Infomaid

A Textual AI and RAG-Enabled Learning Application

A simple textual AI RAG application using Ollama for generative AI, chatting with PDFs AND chatting (querying) documents prepared in xml!

GitHub link: https://github.com/developmentAC/infomaid

Overview

Infomaid is a simple AI prompt-based solution with built in Retrieval augmented generation (RAG) support!

Gradealert

GitHub link: https://github.com/developmentAC/gradeAlert

Table of contents

• Overview
• Tool
• Usage At Terminal
• CSV
• Outputted files
• Placing Gradebook Files
• Pushing in Bulk
• File Structure
• Summary of Commands
• A Work In Progress

Overview

GitHub Classroom is an excellent resource to handle work repositories for a course of many students. Each student, after “accepting” an assignment is issued a unique repository in which work can be completed and pushed to the instructor.

Sentiminer

GitHub link: https://github.com/developmentAC/sentiminer

Table of contents

• Overview
• Mechanism
• Commands
• Output
• References
• Evolution

Overview

Sentiment analysis is the semantic study of emotion in language. This form of analysis is used to determine the level of satisfaction or dissatisfaction in textual data such as reviews, survey responses, online and social media posting and similar. Due to the often high volume of feedback from the above types of textual data, sentiment analysis provides an automated solution for determining the “feeling” of the text.

Infomaid: An AI and RAG-Enabled Learning Application

Date: 4 June 2024

Oliver Bonham-Carter

Email: obonhamcarter at allegheny.edu

Contents

• Overview
• Prerequisites
• Set Up Local Models for Ollama
• Setting Up The Project
• Execution
• Parameters
• Generation
• Output
• Working with PDF Data
• Sample Project
• Testing the Code
• Ethical Note
• A Work In Progress

Overview

Infomaid is a simple AI prompt-based solution with built in Retrieval augmented generation (RAG) support!

Welcome to this simple AI application! Infomaid is an experimental AI prompt-driven solution (i.e., each “chat” involves writing a separate prompt to use with a new execution of Infomaid) to help complete text-based work with information.