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Summarice

A reading workspace for academic PDFs: highlight, annotate, summarize with citations, and search across your library.

How to run

pnpm install
pnpm dev                      # http://localhost:5173

Other scripts: pnpm check (svelte-check), pnpm lint, pnpm format, pnpm test:e2e.

Top-level layout

src/                  SvelteKit app (routes + lib)
  routes/             Pages, grouped into (auth) and (app)
  lib/                Shared code (client + server)
    components/       Common UI: shadcn primitives + shared components
    features/         Feature components and logic (highlights, document-upload, summary, viewer)
    pdf-highlighter/  Vendored PDF highlighter fork
    server/           Server-only modules (AI, Supabase, document-upload, summary, figures, limits)
static/               Static assets served as-is
data/                 Sample PDFs for development
supabase/             DB migrations, seed, Supabase CLI config
eval/                 Python evaluation harness (deferred)
e2e/                  Playwright tests

Most folders have a short README explaining what lives there. Start with src/lib/server/README.md for backend work, or src/routes/README.md for pages.

Stack

SvelteKit 2 + Svelte 5 · TypeScript · Tailwind 4 · shadcn-svelte · Supabase (Postgres, Storage, Auth, pgvector, FTS) · Gemini 3 Flash · OpenAI text-embedding-3-small · pdf.js · Playwright.

Features

  • Highlighting: Text and area highlights persist to Supabase and render in the right sidebar. Semantic highlighting uses fixed slots 1..5 (Key idea, Definition, Evidence, Question, Contradiction).
  • Summaries: Automated, versioned document summaries with interactive citations linked back to source highlights.
  • Figure Interpretation: Multimodal AI interpretation of area highlights to describe diagrams and charts.
  • Annotations: Markdown notes on highlights with support for AI-authored content and CRUD operations.

Team

  • Carlyne Consebido
  • Benjeouelle Lazaro
  • Raymund Klien Mañago
  • Phoebe Renee Moraca

About

A CS 180 (Machine Learning) project

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