Update Dockerfile
Browse files- Dockerfile +43 -46
Dockerfile
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# Use Python 3.10 slim image as base
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FROM python:3.10-slim
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# Install system dependencies
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RUN apt-get update && \
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apt-get install -y \
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build-essential \
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git \
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poppler-utils \
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&& rm -rf /var/lib/apt/lists/*
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# Set working directory
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WORKDIR /app
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# Set environment variables
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ENV PYTHONUNBUFFERED=1
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ENV TRANSFORMERS_CACHE=/app/model_cache
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ENV HF_HOME=/app/model_cache
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ENV TORCH_HOME=/app/model_cache
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ENV CHAINLIT_HOST=0.0.0.0
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ENV CHAINLIT_PORT=7860
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# Install Python dependencies
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COPY requirements.txt .
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RUN pip install --no-cache-dir -r requirements.txt
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# Create necessary directories
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RUN mkdir -p /app/model_cache /app/vectorstore/db_faiss /app/data
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# Copy application files
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COPY model.py ingest.py chainlit.md download_assets.py ./
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# Download models and cache them
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RUN python -c "from transformers import AutoTokenizer, AutoModelForSeq2SeqLM; \
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AutoTokenizer.from_pretrained('google/flan-t5-base'); \
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AutoModelForSeq2SeqLM.from_pretrained('google/flan-t5-base'); \
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from sentence_transformers import SentenceTransformer; \
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SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')"
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#
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#
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EXPOSE 7860
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# Run the Chainlit application
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CMD ["chainlit", "run", "model.py", "--host", "0.0.0.0", "--port", "7860"]
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# Use Python 3.10 slim image as base
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FROM python:3.10-slim
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+
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# Install system dependencies
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RUN apt-get update && \
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apt-get install -y \
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build-essential \
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git \
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poppler-utils \
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&& rm -rf /var/lib/apt/lists/*
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# Set working directory
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WORKDIR /app
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# Set environment variables
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ENV PYTHONUNBUFFERED=1
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ENV TRANSFORMERS_CACHE=/app/model_cache
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ENV HF_HOME=/app/model_cache
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ENV TORCH_HOME=/app/model_cache
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ENV CHAINLIT_HOST=0.0.0.0
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ENV CHAINLIT_PORT=7860
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# Install Python dependencies
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COPY requirements.txt .
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RUN pip install --no-cache-dir -r requirements.txt
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# Create necessary directories
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RUN mkdir -p /app/model_cache /app/vectorstore/db_faiss /app/data
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# Copy application files
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COPY model.py ingest.py chainlit.md download_assets.py ./
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# Download models and cache them
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RUN python -c "from transformers import AutoTokenizer, AutoModelForSeq2SeqLM; \
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AutoTokenizer.from_pretrained('google/flan-t5-base'); \
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AutoModelForSeq2SeqLM.from_pretrained('google/flan-t5-base'); \
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from sentence_transformers import SentenceTransformer; \
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SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')"
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# Expose the port Chainlit runs on
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EXPOSE 7860
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# Run the Chainlit application
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CMD ["chainlit", "run", "model.py", "--host", "0.0.0.0", "--port", "7860"]
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