📌Overview

Purpose: LYRAIOS aims to serve as a comprehensive operating system for AI applications, enhancing their functionality to facilitate interaction with financial networks and blockchain technology.

Overview: LYRAIOS, also known as the LLM-based Your Reliable AI Operating System, is an advanced AI assistant platform that features a modular design capable of integrating various AI applications. It extends capabilities for financial operations and market analysis, making it suitable for a variety of sectors, including education and fintech.

Key Features:

• AI Process Management: Facilitates dynamic task allocation, multi-assistant coordination, resource optimization, and state management, ensuring efficient operation across various AI tasks.

• AI Memory System: Utilizes both short-term and long-term memory storage, preserving conversation context and integrating knowledge bases for improved interaction.

• AI I/O System: Supports multi-modal input processing (text, files, APIs) and structured output formatting, enhancing user experience and interaction functionality.

• Built-in Tools: Offers integrated utilities such as advanced calculators, web search functionalities, financial analysis tools, file management, and research aids, streamlining user tasks.

• FastAPI and Docker Support: Enables a robust backend powered by FastAPI and easy deployment through Docker, enhancing scalability and maintainability.

• Open Protocol Architecture: Provides a pluggable structure for easy integration of third-party tools and services, significantly increasing extensibility compared to traditional systems.

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LYRAIOS

Overview

LYRAIOS is a Model Context Protocol (MCP) operating system for multi-AI agents designed to enhance AI applications by enabling interaction with financial networks and blockchain public chains. It offers advanced AI assistants for various functions, including blockchain operations, fintech market analysis, and educational training systems.

Future Features

Future operations will support advanced VIP features using LYRAI cryptocurrency on the Solana blockchain.

Core Innovations

LYRAIOS introduces breakthroughs in three key areas:

1. Open Protocol Architecture: Modular integration protocol supporting plug-and-play third-party tools/services with extensive extensibility.
2. Multi-Agent Collaboration Engine: Enables dynamic multi-agent collaboration for complex workflows and conflict resolution.
3. Cross-Platform Runtime Environment: Facilitates migration from personal AI assistants to enterprise solutions across various sectors.

System Architecture

LYRAIOS uses a layered architecture consisting of:

• User Interface Layer: Multiple interaction modes (Web UI, Mobile UI, CLI, API Clients).
• Core OS Layer: Implements process management, memory system, I/O system, and security control.
• MCP Integration Layer: Achieves integration with external services.
• External Services Layer: Includes services integrated through the MCP protocol.

Tool Integration Protocol

The Tool Integration Protocol standardizes the integration of third-party tools and services into the LYRAIOS ecosystem.

Key Features

• Standardized Tool Manifest: JSON schema defining capabilities and requirements.
• Pluggable Adapter System: Supports various tool types.
• Secure Execution Environment: Ensures safe tool execution with resource limits.
• Versioning and Dependency Management: Monitors tool versions and dependencies.

Getting Started with Tool Integration

1. Define Tool Manifest.
2. Implement Tool Functionality.
3. Register Tool with LYRAIOS.
4. Use the Tool.

MCP Protocol Overview

The Model Context Protocol (MCP) connects LLM applications and integrations, supporting functions like resources management, prompt handling, and tools integration.

Data Flow

User requests are processed through various system layers, ultimately executing tools when needed.

LYRAIOS Core Features

• AI Process Management: Task scheduling, resource optimization, and state management.
• AI Memory System: Short-term memory and structured knowledge management.
• AI I/O System: Multi-modal input and structured output handling.

Security Considerations

• Transmission Security: Use TLS and verify connections.
• Message Validation: Check and clean incoming messages.
• Resource Protection: Implement access control and monitor usage.

Roadmap

Current Status

• Basic AI Assistant Framework
• Streamlit Web Interface
• FastAPI Backend
• Database Integration

Future Plans

• Advanced error handling
• Workflow designer
• Role-based access control

Setup Workspace

# Clone the repo
git clone https://github.com/GalaxyLLMCI/lyraios
cd lyraios

# Create + activate a virtual env
python3 -m venv aienv
source aienv/bin/activate

# Install dependencies
pip install 'phidata[aws]'

# Setup workspace
phi ws setup

# Run Lyraios locally
phi ws up

Run Lyraios Locally

1. Install Docker Desktop.
2. Export your OpenAI API Key and any other necessary API keys for research integrations.

API Documentation

REST API Endpoints

• Assistant API: Process chat messages with context-aware responses.
• Health Check: Monitor system health status.

API Documentation Access

Interactive API documentation can be accessed at /docs.

Contributing

Contributions are welcome! Please refer to the 1 for more information.

License

This project is licensed under the Apache License 2.0. See the LICENSE file for details.