Numan sheikh commited on
Commit
d506599
·
1 Parent(s): 2e338d1

Add model pre-download steps to Dockerfile to prevent timeout

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Files changed (1) hide show
  1. Dockerfile +12 -2
Dockerfile CHANGED
@@ -8,10 +8,20 @@ WORKDIR /app
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  COPY requirements.txt .
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  # Install any needed packages specified in requirements.txt
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- # Also, download textblob corpora which is required by sentiment_analyzer.py
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  RUN pip install --no-cache-dir -r requirements.txt \
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  && python -m textblob.download_corpora
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  # Copy the entire project directory into the container at /app
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  COPY . .
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@@ -20,4 +30,4 @@ EXPOSE 8501
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  # Define the command to run the Streamlit application
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  # Streamlit runs on 0.0.0.0 by default in Docker
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- CMD ["streamlit", "run", "frontend/app.py", "--server.port=8501", "--server.address=0.0.0.0"]
 
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  COPY requirements.txt .
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  # Install any needed packages specified in requirements.txt
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+ # Also, download textblob corpora
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  RUN pip install --no-cache-dir -r requirements.txt \
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  && python -m textblob.download_corpora
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+ # --- ADD THESE LINES TO PRE-DOWNLOAD HUGGING FACE MODELS ---
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+ # You need to know the exact model IDs your sentiment and sarcasm scripts use.
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+ # I'll use common examples. Adjust if your models are different.
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+ # Example for Sentiment Model (adjust model name if yours is different):
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+ RUN python -c "from transformers import pipeline; pipeline('sentiment-analysis', model='cardiffnlp/twitter-roberta-base-sentiment-latest')"
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+
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+ # Example for Sarcasm Model (adjust model name if yours is different):
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+ RUN python -c "from transformers import AutoTokenizer, AutoModelForSequenceClassification; tokenizer = AutoTokenizer.from_pretrained('mrm8488/distilroberta-base-finetuned-sarcasm'); model = AutoModelForSequenceClassification.from_pretrained('mrm8488/distilroberta-base-finetuned-sarcasm')"
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+ # --- END OF ADDED LINES ---
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+
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  # Copy the entire project directory into the container at /app
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  COPY . .
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  # Define the command to run the Streamlit application
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  # Streamlit runs on 0.0.0.0 by default in Docker
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+ CMD ["streamlit", "run", "frontend/app.py", "--server.port=8501", "--server.address=0.0.0.0"]