Update Dockerfile

Dockerfile

@@ -4,38 +4,47 @@ FROM python:3.10-slim
 # Set working directory
 WORKDIR /app
 
-# 1. Install System Dependencies
+# 1. Install System Dependencies (Minimal)
 RUN apt-get update && apt-get install -y \
     libgl1 \
     libglib2.0-0 \
     && rm -rf /var/lib/apt/lists/*
 
-# 2. Upgrade Pip
-RUN pip install --no-cache-dir --upgrade pip
+# 2. Install 'uv' (The High-Speed Installer)
+RUN pip install uv
 
-# 3. Install Numpy ALONE (Layer 1)
-# We force binary install to prevent compilation spikes
-RUN pip install --no-cache-dir --only-binary=:all: numpy==1.26.4
+# --- THE IRONCLAD INSTALLATION SEQUENCE ---
+# We install dependencies ONE BY ONE to prevent Memory/CPU spikes.
+# If one step fails, you don't lose the progress of the others.
 
-# 4. Install Core Deps (Layer 2)
-RUN pip install --no-cache-dir --only-binary=:all: \
-    pillow<11.0 \
-    huggingface_hub==0.23.0 \
-    cryptography==42.0.5
+# Step A: Numpy (The Foundation) - Memory Heavy
+RUN uv pip install --system --no-cache numpy==1.26.4
 
-# 5. Install Gradio (Layer 3)
-# Installing it last ensures dependencies are already met
-RUN pip install --no-cache-dir --only-binary=:all: gradio==4.44.0
+# Step B: Pillow (Image Processing)
+RUN uv pip install --system --no-cache "pillow<11.0"
 
-# 6. Install Llama Wheel (Layer 4)
-RUN pip install --no-cache-dir https://github.com/mrzeeshanahmed/llama-cpp-python/releases/download/v0.3.17-manylinux-x86_64/llama_cpp_python-0.3.17-cp310-cp310-linux_x86_64.whl
+# Step C: Cryptography (Security)
+RUN uv pip install --system --no-cache cryptography==42.0.5
 
-# 7. Copy App Code
-COPY . .
+# Step D: Hugging Face Hub (Network)
+RUN uv pip install --system --no-cache huggingface_hub==0.23.0
+
+# Step E: Matplotlib (Data Viz - Required by Gradio)
+RUN uv pip install --system --no-cache "matplotlib<4.0"
+
+# Step F: Pandas (Data - Required by Gradio)
+RUN uv pip install --system --no-cache "pandas<3.0"
+
+# Step G: Gradio (The Interface)
+# Since dependencies are already installed above, this will be light.
+RUN uv pip install --system --no-cache gradio==4.44.0
 
-# 8. Configure Network
+# Step H: Llama CPP (The Engine)
+# Using the Pre-Compiled Custom Wheel for Debian/CPU
+RUN uv pip install --system --no-cache https://github.com/mrzeeshanahmed/llama-cpp-python/releases/download/v0.3.17-manylinux-x86_64/llama_cpp_python-0.3.17-cp310-cp310-linux_x86_64.whl
+
+# --- FINAL SETUP ---
+COPY . .
 ENV GRADIO_SERVER_NAME="0.0.0.0"
 EXPOSE 7860
-
-# 9. Launch
 CMD ["python", "app.py"]