user . $HOME/app
 
-# Default command to launch Streamlit
+# Define the command to run the Streamlit app on port "8501" and make it accessible externally
 CMD ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0", "--server.enableXsrfProtection=false"]

app.py

@@ -2,12 +2,13 @@
 import streamlit as st
 import pandas as pd
 import joblib
-from huggingface_hub import hf_hub_download
+
 
 # Download and load the model
 model_path = hf_hub_download(repo_id="Pushpak21/tourism-package-model", filename="best_tourism_package_model.joblib")
 model = joblib.load(model_path)
 
+
 # Feature descriptions
 feature_info = {
     "Age": "Age of the customer (years).",