SCAN

The SCAN (Synthetic Cognitive Augmentation Network) project aims to develop a collaborative multi-agent system that replicates the functions of the prefrontal cortex (PFC) using AI agents to enhance problem-solving, planning, decision-making, and other PFC-related activities.

Table of Contents

• Overview
• Features
• Tech Stack
• Solution
• Configuration
• Usage
  • Clone the Repository
  • Install the Required Packages
  • Set up Environment Variables
  • Run the Main Script
• Contributors
• License
• Acknowledgements
• uv Instructions

Overview

The SCAN project offers a multi-agent system designed to simulate the functions of the prefrontal cortex (PFC), enabling detailed analysis and decision-making simulations. By employing collaborative agents that emulate different components of the PFC, SCAN aims to enhance the capabilities of LLMs through customization. This system aids in understanding cognitive processes, developing advanced AI applications that mimic human cognitive functions, and assisting end users in making better decisions, solving problems, planning, and other PFC-related activities.

Features

• Simulates complex cognitive functions of the PFC
• Utilizes multiple specialized AI agents for different cognitive tasks
• Integrates generative AI for decision making and analysis
• Tracks task progress and updates details dynamically
• Provides detailed reports on cognitive task simulations

Tech Stack

• CrewAI: Framework for orchestrating role-playing, autonomous AI agents
• LangChain: Framework for building language model applications
• LLM Integrations:
  • OpenAI GPT API (used in primary code but can be replaced with various LLMs)

Solution

The SCAN project offers a multi-agent system designed to simulate the functions of the prefrontal cortex (PFC), enabling detailed analysis and decision-making simulations. By employing collaborative agents that emulate different components of the PFC, SCAN aims to enhance the capabilities of LLMs through customization. This system aids in understanding cognitive processes, developing advanced AI applications that mimic human cognitive functions, and assisting end users in making better decisions, solving problems, planning, and other PFC-related activities.

Configuration

To configure the project, create a .env file in the root directory with the following variables:

# OpenAI API Key
OPENAI_API_KEY=your_openai_api_key_here

Usage

Clone the Repository

git clone https://github.com/iLevyTate/SCAN.git
cd SCAN

Install the Required Packages

uv sync --frozen

Set up Environment Variables

Set up your environment variables in the .env file as shown above.

(Optional) Export the API Key in the Terminal

If the API key from the .env file is not being picked up, you can export it directly in the terminal:

export OPENAI_API_KEY=your_openai_api_key_here

Run the Main Script

uv run run-scan

Contributors

Feel free to contribute by submitting issues or pull requests. For major changes, please open an issue first to discuss what you would like to change.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

• CrewAI: For providing the framework to create autonomous AI agents.
• LangChain: For the framework to build language model applications.
• OpenAI: For the language processing capabilities.
• Contributors: Thanks to all contributors who have helped in building and improving the SCAN project.

uv Instructions

For the uv package manager:

• Installation: Install uv via the official instructions at https://docs.astral.sh/uv/getting-started/installation/.
• Add Dependencies: Use uv add <package-name> to add dependencies.
• Run Scripts: Use uv run <command> to run scripts defined in pyproject.toml.