Upload folder using huggingface_hub

Dockerfile

@@ -1,34 +1,24 @@
-# Base image
 FROM python:3.9-slim
 
-# Environment settings
 ENV PYTHONDONTWRITEBYTECODE=1
 ENV PYTHONUNBUFFERED=1
 
-# Create non-root user
-RUN useradd -m -u 1000 user
+# HF requires port 7860
+ENV STREAMLIT_SERVER_PORT=7860
+ENV STREAMLIT_SERVER_ADDRESS=0.0.0.0
 
-# Set working directory
 WORKDIR /app
 
-# Copy dependency file first (better caching)
+# Copy dependencies first
 COPY requirements.txt .
 
-# Install dependencies
 RUN pip install --no-cache-dir -r requirements.txt
 
-# Copy application code
-COPY --chown=user . /app
-
-# Switch to non-root user
-USER user
+# Copy app code
+COPY . .
 
-# Expose Streamlit port
-EXPOSE 8501
-
-# Streamlit configuration
-ENV STREAMLIT_SERVER_PORT=8501
-ENV STREAMLIT_SERVER_ADDRESS=0.0.0.0
+# Expose HF-required port
+EXPOSE 7860
 
-# Run Streamlit app
-CMD ["streamlit", "run", "engine_predict/deployment/app.py"]
+# Start Streamlit
+CMD ["streamlit", "run", "app.py"]

app.py

@@ -10,8 +10,8 @@ HF_MODEL_REPO = "vihu21/adaboost-predictive-maintenance"
 MODEL_FILE = "adaboost_pm.joblib"
 
 model_path = hf_hub_download(
-    repo_id=HF_MODEL_REPO,
-    filename=MODEL_FILE,
+    repo_id="vihu21/adaboost-predictive-maintenance",
+    filename="adaboost_pm.joblib",
     repo_type="model"
 )