Project Info

debAIDe

Devpost

Inspiration

We referenced how people enjoy playing on Chess.com, and the competitive element to it was applicable to many fields. In addition, it is often common to see people pointlessly arguing on social media, without proper moderation, and often unwarranted. It is clear that people need an avenue to argue, but it would also be good to be able to concurrently improve their argumentation and logical reasoning skills. Thus, we believe that a debating app, similar to Chess.com app, would be able to bring people of opposing views together, to come to possible resolutions. We aimed to create a mobile app so it would be accessible and usable for the average person.

What it does

Our debating app, debAIDe, pairs individuals of similar debating skill, and assigns each individual with a stand to defend. Individuals will then take turns proposing arguments and countering their opponentโ€™s arguments, and an AI judge will determine a winner. The winner will have an increase in rating, and the loser will be given advice on how to improve their arguments.

How we built it

For our frontend, we used React Native (Expo) using Expo AV to record audio, Zustand for global state management, React Query to fetch and cache data, and TypeScript for type-safe development. For our backend, we used FastAPI, PostgreSQL, SQLAlchemy, Google Gemini AI (for scoring), Whisper for speech-to-text transcription, and Uvicorn for our server.

Challenges we ran into

The toughest challenge was actually coming up with a good idea. Our society is constantly filled with problems that we would love to solve, so we wanted to create something that would benefit society while also making sure to use AI meaningfully.

Accomplishments we're proud of

Creating a mobile app was a challenge for us, as we were not very experienced in app development, and had to learn a lot in our creation process. We are proud that we created a fully-functional mobile app that looks and works well.

What we learned

We learned how to send information to be processed by Gemini, and to curate our prompts to ensure proper output formats. We also learned how to create an app that stored data from different users, and that could coordinate between different users concurrently.

What's next

We are considering more interesting formats, such as 2v2, clan battles or even โ€œbattle royaleโ€. We are also considering moving into educational mode, where the user can directly pick apart arguments with fallacies.

Analysis

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Metric

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
  • FastAPIIn code
  • PythonIn code
  • ReactIn code
  • TypeScriptIn code
  • PostgreSQLClaimed

4 of 5 appear in the indexed code. 1 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

203 KB

Source files

30

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

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