https://github.com/jshulgach/neurobridge

NeuroBridge: Where AI perception meets real-time robotics control
https://github.com/jshulgach/neurobridge

ai arduino artificial-intelligence computer-vision gpt4 grounding-dino llama llama3 llm python raspberry-pi robot robotics sam

Last synced: 3 months ago
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NeuroBridge: Where AI perception meets real-time robotics control

• Host: GitHub
• URL: https://github.com/jshulgach/neurobridge
• Owner: Jshulgach
• License: apache-2.0
• Created: 2025-03-04T02:10:52.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2025-03-04T05:59:40.000Z (3 months ago)
• Last Synced: 2025-03-04T06:32:47.485Z (3 months ago)
• Topics: ai, arduino, artificial-intelligence, computer-vision, gpt4, grounding-dino, llama, llama3, llm, python, raspberry-pi, robot, robotics, sam
• Homepage:
• Size: 4.88 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        


🤘🤖🤘 Build modular ai-powered robots in your garage right now.




  

  

    

  





  Intro •

  Getting Started •

  Installation



## About 

NeuroBridge is an AI-powered modular server designed for robotic control, vision processing, and LLM-based interactions. It integrates LLM-powered decision-making, real-time perception, and modular execution of AI-driven skills like object detection, voice interaction, and task automation.

🚀 Features:

- LLM Integration 🧠: Handles natural language interactions and command execution.

- AI-Powered Vision 👁️: Camera and object detection with Grounding DINO.

- Task Automation 🤖: Executes robotic actions via a structured AI skills system.

- Modular Architecture ⚡: Components for messaging, skills, and perception are neatly separated.

- Real-time Control 🎛️: Async message handling and AI-driven automation.

🔧 Built with: Python, OpenCV, Groq LLM API, asyncio, threading, and modular AI components.

## Getting Started

The `config.yaml` file contains hyperparameters to load with the AI server. Adjust these according to your preferences.

## Installation

1. Create a virtual environment using [Anaconda](https://www.anaconda.com/products/distribution) or Python's virtualenv

   - Using Anaconda:

      ~~~

      conda create -n ephys

      conda activate ephys

      ~~~

   - Using Python's virtualenv:

     ~~~

     python3 -m venv .ephys

     source .ephys/bin/activate # Linux

     call .ephys/Scripts/activate # Windows

     ~~~

2. Clone the repository and navigate to the project directory

   ~~~

   git clone https://github.com/JShulgach/NeuroBridge.git

   cd NeuroBridge

   ~~~

3. Install dependencies

    ~~~

    pip install -r requirements.txt

    ~~~