SanctuAIry

SanctuAIry is a privacy-first, AI-powered therapeutic assistant. It leverages large language models (LLMs) to simulate therapeutic conversations while prioritizing user confidentiality, privacy, and data security.

Overview

SanctuAIry is designed to run securely in the cloud within confidential virtual machines (VMs), ensuring that sensitive user data—such as therapy sessions and mental health assessments—remains protected and private.

The app aims to provide an empathetic, intelligent, and responsive AI therapist experience by using open-source LLMs, currently powered by Meta’s LLama 3.2 models.

🚧 Work in progress. The app is under constant iteration with new features and improvements being added weekly.

Architecture

SanctuAIry is built with a modular architecture, composed of the following key components:

Frontend

A clean and responsive user interface built with React, enabling users to interact with their AI therapist in a seamless way.

LLM Manager

A backend service layer that:

• Routes user input to the appropriate LLM instance
• Manages session context and conversation flow
• Handles model selection, loading, and creation

LLM Core

The brain of the application, where the actual LLM runs:

• Currently utilizes Meta’s LLama 3.2
• Runs in a secured environment to ensure data isolation and confidentiality
• Designed for performance, context awareness, and therapeutic alignment

Privacy & Security

SanctuAIry is committed to privacy by design:

• All processing is planned to occur in confidential virtual machines with hardware-backed security guarantees
• End-to-end encryption for data in transit, in use, and at rest
• Further planed privancy features:
  • GDPR compliance
  • User-defined data retention and deletion policies

Tech Stack

• Frontend: React and TailwindCSS
• LLM Manager: Node.js and Express
• LLM Core: Ollama, using Meta's LLama 3.2

How to Run SanctuAIry

SanctuAIry can be run either locally for development or deployed securely in the cloud. Choose the method that best fits your needs:

Local Deployment with Docker Compose

To start all services locally using Docker Compose, follow these steps:

1. Prerequisites: Ensure Docker and Docker Compose are installed on your machine.

2. Environment: Copy the example environment file and update the URLs if necessary:

   cp .env.example .env
   # .env:
   # VITE_LLM_MANAGER_URL=http://llm-manager:3000
   # LLM_CORE_URL=http://llm-core:11434
   # NODE_ENV=development
   # PORT=3000
   # OLLAMA_MAX_LOADED_MODELS=2

3. Build & Start: From the project root, run:

   docker-compose up

Cloud Deployment with Terraform

To deploy SanctuAIry securely in the cloud using Google Cloud confidential VMs and Terraform, follow the instructions in the infrastructure/README.md file.

Acknowledgements

• Meta AI for the open-source LLama models
• The open-source community for tools and inspiration ❤️