Adding GPU support for transcription

app/Dockerfile

@@ -1,4 +1,7 @@
-FROM python:3.11-slim
+## GPU-ready base image with CUDA 12 + cuDNN 9 runtime
+# If you don't have an NVIDIA GPU or the NVIDIA Container Toolkit, this image still runs on CPU.
+# For smaller CPU-only images, you can switch back to python:3.11-slim.
+FROM nvidia/cuda:12.4.1-cudnn9-runtime-ubuntu22.04
 
 # Keep python fast/quiet and pip lean
 ENV PYTHONDONTWRITEBYTECODE=1 \
@@ -12,6 +15,7 @@ ENV PYTHONDONTWRITEBYTECODE=1 \
 
 # System deps: ffmpeg for media, curl for healthcheck, jq for scripts, poppler-utils for PDFs
 RUN apt-get update && apt-get install -y --no-install-recommends \
+    python3 python3-pip python3-venv \
     ffmpeg \
     curl \
     jq \
@@ -22,15 +26,15 @@ WORKDIR /app
 
 # Upgrade pip toolchain then install Python deps
 COPY requirements.txt .
-RUN python -m pip install --upgrade pip setuptools wheel \
- && pip install --no-cache-dir -r requirements.txt \
- && pip check || true
+RUN python3 -m pip install --upgrade pip setuptools wheel \
+ && pip3 install --no-cache-dir -r requirements.txt \
+ && pip3 check || true
 
 # App code
 COPY app.py worker.py scanner.py ./
-RUN pip install --no-cache-dir gunicorn==22.0.0
+RUN pip3 install --no-cache-dir gunicorn==22.0.0
 
 # Healthcheck against the app's /health endpoint
 
 EXPOSE 8080
-CMD ["gunicorn", "-b", "0.0.0.0:8080", "app:app", "--workers", "2", "--threads", "4"]
+CMD ["gunicorn", "-b", "0.0.0.0:8080", "app:app", "--workers", "2", "--threads", "4"]