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tfm_ainventory/README.md
Daniel Bedeleanu 704934165f Build [v.1.3.6]
2026-04-11 17:14:22 +03:00

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# 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.
---
## 🛠 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://<SERVER-IP>:3003
---
## 📦 Production Distribution & Versioning
To generate a clean production package and snapshot the current state:
1. Use the AI shortcut command: `save-version`.
2. Alternatively, run `./export_prod.sh` manually.
3. A `.zip` archive will be created (e.g., `aInventory-PROD-v1.3.6.zip`).
4. A backup branch `v.1.3.x` will be created automatically.
---
## 🏗 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](PROJECT_ARCHITECTURE.md).
---
## 🔐 Security & Production Deployment
### Critical Environment Variables
The application requires the following environment variables for production deployment:
| Variable | Purpose | Example |
|----------|---------|---------|
| **JWT_SECRET_KEY** | JWT token signing key (REQUIRED for production) | `openssl rand -hex 32` |
| **ALLOWED_ORIGINS** | CORS-allowed domain origins (comma-separated) | `https://inventory.example.com,https://api.example.com` |
| **DATA_DIR** | SQLite database location | `/app/data` |
| **LOGS_DIR** | Application logs directory | `/app/logs` |
**⚠️ IMPORTANT:**
- In development, `JWT_SECRET_KEY` defaults to an ephemeral random value, which is reset on restart.
- For production, set `JWT_SECRET_KEY` to a stable, long random string and store it in a secrets manager (AWS Secrets, HashiCorp Vault, etc.).
- `ALLOWED_ORIGINS` **must** be set to your actual production domain(s). Wildcard origins (`*`) are rejected when `allow_credentials=True`.
### Docker Production Deployment
```bash
# Set environment variables
export JWT_SECRET_KEY="$(openssl rand -hex 32)"
export ALLOWED_ORIGINS="https://your-domain.com"
# Launch stack
docker-compose up -d --build
```
For detailed security audit report, see [dev_docs/SECURITY_REPORT.md](dev_docs/SECURITY_REPORT.md).
---
## 📜 AI Operational Rules
AI agents working on this project MUST follow the guidelines in [AI_RULES.md](AI_RULES.md).