Dockerfile

FROM python:3.10-slim

# Set working directory
WORKDIR /app

# Install system dependencies, including libgl1 for OpenCV
RUN apt-get update && apt-get install -y \
    git \
    git-lfs \
    gcc \
    python3-dev \
    libgl1 \
    libglib2.0-0 \
    && rm -rf /var/lib/apt/lists/*

# Initialize git-lfs
RUN git lfs install

# Clone the fastsdcpu repository
RUN git clone https://github.com/rupeshs/fastsdcpu.git .

# Create writable directories for cache, configs, and results
RUN mkdir -p /app/.cache/huggingface /app/configs /app/results && \
    chmod -R 777 /app/.cache /app/configs /app/results

# Set environment variables for Hugging Face cache and OpenVINO telemetry
ENV HF_HOME=/app/.cache/huggingface
ENV XDG_CACHE_HOME=/app/.cache
ENV OPENVINO_TELEMETRY=0

# Install Python dependencies
RUN python -m venv env && \
    . env/bin/activate && \
    pip install --upgrade pip && \
    pip install torch==2.2.2 --index-url https://download.pytorch.org/whl/cpu && \
    pip install -r requirements.txt

# Download a default model (corrected URL for lcm-lora-sdv1-5)
RUN git clone https://huggingface.co/latent-consistency/lcm-lora-sdv1-5 /models/lcm-lora-sdv1-5 || \
    echo "Model clone failed. Please check network or manually download the model."

# Configure the model path
RUN echo "/models/lcm-lora-sdv1-5" > configs/lcm-lora-models.txt && \
    chmod 666 configs/lcm-lora-models.txt

# Expose the API port
EXPOSE 8000

# Activate virtual environment and run the API server
CMD ["/bin/bash", "-c", ". env/bin/activate && python src/app.py --api"]