Update Dockerfile

Dockerfile

@@ -1,40 +1,62 @@
-# Use a highly optimized, clean modern Python image foundation
+# ── Base image ────────────────────────────────────────────────────────────────
 FROM python:3.11-slim
 
-# Enforce immediate log flushing to prevent output tracking buffering delays
 ENV PYTHONUNBUFFERED=1
 
-# Hugging Face requires a non-root user for security and file caching
+# ── Non-root user (required by Hugging Face Spaces) ───────────────────────────
 RUN useradd -m -u 1000 user
-USER user
 ENV HOME=/home/user \
     PATH=/home/user/.local/bin:$PATH
 
+# Fix: point HF cache to the user's writable home so the pre-downloaded model
+# is found at runtime (same path used in app.py via os.environ.setdefault).
+ENV HF_HOME=/home/user/.cache/huggingface \
+    TRANSFORMERS_CACHE=/home/user/.cache/huggingface
+
 WORKDIR $HOME/app
 
-# Switch to root temporarily to install system dependencies
+# ── System dependencies ───────────────────────────────────────────────────────
 USER root
 RUN apt-get update && apt-get install -y --no-install-recommends \
-    build-essential \
+        build-essential \
     && rm -rf /var/lib/apt/lists/*
 USER user
 
-# Copy requirements file first to exploit Docker layer caching systems
+# ── Python dependencies ───────────────────────────────────────────────────────
 COPY --chown=user requirements.txt .
 
-# Upgrade pip and install libraries
+# Step 1 — Install PyTorch CPU wheel from its dedicated index
 RUN pip install --no-cache-dir --upgrade pip && \
-    pip install --no-cache-dir -r requirements.txt
-
-# Pre-download the Hugging Face model during the build phase so it doesn't cause startup timeouts
-RUN python -c "from chronos import BaseChronosPipeline; BaseChronosPipeline.from_pretrained('amazon/chronos-bolt-base')"
-
-# Copy the core script and frontend code layers into the deployment engine
+    pip install --no-cache-dir \
+        torch==2.3.1 \
+        --index-url https://download.pytorch.org/whl/cpu
+
+# Step 2 — Install the remaining packages from PyPI
+RUN pip install --no-cache-dir \
+        streamlit==1.35.0 \
+        chronos-forecasting==1.3.0 \
+        pandas==2.2.2 \
+        numpy==1.26.4 \
+        plotly==5.22.0
+
+# ── Pre-download model weights at build time ──────────────────────────────────
+# Runs as `user` with HF_HOME set above — weights land in the correct cache dir
+RUN python -c "\
+import os; \
+os.environ['HF_HOME'] = '/home/user/.cache/huggingface'; \
+from chronos import BaseChronosPipeline; \
+BaseChronosPipeline.from_pretrained('amazon/chronos-bolt-base', device_map='cpu')"
+
+# ── Application code ──────────────────────────────────────────────────────────
 COPY --chown=user app.py .
 COPY --chown=user interface.py .
 
-# Streamlit network routing configured specifically for Hugging Face Spaces
+# ── Network ───────────────────────────────────────────────────────────────────
 EXPOSE 7860
 
-# Run the app on Port 7860 and disable Streamlit telemetry to prevent silent hanging
-CMD ["streamlit", "run", "interface.py", "--server.port=7860", "--server.address=0.0.0.0", "--browser.gatherUsageStats=false", "--server.headless=true"]
+# ── Entrypoint ────────────────────────────────────────────────────────────────
+CMD ["streamlit", "run", "interface.py", \
+     "--server.port=7860", \
+     "--server.address=0.0.0.0", \
+     "--browser.gatherUsageStats=false", \
+     "--server.headless=true"]