Create Dockerfile

Dockerfile

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+# Use a slim Python base image for efficiency
+FROM python:3.11-slim
+
+# Set the working directory
+WORKDIR /app
+
+# Install system dependencies required for OpenVINO and image processing
+RUN apt-get update && apt-get install -y \
+    libgl1-mesa-glx \
+    libglib2.0-0 \
+    libgomp1 \
+    wget \
+    git \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy the requirements file first for better caching
+COPY requirements.txt .
+
+# Install Python dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Pre-download the OpenVINO models during the build phase
+RUN mkdir -p /app/models/base /app/models/controlnet /app/models/loras
+
+# Download the base LCM model
+RUN wget -q -P /app/models/base https://huggingface.co/rupeshs/LCM-dreamshaper-v7-openvino/resolve/main/dreamshaper-v7-lcm/openvino_model.xml && \
+    wget -q -P /app/models/base https://huggingface.co/rupeshs/LCM-dreamshaper-v7-openvino/resolve/main/dreamshaper-v7-lcm/openvino_model.bin
+
+# (Optional) You can pre-download the LoRAs here using wget, or let the app download them on-demand.
+
+# Copy the application code
+COPY app.py .
+
+# Expose the port Hugging Face Spaces uses
+EXPOSE 7860
+
+# Command to run the FastAPI application
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]