Simplify Dockerfile and add HF token authentication for gated model access

Dockerfile

@@ -1,32 +1,6 @@
 # Dockerfile for SAP Finance Dashboard with RPT-1-OSS Model
-# Multi-stage build to optimize image size for HuggingFace Spaces
+# Optimized single-stage build for HuggingFace Spaces
 
-# Stage 1: Build wheels for heavy dependencies
-FROM python:3.11-slim as builder
-
-WORKDIR /wheels
-
-# Install build dependencies
-RUN apt-get update && apt-get install -y --no-install-recommends \
-    build-essential \
-    git \
-    && rm -rf /var/lib/apt/lists/*
-
-# Create wheels directory for pip to use
-RUN mkdir -p /wheels
-
-# Build torch and other ML libraries as wheels (lighter than full install)
-RUN pip wheel --no-cache-dir --wheel-dir=/wheels \
-    torch==2.0.0 \
-    torchvision==0.15.0 \
-    torchaudio==2.0.0 \
-    transformers==4.30.0 2>&1 || true
-
-# Build other dependencies as wheels
-RUN pip wheel --no-cache-dir --wheel-dir=/wheels \
-    git+https://github.com/SAP-samples/sap-rpt-1-oss 2>&1 || true
-
-# Stage 2: Runtime image (minimal size)
 FROM python:3.11-slim
 
 # Set environment variables
@@ -35,11 +9,13 @@ ENV PYTHONUNBUFFERED=1
 ENV GRADIO_SERVER_NAME=0.0.0.0
 ENV GRADIO_SERVER_PORT=7860
 ENV TORCH_HOME=/app/torch_cache
+ENV HUGGINGFACE_HUB_CACHE=/app/hf_cache
 
 # Install minimal system dependencies
 RUN apt-get update && apt-get install -y --no-install-recommends \
     git \
     curl \
+    build-essential \
     && rm -rf /var/lib/apt/lists/*
 
 WORKDIR /app
@@ -48,27 +24,28 @@ WORKDIR /app
 COPY requirements.txt .
 
 # Install base dependencies
-RUN pip install --no-cache-dir --upgrade pip && \
+RUN pip install --no-cache-dir --upgrade pip setuptools wheel && \
     pip install --no-cache-dir -r requirements.txt
 
-# Install stable gradio version
+# Install Gradio (pinned for stability)
 RUN pip install --no-cache-dir "gradio==4.44.1"
 
-# Copy pre-built wheels from builder stage and install them
-COPY --from=builder /wheels /wheels
-RUN pip install --no-cache-dir --no-index --find-links=/wheels \
+# Install core ML libraries (pre-built wheels, no compilation needed)
+RUN pip install --no-cache-dir \
     torch==2.0.0 \
-    transformers==4.30.0 2>&1 || true && \
-    rm -rf /wheels
+    transformers==4.30.0 \
+    scikit-learn==1.2.0
 
-# Try installing sap-rpt-oss directly (will use pre-built wheels if available)
-RUN pip install --no-cache-dir git+https://github.com/SAP-samples/sap-rpt-1-oss 2>&1 || true
+# Install SAP-RPT-1-OSS from GitHub
+# Note: Requires HF_TOKEN environment variable for gated model access
+RUN pip install --no-cache-dir \
+    git+https://github.com/SAP-samples/sap-rpt-1-oss
 
 # Copy application code
 COPY . .
 
-# Create data directory and torch cache directory
-RUN mkdir -p /app/data /app/torch_cache
+# Create required directories
+RUN mkdir -p /app/data /app/torch_cache /app/hf_cache
 
 # Expose port
 EXPOSE 7860

app_gradio.py

@@ -74,6 +74,23 @@ def _patch_gradio_client_schema_bug():
 _ensure_hf_folder_compat()
 _patch_gradio_client_schema_bug()
 
+# Setup HuggingFace authentication for gated model access
+def _setup_hf_auth():
+    """Authenticate with HuggingFace Hub using token from environment."""
+    try:
+        from huggingface_hub import login
+        
+        hf_token = os.getenv("HF_TOKEN") or os.getenv("HUGGINGFACE_TOKEN")
+        if hf_token:
+            login(token=hf_token, add_to_git_credential=False)
+            print("✓ HuggingFace authentication configured")
+        else:
+            print("⚠ HF_TOKEN not found. Gated model access will fail if not already cached.")
+    except Exception as e:
+        print(f"⚠ HuggingFace auth setup failed: {e}")
+
+_setup_hf_auth()
+
 import gradio as gr
 print(f"Gradio version: {gr.__version__}")
 import pandas as pd