→ How to run — Use your input/chat.db and input/contacts.vcf, then run the import and app.

receipts/
├── frontend/          # Next.js TypeScript frontend
│   ├── src/
│   │   └── app/      # Next.js App Router
│   ├── package.json
│   └── tsconfig.json
├── backend/           # Express.js TypeScript backend
│   ├── src/
│   │   └── index.ts  # Backend entry point
│   ├── package.json
│   └── tsconfig.json
├── python/            # Python ML processing module
│   ├── imessage_processor.py  # Main processing script
│   ├── data/          # CSV data and outputs
│   ├── embeddings/    # FAISS indices and embeddings
│   └── requirements.txt
└── package.json       # Root workspace configuration

Install all dependencies for both frontend and backend:

npm install

This will install dependencies for both workspaces automatically.

Run both frontend and backend in development mode:

npm run dev

Or run them separately:

# Frontend only (runs on http://localhost:3000)
npm run dev:frontend

# Backend only (runs on http://localhost:3001)
npm run dev:backend

Build both frontend and backend:

npm run build

Or build separately:

npm run build:frontend
npm run build:backend

You can also run commands directly in each workspace:

# Frontend
cd frontend
npm run dev

# Backend
cd backend
npm run dev

The python/ directory contains the iMessage processing module for embeddings, drama detection, and conversation summaries.

cd python
pip install -r requirements.txt

See python/README.md for detailed documentation.

Quick start:

from imessage_processor import process_all, search_messages, get_drama_summary

# Process all data
df, summaries = process_all()

# Search messages
results = search_messages("deadline", top_k=5)

# Get drama summary
summary = get_drama_summary("Chat Name")

• Frontend developer: Work in the frontend/ directory
• Backend developer: Work in the backend/ directory
• ML/Python developer: Work in the python/ directory

This separation minimizes merge conflicts as each team member works in their own directory.