Update Dockerfile

Dockerfile

@@ -1,48 +1,51 @@
-# Base image (as requested - WARNING: Lacks CUDA drivers for GPU acceleration)
+# Use an official Python runtime as a parent image
 FROM python:3.9-slim
 
-# Set environment variables
-ENV DEBIAN_FRONTEND=noninteractive
-ENV PYTHONUNBUFFERED=1
-ENV SHELL=/bin/bash
-
-# Set working directory
+# Set the working directory in the container
 WORKDIR /app
 
-# Install system dependencies from packages.txt (via apt-get)
-# Includes: ffmpeg (needed by ffmpeg-python), git (needed by parler-tts install)
-# Includes: build-essential & python3-dev (needed for compiling some pip packages)
-# Includes: curl (needed for HEALTHCHECK)
+# Install system dependencies:
+# - build-essential: For compiling some Python packages if needed
+# - curl, git, software-properties-common: General utilities, git for some pip installs
+# - ffmpeg: For video processing
+# - python3-dev: For C extensions if any Python package needs to build them
+# - libsndfile1: For soundfile to work correctly
 RUN apt-get update && apt-get install -y --no-install-recommends \
     build-essential \
     curl \
-    software-properties-common \
     git \
+    software-properties-common \
     ffmpeg \
     python3-dev \
-    && \
-    # Clean up apt cache to reduce image size
-    rm -rf /var/lib/apt/lists/*
+    libsndfile1 \
+    && rm -rf /var/lib/apt/lists/*
 
-# Copy requirements file first to leverage Docker cache
+# Copy the requirements file into the container at /app
 COPY requirements.txt ./
 
-# Install Python dependencies from the requirements file
-# Note: On this non-CUDA base, pip will likely install CPU-only torch/diffusers.
-RUN pip3 install --no-cache-dir -r requirements.txt
-
-# Copy the application code from your local 'src' directory to the container's '/app/src' directory
-COPY src/ ./src/
-
-# Expose the default Streamlit port
-EXPOSE 8501
-
-# Health check for Hugging Face Spaces compatibility
-# Checks if the Streamlit core endpoint is reachable
-HEALTHCHECK --interval=15s --timeout=5s --start-period=30s --retries=3 \
-  CMD curl --fail http://localhost:8501/_stcore/health || exit 1
-
-# Command to run the Streamlit application when the container starts
-# Points to the script inside the 'src' directory
-# Includes flags to make Streamlit accessible externally on the specified port
-CMD ["streamlit", "run", "src/app_hf_space_optimized.py", "--server.port=8501", "--server.address=0.0.0.0"]
+# Install any needed packages specified in requirements.txt
+# --no-cache-dir: Reduces image size by not storing the pip cache
+# It's good practice to upgrade pip first
+RUN pip install --no-cache-dir --upgrade pip
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the rest of the application code into the container at /app
+COPY . .
+
+# Make port 7860 available to the world outside this container (Streamlit default)
+# Hugging Face Spaces will handle the actual port mapping.
+EXPOSE 7860
+
+# Define environment variables for Hugging Face Hub caching (optional but good practice)
+# These will be overridden by HF Spaces secrets/vars if set there, but good defaults.
+ENV HUGGINGFACE_HUB_CACHE=/app/.cache/huggingface/hub
+ENV HF_HOME=/app/.cache/huggingface
+ENV TRANSFORMERS_CACHE=/app/.cache/huggingface/hub
+ENV DIFFUSERS_CACHE=/app/.cache/huggingface/hub
+# Create the cache directory and set permissions (if needed, usually pip creates it)
+# RUN mkdir -p /app/.cache/huggingface/hub && chmod -R 777 /app/.cache
+
+# Command to run the Streamlit application
+# The --server.port and --server.address are important for HF Spaces.
+# --server.fileWatcherType none can prevent issues in some environments.
+CMD ["streamlit", "run", "app.py", "--server.port=7860", "--server.address=0.0.0.0", "--server.fileWatcherType=none"]