This repository contains the implementation of a plugin for the Cheshire Cat AI framework - Implemented by Diego Quattrone and Francesco Vichi for neurotech hakcathon jointly organized by Imperial College Neurotech Society, Entrepreneur First and NeuroTechX. This framework leverages cutting-edge AI technologies to support complex computational tasks within neuroscience and other research domains.
This plugin is designed to assist researchers in neuroscientific studies by utilizing a powerful Large Language Model (LLM). Its features include:
- Data analysis: Facilitating the interpretation of complex neuroscientific datasets.
- Research Assistance: Providing contextual information and generating scientific insights.
- Deterministic code execution: Enabling to execute automatically the computation algorithm, written by humans, by matching them with the specific request of the user.
To use this plugin, follow these steps:
- Clone the repository:
git clone https://github.com/your-repo-link cd your-repo-folder - Build and run the Docker container:
docker-compose up --build
Once the Docker container is running, connect to the Cheshire Cat AI framework and use the plugin to assist in research tasks. Detailed documentation for specific commands and examples will be added soon. Remember that the framework is LLM agnostic (and so is sAInapse): so you can choose whatever model and embedder you want to use.
Watch the video below to see the tool in action:
Thanks to the Cheshire Cat AI team for their support and framework, which made this plugin possible.