• 

  Verity Landing Page

• 

  Verity Session with speech detection and fact-verification

Verity

Inspiration

The Internet has become the backbone of modern society, and is used to share information and other things to everyone. Now more than ever, the Internet has become an invaluable resource for almost everything. With the increase in reliance on the Internet, there has also been an alarming increase in the spread of misinformation. We were inspired to build our project because we noticed how much misinformation has entered our daily lives in things like social media, news articles, and sometimes even informational websites. Our goal is help everyone figure out for themselves what the truth is.

What it does

Our tool helps users reveal the truth in their conversations. It records and transcribes speech in real time. Any sentence can be clicked and automatically fact-checked against multiple reputable sources, all of which are conveniently linked in a quick AI report for transparency.

How we built it

Our project is built off of Next.js infrastructure alongside a Flask RESTful API server. Our backend utilizes a queue system to handle requests, which query Gemini API alongside a local retriever model using Langchain & Ollama libraries. We source our information through Wikipedia’s API, as it gives easily obtainable sourcing and straight-to-the-point information.

Challenges we ran into

We overcame many challenges during the development process, the most difficult being optimizing the retrieval model and the entire pipeline for latency.

Accomplishments that we're proud of

We are proud of the cohesive application that we've built, linking together a powerful backend, responsive and easy to use UI, all while leveraging Gemini and Ollama. It is a fully working project and the first step towards an important goal.

What we learned

We learned a great deal about the science behind RAG (Retrieval Augmented Generation), pipelining, and model optimization when working with webpage datasets. Additionally, our use of Gemini API taught us how to optimize our prompts for the best straightforward responses. Some of us were not familiar with React & Next, and learned about important React fundamentals (such as useState, references, and routing).

What's next for Verity

The path to bringing Verity to everyone will include extensive testing and fine tuning, user testing, and lots of sleepless nights trying to fix bugs. Our goal is to continue development of Verity to improve its performance, add new features, and most importantly scale it to a production version that we everyone can use.

Built With

• flask
• gemini
• langchain
• next.js
• ollama
• python
• react
• typescript
• webspeechapi
• wikipedia