## Inspiration

This app is inspired by the Prompt feature from Instagram Story. A lot of people participated and share pictures, including videos around one topic but at the end of the day, those stories disappear. We want to be a platform for short-video that people can enjoy interacting and sharing their moments or thoughts around topics and if they think the content will go viral, they can collect the video as an NFT.

## What it does

The app randomly selects a prompt (generated by us and the users) then the user will upload a short video that relates to the prompt. In the future, people can search for a keyword or prompt and see all videos relating to it.

## How we built it

* The videos are uploaded and stored on the Livepeer network and the web app is built using React.

## Challenges we ran into

* We had some difficulty linking firebase with Livepeer and React.
* We faced challenges when we tried to deploy local react code to /public web host

## Accomplishments that we're proud of

* Distributing work efficiently

## What we learned

* decentralized video infrastructure network.
* How to use Livepeer with React applications
* How to use firebase/firestore nosql dataase

## What's next for Chit Chat

* Using OpenAI to randomly generate prompts
* Allows users to choose categories and add prompts to the system
* Optimize it for mobile
* add an option to mint video as NFT on the web app
## Inspiration

While we are gradually normalizing discussion surrounding burnout and productivity, it still feels like many of us find trouble in balancing ourselves and ambition. The drive to achieve has been deeply baked into our culture and education, and it is not unusual to resort to measuring ourselves with external accomplishments, oftentimes at the cost of our own well-being. Our project aims to challenge these norms and ultimately the social stigmas surrounding setting smaller, incremental or “trivial” goals, reinventing discourse and framing the issues in a new context that tries to put us and our ambition in harmony.

## What it does

It’s simple. Have a task you need to do? Form a pact with someone, be it a friend, someone who’s in the same boat, or someone else. Write out what you’re going to do, go do it, and then memorialize it as an NFT commemorating both of your achievements. You’re rewarded for taking it slow, as to build your confidence and self-accountability. The NFT represents the fact that no task is too small, and builds towards who you are as a whole across your lifetime. We found that in practice, it’s nice to do things together.

## How we built it

Pact is built on Next.js, MongoDB, Express server, Websocket, Crossmint API, Magic UI and Gsap.

## Challenges we ran into

One issue that we had to face was ideation and trying to come up with something feasible and relatable. We spent almost the entire first day bouncing around topics and debating whether or not we should continue with our idea. One learning curve that we had to face was trying to fully utilize a database and a websocket at the same time. We faced issues with running the express server, managing connections, and trying to fully understand where the websocket would come into play within our entire application.
## Inspiration

There are millions of people around the world who have a physical or learning disability which makes creating visual presentations extremely difficult. They may be visually impaired, suffer from ADHD or have disabilities like Parkinsons. For these people, being unable to create presentations isn’t just a hassle. It’s a barrier to learning, a reason for feeling left out, or a career disadvantage in the workplace. That’s why we created **Pitch.ai.**

## What it does

Pitch.ai is a web app which creates visual presentations for you as you present. Once you open the web app, just start talking! Pitch.ai will listen to what you say and in real-time and generate a slide deck based on the content of your speech, just as if you had a slideshow prepared in advance.

## How we built it

We used a **React** client combined with a **Flask** server to make our API calls. To continuously listen for audio to convert to text, we used a react library called “react-speech-recognition”. Then, we designed an algorithm to detect pauses in the speech in order to separate sentences, which would be sent to the Flask server.

The Flask server would then use multithreading in order to make several API calls simultaneously. Firstly, the **Monkeylearn** API is used to find the most relevant keyword in the sentence. Then, the keyword is sent to **SerpAPI** in order to find an image to add to the presentation. At the same time, an API call is sent to OpenAPI’s GPT-3 in order to generate a caption to put on the slide. The caption, keyword and image of a single slide deck are all combined into an object to be sent back to the client.

## Challenges we ran into

* Learning how to make dynamic websites
* Optimizing audio processing time
* Increasing efficiency of server

## Accomplishments that we're proud of

* Made an aesthetic user interface
* Distributing work efficiently
* Good organization and integration of many APIs

## What we learned

* Multithreading
* How to use continuous audio input
* How to use React hooks, Animations, Figma

## What's next for Pitch.ai

* Faster and more accurate picture, keyword and caption generation
* "Presentation mode”
* Integrate a database to save your generated presentation
* Customizable templates for slide structure, color, etc.
* Build our own web scraping API to find images