| # Use an official Python runtime as the base image | |
| FROM python:3.9 | |
| # Ensure Python output is unbuffered for real-time logging | |
| ENV PYTHONUNBUFFERED=1 | |
| # Set HOME so that PaddleOCR uses /app/.paddleocr instead of the root directory. | |
| ENV HOME=/app | |
| # Set custom cache directories for PaddleOCR and Transformers (for large model files) | |
| ENV PADDLEOCR_CACHE_DIR=/app/.cache/paddleocr | |
| ENV TRANSFORMERS_CACHE=/app/.cache/huggingface | |
| # Create /app (ensuring HOME exists), install system dependencies including Git LFS and ccache, | |
| # then set up Git LFS configuration. | |
| RUN mkdir -p /app && \ | |
| apt-get update && apt-get install -y --no-install-recommends \ | |
| build-essential \ | |
| libgl1-mesa-glx \ | |
| libglib2.0-0 \ | |
| git-lfs \ | |
| ccache && \ | |
| # Create an empty .gitconfig to satisfy Git LFS requirements. | |
| touch /app/.gitconfig && \ | |
| git lfs install --force && \ | |
| rm -rf /var/lib/apt/lists/* | |
| # Create necessary directories with full permissions so that model files can be downloaded. | |
| RUN mkdir -p /app/.paddleocr /app/.cache/paddleocr /app/.cache/huggingface && \ | |
| chmod -R 777 /app/.paddleocr /app/.cache/paddleocr /app/.cache/huggingface | |
| # Set the working directory for the container. | |
| WORKDIR /app | |
| # Copy the repository contents into the container. | |
| COPY . /app | |
| # Upgrade pip and install Python dependencies. | |
| # Note: We install PaddlePaddle (CPU-only) using the official find-links URL, then PaddleOCR. | |
| RUN pip install --upgrade pip setuptools wheel && \ | |
| pip install --no-cache-dir \ | |
| flask==3.1.0 \ | |
| opencv-python-headless==4.11.0.86 \ | |
| numpy==1.23.5 \ | |
| spacy==3.8.3 \ | |
| spacy-legacy==3.0.12 \ | |
| spacy-loggers==1.0.5 \ | |
| sentence-transformers==3.4.1 \ | |
| transformers==4.49.0 \ | |
| torch==2.6.0 \ | |
| requests==2.32.3 && \ | |
| pip install --no-cache-dir paddlepaddle==2.6.2 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html && \ | |
| pip install --no-cache-dir paddleocr==2.9.1 | |
| # Download spaCy's English model ("en_core_web_md") | |
| RUN python -m spacy download en_core_web_md | |
| # Pre-load heavy models and tokenizers so they're cached inside the image: | |
| # • SentenceTransformer's "all-mpnet-base-v2" | |
| # • spaCy's "en_core_web_md" | |
| # • Transformers model and tokenizer "roberta-large-mnli" used by your entailment classifier | |
| # • PaddleOCR's models (downloaded into /app/.paddleocr) | |
| #RUN python -c "from sentence_transformers import SentenceTransformer; SentenceTransformer('all-mpnet-base-v2')" && \ | |
| # python -c "import spacy; spacy.load('en_core_web_md')" && \ | |
| # python -c "from transformers import AutoModel, AutoTokenizer; AutoModel.from_pretrained('roberta-large-mnli'); AutoTokenizer.from_pretrained('roberta-large-mnli')" && \ | |
| # python -c "from paddleocr import PaddleOCR; PaddleOCR(use_angle_cls=True, lang='en')" | |
| # Expose port 7860 for the Flask application. | |
| EXPOSE 7860 | |
| # Specify the Flask application entry point. | |
| ENV FLASK_APP=app.py | |
| # Run the Flask application when the container starts. | |
| CMD | |