Update Dockerfile

Dockerfile

@@ -1,22 +1,43 @@
-FROM python:3.9-slim
+# Dockerfile — predownload model at build time (recommended)
+FROM python:3.11-slim
 
 ENV DEBIAN_FRONTEND=noninteractive
 WORKDIR /app
 
+# system deps
 RUN apt-get update && apt-get install -y --no-install-recommends \
-    build-essential libgomp1 ca-certificates && rm -rf /var/lib/apt/lists/*
+    ca-certificates libgomp1 && rm -rf /var/lib/apt/lists/*
 
+# copy code & requirements
 COPY . /app
 
+# upgrade pip
 RUN python -m pip install --upgrade pip setuptools wheel
+
+# install only Python deps first
 RUN pip install --no-cache-dir -r requirements.txt
 
+# Download model from HF into /opt/model at build-time
+# If repo is private, set build secret or pass HF_TOKEN as build-arg (see notes below)
+ARG HF_MODEL_REPO="sathishaiuse/wellness-classifier-model"
+ARG HF_MODEL_FILENAME=""
+ARG HF_TOKEN=""
+RUN python - <<PY
+from huggingface_hub import snapshot_download
+import os
+repo = os.environ.get('HF_MODEL_REPO', '${HF_MODEL_REPO}')
+token = os.environ.get('HF_TOKEN', '${HF_TOKEN}') or None
+# snapshot_download will save the repo files into /opt/model/<repo-name>
+local = snapshot_download(repo, token=token, cache_dir="/opt/model_cache")
+print("Downloaded to:", local)
+PY
+
+# create unpriv user
 RUN useradd -m -u 1000 user
 USER user
 ENV HOME=/home/user PATH=/home/user/.local/bin:$PATH
-
 WORKDIR $HOME/app
 RUN cp -r /app/* $HOME/app/ || true
 
 EXPOSE 8501
-CMD ["streamlit","run","app.py","--server.port=8501","--server.address=0.0.0.0","--server.enableXsrfProtection=false"]
+CMD ["streamlit","run","app.py","--server.port=8501","--server.address=0.0.0.0"]