Update Dockerfile

Dockerfile

@@ -1,119 +1,37 @@
-# Builder stage
+# Base image with CUDA support
 FROM nvidia/cuda:12.1.0-cudnn8-runtime-ubuntu22.04
 
-# Add these lines after the FROM statement
-
-# System-level configuration
-ENV DEBIAN_FRONTEND=noninteractive \
-    PYTHONUNBUFFERED=1 \
+# Set environment variables
+ENV PYTHONUNBUFFERED=1 \
+    DEBIAN_FRONTEND=noninteractive \
     CUDA_HOME=/usr/local/cuda \
     PATH=/usr/local/cuda/bin:$PATH \
-    LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH \
-    TORCH_CUDA_ARCH_LIST="8.6" \
-    PIP_NO_CACHE_DIR=1 \
-    TORCH_NVCC_FLAGS="-Xfatbin -compress-all" \
-    MAX_JOBS=4
+    LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
 
-# Install build dependencies
+# Install Python and pip
 RUN apt-get update && apt-get install -y --no-install-recommends \
+    python3 \
     python3-pip \
-    && apt-get clean \
-    && rm -rf /var/lib/apt/lists/* \
-    && python3 -m pip install --no-cache-dir --upgrade pip
-
-
-# Set up Python
-RUN ln -sf /usr/bin/python3 /usr/bin/python && \
-    curl -sS https://bootstrap.pypa.io/get-pip.py | python3 && \
-    python3 -m pip install --no-cache-dir pip==23.3.1 setuptools==69.0.3 wheel==0.42.0 && \
-    rm -rf /root/.cache/pip/*
-
-# Replace the pip install command (around line 80) with:
-RUN python3 -m pip install --no-cache-dir -r requirements.txt && \
-    rm -rf /root/.cache/pip/* && \
-    find /usr/local/lib/python3.* -name '*.pyc' -delete && \
-    find /usr/local/lib/python3.* -name '__pycache__' -exec rm -r {} +
-
-# Runtime stage
-FROM nvidia/cuda:12.1.0-cudnn8-runtime-ubuntu22.04
+    curl \
+    && rm -rf /var/lib/apt/lists/*
 
-# Copy Python environment from builder
-COPY --from=builder /usr/local /usr/local
-COPY --from=builder /usr/bin/python* /usr/bin/
-COPY --from=builder /usr/lib/python* /usr/lib/
-COPY --from=builder /usr/bin/ffmpeg /usr/bin/
-COPY --from=builder /usr/lib/x86_64-linux-gnu/libsndfile* /usr/lib/x86_64-linux-gnu/
-
-# Runtime environment configuration
-ENV PYTHONUNBUFFERED=1 \
-    CUDA_HOME=/usr/local/cuda \
-    PATH=/usr/local/cuda/bin:$PATH \
-    LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH \
-    TORCH_CUDA_ARCH_LIST="8.6" \
-    NVIDIA_VISIBLE_DEVICES=0 \
-    NVIDIA_DRIVER_CAPABILITIES=compute,utility,video \
-    CUDA_MODULE_LOADING=LAZY \
-    PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:1024 \
-    OMP_NUM_THREADS=8 \
-    MKL_NUM_THREADS=8 \
-    CUDA_LAUNCH_BLOCKING=0 \
-    NCCL_P2P_DISABLE=1
-
-# Set up application directory
+# Set up working directory
 WORKDIR /app
-RUN mkdir -p /app/cache /app/src && \
-    chmod 777 /app/cache && \
-    rm -rf /tmp/* /var/tmp/*
-
-# Install dependencies
-COPY requirements.txt /app/src/
-WORKDIR /app/src
-RUN pip3 install --no-cache-dir -r requirements.txt && \
-    rm -rf /root/.cache/pip/* && \
-    find /usr/local/lib/python3.* -name '*.pyc' -delete && \
-    find /usr/local/lib/python3.* -name '__pycache__' -exec rm -r {} +
 
-# Copy application code
-COPY . /app/src/
+# Copy requirements first to leverage Docker cache
+COPY requirements.txt .
 
-# Remove unnecessary files
-RUN rm -rf \
-    /app/src/.git* \
-    /app/src/*.pyc \
-    /app/src/__pycache__ \
-    /app/src/*.log \
-    /app/src/*.tmp \
-    /root/.cache/* \
-    /tmp/* \
-    /var/tmp/* \
-    /var/cache/apt/* \
-    /var/lib/apt/lists/* \
-    /usr/share/doc/* \
-    /usr/share/man/* \
-    /usr/local/share/doc/* \
-    /usr/local/share/man/*
+# Install Python dependencies
+RUN pip3 install --no-cache-dir -r requirements.txt
 
-# Runtime environment
-ENV MODEL_PATH=/app/cache \
-    PYTHONPATH=/app/src:$PYTHONPATH
+# Copy the rest of your application
+COPY . .
 
-# GPU verification
-RUN python3 -c '\
-import torch; \
-import os; \
-assert torch.cuda.is_available(), "CUDA unavailable"; \
-print(f"PyTorch version: {torch.__version__}"); \
-print(f"CUDA version: {torch.version.cuda}"); \
-print(f"CUDA device count: {torch.cuda.device_count()}"); \
-device = torch.cuda.current_device(); \
-print(f"Current device: {torch.cuda.get_device_name(device)}"); \
-print(f"Device memory: {torch.cuda.get_device_properties(device).total_memory / 1024**3:.2f} GB"); \
-print(f"Architecture: {torch.cuda.get_device_capability(device)}");'
+# Verify GPU setup
+RUN python3 -c "import torch; assert torch.cuda.is_available(), 'CUDA not available'"
 
+# Expose port
 EXPOSE 8000
 
-# Add healthcheck
-HEALTHCHECK --interval=30s --timeout=10s --retries=3 \
-    CMD curl -f http://localhost:8000/health || exit 1
-
-CMD ["python", "server.py"]
+# Start the application
+CMD ["python3", "server.py"]