Update Dockerfile

Dockerfile

@@ -1,47 +1,60 @@
-# Dockerfile — patched: python:3.11-slim + system libs + baked model + /tmp/model perms
-FROM python:3.11-slim
+# Dockerfile
+FROM python:3.10-slim
 
-ENV DEBIAN_FRONTEND=noninteractive \
-    PYTHONUNBUFFERED=1 \
-    STREAMLIT_SERVER_HEADLESS=true \
-    STREAMLIT_SERVER_RUN_ON_SAVE=false \
-    STREAMLIT_SERVER_ENABLECORS=false \
-    STREAMLIT_SERVER_PORT=8501 \
-    STREAMLIT_SERVER_ADDRESS=0.0.0.0
+# Set non-root user if you want (optional)
+# RUN adduser --disabled-password appuser
+# USER appuser
 
+ENV DEBIAN_FRONTEND=noninteractive
 WORKDIR /app
 
-# Install minimal system libs needed by numpy/scipy/xgboost wheels
-RUN apt-get update && apt-get install -y --no-install-recommends \
-    libgomp1 \
-    libopenblas-dev \
-    ca-certificates \
-    && rm -rf /var/lib/apt/lists/*
-
-# Copy project files into image
-COPY . /app
+# Build args for secret/token usage at build time (if you provide it)
+ARG HF_TOKEN
+ENV HF_TOKEN=${HF_TOKEN}
 
-# Ensure /tmp/model exists and is writable by the runtime non-root user (UID 1000).
-# Also copy a baked model if present in repo root, and set permissive ownership/permissions.
-RUN mkdir -p /tmp/model && \
-    cp /app/best_overall_XGBoost.joblib /tmp/model/best_overall_XGBoost.joblib 2>/dev/null || true && \
-    chown -R 1000:1000 /tmp/model && \
-    chmod -R a+rwx /tmp/model
+# Copy requirements first for better caching
+COPY requirements.txt /app/requirements.txt
 
-# Upgrade pip & install Python dependencies from requirements.txt
-RUN python -m pip install --upgrade pip setuptools wheel
-RUN pip install --no-cache-dir -r requirements.txt
+# Install system deps and python deps
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        ca-certificates \
+        git \
+    && rm -rf /var/lib/apt/lists/*
 
-# Create non-root user and switch
-RUN useradd -m -u 1000 user
-USER user
-ENV HOME=/home/user PATH=/home/user/.local/bin:$PATH
+RUN pip install --upgrade pip
+RUN pip install -r /app/requirements.txt
 
-# Use user's home app dir for runtime; copy app files there
-WORKDIR $HOME/app
-RUN cp -r /app/* $HOME/app/ || true
+# Copy app source
+COPY . /app
 
+# Pre-download model during build (if HF_TOKEN / repo available)
+# This will try to download the model and save it to the HF cache; it will also
+# leave a copy in the default cache path which is fine for runtime.
+RUN python - <<'PY'
+import os, sys
+from huggingface_hub import hf_hub_download
+repo = os.getenv("HF_MODEL_REPO", "sathishaiuse/wellness-classifier-model")
+fname = os.getenv("HF_MODEL_FILENAME", "best_overall_XGBoost.joblib")
+token = os.getenv("HF_TOKEN") or None
+try:
+    print("Attempting to pre-download model:", repo, fname, "token_present=", bool(token))
+    path = hf_hub_download(repo_id=repo, filename=fname, token=token)
+    print("Model downloaded to:", path)
+    # Also copy to /app for easier direct loading if desired
+    import shutil
+    dest = os.path.join("/app", os.path.basename(path))
+    try:
+        shutil.copy(path, dest)
+        print("Copied model to", dest)
+    except Exception as e:
+        print("Could not copy model to /app:", e)
+except Exception as e:
+    print("Pre-download failed (continues build). Error:", e)
+PY
+
+# Expose port for local testing (Streamlit default 8501)
 EXPOSE 8501
 
-# Run streamlit with explicit flags (single-line JSON array)
-CMD ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0", "--server.headless=true", "--server.runOnSave=false", "--server.enableCORS=false", "--server.enableXsrfProtection=false", "--logger.level=debug"]
+# default command for Streamlit (adjust if your original app uses different flags)
+CMD ["streamlit", "run", "app.py", "--server.port=8501", "--server.headless=true"]