Autonomous AI agents are reshaping software development. However, running multi-agent swarms that autonomously generate, review, and execute code directly on host systems introduces massive security, stability, and orchestration challenges.
To tackle this, I built NeuroHive — an open-source, full-stack Multi-Agent Swarm Orchestrator and Sandboxed Code Execution Studio.
🧠 The Swarm Architecture
NeuroHive breaks down engineering tasks and distributes them across four specialized autonomous agents:
- 🏛️ Atlas (System Architect): Decomposes complex objectives, designs algorithmic blueprints, and establishes execution flow.
- ⚡ Cygnus (Lead Engineer): Generates optimized, production-grade Python code implementing the architecture.
- 🛡️ Vanguard (Security Auditor): Runs static security checks, scans for unsafe system calls, and mitigates malicious payload risks.
- 🚀 Sentinel (Execution Engine): Runs the verified solution within a sandboxed, isolated subprocess runtime with strict timeout and memory boundaries.
⚡ Key Highlights
- 🖥️ Cyberpunk Web Studio GUI: Real-time web dashboard visualizing agent communications, thought progression, and code generation live.
- 🔒 Isolated Execution Sandbox: Enforces timeout controls, memory guards, and execution isolation to protect host environments.
- 🌐 Polyglot & Zero-Bloat: Native integration of Python, WebSockets, JavaScript/HTML5 UI, and Linux subprocess primitives.
- 📦 100% Free & Open-Source: Fully accessible under the MIT license.
🚀 Quick Start (Under 60 Seconds)
You can launch NeuroHive locally with a single command:
bash
git clone https://github.com/EngJoDev/neurohive.git
cd neurohive
chmod +x run.sh
./run.sh start --port 9090
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