python --version
# Should show Python 3.8 or higher

# Test OpenGL context creation
python -c "import moderngl; ctx = moderngl.create_standalone_context(); print('✅ OpenGL works!')"

pip install moderngl numpy pillow

pip install matplotlib seaborn scikit-learn tqdm

pip install torch transformers
# Note: Can be uninstalled after model conversion

git clone https://github.com/chimera-ai/chimera.git
cd chimera

# Run basic demo
python chimera_v3/demo_pure.py

# Run examples
python examples/math_operations.py

# 1. Clone repository
git clone https://github.com/chimera-ai/chimera.git
cd chimera

# 2. Create virtual environment (recommended)
python -m venv chimera-env
source chimera-env/bin/activate  # On Windows: chimera-env\Scripts\activate

# 3. Install all dependencies
pip install -r requirements.txt

# 4. Install in development mode
pip install -e .

# 5. Install development tools
pip install -r requirements-dev.txt

# 6. Run tests
python -m pytest tests/

# 7. Check code style
flake8 chimera_v3/
black --check chimera_v3/
mypy chimera_v3/

# Pre-commit hooks (optional but recommended)
pip install pre-commit
pre-commit install

# Documentation tools
pip install sphinx sphinx-rtd-theme myst-parser

# Profiling tools
pip install line_profiler memory_profiler

# Pull the latest image
docker pull chimera-ai/chimera:latest

# Run with GPU support
docker run --gpus all -p 8080:8080 chimera-ai/chimera:latest

# Build the image
docker build -t chimera-ai .

# Run with different configurations
docker run -p 8080:8080 chimera-ai  # CPU only
docker run --gpus all -p 8080:8080 chimera-ai  # With GPU

version: '3.8'
services:
  chimera:
    build: .
    ports:
      - "8080:8080"
    volumes:
      - ./models:/app/models
      - ./data:/app/data
    environment:
      - CUDA_VISIBLE_DEVICES=0
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]

# Install Visual Studio Build Tools
# Install GPU drivers (NVIDIA/AMD/Intel)
# Enable WSL2 for better performance (optional)

# Using PowerShell
git clone https://github.com/chimera-ai/chimera.git
cd chimera

# Create virtual environment
python -m venv chimera-env
chimera-env\Scripts\activate

# Install dependencies
pip install moderngl numpy pillow

# Test installation
python chimera_v3/demo_pure.py

# Install system dependencies
sudo apt update
sudo apt install python3-dev python3-pip
sudo apt install mesa-utils  # For OpenGL utilities

# Install Python dependencies
pip3 install moderngl numpy pillow

# Test OpenGL
glxinfo | grep "OpenGL version"

# Install dependencies
sudo pacman -S python python-pip mesa

# Install Python packages
pip install moderngl numpy pillow

# Install dependencies
sudo dnf install python3-devel mesa-libGL-devel

# Install Python packages
pip3 install moderngl numpy pillow

# Install dependencies
pip install moderngl numpy pillow

# Test installation
python chimera_v3/demo_pure.py

# Install dependencies (includes Metal backend)
pip install moderngl numpy pillow

# May need to install additional dependencies
brew install mesa-glu

# Test installation
python chimera_v3/demo_pure.py

# Install optimal NVIDIA drivers
# Ubuntu: sudo ubuntu-drivers autoinstall
# Windows: Update via GeForce Experience

# Verify CUDA compatibility (optional)
nvidia-smi

# Install NVIDIA tools for monitoring
pip install pynvml

# Enable persistent mode
sudo nvidia-persistenced --persistence-mode

# Install ROCm (if available)
# Ubuntu: Follow ROCm installation guide

# Test OpenGL
glxinfo | grep "OpenGL vendor"

# Update Intel drivers
# Ubuntu: sudo apt install intel-media-va-driver

# Verify OpenGL
glxinfo | grep "OpenGL version"

# Update GPU drivers to latest version
# Check OpenGL version support
python -c "import moderngl; print(moderngl.create_standalone_context().info)"

# Install/update moderngl
pip uninstall moderngl
pip install --upgrade moderngl

# Check system dependencies
# Ubuntu: sudo apt install libgl1-mesa-glx
# Windows: Install OpenGL runtime
# macOS: Install Xcode command line tools

# Reduce memory usage
export MODERNGL_MAX_TEXTURE_SIZE=2048

# Or in Python:
import os
os.environ['MODERNGL_MAX_TEXTURE_SIZE'] = '2048'

# Force specific OpenGL version
export MESA_GLSL_VERSION_OVERRIDE=330
export MODERNGL_GLSL_VERSION=330

# Install Microsoft Visual C++ redistributables
# Update Windows to latest version
# Enable hardware acceleration in Windows settings

# Install 32-bit libraries if needed
sudo apt install libgl1-mesa-glx:i386

# Check GPU permissions
sudo usermod -a -G video $USER

# Reset OpenGL preferences
defaults delete com.apple.opengl

# Update to latest macOS
softwareupdate --install -a

# Test 1: OpenGL context
python -c "
import moderngl
ctx = moderngl.create_standalone_context()
print('✅ OpenGL context created successfully')
print(f'OpenGL version: {ctx.info}')
ctx.release()
"

# Test 2: Basic operations
python -c "
import numpy as np
import moderngl

ctx = moderngl.create_standalone_context()
a = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32)
print('✅ NumPy operations work')
ctx.release()
"

# Test 3: CHIMERA imports
python -c "
try:
    import chimera_v3
    print('✅ CHIMERA imports successful')
except ImportError as e:
    print(f'❌ Import failed: {e}')
"

# Test 4: Demo execution
python chimera_v3/demo_pure.py

# Run performance tests
python examples/benchmark_suite.py

# Expected output (varies by hardware):
# Matrix Multiplication: 43.57× speedup vs CPU
# Self-Attention: 25.1× speedup vs CPU

# Update from Git
cd chimera
git pull origin main

# Reinstall if needed
pip install -e .

# Update dependencies
pip install -r requirements.txt --upgrade

# Models and trained weights
cp -r models/ models_backup_$(date +%Y%m%d)/

# Configuration files
cp -r configs/ configs_backup_$(date +%Y%m%d)/

# Logs and outputs
cp -r logs/ logs_backup_$(date +%Y%m%d)/