LegalLingua

Landing Page
Summary and Translation text after uploading pdf
Interface to upload pdf, choose language to translate to, and model to use

Inspiration

We all came together to solve a problem that people struggle with on a regular basis. We are we were immigrants who hail from different places in the world where English is not a prevalent language! We thought to ourselves, what is someone that is difficult and is often. detriment to various communities? We discovered that we could leverage our knowledge to help communities that either are drawn into confusion or are taken advantage of through legal documentation that is often difficult to understand, even for those who are fluent in English.

What it does

We leveraged large language models, ORC, and base 64 to scan documents, summarize them, and translate them to a person's language. We do this summarization and translation by implementing Together.ai's api and fine tuning models using our datasets.

How we built it

We built it by splitting the team into various roles - Juan: Front-end, Aleks: Front-end / Back-end, Randolf: APIs, ML/AI, and Xiang (UI/UX / Front-end). Our technology/ Design stack: Tailwind.css, Python, Javascript, Together.ai API, Google Vision API, Typescript, Javascript, Next.js, Libraries for transforming PDFs.

Challenges we ran into

We all ran into tough challenges as we struggled to connect components together which include: - Working with Pdf documents: searching for the best libraries to help convert documents to images - Connecting to google vision api after obtaining said images - Working with timeouts with displaying words using visual effects in the front-end - Loading effects, creating try-catch statements using logical processing - Designing the website using sigma to have a simple but elegant UI/UX - Congregating data to use in together.ai's LLMs (LLaMA - for summarization, llama 2 - for key points / insights) using python scripting - Working with Together.ai's prompting to ensure the best answer quality for the queries needed to operate our platforms

Accomplishments that we're proud of

- Undertaking such an ambitious project 
- Working tirelessly through problems without sleeping much
- Communicating our ideas about the project, while also helping each troubleshoot problems

What we learned

- We learned that creating projects that are meaningful to us as individuals is much more rewarding than simply creating a project for the sake of a project
- How different technologies interact with each other and how they all play a role in the development process.
- Working with a team, delegating tasks so that each person has something to work on.

What's next for LegalLingua

- Improving the large language models so that the summarization and translation process is easier to do/ much faster
- Increase capacity sizes for pdf / document input so that we can accept a larger variety of legal documentation.