HackStack

Project Info

Rallie

Devpost

This project did not submit a demo video on Devpost.

Inspiration

I am a student activist, and I have faced bureaucratic systems often. My team and I are building the tools we wish we had when we were learning about new systems, using advanced AI technologies

What it does

We have a dataset we collected through interviewing UC Santa Cruz (UCSC) students at the hackathon using an agentic interviewer. You, as a student of UCSC, can learn from the trials of your predecessors.

How we built it

We built it using Cloudflare for our infra, Gemini for our inference, MongoDB for our database, FastAPI for our backend, and a React front end. Other tools used: MongoDB, BAML, LangChain, Pydantic, Vite, Typescript, Python.

Challenges we ran into

A challenge I spent a ton of time on was configuring a cloudflare tunnel. I had to step into unfamiliar territory, and failing meant letting my team mates down. Something I found difficult was learning how to communicate over http from the back end to the front end. It required a lot of coordination and exposed some oversights on both ends that we would have otherwise overlooked.

Accomplishments we're proud of

Getting the front end and back end connected Having time to gather data from real interviews Getting the cloudflare site working

What we learned

Database frameworks Different perspectives on bureaucracy Rallie's future: Pre Release Interview UCSC students to gather pre-release dataset Perfect RAG pipeline Add Wiki feature Chat history feature Chat history feature Beta Testing UX Testing, nail interaction design for agents Focus on gathering early adopters and building community Release A final version of Rallie is one where we have a stable knowledge-base of UCSC, that will last for decades. We aim to expand to other schools and communities, because the problems we face here at UCSC are not unique.

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
  • CSSIn code
  • FastAPIIn code
  • HTMLIn code
  • JavaScriptIn code
  • LangChainIn code
  • PythonIn code
  • ReactIn code
  • Tailwind CSSIn code
  • Google GeminiClaimed
  • MongoDBClaimed
  • TypeScriptClaimed

8 of 11 appear in the indexed code. 3 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

133 KB

Source files

40

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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