# Project export: Study Speed

This document was generated by HackStack to give an AI agent context about a hackathon project. Sections are labeled with their provenance; content marked as truncated was cut to keep this document small.

## Project metadata

- Hackathon: TreeHacks 2024
- Tagline: You have a lot of things to learn. This helps you do it faster.
- Devpost: https://devpost.com/software/study-speed
- GitHub: not linked
- Team: contributor stats unavailable

## Devpost submission (written by the team)

### Inspiration

Canvas, Instructure, Quizlet, Kahoot - What do these have in common? They host information and try to get you a learning experience but ends up being nominal. We wanted a way to make studying fast and catching up with any class as easy as possible

### What it does

What we do is take your current data as is that has text: PDFs, PPTs and TXTs and let you talk directly to them for any information you need to catch up on.

### How we built it

We use MongoDB as our backend with Python alongside LangChain. We use React as our frontend.

### Challenges we ran into

Wifi bandwidth constraints here and there were the largest impedance!

### Accomplishments we're proud of

We immediately got PDF and text-based document parsing working.

### What we learned

Document mining is a fun task, especially learning to help yourself learn with a project like this!

### What's next

Scrape your Canvas, email, quizlet, and more for any files and turn it into a multimodal query and quiz creator. Make sure to overcome the issues of data input so it can be as frictionless as possible to use and automatically generate topics for each class in byte size information.

## README (from the GitHub repository)

No README available.

## Detected evidence (automated analysis)

No repository was indexed for this project. Claimed technologies below could not be checked against code.
- Flask (technology) — claimed on Devpost, not found in the code
- LangChain (technology) — claimed on Devpost, not found in the code
- MongoDB (technology) — claimed on Devpost, not found in the code
- OpenAI (technology) — claimed on Devpost, not found in the code
- Python (language) — claimed on Devpost, not found in the code

## Codebase structure

No repository index available.

## Key source files

No repository index available; no source files included.