chatmof 0.1.10

chatmof

ChatMOF : An Autonomous AI System for Predicting and Generating Metal-Organic Frameworks

ChatMOF is an autonomous Artificial Intelligence (AI) system that is built to predict and generate of metal-organic frameworks (MOFs). By leveraging a large-scale language model (GPT-4 and GPT-3.5-turbo), ChatMOF extracts key details from textual inputs and delivers appropriate responses, thus eliminating the necessity for rigid structured queries. The system is comprised of three core components (i.e. an agent, a toolkit, and an evaluator) and it forms a robust pipeline that manages a variety of tasks, including data retrieval, property prediction, and structure generation. The study further explores the merits and constraints of using large language models (LLMs) AI system in material sciences using and showcases its transformative potential for future advancements.

NOTE: We've resolved the unavailability issue, if you run into any further issues please leave a github issue.

Install

Dependencies

NOTE: This package is primarily tested on Linux. We strongly recommend using Linux for the installation.

python>=3.9

Installation

$ pip install chatmof

If you have a dependency issues between torch and moftransformer, uninstall torch and pytorch-lightning, install torch <2.0.0, and reinstall.

For prediction and generation task, you have to setup modules.

$ chatmof setup

Add the following line to .bashrc for the openai api key.

# openai api key
export OPENAI_API_KEY="enter_your_api_key"

If you want to search the internet, you'll need to enter the GOOGLE_API_KEY and GOOGLE_CSE_ID into .bashrc.

# google api and cse_id
export GOOGLE_API_KEY="enter_your_api_key"
export GOOGLE_CSE_ID="enter_your_id"

For MOF generation, you need to install GRIDAY.

$ chatmof install-griday

How to use ChatMOF

You can use it by running chatmof's run function.

$ chatmof run

You can adjust argument of Chatmof such as model and temperature.

$ chatmof run --model-name gpt-3.5-turbo --temperature 0.5

You can use help to see more options.

$ chatmof run --help

Example of ChatMOF

1) Search task

2) prediction task

3) prediction task

Architecture

ChatMOF comprises three core components: an agent, toolkits, and an evaluator. Upon receiving a query from human, the agent formulates a plan and selects a suitable toolkit. Subsequently, the toolkit generates outputs following the proposed plan, and the evaluator makes these results into a final response.

Citation

if you want to cite ChatMOF, please refer to the following paper:

ChatMOF: An Autonomous AI System for Predicting and Generating Metal-Organic Frameworks, arxiv:2308.01423 [link]

Contributing 🙌

Contributions are welcome! If you have any suggestions or find any issues, please open an issue or a pull request.

License 📄

This project is licensed under the MIT License. See the LICENSE file for more information.