QModel / Dockerfile
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# QModel 6 - Islamic RAG API
# =============================
# Dockerfile for QModel API
# Supports both Ollama and HuggingFace backends via .env configuration
#
# Build: docker build -t qmodel .
# Run: docker run -p 8000:8000 --env-file .env qmodel
FROM python:3.11-slim
# Metadata
LABEL maintainer="QModel Team"
LABEL description="QModel v6 - Quran & Hadith RAG API"
LABEL version="4.1"
# Environment variables
ENV PYTHONDONTWRITEBYTECODE=1 \
PYTHONUNBUFFERED=1 \
PIP_NO_CACHE_DIR=1
# Set working directory
WORKDIR /app
# Install system dependencies
# - build-essential: For compiling Python packages
# - libopenblas-dev: For numerical operations (FAISS, numpy)
# - libomp-dev: For OpenMP (FAISS parallelization)
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
libopenblas-dev \
libomp-dev \
curl \
&& rm -rf /var/lib/apt/lists/*
# Copy requirements and install Python dependencies
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
# Copy application code
COPY . .
# Expose port for API
EXPOSE 8000
# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=60s --retries=3 \
CMD curl -f http://localhost:8000/health || exit 1
# Start application
# Configure via .env: LLM_BACKEND=ollama or LLM_BACKEND=hf
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]