## Inspiration

Several months ago, a friend of mine (with significantly more coding experience than me!) introduced a Markov's Chain-powered chatbot to our Discord server. The bot has since stopped functioning for reasons beyond my understanding, but I've always been curious about what it would take to build one of my own -- and what better time and place to try it out than at a hackathon?

## What it does

After adding Kenku Bot to a Discord server, members can <(optin to allow the bot to start recording their messages (or <(optout anytime to put message collection on pause). Once it's collected enough message data, the <(mimic command will prompt it to generate a sentence of its own based on the messages it has learned from opted-in members. Kenku also responds to its own name in the same way as the <(mimic command.

## How I built it

Lots of tutorial-watching and article-reading! I learned to host Discord bots from freeCodeCamp.org's YouTube channel, and modified the Markov's Chain script to pull from my own ever-changing database rather than a .txt file from an open-source script on Tech.io.

## Challenges I ran into

The previously-mentioned database was the hardest part: just as with the Discord API, I was learning to use repl.it's built-in database for the first time, armed with little more than the absolute basics of Python knowledge. However, unlike the Discord API, I struggled a great deal to find documentation or even advice on how to use it, and without an understanding of the coding "vocabulary" I needed to communicate my intentions, I often found myself stuck on how to search for how-to's regarding even the simplest tasks.

## Accomplishments that I'm proud of

The opt-in/opt-out system is a special point of pride of mine - being entirely dependent on the very same repl.it database that gave me so much grief, it took a lot of trial and error to work out, so I'm pleased to say it finally functions exactly as it was intended to!

## What I learned

* How to create a bot with Discord's API
* How to use repl.it's built-in database
* How to keep a browser-based script running indefinitely
* Basics of dictionary objects
* Basics of pickling

## What's next for Kenku Bot

* Command to generate a message from one user's specific message data, rather than the entire server's
* Additional commands to generate messages from fixed sources (ie. podcast transcripts, musical theatre librettos, etc.)
## Inspiration

The inspiration for "Newstral" came from a deep-seated belief in the importance of reliable and unbiased news sources in today's information age. We were inspired by the need to counter misinformation and fake news with a platform that delivers accurate, trustworthy news to the public.

## What it does

"Newstral" is a revolutionary news platform that harnesses cutting-edge technology to curate and deliver high-quality, impartial news content to its users. It sifts through various sources to provide a comprehensive and well-rounded perspective on current events, ensuring that users can make informed decisions and stay updated on the latest news.

## How we built it

We built "Newstral" through a collaborative effort of passionate individuals with backgrounds in technology, journalism, and data analysis. We leveraged state-of-the-art natural language processing algorithms and machine learning techniques to curate, categorize, and present news content in a user-friendly manner. Our team's dedication to accuracy and impartiality is at the core of "Newstral."

## Challenges we ran into

Creating "Newstral" came with its set of challenges. We encountered difficulties in designing algorithms that could separate unbiased news from opinion pieces. More specifically, we had trouble with properly implementing the machine learning algorithm. Additionally, ensuring a seamless user experience while handling vast amounts of real-time data presented technical challenges. We had trouble creating the best UX/UI interface possible for all audiences to comprehend However, our team's persistence and commitment helped us overcome these obstacles.

## Accomplishments that we're proud of

We're proud of creating a platform that addresses the critical issue of information reliability in the digital age. "Newstral" is an accomplishment that promotes transparency and accountability in the news industry while offering users a trustworthy source of information. Our dedication to delivering accurate, unbiased news remains a significant achievement.

## What we learned

Through the process of building "Newstral," we've learned the importance of collaboration between experts in technology and journalism. We've also gained insights into the challenges of combating fake news and misinformation. Our journey has emphasized the significance of impartiality, integrity, and transparency in journalism. Moreover, dividing up work cultivates great teamwork and deadlines passed!

## What's next for Newstral

The future of "Newstral" is exciting. We plan to expand our platform's capabilities by incorporating more languages and sources, making it a global resource for reliable news. We will continue refining our algorithms to enhance the user experience. Additionally, we aim to establish partnerships with credible news organizations to further improve the breadth and depth of our coverage. "Newstral" will be at the forefront of ensuring accurate, unbiased news is accessible to all.
## Inspiration

We were inspired very locally, by the resident hot dog stand owner, Nasir Al-Huttam. He's been taking orders for the UTSc community for almost a decade, and has been in need of an easier way of taking orders, as taking orders through text has been somewhat cumbersome for him.

## What it does

Using a chatbot powered by Microsoft Azure and Recast.ai, we've created a chatbot that takes orders from the customer from the Facebook Messenger App, and gives the user an interactive, intuitive experience akin to buying from another human, allowing them to even pay for their meal in advance, further streamlining the process.

## How we built it

For frontend, we used HTML and CSS, in combination with JQuery and Javascript to receive json files from the serverside, and interpret that information into display material for the business owner to look.

Recast.ai as well as the Microsoft Bot Framework was used to create the chatbot and program natural language and reactive conversation with the user. Node.js was also used.

The backend is powered by Python and Flask, using Microsoft Azure to deploy the database, postgreSQL, SQLAlchemy were also used.

## Challenges we ran into

Frontend-backend interactions, getting the JQuery to work properly.

## Accomplishments that we're proud of

Creating a functional chatbot that can handle a variety of situations, creating a clean, sleek user interface on the frontend.

## What we learned

Frontend-to-backend interactions, JQuery functionality, the basics of creating a chatbot.

## What's next for DogGo

Finishing the app in time to deploy to Nasir, then seeing if it can be looked into as a business venture.