We are all Juniors and Seniors in Cornell, and know what kind of services our friends need. We wanted to tackle as many services as possible in one solution. We also wanted to learn something new. Each team member had something they wanted to try out for the first time, so that is how we came up with this idea.
What it does
Our chatbot answers pre-formatted questions by scraping information from the web and parsing it. Categories of questions that can be asked are weather, dining hall menus, class exam schedules, and Cornell building address. When users questions is out of format, our bot redirects the user to our help feature.
How we built it
We used slack api in order to build the basis of the bot. We used beautiful soup in order to scrape the data from a particular website and selenium in order to find the data that we need automatically. For features such as the weather, we used the python weather api to gain weather information of every city in the world.
Challenges we ran into
The challenges we faced was the limitations that Slack Api had in developing new features. As one of our goals was to add the google map api and incorporate a map into the response, slack api had limitations on adding the functionality.
Accomplishments that we're proud of
We are proud of incorporating python weather framework, Beautiful Soup which allowed us to do data scraping from a particular website
What we learned
We've learned the importance of working as a team. As we all worked on individual parts of the project, we recognized the importance of communication and helping each other out.
What's next for Cornell Ask Bot
For Cornell Ask we are planning to incorporate AI features. By using neural networks, we will teach the bot how to get data from online and slowly let it learn itself various commands. Thus, whenever a user writes down and a new command and doesn't recognize, the user will respond back to the bot with a potential response and will learn the new data gained from the user.