Update Dockerfile

Dockerfile

@@ -1,23 +1,29 @@
-# Use the official Python 3.9 slim image
-FROM python:3.9-slim
+# Use official Python 3.10 image with slim variant for smaller size
+FROM python:3.10-slim
 
-# Set the working directory
-WORKDIR /app
+# Set environment variables
+ENV PYTHONDONTWRITEBYTECODE=1 \
+    PYTHONUNBUFFERED=1 \
+    HF_HOME=/app/.cache \
+    TRANSFORMERS_CACHE=/app/.cache
 
-# Create and configure the cache directory with recursive permissions
-RUN mkdir -p /app/.cache && chmod -R 777 /app/.cache
+# Create directories and set permissions
+WORKDIR /app
+RUN mkdir -p /app/.cache /app/models && \
+    chmod -R 777 /app/.cache /app/models
 
-# Set environment variables for caching
-ENV TRANSFORMERS_CACHE=/app/.cache
-ENV HF_HOME=/app/.cache
+# Install system dependencies for audio processing
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    libsndfile1 \
+    ffmpeg && \
+    rm -rf /var/lib/apt/lists/*
 
-# Install dependencies
+# Install Python dependencies
 COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt
 
-# Pre-download the model (replace 'suno/bark' with a valid model if needed)
-RUN mkdir -p /app/models/suno-bark && \
-    python -c "from transformers import AutoTokenizer, AutoProcessor, BarkModel; \
+# Pre-download and cache models
+RUN python -c "from transformers import AutoTokenizer, AutoProcessor, BarkModel; \
                tokenizer = AutoTokenizer.from_pretrained('suno/bark'); \
                processor = AutoProcessor.from_pretrained('suno/bark'); \
                model = BarkModel.from_pretrained('suno/bark'); \
@@ -28,5 +34,6 @@ RUN mkdir -p /app/models/suno-bark && \
 # Copy application code
 COPY app.py .
 
+# Expose port and run
 EXPOSE 7860
 CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]