ARKOS - Introduction

Automated Resource Knowledgebase Operating System - An open-source interface for local LLM agent building with long-term memory

Welcome to ARKOS

ARK (Automated Resource Knowledgebase) Operating System improves resource management through intelligent automation. Using tailored processess and adaptive memory, ARKOS streamlines the collection, organization, and access to resource data, facilitating efficient decision-making and personalized AI interactions.

Quick Summary

ARKOS is an open-source interface for local LLM agent building utilizing long-term memory for personalized requests. We’re primarily focusing on targeting MIT students for initial deployment.

What is ARKOS?

ARKOS is a comprehensive framework for building intelligent agents with the following features:

Core Features:

• Multi-Provider LLM Support: Unified interface for OpenAI-compatible endpoints, SGLANG, and local models via AsyncOpenAI client
• Dual-tier Memory System: PostgreSQL for short-term context + Mem0/Supabase for long-term vector memory
• State Machine Architecture: YAML-configurable state graphs for conversation flow management
• MCP Tool Integration: Model Context Protocol support for connecting external tools and services
• OpenAI-Compatible API: FastAPI server with /v1/chat/completions endpoint (streaming supported)
• CLI Interface: Interactive command-line interface for testing and development

Key Features

Multi-Model Support

Seamless integration with SGLANG, local models, and OpenAI-compatible endpoints

Dual-tier Memory

PostgreSQL for conversation context + Mem0/Supabase for semantic long-term memory

State Machine

YAML-configurable state graphs with automatic transition handling

MCP Tools

Model Context Protocol integration with per-user authentication support

Streaming API

Real-time streaming responses via OpenAI-compatible endpoint

Agent Orchestration

Intelligent agent with tool calling, memory retrieval, and state management

Architecture Overview

ARKOS employs a modular architecture with clear separation of concerns:

Technology Stack

• Core Language: Python 3.8+
• Web Framework: FastAPI + Uvicorn
• LLM Interface: AsyncOpenAI client (OpenAI-compatible)
• Data Validation: Pydantic 2.x
• Database: PostgreSQL (psycopg2-binary) + Supabase
• Memory: Mem0 for vector storage and retrieval
• Embeddings: Sentence Transformers via HuggingFace
• Configuration: YAML + python-dotenv
• HTTP Client: aiohttp for async requests
• Authentication: google-auth-oauthlib for OAuth flows

Project Status

ARKOS is under active development. The core architecture is stable, but APIs may change as we refine the system based on user feedback and research insights.

Use Cases

ARKOS is designed for:

1. Personal AI Assistants: Build agents that remember conversations and learn from interactions
2. Research Tools: Create intelligent research assistants with persistent knowledge bases
3. Educational Applications: Develop tutoring systems that adapt to student learning patterns
4. Task Automation: Build agents that can manage complex, multi-step workflows
5. Knowledge Management: Create systems that organize and retrieve information intelligently

Getting Started

Ready to build your first ARKOS agent?

Quick Start Guide

Get up and running with ARKOS in minutes

Contributing

ARKOS is open-source and welcomes contributions! Whether you’re interested in adding new features, improving documentation, or reporting bugs, we’d love to have you involved.

GitHub Repository

View source code and contribute

Development Guide

Set up your development environment

Becoming a Core Maintainer

We are actively looking for committed contributors who want to help shape the long term direction of the project.

Core maintainers are expected to:

• Make regular, high quality contributions
• Participate in design and architecture discussions
• Review pull requests and help guide technical decisions
• Uphold the project’s standards around reliability, security, and documentation
• Attend weekly maintainer meetings to coordinate work and align on priorities

If you are interested in becoming a core maintainer, email [e-mail] with a brief introduction and a summary of your contributions or areas of interest.

Team

Name	Role	Affiliation
Nathaniel Morgan	Project Leader	MIT
Kshitij Duraphe	Dev Ops	Industry
Ilya Gulko	Backend	MIT
Jack Luo	Backend	Georgia Tech
Angela Liu	Backend	MIT
Ishaana Misra	Backend	MIT
Hudson Hilal	Backend	MIT
Joshua Guo	Frontend	MIT
Calvin Baker	Backend	MIT

License

ARKOS is released under the AGPL-3.0 License.