Fix Dockerfile - use libgl1 for Debian Trixie compatibility

Dockerfile

@@ -2,12 +2,6 @@
 # FarmEyes - HuggingFace Spaces Dockerfile
 # =============================================================================
 # AI-Powered Crop Disease Detection for African Farmers
-# 
-# This Dockerfile is optimized for HuggingFace Spaces free tier:
-# - Uses Python 3.10 slim image
-# - Installs llama-cpp-python for CPU inference
-# - Downloads N-ATLaS GGUF model at runtime (~4.92GB)
-# - Runs on port 7860 (HF Spaces default)
 # =============================================================================
 
 FROM python:3.10-slim
@@ -22,17 +16,16 @@ ENV HOST=0.0.0.0
 ENV PORT=7860
 
 # Install system dependencies
-# - ffmpeg: for audio processing (Whisper)
-# - libsm6, libxext6, libgl1: for OpenCV (image processing)
-# - build-essential, cmake: for compiling llama-cpp-python
+# Note: Using libgl1 instead of libgl1-mesa-glx for Debian Trixie compatibility
 RUN apt-get update && apt-get install -y --no-install-recommends \
     ffmpeg \
     libsm6 \
     libxext6 \
-    libgl1-mesa-glx \
+    libgl1 \
     build-essential \
     cmake \
     git \
+    curl \
     && rm -rf /var/lib/apt/lists/*
 
 # Copy requirements first (for Docker cache optimization)
@@ -42,11 +35,9 @@ COPY requirements.txt .
 RUN pip install --no-cache-dir --upgrade pip
 
 # Install Python dependencies
-# Note: llama-cpp-python is compiled for CPU (no CUDA on free tier)
 RUN pip install --no-cache-dir -r requirements.txt
 
 # Install llama-cpp-python for CPU
-# This enables GGUF model inference
 RUN pip install --no-cache-dir llama-cpp-python
 
 # Copy all application code
@@ -58,13 +49,5 @@ RUN mkdir -p /app/uploads /app/temp
 # Expose port 7860 (HuggingFace Spaces default)
 EXPOSE 7860
 
-# Health check
-HEALTHCHECK --interval=30s --timeout=30s --start-period=5s --retries=3 \
-    CMD curl -f http://localhost:7860/api/health || exit 1
-
 # Run the application
-# The app will:
-# 1. Start FastAPI server
-# 2. Download N-ATLaS GGUF model on first request (~5-15 min)
-# 3. Serve the web interface
-CMD ["python", "main.py"]
+CMD ["python", "main.py"]