Update Dockerfile

Dockerfile

@@ -1,37 +1,28 @@
+# Use a slim official Python image
 FROM python:3.10-slim
 
-ENV PYTHONDONTWRITEBYTECODE=1
-ENV PYTHONUNBUFFERED=1
-ENV HF_HOME=/app/hf_cache
-ENV NLTK_DATA=/app/nltk_data
-ENV PORT=8080
+# Create a new user
+RUN useradd -m appuser
 
-WORKDIR /app
+# Set work directory
+WORKDIR /home/appuser/app
 
-# System dependencies
-RUN apt-get update && apt-get install -y \
-    gcc \
-    python3-dev \
-    curl \
-    && rm -rf /var/lib/apt/lists/*
-
-# Copy code and install Python deps
+# Copy and install dependencies
 COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt
 
-# Download NLTK data
-RUN python -c "import nltk; nltk.download('punkt', download_dir='/app/nltk_data')"
-
-# Preload huggingface model (optional)
-RUN python -c "from transformers import AutoTokenizer, AutoModelForSequenceClassification; \
-               AutoTokenizer.from_pretrained('priyabrat/AI.or.Human.text.classification', cache_dir='/app/hf_cache'); \
-               AutoModelForSequenceClassification.from_pretrained('priyabrat/AI.or.Human.text.classification', cache_dir='/app/hf_cache')"
-
-# Copy all app files
+# Copy code and give permissions
 COPY . .
 
-# Fix permissions — make hf_cache and nltk_data writable by everyone
-RUN chmod -R 777 /app/hf_cache /app/nltk_data || true
+# Change ownership and switch to non-root
+RUN chown -R appuser:appuser /home/appuser
+USER appuser
 
+# Download NLTK tokenizer data
+RUN python -c "import nltk; nltk.download('punkt')"
+
+# Expose port
 EXPOSE 8080
-CMD ["gunicorn", "app:app"]
+
+# Run using uvicorn
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8080"]