AetherAI

Adaptive intelligence for every device.

AetherAI is an open‑source universal AI runtime designed to work on any device, with any model, under any conditions. Whether you're offline on a low‑power machine or online with access to powerful cloud models, AetherAI automatically selects the best available backend to deliver a seamless AI experience.

AetherAI is not a model — it’s the intelligence layer that sits above models. It detects your hardware, storage, and connectivity, then routes requests to the most capable engine available. When resources improve, it upgrades itself. When conditions worsen, it gracefully falls back. One interface, many possibilities.

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✨ Features

🔄 Adaptive Model Selection

AetherAI automatically chooses the best model based on:

• CPU/GPU availability
• RAM and storage
• Internet connectivity
• User preferences

🌐 Local + Cloud Hybrid

Use local models offline, cloud models online, or mix both.
AetherAI switches seamlessly without breaking the user experience.

📦 Self‑Managing Model System

• Downloads models automatically
• Upgrades to better models when storage allows
• Keeps a lightweight fallback model for offline use
• Supports multiple quantization formats

🧠 Unified API

Developers interact with one simple interface.
AetherAI handles the routing, loading, and execution behind the scenes.

🖥️ Cross‑Platform

Designed to run on:

• Windows
• macOS
• Linux
• Low‑power devices (where supported models allow)

🛠️ Extensible Architecture

Add:

• New model backends
• New cloud providers
• New hardware detection modules
• New routing strategies

AetherAI is built to grow with the community.

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🚀 Getting Started

⚠️ AetherAI is in early development.
Installation instructions will be added as the project evolves.

Clone the repository

git clone https://github.com/yourusername/AetherAI.git
cd AetherAI

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Project Structure

AetherAI/
│
├── aetherai/               # Core source code
│   ├── runtime/            # Routing engine, hardware detection
│   ├── models/             # Local model loaders, cloud adapters
│   ├── storage/            # Model manager, downloads, upgrades
│   ├── net/                # Connectivity detection
│   ├── api/                # Unified interface for apps
│   └── utils/              # Shared helpers
│
├── examples/               # Example scripts and integrations
├── docs/                   # Documentation site
├── tests/                  # Automated tests
│
├── README.md
├── CONTRIBUTING.md
├── LICENSE
└── ROADMAP.md

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🧩 How It Works

AetherAI is built around four core components:

1. Hardware Detector

Identifies CPU/GPU, RAM, and storage to determine what models can run.

2. Connectivity Monitor

Detects online/offline status and network quality.

3. Model Manager

Downloads, installs, updates, and removes local models. Keeps a fallback model for offline use.

4. Routing Engine

Chooses the best model (local or cloud) for each request. Developers don’t need to think about backends — AetherAI handles it.

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🤝 Contributing

AetherAI is open to contributions of all kinds:

• Code

• Documentation

• Model adapters

• Cloud provider integrations

• Bug reports

• Feature suggestions

See CONTRIBUTING.md for guidelines.

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🗺️ Roadmap (High‑Level)

• Basic hardware detection

• Local model loading

• Cloud model adapters

• Routing engine MVP

• Automatic model upgrades

• Unified API

• Plugin system

• Cross‑platform packaging

• v1.0 release

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📜 License

AetherAI is released under the MIT License.

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🌟 Vision

AetherAI aims to become the standard open‑source AI runtime — a flexible, intelligent layer that lets developers build once and run anywhere, without worrying about models, hardware, or connectivity.

If you believe AI should be accessible, adaptable, and open, you’re in the right place.

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⭐ Support the Project

If you like the vision, consider starring the repository. It helps the project grow and reach more contributors.