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Welcome to the official wiki for the AGI-Server project. This page serves as the central hub and starting point for developers, researchers, and contributors interested in the Autonomous Artificial Superintelligence Operating System (ASI-OS).
To contribute effectively, it is essential to first understand the project's core vision. This section defines the fundamental concept of ASI-OS, outlining its purpose and the mission that guides its development. This vision is the foundation upon which the entire architecture is built.
ASI-OS is the Autonomous Artificial Superintelligence Operating System, a self-evolving cognitive ecosystem designed to operate autonomously on local infrastructure. Its primary purpose is to provide a robust, secure, and extensible platform for a locally hosted Artificial General Intelligence (AGI), ensuring that its advanced capabilities remain under the user's control.
The project's guiding principle and motto is simple yet profound: "Made for a better world." This mission directly informs our architectural choices, prioritizing local, offline operation to guarantee user privacy and data sovereignty, and embedding governance mechanisms directly into the system's core. The following sections will detail the underlying architecture designed to make this vision a reality.
Our architecture is a direct reflection of our core design principles. Understanding this structure is crucial for anyone looking to use the system, contribute to its development, or extend its capabilities. Our design emphasizes a clear separation of concerns, modularity, and operational stability.
ASI-OS separates active operation from long-term evolution through a dual architecture composed of two primary components:
- The live runtime kernel (Sovereign-Loop), which handles real-time tasks and active processes.
- The offline cognitive ecosystem for skill synthesis and self-improvement, where the system can learn, evolve, and develop new capabilities.
This bifurcation is a core design principle that allows for aggressive, offline experimentation and skill development without risking the stability of the live, operational kernel.
To enforce maintainability and a clear separation of concerns, the project mandates a professional src layout. The core directory structure is organized as follows:
ASI-OS/
├── manage.py # Unified CLI Entry Point (Server, Learn, Test)
├── src/ # Core Source Code
│ ├── boot.py # Runtime Kernel Entry
│ ├── agents/ # Autonomous Agents (Professor, Alpha, etc.)
│ ├── core/ # System Kernel (Switchboard, Safety, Memory)
│ ├── gpia/ # General Purpose Intelligent Agent Logic
│ ├── hnet/ # Hierarchical Neural Memory
│ └── skills/ # Skill Registry (Proprietary implementations ignored)
├── scripts/ # Operational & Maintenance Scripts
├── tests/ # Test Suite (pytest)
├── docs/ # System Documentation
└── configs/ # Configuration Files
This structure ensures modularity and separation of concerns, isolating different functional parts of the system—from the core kernel logic to individual agent definitions. This organization makes it easy for new developers to navigate the codebase and get started with the system.
This section provides a practical, step-by-step guide to get a local instance of ASI-OS up and running. To simplify interaction with the system, all primary operations are centralized through a single command-line interface.
Follow these steps to install the ASI-OS project on your local machine.
- Ensure you have the required prerequisite installed: Python 3.11+.
- Clone the official repository from GitHub:
- Navigate into the newly created project directory:
- Install the necessary dependencies using one of the following commands:
- OR
The manage.py script serves as the Unified Management CLI for all system operations. Below are the primary commands for interacting with ASI-OS.
- Start the Server: Launches the live runtime kernel (Sovereign-Loop).
- Initiate a Learning Session: Initiates an autonomous learning cycle between the Professor and Alpha agents.
-
Run the Test Suite: Executes the
pytestsuite to verify system integrity. - Clean System Artifacts: Removes temporary files and generated artifacts from previous sessions.
For a deeper understanding of the system's capabilities, please refer to the detailed documentation.
Beyond its immediate functions, the long-term viability and trustworthiness of ASI-OS are built on the foundational pillars of safety and extensibility. This section details the project's unwavering commitment to these core principles, ensuring the system is both responsible and adaptable.
The system is engineered with transparency and safety as foundational pillars. We have implemented several mechanisms to ensure responsible operation and alignment with emerging governance standards.
-
Safety Governor: Hardware and cognitive guardrails are strictly enforced by the
src/core/safety_governor.pymodule, preventing unintended or harmful actions. -
Full Traceability: All autonomous actions are meticulously logged in the
data/ledger/directory, creating immutable audit trails for complete transparency and analysis. -
Human-in-the-Loop Control: The
manage.pyCLI is designed to ensure that a human operator maintains oversight and must authorize all critical system operations. - Privacy by Design: The system is built for local, offline operation. This core design choice keeps sensitive user data and proprietary skills secure on local infrastructure.
These robust safety features provide the stable foundation necessary to confidently open the system to community-driven extensibility.
The modular architecture of ASI-OS is explicitly designed to be extended by our community of developers and researchers. Adding new functionality is a straightforward process.
-
Adding Skills: New capabilities can be added to the system by placing them in the
src/skills/directory. The system loader will automatically discover and register them. -
Defining Agents: New autonomous agent behaviors and logic can be defined within the
src/agents/directory. -
Creating Scripts: Custom operational tasks and maintenance utilities can be placed in the
scripts/folder for easy execution. Be sure to use the standardized import block to accesssrc/components.
This layered approach to extensibility allows contributors to add value at every level of the system, from low-level skills to high-level operational automation. We built this extensible framework specifically to empower our community to accelerate the system's evolution.
This final section provides a quick-reference summary of the project's current status and key metrics. It also serves as a directory to more in-depth documentation for users who wish to dive deeper into the system's mechanics.
The following table summarizes the key vitals for the AGI-Server project.
Metric | Status -- | -- Current Release | v0.2.0 - Professional Architecture Milestone License | Apache-2.0 License Primary Language | Python (72.8%) Contributors | 3 Stars | 2For a more comprehensive understanding, the following documents are available in the docs/ directory:
- Architecture Overview: A deep dive into the system's core philosophy and design principles.
- Gardener Guide: A guide to understanding the autonomous filesystem organizer.
- Agents Manifest: A detailed breakdown of the capabilities of the multi-agent swarm.
- System Status: Information on the current operational status and key performance metrics.