Optimize Dockerfile for Hugging Face Spaces deployment

Dockerfile

@@ -1,13 +1,11 @@
-# Use an official NVIDIA CUDA base image with Ubuntu 22.04 to ensure Vast.ai compatibility and GPU support
-FROM nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu22.04
+# Lightweight Python image for Hugging Face Spaces (no GPU needed for edge-tts)
+FROM python:3.10-slim
 
 # Set non-interactive to avoid prompts during apt-get
 ENV DEBIAN_FRONTEND=noninteractive
 
-# Install Python 3.10, pip, ffmpeg, and libsndfile1 for audio processing stability
+# Install ffmpeg and libsndfile1 for audio processing
 RUN apt-get update && apt-get install -y \
-    python3 \
-    python3-pip \
     ffmpeg \
     libsndfile1 \
     && rm -rf /var/lib/apt/lists/*
@@ -15,24 +13,23 @@ RUN apt-get update && apt-get install -y \
 # Set the working directory
 WORKDIR /app
 
-# Upgrade pip for better dependency resolution
-RUN pip3 install --no-cache-dir --upgrade pip
-
-# Install PyTorch explicitly for CUDA 11.8 to ensure full RTX 3090 / Vast.ai compatibility
-# (Done before other requirements to ensure correct indexing)
-RUN pip3 install --no-cache-dir torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
+# Upgrade pip
+RUN pip install --no-cache-dir --upgrade pip
 
 # Copy the requirements file into the container
 COPY requirements.txt .
 
 # Install dependencies
-RUN pip3 install --no-cache-dir -r requirements.txt
+RUN pip install --no-cache-dir -r requirements.txt
 
 # Copy the rest of the application code
 COPY . .
 
-# Expose the FastAPI port
-EXPOSE 8000
+# Create required directories
+RUN mkdir -p outputs temp models
+
+# Hugging Face Spaces requires port 7860
+EXPOSE 7860
 
-# Run the FastAPI application using uvicorn
-CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8000"]
+# Run the FastAPI application on port 7860 (Hugging Face requirement)
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]