The Aether is a scalable and intelligent system designed to interact with users in a natural and intuitive manner. Powered by cutting-edge technology, it can perform a variety of tasks using Natural Language Processing (NLP) and Voice Command Recognition. Key capabilities include:

• Voice Command Recognition: Executes user commands via speech recognition, such as opening applications, adjusting system settings, and controlling hardware.
• Task Automation: Automates system-level tasks including file management, program launching, email sending, and code generation.
• Dynamic Conversations: Integrated with OpenAI GPT, enabling meaningful conversations and the ability to reason through complex instructions, while also dynamically generating code.
• System Access: Full access to system resources allows managing applications, controlling hardware, and ensuring security and privacy.
• Personalization: Learns and adapts to the user's preferences over time, optimizing the user experience.

This assistant is designed to be modular, adaptable, and ready for future enhancements as technology evolves, providing deep integration with external services like email providers, web search engines, and more.

• Natural Language Processing (NLP): Understands and generates human-like responses via OpenAI GPT, facilitating a natural conversation with users.
• Voice Command Execution: Launch apps, take screenshots, set reminders, and perform various tasks based on voice commands.
• System Integration: Offers full control over system applications, hardware (volume, microphone), file manipulation, and script execution.
• Task Automation: Dynamically generates and runs scripts, enabling the assistant to act as a personal coding assistant.
• Scalable Architecture: Built to scale, allowing integration with IoT devices, machine learning tasks, and cloud-based services.
• Future-Proof Design: Modular components make the assistant adaptable to future advancements in AI and NLP.

To run the Aether, you need the following tools:

• Docker: Ensures easy deployment and cross-platform compatibility. Follow the official Docker installation guide here.
• OpenAI API Key: Required for GPT model integration. Sign up on OpenAI to obtain an API key.

Follow these steps to get the Aether running inside a Docker container:

1. Clone or Download the Repository: Clone the repository or download the latest release from the GitHub page:

   git clone https://github.com/n03stalg1a/aether.git
   cd aether

2. Build the Docker Image: Use the following command to build the Docker image:

   docker build -t aether .

3. Run the Docker Container: After building the image, run the container in detached mode to start the assistant in the background:

   docker run -d --name aether aether

4. Interact with the Assistant: Once the container is running, you can interact with the assistant using your microphone. It will process voice commands, run actions, and provide responses.

   • Ensure that your local microphone and speakers are connected for real-time interaction.

Set the following environment variables before running the assistant:

• OPENAI_API_KEY: The API key required for OpenAI GPT model access.

export OPENAI_API_KEY="your-api-key-here"

For security, it's recommended to set this key as an environment variable instead of hardcoding it in the code.

The assistant relies on several Python libraries, which are automatically installed during the Docker build process. You can also install them manually if needed:

• pyttsx3: Text-to-speech functionality.
• SpeechRecognition: Converts speech into text for voice command handling.
• openai: Python client for interacting with the OpenAI API.
• requests: Makes API calls.
• subprocess: Allows interaction with the operating system.
• pyautogui: Automates the GUI for tasks like opening applications.

These dependencies are listed in requirements.txt:

pyttsx3
SpeechRecognition
openai
requests
subprocess
pyautogui

As AI and machine learning technologies evolve, the Aether assistant will be expanded to incorporate new capabilities:

1. Enhanced Memory: The assistant could evolve from storing basic preferences to a full user profile, remembering interactions and anticipating user needs.
2. Voice Emotion Recognition: By detecting emotional tones in voice, the assistant can modify its responses for more empathetic and personalized interactions.
3. Multi-Language Support: Expand the assistant’s reach by supporting multiple languages.
4. IoT Integration: The assistant could connect to smart devices, enabling voice control of lights, thermostats, and security systems.
5. Personalized Task Automation: Using machine learning, the assistant could automatically learn and perform tasks based on user habits.
6. Cloud and Web Integration: Interface with cloud services like Google Drive and third-party APIs for weather, news, and more.
7. Computer Vision: By incorporating visual and gesture recognition, the assistant could interact with physical objects or respond to visual cues.
8. Voice Authentication: Increase security by adding voice authentication to control sensitive tasks.
9. AI-Powered Creativity: Generate creative content such as writing, music, or art based on user prompts.

We welcome contributions to Aether! To get started:

1. Fork the repository
2. Make your changes
3. Submit a pull request

All contributions are reviewed for quality, security, and functionality.

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