@Antigravity AI Antigravity AI authored 2 days ago
.agent feat(ui): move logout button from sidebar to profile page 2 days ago
.vscode fix: remove forced sessionId reset in websocket service 15 days ago
agent-node feat: add daemon/service installation for Mac and Linux 2 days ago
ai-hub feat: add swarm control chat history clear & agent node auto-update system 2 days ago
deployment feat: add swarm control chat history clear & agent node auto-update system 2 days ago
docs refactor: re-org frontend folder structure to simply be 'frontend' 2 days ago
frontend refactor: re-org frontend folder structure to simply be 'frontend' 2 days ago
scripts refactor: re-org frontend folder structure to simply be 'frontend' 2 days ago
skills feat: add swarm control chat history clear & agent node auto-update system 2 days ago
.gitignore security: scrub hardcoded GITBUCKET_TOKEN and update .gitignore #6 12 days ago
LICENSE feat: agent node mesh integration and UI polish 7 days ago
README.md refactor: re-org frontend folder structure to simply be 'frontend' 2 days ago
docker-compose.yml refactor: re-org frontend folder structure to simply be 'frontend' 2 days ago
nginx.conf fix: resolve TTS stream network errors and optimize Nginx for streaming 13 days ago
README.md

๐Ÿง  Cortex Hub: Autonomous AI Agent Mesh & Orchestrator

Cortex Hub is a state-of-the-art, modular AI orchestration platform that bridges the gap between Large Language Models (LLMs) and local execution via a distributed Agent Node Mesh. It features a modern React-based workspace, a powerful Skill System, and advanced RAG (Retrieval-Augmented Generation) capabilities.

โœจ Key Features

  • ๐ŸŒ Distributed Agent Mesh: Connect multiple local or remote nodes (Linux, macOS, Windows) to your Hub. Each node can execute tasks, manage files, and provide terminal access.
  • ๐Ÿ› ๏ธ Extensible Skill System: Orchestrate AI capabilities via "Skills" (Browser Automation, Terminal Control, File Management). Dynamic permissioning allows granular control over which users or groups can access specific nodes and skills.
  • ๐Ÿ“‚ Private RAG Pipeline: Securely ingest documents into a FAISS vector store to ground AI responses in factual, local data.
  • ๐Ÿ” Industrial-Grade Security: Integrated with OIDC (OpenID Connect) for secure user authentication and Role-Based Access Control (RBAC).
  • ๐Ÿ–ฅ๏ธ Unified Command Center: A sleek, premium React frontend for managing sessions, configuring nodes, and monitoring the swarm in real-time.

๐Ÿ’ฌ How to Use

1. Connecting Nodes

Download the Agent Node Bundle from the "Nodes" page in the dashboard. Unzip and run ./run.sh (Linux/macOS) or run.bat (Windows). The node will automatically connect to your Hub using the pre-configured security token.

2. Using Skills

Skills like Browser Automation and Terminal Control are available directly in your chat sessions. You can attach specific nodes to a session to give the AI hands-on access to those environments.


๐Ÿš€ Quick Start (Local Development)

The easiest way to get started is using the pre-configured Dev Container or local Docker Compose.

Prerequisites

  • Docker & Docker Compose
  • Python 3.11+ (if running without Docker)
  • Node.js 18+ (for frontend development)

1. Configure Secrets

Copy the example environment file and add your API keys (Gemini, OpenAI, etc.):

cp .env.example .env

2. Launch the Stack

Initialize the Hub (Backend, Frontend, and Database) in one command:

docker compose up -d --build

๐Ÿ—๏ธ Deployment Architecture

Cortex Hub uses a layered deployment strategy to keep the core codebase clean while supporting specific production environments.

๐Ÿ“‚ Folder Structure

  • ai-hub/: The Core Python (FastAPI) backend.
  • frontend/: The React-based unified dashboard.
  • agent-node/: The lightweight client software for distributed nodes.
  • skills/: Source for AI capabilities (Shell, Browser, etc.).
  • deployment/: Environment-specific overrides (e.g., jerxie-prod with NFS support).
  • scripts/: Centralized automation for sync, rebuilding, and maintenance.

๐Ÿšข Production Deployment

For Jerxie AI production instances, we use the centralized remote deployer:

# Sync local changes and rebuild on the production server
REMOTE_PASS='<PASSWORD>' bash scripts/remote_deploy.sh

๐Ÿ›๏ธ Project Layout

.
โ”œโ”€โ”€ ai-hub/             # Backend API & Orchestrator
โ”œโ”€โ”€ ui/                 # Frontend Workspace (React)
โ”œโ”€โ”€ agent-node/         # Distributed Node Client
โ”œโ”€โ”€ skills/             # AI Skill Definitions
โ”œโ”€โ”€ deployment/         # Env Overrides (NFS, SSL, OIDC)
โ”œโ”€โ”€ scripts/            # CI/CD & Maintenance Scripts
โ”œโ”€โ”€ cortex.db           # Local SQLite Cache
โ””โ”€โ”€ docker-compose.yml  # Generic Development Entrypoint

๐Ÿงช Testing

  • Backend: pytest ai-hub/tests/
  • Frontend Health: scripts/frontend_tester
  • Connectivity: scripts/test_ws.js

โš–๏ธ License

Distributed under the MIT License. See LICENSE for more information.