This project provides the MicroLab Suite, an open-source, DIY hardware and software stack for automated controlled lab reactors (CLRs). It aims to democratize chemical synthesis by offering a low-cost, hackable platform for designing and producing compounds, akin to how 3D printers impacted manufacturing. The target audience includes chemists, researchers, and hobbyists interested in building and operating their own automated lab equipment.

How It Works

The MicroLab Suite translates compound synthesis information into executable recipes for the MicroLab hardware. The software stack includes a backend API and a web-based GUI. The system is designed for flexibility, allowing users to either build the physical MicroLab hardware or emulate it for development and testing purposes. This dual approach facilitates both practical use and software iteration.

Quick Start & Requirements

• Docker: docker-compose up --build gui (for API & GUI) or docker-compose up --build api (for API only).
• Local Setup (Backend): Python 3.9-3.13, pip, virtualenv. Install dependencies with pip install -r requirements.txt. Run with python main.py.
• Local Setup (GUI): yarn. Install dependencies with yarn install, run with yarn start.
• Hardware Emulation: Requires setting "MicroLab Controller" to "simulation-pi" and "Lab Hardware Config" to "ftv_simulation_microlabv0.5.0" in settings.
• Raspberry Pi Setup: Requires screen, git, python3-flask, python3-pip, python3-serial, python3-libgpiod.
• Documentation: About the MicroLab and MicroLab Suite, How to build & use the MicroLab and MicroLab Suite

Highlighted Details

• Offers both hardware emulation and a physical build path.
• Dockerized development environment for simplified setup.
• Supports Python 3.9-3.13 for backend development.
• Web GUI accessible via yarn start.

Maintenance & Community

• No specific contributors, sponsorships, or roadmap details are highlighted in the README.

Licensing & Compatibility

• The README does not explicitly state a license.

Limitations & Caveats

The project requires some electronics knowledge for hardware assembly. While Docker simplifies setup, local installation may require specific Python versions and package management. The README does not detail specific hardware requirements beyond general Pi compatibility.