Update Dockerfile

Dockerfile

@@ -4,25 +4,22 @@ FROM python:3.10-slim
 # Set working directory
 WORKDIR /app
 
-# 1. Install Build Tools
-# strictly required for the fallback compilation
+# 1. Install System Dependencies
+# Basic tools required for the OS simulation
 RUN apt-get update && apt-get install -y \
-    git \
     curl \
-    build-essential \
-    cmake \
-    libopenblas-dev \
+    git \
+    libgomp1 \
     && rm -rf /var/lib/apt/lists/*
 
-# 2. CRITICAL: Upgrade pip
-# Old pip versions (default in 3.10-slim) often fail to find binary wheels,
-# forcing a slow source build. Upgrading fixes this.
+# 2. Upgrade pip (Essential for finding modern wheels)
 RUN pip install --upgrade pip setuptools wheel
 
 # 3. Download Retro Font (VT323)
 RUN curl -L -o /app/VT323.ttf https://github.com/google/fonts/raw/main/ofl/vt323/VT323-Regular.ttf
 
-# 4. Install Python Dependencies (Split for caching)
+# 4. Install Core Python Dependencies (Split for caching)
+# These are safe and install quickly.
 RUN pip install --no-cache-dir \
     torch \
     torchvision \
@@ -38,11 +35,14 @@ RUN pip install --no-cache-dir \
     safetensors \
     scipy
 
-# 5. Install Llama-CPP-Python (The Fix)
-# - CMAKE_ARGS="-DLLAMA_NATIVE=OFF": Prevents hanging on architecture detection.
-# - -v: Verbose mode so you can see the build scrolling instead of freezing.
-ENV CMAKE_ARGS="-DLLAMA_NATIVE=OFF -DLLAMA_BLAS=ON -DGGML_NATIVE=OFF"
-RUN pip install --no-cache-dir -v llama-cpp-python
+# 5. ATTEMPT Fast Llama Install (Optional)
+# --only-binary: Prevents the slow compilation loop.
+# || true: Allows the build to continue even if this fails.
+# We will handle the missing library in app.py
+RUN pip install llama-cpp-python \
+    --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cpu \
+    --only-binary=llama-cpp-python \
+    || echo "⚠️ Llama-CPP wheel not found. Skipping to avoid compile hang."
 
 # 6. Create a non-root user
 RUN useradd -m -u 1000 user
@@ -63,12 +63,17 @@ from flask_sock import Sock
 from diffusers import StableDiffusionPipeline, AutoencoderTiny, LCMScheduler
 from PIL import Image, ImageDraw
 
-# Graceful degradation if library fails (prevents crash loop)
+# ============================================================================
+# SAFE IMPORT LOGIC
+# ============================================================================
 try:
     from llama_cpp import Llama
+    HAS_LLM = True
+    print("[*] Llama-CPP module loaded successfully.")
 except ImportError:
-    Llama = None
-    print("[!] CRITICAL: Llama-cpp-python failed to import. AI features will be limited.")
+    HAS_LLM = False
+    print("[!] NOTICE: Llama-CPP not found. Text generation features will be disabled.")
+    print("[!] The graphical OS and image generation will still work perfectly.")
 
 # ============================================================================
 # 1. FRONTEND ASSET
@@ -357,15 +362,6 @@ class OSKernel:
                 return {"action": "focus", "pid": proc.pid}
         return {"action": "none"}
 
-class LatentFileSystem:
-    def __init__(self, root_path="./litewin_disk"):
-        self.root = Path(root_path)
-        self.root.mkdir(exist_ok=True)
-
-class LatentVM:
-    def execute(self, bytecode: str, target_latent: torch.Tensor) -> torch.Tensor:
-        return target_latent # Placeholder for VM execution
-
 # ============================================================================
 # 3. SERVER & ML PIPELINE
 # ============================================================================