# SysCRED Docker Configuration for Hugging Face Spaces # OPTIMIZED version with Distilled Models for faster startup FROM python:3.10-slim WORKDIR /app ENV PYTHONDONTWRITEBYTECODE=1 ENV PYTHONUNBUFFERED=1 ENV PYTHONPATH=/app # ============================================ # KEY OPTIMIZATION: Use distilled models # ============================================ ENV SYSCRED_LOAD_ML_MODELS=true ENV SYSCRED_USE_DISTILLED=true ENV TRANSFORMERS_CACHE=/app/.cache/huggingface ENV HF_HOME=/app/.cache/huggingface # Install system dependencies RUN apt-get update && apt-get install -y \ build-essential \ && rm -rf /var/lib/apt/lists/* # Copy optimized requirements (distilled models, CPU-only torch) COPY requirements-distilled.txt /app/requirements.txt # Install dependencies RUN pip install --no-cache-dir -r requirements.txt # ============================================ # PRE-DOWNLOAD DISTILLED MODELS (Build Time) # This avoids timeout during first request # ============================================ RUN python -c "from transformers import pipeline; \ pipeline('sentiment-analysis', model='distilbert-base-uncased-finetuned-sst-2-english'); \ pipeline('ner', model='dslim/bert-base-NER'); \ print('✓ Distilled models pre-downloaded')" # Download small spaCy models RUN pip install spacy && \ python -m spacy download en_core_web_sm && \ python -m spacy download fr_core_news_sm && \ echo '✓ spaCy models downloaded' # Pre-download sentence transformer (small version) RUN python -c "from sentence_transformers import SentenceTransformer; \ SentenceTransformer('all-MiniLM-L6-v2'); \ print('✓ Sentence transformer pre-downloaded')" # Copy application code COPY syscred/ /app/syscred/ # Create user for HF Spaces (required) RUN useradd -m -u 1000 user USER user ENV HOME=/home/user ENV PATH=/home/user/.local/bin:$PATH WORKDIR /app EXPOSE 7860 # Run with HF Spaces port (7860) # Increased workers to 4 for better concurrency, timeout 600s CMD ["gunicorn", "--bind", "0.0.0.0:7860", "--workers", "1", "--threads", "4", "--timeout", "600", "syscred.backend_app:app"]