Get StartedQuickstart

GET STARTED

Quickstart

Get your Invenicum instance running and create your first AI-assisted collection in under 10 minutes.


Prerequisites

Docker

Container engine and Docker Compose installed.

GET DOCKER

Gemini API Key

Required for AI-powered object recognition.

GET KEY

PostgreSQL

Primary database (v15+ recommended).

Included in Compose

Note: Invenicum uses the Google Gemini API, so you don’t need a powerful local GPU to process your item images.

Quick Setup

Step 01

Create Docker Compose Configuration

Create a docker-compose.yml file with the following content:

docker-compose.yml
version: '3.8'
services:
app:
  image: ghcr.io/lopiv2/invenicum:latest
  ports:
    - "3000:3000"
  environment:
    - DB_URL=postgres://user:pass@db:5432/invenicum
    - AI_PROVIDER=gemini
    - GEMINI_API_KEY=your_google_gemini_key_here
  depends_on:
    - db
db:
  image: postgres:15-alpine
  volumes:
    - ./data/db:/var/lib/postgresql/data
  environment:
    - POSTGRES_USER=user
    - POSTGRES_PASSWORD=pass
    - POSTGRES_DB=invenicum
Step 02

Start the Services

Run the following command in your terminal within the same folder:

docker-compose up -d
  • Docker will pull the image and start the services in the background.

Step 03

Access the Dashboard

Open your browser and go to http://localhost:3000. Follow the steps to create your initial admin account.

Step 04

Create Your First Container

Create a container (e.g., “Shelf A” or “Toolbox”). These are the physical locations where you will organize your assets.

Step 05

Define an Asset Type

”Asset Types are templates for your items.”

  • Add a type (e.g., “Electronics”)
  • Define custom fields you need to track.
Step 06

Add Your First Item with AI

Veni Chat

”Add a blue Bosch drill that is in the garage…”

URL Import

Autofill data by pasting an Amazon or eBay link.

Barcode

Scan barcodes and let the AI find the metadata.

Troubleshooting

Port 3000 is already in use

If port 3000 is occupied, edit your docker-compose.yml and change the ports line to “3001:3000”.

Database connection failed

Ensure the database container is running with docker ps and that credentials in DB_URL match the database settings.

Can’t connect to Gemini AI

Check that your API key is valid in Google AI Studio and that your server has internet access for external requests.

Getting Help