Update Dockerfile

Dockerfile

@@ -1,34 +1,41 @@
-# Base
 FROM python:3.10-slim
-
-# System deps for LightGBM (OpenMP)
-RUN apt-get update \
- && apt-get install -y --no-install-recommends libgomp1 \
- && rm -rf /var/lib/apt/lists/*
-
-# App workdir
+RUN apt-get update && apt-get install -y --no-install-recommends libgomp1 && rm -rf /var/lib/apt/lists/*
 WORKDIR /app
-
-# Copy files first (owned by root initially)
-COPY app.py . 
 COPY requirements.txt .
-COPY subset_best_model.pkl .
-COPY GTT.csv .
-
-# Install Python deps
-RUN pip install --no-cache-dir -r requirements.txt
-
-# Make /app writable for the runtime user to avoid PyCaret logging warnings
-# (Hugging Face Spaces often runs as a non-root user)
-RUN chmod -R a+rw /app
-
-# Optional: pre-create a writable log file to silence the warning completely
-RUN touch /app/logs.log && chmod 666 /app/logs.log
-
-# Gradio / Matplotlib envs
+RUN pip install --no-cache-dir -r requirements.txt && pip install --no-cache-dir huggingface_hub
+
+# Generate app.py during build so it's not in the repo
+RUN python - <<'PY'
+import textwrap, pathlib
+code = """
+import os
+from huggingface_hub import hf_hub_download
+from pycaret.classification import load_model, predict_model
+import gradio as gr
+import pandas as pd
+
+REPO = os.getenv("MODEL_REPO", "<USERNAME>/my-private-model")
+FNAME = os.getenv("MODEL_FILE", "subset_best_model.pkl")
+TOKEN = os.getenv("HF_TOKEN")
+
+local_path = hf_hub_download(repo_id=REPO, filename=FNAME, token=TOKEN)
+model = load_model(local_path)
+
+def infer(csv_text):
+    df = pd.read_csv(pd.compat.StringIO(csv_text)) if "," in csv_text else pd.read_csv(csv_text)
+    out = predict_model(model, data=df)
+    return out.to_csv(index=False)
+
+demo = gr.Interface(fn=infer, inputs=gr.Textbox(lines=8, label="CSV (paste) or path"),
+                    outputs=gr.Textbox(label="Predictions CSV"))
+if __name__ == "__main__":
+    import os
+    port = int(os.getenv("PORT", "7860"))
+    demo.launch(server_name="0.0.0.0", server_port=port)
+"""
+pathlib.Path("app.py").write_text(textwrap.dedent(code), encoding="utf-8")
+PY
+
+ENV GRADIO_SERVER_NAME=0.0.0.0 MPLCONFIGDIR=/tmp/matplotlib PYTHONUNBUFFERED=1
 EXPOSE 7860
-ENV GRADIO_SERVER_NAME=0.0.0.0
-ENV MPLCONFIGDIR=/tmp/matplotlib
-ENV PYTHONUNBUFFERED=1
-
 CMD ["python", "app.py"]