PathwayIQ MVP Monorepo

Accuracy-first MVP for AI-assisted California college pathway planning.

Monorepo Layout

• api/ FastAPI backend (credit resolution, planning, validation, metadata, PDF export)
• frontend/ React + Tailwind web app (intake wizard, credit summary, timeline)
• data-pipeline/ seed generation scripts and SQL schema
• shared-schemas/ shared JSON contract snapshots
• infra/ deployment notes

Quick Start

Backend

cd api
python -m venv .venv
.\.venv\Scripts\Activate.ps1
pip install -r requirements.txt
uvicorn app.main:app --reload

Backend runs at http://localhost:8000.

Optional Gemini configuration for AI schedule optimization and explanation generation:

$env:GEMINI_API_KEY="<your_key>"
$env:GEMINI_MODEL="gemini-1.5-flash"
$env:GEMINI_ENABLE_SCHEDULING="true"

Frontend

cd frontend
npm install
npm run dev

Frontend runs at http://localhost:5173.

API Endpoints

• POST /v1/credits/resolve
• POST /v1/plans/generate
• POST /v1/plans/rebuild
• POST /v1/plans/validate
• POST /v1/igetc/tracker
• GET /v1/metadata/schools
• GET /v1/metadata/majors?school_id=...
• GET /v1/metadata/courses?school_id=...
• GET /v1/metadata/course-offerings?school_id=...&season=...
• GET /v1/policy/version
• POST /v1/export/pdf

Scope Included

• UC system + Las Positas College + San Joaquin Delta College
• 5 majors across UCs: CS, Data Science, Biology, Economics, Psychology
• Deterministic planner with prerequisite validation
• Policy-versioned output
• URL-shareable plan state + PDF export

Notes

This implementation intentionally keeps policy data as seeded demo data and isolates ingestion logic in data-pipeline/ for expansion.