What is Ai Automated Aspen

AI-automated-Aspen is a project designed to integrate Aspen series software with Large Language Models (LLMs) and Model Context Protocol (MCP) tools, enhancing data processing and analysis capabilities.

Use cases

Use cases include automating the collection of Aspen Backup files for analysis, enhancing documentation processes, and integrating Aspen software with advanced AI tools for improved decision-making.

How to use

To use AI-automated-Aspen, set up a Python environment by installing required packages, configure the MCP tools in the ‘mcp_config.json’ file, and collect training data by running specific Python scripts to gather Aspen Backup files from GitHub.

Key features

Key features include integration with LLMs, automated data collection from GitHub, configuration flexibility through JSON files, and the ability to process diverse Aspen Backup files.

Where to use

AI-automated-Aspen can be utilized in fields such as data science, software development, and research where Aspen software is relevant, particularly in industries focusing on simulation and modeling.

AI-automated-Aspen

This project aims to integrate Aspen series software with LLMs and MCP tools

Requirements

• Local docker-based MCP tools (refer to https://github.com/modelcontextprotocol/servers/tree/main).

See docs in Github and Filesystem servers to set up docker-based MCPs

• GitHub API key: see https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens

• Python 3.11+ (this is for later integration with Langgraph Studio)

Quick start

1. Python environment setup: pip install -r requirements.txt

2. Configuration: configs/mcp_config.json contains the configuration for the MCP tools.

3. Add your GitHub API key to the env section.

2. Add the path to the data directory in the filesystem section. Please note that the path should be the absolute path to the local data directory. e.g., “C:\Users\…\data”. This folder will be the folder that the agents read from and write to.

Usage: Training data collection

The very first step of this project is to collect as many .BKP (Aspen Backup files) as possible and as diversed as possible.

The current strategy is to use MCP tools, including GitHub and Serp tool, to locate .BKPfiles on the internet and provide according documentations on the .BKP files.

It takes the following steps:

1. run python -m src.data_collection_github_agent.graph to create lists of .BKP files from GitHub. The agent will automatically create a list of .BKP files and save it to the data directory.

2. run python -m scripts.create_download_list to create a list of download links for the .BKP files.

3. use third party tool to download the .BKP files from the download links. Recommend using aria2 to download the files if you are on linux systems and Xunlei on windows systems.