Project FluentAI

Overview

Project FluentAI is a Universal Windows Platform (UWP) application designed to provide a modern, responsive AI assistant experience on Windows 10 and 11. It integrates with both Google Gemini and local Ollama models, offering a flexible and powerful conversational AI interface. The application features a clean, Windows 10-inspired user interface, robust conversation management, and customizable settings for AI model selection and application theme.

Features

• Intelligent AI Chat: Engage in conversations with AI models, powered by either Google Gemini (via API) or local Ollama instances.
• Conversation Management: Create, rename, pin, and delete chat conversations, allowing for organized and persistent interactions.
• Search Functionality: Easily find specific conversations using a built-in search feature.
• Theming Options: Personalize the application's appearance with Light, Dark, or System theme settings.
• Responsive User Interface: The UI adapts seamlessly to different window sizes, providing an optimal experience on various devices.
• Message Actions: Copy or delete individual messages within a conversation using context menus.
• Customizable AI Backend: Switch between Gemini and Ollama models, and configure API keys and local model names directly within the application settings.

Technologies Used

• Universal Windows Platform (UWP): The framework for building modern Windows applications.
• C#: The primary programming language for the application logic.
• XAML: Used for defining the application's user interface.
• .NET: The underlying framework for application development.
• MVVM (Model-View-ViewModel): Architectural pattern used for clear separation of concerns.
• Newtonsoft.Json: A popular JSON framework for .NET, used for serializing and deserializing AI model requests and responses.

Architecture

The application follows the MVVM architectural pattern, promoting a clean separation between the UI (Views), application logic (ViewModels), and data (Models).

• Views: XAML pages like ChatPage.xaml and SettingsPage.xaml define the visual structure and layout.
• ViewModels: Classes like MainViewModel.cs handle the application's business logic, data manipulation, and interaction with AI services. They expose data and commands to the Views.
• Models: Simple C# classes such as ChatItem.cs and Message.cs represent the data structures used within the application.

Prerequisites

To build and run Project FluentAI, you will need:

• Windows 10 or 11: The application targets UWP, requiring a compatible Windows operating system.
• Visual Studio: Recommended for development, specifically Visual Studio 2019 or newer with the "Universal Windows Platform development" workload installed.
• .NET SDK: Compatible with the project's target framework.
• Ollama (Optional): If you plan to use local AI models, you will need to have an Ollama server running locally with the desired models installed (e.g., qwen3:8b).
• Google Gemini API Key (Optional): If you plan to use the Gemini API, you will need an API key from the Google AI Studio.

Installation and Setup

1. Clone the repository:

   git clone https://github.com/xiefnity/FluentAI-UWP.git
   cd ProjectFluentAI

2. Open in Visual Studio: Open the Project FluentAI.sln file in Visual Studio.
3. Restore NuGet Packages: Visual Studio should automatically restore the necessary NuGet packages (Microsoft.NETCore.UniversalWindowsPlatform and Newtonsoft.Json). If not, right-click on the solution in Solution Explorer and select "Restore NuGet Packages."
4. Build the Project: Build the solution (Build > Build Solution) to ensure all dependencies are resolved and the project compiles successfully.
5. Run the Application: Select the desired target (e.g., "Local Machine") and run the application from Visual Studio.

Configuration

Upon launching the application, navigate to the Settings page to configure your AI models and theme:

• App Theme: Choose between Light, Dark, or System default.
• Use Local Models (Ollama): Toggle this switch to enable or disable local Ollama integration. If enabled, specify the Ollama Model Name (e.g., qwen3:8b).
• Use Gemini API: Toggle this switch to enable or disable Google Gemini integration. If enabled, provide your Gemini API Key.

Contributing

Contributions are welcome! Please feel free to fork the repository, make your changes, and submit a pull request. For major changes, please open an issue first to discuss what you would like to change.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

• Developed by XIEFNITY (github.com/xiefnity)
• Inspired by modern Windows UI/UX principles.