All projects
·
About Matt
A submission to the North Star Challenge (Access & Equity track). Built with AI-assisted development — designed and directed by me, implemented with AI pair programming.
Description
What it does: North Star
is a set of downloadable, privacy-preserving AI components that run entirely
on a user's own device — no API keys, no account, no internet required.
Everything is orchestrated with LangGraph state machines and powered by a
local LLM through Ollama, so a student with a laptop and no data plan still
gets a full study and fitness toolkit.
Why it matters: The whole
project is built around access and equity. It's designed for a group of
students in one room with no internet — often sharing one device — so it
ships features like Study Packs (bundle decks and quizzes into a
portable file, shared by USB or messaging, no server) and a Group
Quiz mode for studying together offline.
How it was built: A Python
monorepo with a shared polaris_core (LLM, embeddings, config,
memory) and four installable packages. LangGraph routes each request to the
right specialist; Chroma stores notes locally for cited retrieval; the
fitness pipeline is defined by editable markdown agent files. A serverless
hosted version also exists (React SPA + FastAPI on Cloud Run with a Groq
fallback) for people who can't run a model locally.
The four components
North Star (Polaris) — Four Offline Components
═════════════════════════════════════════════════
┌──────────────┬────────────────┬────────────────┬────────────────┐
│ Study LLM │ Study RAG │ Fitness Agents │ College Planner│
│ (6 areas) │ (vector notes) │ (MD-defined) │ (app tracker) │
│ │ │ │ │
│ Flashcards │ ingest → embed │ parse .fit / │ deadlines / │
│ Quizzing │ → store → │ .tcx / .gpx │ status / notes │
│ CV Builder │ retrieve → │ → metrics → │ 4-year credit │
│ Advisor │ grade → │ growth plan → │ map │
│ Citations │ cited answer │ review │ export → .ics │
│ Essay Helper │ (Chroma, disk) │ (agent mds/) │ │
└──────────────┴────────────────┴────────────────┴────────────────┘
shared core: polaris_core (LLM · embeddings · config · memory)
LangGraph + Ollama (all local)
Dev Notes
Problem Solved
Most study AI assumes reliable internet, an account, and money for API
calls. North Star removes all three — it downloads once and runs on the
device, so cost and connectivity stop being barriers to good study tools.
Technical Highlights
Four LangGraph-orchestrated components share one local core. The Study
LLM routes across the six Polaris areas; Study RAG gives cited answers
from a local Chroma DB; fitness agents are pure markdown you can edit
without touching code; and Study Packs make everything shareable offline.
What's Next
Native Android and iOS wrappers (scaffolds are in the repo), a smoother
one-command installer, and expanding the College Planner's 4-year
credit-mapping.
View the submission on GitHub
Back to top