Butler - An Intelligent Assistant System

Butler is a feature-rich, intelligent assistant system developed in Python. It integrates natural language processing, a powerful algorithms library, dynamic program management, a sandboxed code interpreter, and an extensible plugin system. Designed with a modular architecture, Butler is capable of performing a wide range of complex tasks through text, voice, or API commands.

This project also includes a comprehensive library of common algorithms and exposes them through a developer-friendly REST API, making them accessible from any programming language.

Features

• Conversational AI: Uses the DeepSeek API for natural language understanding and response generation.
• Extensible Program Management: Dynamically loads and executes external program modules.
• Advanced Algorithm Library: A rich, efficient, and well-documented library of algorithms.
• Developer-Friendly API: A dedicated REST API for direct access to the algorithm library.
• Interactive Command Panel: A Tkinter-based GUI for text-based interaction.
• Voice Interaction: Supports voice commands and speech synthesis using Azure Cognitive Services.
• Local Code Interpreter: A secure, sandboxed environment for executing Python code generated from natural language commands.
• Plugin System: Easily extend Butler's functionality with custom plugins.

Project Structure

The project is organized into several key directories:

• butler/: The core of the Butler assistant, including the main application logic, GUI, and conversational AI integration.
• local_interpreter/: A standalone, sandboxed code interpreter for safely executing code generated from natural language.
• package/: A collection of standalone modules and tools that can be invoked by the Butler assistant.
• plugin/: A framework for creating and managing plugins to extend Butler's capabilities.
• logs/: Contains log files for the application.

Getting Started

Installation

1. Clone the repository:

   git clone https://github.com/PAYDAY3/Butler.git
   cd Butler

2. Create a virtual environment (recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

4. Configure API Keys: Create a .env file in the root directory by copying the .env.example file. Then, add your API keys:

   DEEPSEEK_API_KEY="your_deepseek_api_key"
   AZURE_SPEECH_KEY="your_azure_speech_key"
   AZURE_SERVICE_REGION="your_azure_service_region"
   

Usage

Easy Launch (Recommended)

Once you have installed the dependencies and configured your API keys, you can start the application easily:

• On Windows: Simply double-click the run.bat file.
• On macOS or Linux: Run the run.sh script from your terminal with ./run.sh, or double-click it in your file manager (you may need to grant it execute permissions first with chmod +x run.sh).

These scripts will open the main application with its graphical user interface.

Manual Launch

If you prefer, you can still run the application manually from the command line.

Butler Assistant

To start the Butler assistant with its GUI:

python -m butler.main

You can interact with the assistant by typing commands in the input box or by using voice commands.

Local Interpreter

To run the standalone local code interpreter:

python -m local_interpreter.main

This will start a command-line interface where you can type natural language commands to be executed in a sandboxed environment.

Algorithms API

To start the REST API server for the algorithms library:

python -m butler.api

The server will run on http://localhost:5001. You can then make requests to the available endpoints (e.g., /api/sort, /api/search).

Packages

The package/ directory contains a collection of tools and utilities that can be executed by the Butler assistant. Each module in this directory should have a run() function, which serves as the entry point for execution.

To add a new package, simply create a new Python file in the package/ directory and implement a run() function within it. Butler will automatically discover and be able to execute it.

Plugins

The plugin/ directory contains plugins that extend the functionality of the Butler assistant. Each plugin should inherit from plugin.abstract_plugin.AbstractPlugin and implement the required methods.

The PluginManager will automatically load any valid plugins placed in this directory.

Contribution

We welcome contributions! Please feel free to submit a Pull Request. When contributing, please ensure your code adheres to the project's style and that you update documentation where appropriate.

License

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