Implement WSL GPU support for Ollama integration and reorganize documentation

This commit includes:
- Fix for NVIDIA libraries in WSL (symlinks and paths)
- Enhanced Docker NVIDIA runtime integration
- New scripts for managing Ollama processes and diagnosing issues
- Jupyter notebook (nvidia_wsl_fix_guide.ipynb) for WSL GPU troubleshooting
- Documentation of GPU status and fixes
- Reorganization of docs directory into logical categories (setup, guides, architecture, troubleshooting, status)

Author: msalsouri

docs/AI_ASSISTANT_GUIDE.md

@@ -0,0 +1,113 @@
+# AI Assistant Guide for CodexContinue Project
+
+## Project Overview
+
+CodexContinue is a cross-platform development project that integrates machine learning capabilities with a web application. The project is designed to run on both macOS and Windows (via WSL - Windows Subsystem for Linux) environments, with specific optimizations for each platform.
+
+## Repository Structure
+
+- `app/`: Core application code
+- `backend/`: Backend API server built with FastAPI
+- `frontend/`: Frontend web interface
+- `ml/`: Machine learning components and model integration
+- `docker/`: Docker configuration for containerized development
+- `scripts/`: Utility scripts for setup, maintenance, and diagnostics
+- `docs/`: Documentation for various aspects of the project
+- `notebooks/`: Jupyter notebooks for data analysis and demonstrations
+
+## Current Development Context
+
+You are assisting with the cross-platform setup of CodexContinue, specifically focusing on:
+
+1. **Windows WSL Development Environment**: Setting up the development environment in Windows Subsystem for Linux with GPU support for machine learning components
+2. **DevContainer Configuration**: Ensuring proper DevContainer configuration across platforms
+3. **Ollama Integration**: Configuring Ollama (a large language model server) to run properly with GPU acceleration in WSL
+
+## Key Files and Directories
+
+### Configuration Files
+
+- `.devcontainer/`: Contains DevContainer configuration
+- `docker-compose.yml`: Main Docker Compose configuration
+- `docker-compose.macos.yml`: macOS-specific Docker Compose overrides (CPU-only for Ollama)
+- `docker-compose.dev.yml`: Development environment Docker Compose configuration
+
+### Documentation
+
+- `docs/WINDOWS_WSL_GUIDE.md`: Guide for setting up the project in WSL
+- `docs/DEVCONTAINER_TROUBLESHOOTING.md`: Troubleshooting for DevContainer issues
+- `docs/DEVCONTAINER_VOLUME_MOUNT_FIX.md`: Solutions for volume mounting issues in WSL
+
+### Scripts
+
+- `scripts/fix-devcontainer.sh`: Script to fix DevContainer configuration issues
+- `scripts/wsl-quick-setup.sh`: Quick setup script for WSL environment
+- `scripts/start-ollama-wsl.sh`: Script to start Ollama in WSL with GPU support
+- `scripts/check-platform.sh`: Verify environment configuration
+
+### Machine Learning
+
+- `ml/models/ollama/`: Ollama model configuration
+- `ml/scripts/build_codexcontinue_model.sh`: Script to build the custom model
+
+## Development Workflow
+
+1. **Repository Setup**: The project is maintained in a Git repository with coordination between macOS and Windows environments
+2. **Container-Based Development**: Development is primarily done in Docker containers via VS Code DevContainers
+3. **Platform-Specific Configurations**:
+   - macOS uses CPU-only mode for Ollama
+   - Windows (WSL) uses GPU acceleration for Ollama
+
+## Recent Changes
+
+Recent work has focused on:
+
+1. Adding WSL support with GPU acceleration
+2. Fixing DevContainer configurations for cross-platform compatibility
+3. Creating documentation and scripts for smoother onboarding
+
+## Current Status
+
+The project has been successfully:
+
+1. Set up on macOS
+2. Configured for Windows WSL development
+3. Fixed for DevContainer issues between platforms
+
+The user is now at the stage of verifying the GPU integration with Ollama in the WSL environment.
+
+## Common Issues and Solutions
+
+1. **Volume Mount Issues in WSL**: Fixed by using relative paths instead of `${localWorkspaceFolder}`
+2. **GPU Integration in WSL**: Requires proper NVIDIA driver installation and container toolkit setup
+3. **Cross-Platform Development**: Docker volumes are platform-specific, so models need to be built separately on each platform
+
+## Next Steps
+
+1. Verify GPU support in WSL for Ollama
+2. Test the full application stack
+3. Continue development across both platforms
+
+## Terminology
+
+- **WSL**: Windows Subsystem for Linux
+- **DevContainer**: Development containers for VS Code
+- **Ollama**: Self-hosted large language model server
+- **CodexContinue**: The project name, referring to an AI-assisted coding and documentation tool
+- **Docker**: Containerization platform used for development and deployment
+- **GPU**: Graphics Processing Unit, used for accelerating machine learning tasks
+- **NVIDIA**: Manufacturer of GPUs, relevant for WSL GPU support
+- **FastAPI**: Web framework for building APIs with Python
+- **Docker Compose**: Tool for defining and running multi-container Docker applications
+- **Jupyter Notebooks**: Interactive notebooks for data analysis and visualization
+- **Volume Mounting**: The process of linking directories between the host and container
+- **Cross-Platform Development**: Developing software that runs on multiple operating systems
+- **Containerization**: The practice of packaging software into containers for consistent deployment
+- **Machine Learning**: A subset of AI focused on building systems that learn from data
+- **Model Integration**: The process of incorporating machine learning models into applications
+- **API**: Application Programming Interface, a set of rules for building software applications
+- **Frontend**: The user interface of the application
+- **Backend**: The server-side logic and database interactions of the application
+- **Dockerfile**: A script containing instructions to build a Docker image
+- **Image**: A lightweight, standalone, executable package that includes everything needed to run a piece of software
+- **Container**: A standard unit of software that packages up code and all its dependencies