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Browse files- Dockerfile +19 -1
Dockerfile
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FROM nvcr.io/nvidia/pytorch:23.09-py3
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WORKDIR /app
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RUN apt-get update && apt-get install -y \
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curl \
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git \
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build-essential \
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&& rm -rf /var/lib/apt/lists/*
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COPY requirements.txt ./
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RUN pip install --no-cache-dir numpy==1.24.4
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RUN pip install --no-cache-dir -r requirements.txt
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RUN python3 -m spacy download en_core_web_sm
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COPY src/ ./src/
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EXPOSE 8501
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HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
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ENTRYPOINT ["streamlit", "run", "src/streamlit_app.py", "--server.port=8501", "--server.address=0.0.0.0"]
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# 1. Use an official PyTorch base image
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FROM nvcr.io/nvidia/pytorch:23.09-py3
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# Set working directory inside the container
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WORKDIR /app
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# Install system dependencies (curl, git, etc.)
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RUN apt-get update && apt-get install -y \
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curl \
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git \
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build-essential \
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&& rm -rf /var/lib/apt/lists/*
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# ----------------------------------------------------------------------
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# CRITICAL FIX 1: Pin NumPy AND Force Reinstallation of PyTorch
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# ----------------------------------------------------------------------
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# 1a. Copy requirements and install the pinned NumPy version first
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COPY requirements.txt ./
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RUN pip install --no-cache-dir numpy==1.24.4
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# 1b. Force re-install PyTorch to link it correctly with the new NumPy 1.24.4 version
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RUN pip install --no-cache-dir torch
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# 1c. Install remaining Python packages from requirements
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RUN pip install --no-cache-dir -r requirements.txt
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# ----------------------------------------------------------------------
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# CRITICAL FIX 2: Download the spaCy language model data
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RUN python3 -m spacy download en_core_web_sm
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# Copy application source code to the container
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COPY src/ ./src/
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# Expose the port Streamlit runs on
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EXPOSE 8501
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HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
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# Command to run the Streamlit application
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ENTRYPOINT ["streamlit", "run", "src/streamlit_app.py", "--server.port=8501", "--server.address=0.0.0.0"]
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