Building a Discord bot that provides access to mental health resources for university students is an opportunity to make a real impact in the lives of many young adults. By providing a simple and anonymous way for students to access the resources they need, the bot can help them navigate the often-confusing world of mental health care and find the support they need. It's a chance to empower students to take control of their own well-being and to make a difference in the fight against mental health stigma.
What it does
This Discord bot is designed to provide university students with access to existing mental health resources. The bot's main function is to answer simple questions asked via the digital bot, with the goal of providing students with the information and resources they need to take care of their mental health. The bot also provides anonymous access to resources, allowing students to access them without having to share their personal information. Additionally, the bot's communication back to the students is phased, starting with a list of suggestions to do, then some helpful tips, and based on the student's engagement, it recommends local support groups/therapists/ etc. It ultimately aims to be a valuable tool for university students in need of mental health support, providing the resources they need in a simple, anonymous, and flexible way.
How we built it
We used Python for this project.
Challenges we ran into
First time any of us used NLPs, therefore we underestimated how long it would take to incorporate the chat bot, in addition since NLPs are not deterministic we had a hard time classifying or binning the users input
Accomplishments that we're proud of
Successfully able to create a discord bot, that can interact with the user's prompts using the co:here API and Google API.
What we learned
Taking the time to flesh out an Idea and form concrete tasks is critical. As this was the first Hackathon for most of us, we didn't fully flesh out our initial idea which resulted in a lot of wasted time going in circles.
What's next for Aura
Learn how to be implement more sophisticated NLP algorithms
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