## Inspiration

The idea for SlideForge came from the struggles researchers face when trying to convert complex academic papers into presentations. Many academics spend countless hours preparing slides for conferences, lectures, or public outreach, often sacrificing valuable time they could be using for research. We wanted to create a tool that could automate this process while ensuring that presentations remain professional, audience-friendly, and adaptable to different contexts.

## What it does

SlideForge takes LaTeX-formatted academic papers and automatically converts them into well-structured presentation slides. It extracts key content such as equations, figures, and citations, then organizes them into a customizable slide format. Users can easily adjust the presentation based on the intended audience—whether it’s for peers, students, or the general public. The platform provides customizable templates, integrates citations, and minimizes the time spent on manual slide creation.

## How we built it

We built SlideForge using a combination of Python for the backend and JavaScript with React for the frontend. The backend handles the LaTeX parsing, converting key elements into slides using Flask to manage the process. We also integrated JSON files to store and organize the structure of presentations, formulas, and images. On the frontend, React is used to create an interactive user interface where users can upload their LaTeX files, adjust presentation settings, and preview the output.

## Challenges we ran into

One of the biggest challenges we faced was ensuring that the LaTeX parser could accurately extract and format complex equations and figures into slide-friendly content. Maintaining academic rigor while making the content accessible to different audiences also required a lot of trial and error with the customizable templates. Finally, integrating the backend and frontend in a way that made the process seamless and efficient posed technical hurdles that required collaboration and creative problem-solving.

## Accomplishments that we're proud of

We’re proud of the fact that SlideForge significantly reduces the time required for researchers to create professional presentations. What used to take hours can now be done in minutes. We’re also proud of the adaptability of our templates, which allow users to target different audiences without needing to redesign their slides from scratch. Additionally, the successful integration of LaTeX parsing and slide generation is a technical achievement we’re particularly proud of.

## What we learned

Throughout this project, we learned a lot about LaTeX and how to parse and handle its complex structures programmatically. We also gained a deeper understanding of user experience design, ensuring that our platform was both intuitive and powerful. From a technical standpoint, integrating the backend and frontend and ensuring smooth communication between the two taught us valuable lessons in full-stack development.

## What's next for SlideForge

Next, we plan to expand SlideForge’s functionality by adding more customization options for users, such as advanced styling and animation features. We’re also looking into integrating cloud storage solutions so users can save and edit their presentations across devices. Additionally, we hope to support more document formats beyond LaTeX, making SlideForge a universal tool for academics and professionals alike.
## Inspiration

Commuting can be unpleasant, especially early in the morning when you are tired and want to sleep. With a GPS based alarm you can safely sleep on the bus/train knowing you will not miss your stop.

## What it does

GPS based alarm

## How we built it

Smashing through bugs until something came out

## Challenges we ran into

Android development

## Accomplishments that we're proud of

Getting it to work, learning new skills

## What we learned

Android development

## What's next for Snoozy

Amazing things
## Inspiration

As CS Students, math enthusiasts and amateur researches, we know the struggle and the beauty of watching code become artistic, organized writing. Yet, it is so difficult to become comfortable without extensive experience. We hope to enable anyone to quickly form perfect documents, quickly and intuitively.

## What it does

The crux of our application is a Fine-Tuned LLM Copilot, OCR for handwritten math, and custom commands integrated with a blazingly fast native LaTeX IDE and Renderer in browser.

We have built in commands for common things like logical-and, logical-or, and even Demorgans Law so that your paper or proof shouldn’t be hindered by a curly bracket. The main part of our product is an AI model using Together.ai with CodeLlama-2 trained on a large data set of 450 common prompts in Discrete Math and research papers. A prompt like “create a bullet point for my education section on my resume at the Stanford” would spit a perfectly formatted block of latex in our proprietary IDE. Or “perform DeMorgans law on Set A and Set B”. This is chips and guac for us. Have messy handwritten math? No problem at all!

## How we built it

The backend was built using a TexLive renderer in a Docker container that is run to consistently render the Tex Document continuously so you can see your changes “live”. The frontend was built with Typescript + React with Vite, and the backend with FastAPI, Firebase Auth for authentication, and Postgres for database storage so that users can save to the cloud in the future. This was used in tandem with Monaco Editor from Microsoft for all the logic we embedded to deal with the autocomplete and code snippet replacement commands. For the ML Model we trained it using Together.ai for a fine-tuned CodeLlama-2. For OCR, we leveraged MathPix APIs.

## Challenges we ran into

We found no shortage of challenges. Our biggest issue was giving the ML model permission to write into the IDE as the package configurations coupled with the extensive setup for the Tex Renderer to take this input. We decided to approach it using custom commands (such as /ai) to give the user command over when they want to get help. It was quite the challenge. Of course, building the container and integrating it with the backend was no small feat either. We put these different puzzle pieces together and realized there was more color to the bigger picture than we anticipated.

## Accomplishments that we're proud of

We are most proud of creating an integrated IDE. None of us have experience making developer tools so we were very proud with how we learned the tech to power our application. The key thing is in Monaco Editor Latex was not a supported language compatible with the IDE. As such we had to bruteforce produce mappings of the key words like \textbf{} and link smart highlighting with the intellisense that runs Monaco Editor to get a fully functioning IDE tailored to our use cases. As an extension we are especially proud of our Latex CoPilot. Utilizing Together to integrate a smart AI code generator that intakes English semantic was an enriching experience to accomplish, especially building the model from the ground up and linking it to the IDE.

## What we learned

We see ourselves enhancing the ML model to implement more tailored Tex code and even make suggestions based on what the user wants. Furthermore, we see ourselves implementing our own syntactical language that overlaps Tex that makes it more user friendly maintaining a consistent lexical structure throughout, as to interpreting English input and immediately translating it into Tex. Finally, Nonetheless, we enjoyed this project and were able to see the fruit of our work taking our old Discrete Math work and research papers being written in this app of ours.

## What's next for \LeTEXT

We see ourselves enhancing the ML model to implement more tailored Tex code and even make suggestions based on what the user wants. Furthermore, we see ourselves implementing our own syntactical language that overlaps Tex that makes it more user friendly maintaining a consistent lexical structure throughout, as to interpreting English input and immediately translating it into Tex. We also intend to add cloud storage for users. Nonetheless, we enjoyed this project and were able to see the fruit of our work taking our old Discrete Math work and research papers being written in this app of ours.