TFM aInventory (2026 Edition)

A unified, offline-first Inventory Management System built as a Progressive Web App (PWA). Features include AI-powered label extraction (OCR), local barcode/QR scanning, and multi-user authentication with LDAP support.

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🛠 Project Modes

This project supports three distinct operational modes:

1. 🚀 Development Mode (Bare-Metal)

Ideal for local development on macOS/Linux.

• Command: ./start_server.sh
• Details: Runs FastAPI (backend) and Next.js (frontend) in development mode. Uses local-ssl-proxy for HTTPS.
• Backend: http://localhost:8000
• Frontend: https://localhost:3003

2. 🐳 Docker Mode (Recommended for Production)

Isolated and portable container stack.

• Command: docker-compose up -d --build
• Details: Uses Caddy as a reverse proxy for HTTPS. Persistent data and logs are mapped to ./data and ./logs.
• Access: https://localhost:3003

3. 🐧 Standalone Linux Mode (Systemd)

Native Linux installation (Alma/Debian/Ubuntu) without Docker dependencies.

• Installation: sudo ./install_service.sh
• Execution: sudo systemctl start inventory
• Details: Compiles the frontend for production and manages the entire stack as a system service.
• Access: https://:3003

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📦 Production Distribution

To generate a clean production package without AI-agent metadata or development artifacts:

1. Run ./export_prod.sh
2. A .zip archive will be created (e.g., aInventory-PROD-v1.3.2.zip).
3. This archive contains a specialized README.txt with deployment-only instructions.

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🏗 Technical Overview

• Backend: FastAPI (Python 3.12+)
• Frontend: Next.js 15+ (React PWA)
• Database: SQLite (SQLAlchemy) with Dexie.js (IndexedDB) for client-side sync.
• Proxy: Caddy (Docker) or local-ssl-proxy (Standalone/Dev).
• AI Engine: Google Gemini (Generative AI SDK).

For more details, see PROJECT_ARCHITECTURE.md.

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📜 AI Operational Rules

AI agents working on this project MUST follow the guidelines in AI_RULES.md.