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-# Use an official Python runtime as a base image
-FROM python:3.9-slim
-
-# Ensure Python output is unbuffered for real-time logging
-ENV PYTHONUNBUFFERED=1
-
-# Set HOME to a known writable directory so PaddleOCR uses /app/.paddleocr instead of the root
-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 prepare 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 appease Git LFS when it runs
-    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 into them.
-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 inside the container
-WORKDIR /app
-
-# Copy the current repository contents into /app inside the container.
-COPY . /app
-
-# Upgrade pip and install Python dependencies.
-# Note: We install PaddlePaddle (CPU-only) using the official find-links option.
-RUN pip install --upgrade pip setuptools wheel && \
-    pip install --no-cache-dir \
-      flask \
-      opencv-python-headless \
-      numpy \
-      spacy \
-      sentence-transformers \
-      transformers \
-      requests && \
-    pip install --no-cache-dir paddlepaddle==2.5.2 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html && \
-    pip install --no-cache-dir paddleocr
-
-# Download spaCy's English model (en_core_web_md)
-RUN python -m spacy download en_core_web_md
-
-# Pre-load heavy models so that they're cached inside the image:
-#   • SentenceTransformer's "all-mpnet-base-v2"
-#   • spaCy's "en_core_web_md" (reinforcing that the model is loaded)
-#   • Transformers model "roberta-large-mnli" used for 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; AutoModel.from_pretrained('roberta-large-mnli')" && \
-    python -c "from paddleocr import PaddleOCR; PaddleOCR(use_angle_cls=True, lang='en')"
-
-# Expose the port your Flask app will run on (defaults to port 7860)
-EXPOSE 7860
-
-# Specify the Flask application entry point (modify if your main file name is different)
-ENV FLASK_APP=app.py
-
-# Run the Flask app when the container starts
-CMD ["flask", "run", "--host=0.0.0.0", "--port=7860"]