Dockerfile

Dockerfile

@@ -2,39 +2,37 @@ FROM python:3.10-slim
 
 WORKDIR /code
 
-# Install system dependencies required for building some Python packages
+# Install system dependencies
 RUN apt-get update && apt-get install -y \
     gcc \
     g++ \
     git \
     wget \
-    ffmpeg \
     && rm -rf /var/lib/apt/lists/*
 
-# Set environment variables for Hugging Face cache and tokenizers
-ENV HF_HOME=/code/cache
+# Set environment variables
 ENV TRANSFORMERS_CACHE=/code/cache
+ENV HF_HOME=/code/cache
 ENV TOKENIZERS_PARALLELISM=false
 
-# Copy requirements first for better Docker layer caching
+# Copy requirements first for better caching
 COPY requirements.txt /code/requirements.txt
 
-# Upgrade pip and install Python dependencies
+# Install Python dependencies
 RUN pip install --no-cache-dir --upgrade pip
-RUN pip install --no-cache-dir -r /code/requirements.txt
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
 
-# Pre-download the models at build time to avoid runtime delays.
-# This ensures the application starts up quickly in the Space.
-# RUN python -c "from transformers import pipeline; import whisper; pipeline('summarization', model='facebook/bart-large-cnn'); whisper.load_model('base', download_root='/code/cache')"
+# Download models at build time to avoid runtime delays
+RUN python -c "from sentence_transformers import SentenceTransformer; SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')"
 
-# Copy the rest of the application code into the container
-COPY . /code/
+# Copy the application code
+COPY . /code
 
-# Create the cache directory (the ENV variables point here)
+# Create cache directory
 RUN mkdir -p /code/cache
 
-# Expose the port Gradio runs on
+# Expose port 7860 for Hugging Face Spaces
 EXPOSE 7860
 
-# Command to run the application
-CMD ["python3", "app.py"]
+# Run the application
+CMD ["python", "app.py"]