feat : update requetment

Dockerfile

@@ -1,31 +1,32 @@
 # veggie_model_service/Dockerfile
-
-# Base image
 FROM python:3.9-slim
 
-# Install dep OS untuk OpenCV
-RUN apt-get update && apt-get install -y \
+ENV PYTHONUNBUFFERED=1 \
+    PIP_NO_CACHE_DIR=1 \
+    PORT=7860
+
+# deps OS untuk OpenCV
+RUN apt-get update && apt-get install -y --no-install-recommends \
     libgl1 \
     libglib2.0-0 \
     && rm -rf /var/lib/apt/lists/*
 
-# User non-root (standar HF)
+# user non-root (standar HF)
 RUN useradd -m -u 1000 user
 USER user
 ENV PATH="/home/user/.local/bin:${PATH}"
 
-# Workdir
 WORKDIR /app
 
-# Install dependencies
+# install deps dulu (biar layer cache enak)
 COPY --chown=user requirements.txt /app/requirements.txt
-RUN pip install --no-cache-dir --upgrade -r requirements.txt
+RUN python -m pip install --upgrade pip \
+ && python -m pip install --user -r /app/requirements.txt
 
-# Copy semua file proyek (app.py, model, scaler)
+# copy project
 COPY --chown=user . /app
 
-# Expose port HF
 EXPOSE 7860
 
-# Jalankan FastAPI via uvicorn
-CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]
+# pakai PORT dari HF kalau ada
+CMD ["bash", "-lc", "uvicorn app:app --host 0.0.0.0 --port ${PORT}"]

requirements.txt

@@ -1,11 +1,10 @@
-fastapi
-uvicorn[standard]
+fastapi>=0.100
+uvicorn[standard]>=0.23
+python-multipart>=0.0.6
 
-tensorflow-cpu
 numpy
 scikit-learn
 scikit-image
 opencv-python-headless
 pillow
-
-# kalau di training kamu pakai library tambahan, tambahkan juga
+tensorflow-cpu