Project Info

PawPals

Inspiration

As college students, we both agreed that fun trips definitely make college memorable. However, we are sometimes hesitant about initiating plans because of the low probability of plans making it out of the group chat. Our biggest problem was being able to find unique but local activities to do with a big group, and that inspired the creation of PawPals.

What it does

Based on a list of criteria, we prompt OpenAI's API to generate the perfect itinerary for your trip, breaking down hour by hour a schedule of suggestions to have an amazing trip. This relieves some of the underlying stresses of planning trips such as research and decision-making.

How we built it

On the front-end, we utilized Figma to develop an UI design that we then translated into React.js to develop a web app. We connect a Python back-end through the utilization of Fast API to integrate the usage of SQLite and OpenAI API into our web application.

Challenges we ran into

Some challenges we ran into were the lack of experience in Full-Stack development. We did not have the strongest technical skill sets needed; thus, we took this time to explore and learn new technologies in order to accomplish the project. Furthermore, we recognized the long time it takes for OpenAI API to generate text, leading us to in the future output the generated text as a stream utilizing the SDK for it by Vercel.

Accomplishments we're proud of

As a team of two, we were very proud of our final product and took pride in our work. We came up with a plan and vision that we truly dedicated ourselves to in order to accomplish it. Even though we have not had too much experience in creating a full-stack application and developing a Figma design, we decided to take the leap in exploring these domains, going out of our comfort zone which allowed us to truly learn a lot from this experience.

What we learned

We learned the value of coming up with a plan and solving problems that arise creatively. There is always a solution to a goal, and we found that we simply need to find it. Furthermore, we both were able to develop ourselves technically as we explored new domains and technologies, pushing our knowledge to greater breadth and depth. We were also able to meet many people along the way that would provide pieces of advice and guidance on paths and technologies to look into. These people accelerated the learning process and truly added a lot to the hackathon experience. Overall, this hackathon was an amazing learning experience for us!

What's next

We hope to deploy the site on Vercel and develop a mobile application of the app. We believe with the streaming technology, we can create faster response time. Furthermore, through some more scaling in interconnectivity with friends, budgeting, and schedule adjusting, we will be able to create an application that will definitely shift the travel planning industry!

Analysis

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Metric

Daniel Kim
23

Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only

CSSIn code
HTMLIn code
JavaScriptIn code
PythonIn code
ReactIn code
FastAPIClaimed
OpenAIClaimed

5 of 7 appear in the indexed code. 2 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

77 KB

Source files

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.