Your second brain for chat — ingest conversations, structure them with AI, and ask what matters with natural language (including recall in iMessage on macOS).
Built for: USC BIA Trae × MiniMax Hackathon 2026 — hackathon submission on Devpost.
| Live app | traerecall1ehv.vercel.app |
| Devpost | Recall — Devpost |
- David Gao
- Anthony Wen
- Web dashboard — Sign in with Google, paste or import chat-style text from WeChat, WhatsApp, iMessage (Photon), and other sources, and save structured memories.
- Mirror Memory — RAG over your saved items (semantic search + MiniMax answers in your context).
- Mirror Personality — Optional “Analyze me” profile from ingested memories.
- Categories & analytics — Auto-categorized memories (e.g. Food, Events, Sports, Ideas, Medical) and a “digital diet” view.
- iMessage agent (macOS) — Local Photon agent: say
recallin a thread for Mirror Memory; optionalrecall all/ scan-all ingest; optional location-based nudges via iMessage when the notify poller is running. - Settings — Notification frequency, iMessage delivery target, optional Notion connection.
- Frontend: React, Vite, TypeScript, Tailwind CSS
- Backend: Node.js, Express (serverless bundle on Vercel)
- Auth & data: Supabase (Auth, PostgreSQL, pgvector for embeddings)
- AI: MiniMax (extraction, embeddings, RAG / Mirror Memory, optional vision path)
- iMessage: Photon iMessage Kit (macOS agent)
- Deploy: Vercel (app + API)
- Other: Google OAuth, TRAE (development workflow per team)
For architecture, env vars, and local setup (API + web + optional iMessage agent):
npm install
cp .env.example .env
npm run devSee docs/GOAL.md and docs/PROGRESS.md for full detail.