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How to build Inventory tracking platform with Lovable?

Build a scalable inventory tracking platform with Lovable. Follow our step-by-step guide to streamline and optimize inventory management today!

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How to build Inventory tracking platform with Lovable?

 
Setting Up Project Files in Lovable
 

  • Create a new project in Lovable. Since Lovable does not have a terminal, you will create all necessary files manually in the Lovable file editor.
  • Create the following files in your project:
    • index.html – This will be the main HTML file containing the user interface.
    • script.js – This file will hold all JavaScript logic for managing your inventory data.
    • style.css – This is where you will define the styling for your platform.
    • package.json – Even though you cannot use a terminal, add this file to specify any dependencies. Lovable will read it automatically.

 
Configuring Dependencies
 

  • Open the package.json file and add the following code snippet to list any external libraries you might need (for this example we use Lodash for data operations):

{
  "name": "inventory-tracker",
  "version": "1.0.0",
  "description": "Inventory tracking platform built with Lovable",
  "dependencies": {
    "lodash": "^4.17.21"
  }
}
  • This step ensures that any dependency manager integrated with Lovable will fetch and link the necessary libraries automatically.

 
Building the User Interface
 

  • Open the index.html file and paste the following HTML code. This code creates a header, a form for adding inventory items, and a table to display the items.

<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <title>Inventory Tracking Platform</title>
  <link rel="stylesheet" href="style.css">
</head>
<body>
  <h1>Inventory Tracker</h1>
  <form id="inventory-form">
    <input type="text" id="item-name" placeholder="Item Name" required>
    <input type="number" id="item-quantity" placeholder="Quantity" required>
    <input type="number" id="item-price" step="0.01" placeholder="Price" required>
    <button type="submit">Add Item</button>
  </form>
  <table id="inventory-table">
    <thead>
      <tr>
        <th>Name</th>
        <th>Quantity</th>
        <th>Price</th>
      </tr>
    </thead>
    <tbody>
      <!-- Inventory items will be inserted here dynamically -->
    </tbody>
  </table>
  <script src="script.js"></script>
</body>
</html>
  • This file constitutes the primary interface where users can enter new inventory items and view the current list.

 
Styling the Platform
 

  • Open the style.css file and add the following CSS to style your form and table for a clean appearance:

body {
  font-family: Arial, sans-serif;
  margin: 20px;
  padding: 0;
  background-color: #f4f4f4;
}

h1 {
  text-align: center;
}

form {
  display: flex;
  justify-content: center;
  margin-bottom: 20px;
}

form input, form button {
  margin: 0 5px;
  padding: 10px;
  font-size: 1em;
}

table {
  margin: 0 auto;
  border-collapse: collapse;
  width: 80%;
  background-color: #fff;
}

thead th {
  background-color: #333;
  color: #fff;
  padding: 10px;
}

tbody td {
  border: 1px solid #ddd;
  padding: 10px;
  text-align: center;
}
  • This CSS ensures that your inventory tracker looks neat and is easy to use.

 
Adding JavaScript Logic for Inventory Management
 

  • Open the script.js file and insert the following JavaScript code. This code handles adding new inventory items, storing them in an array, and dynamically updating the table.

document.addEventListener('DOMContentLoaded', function() {
  const form = document.getElementById('inventory-form');
  const tableBody = document.querySelector('#inventory-table tbody');
  let inventory = [];

  // Function to render the inventory table
  function renderInventory() {
    tableBody.innerHTML = '';
    inventory.forEach(function(item) {
      const row = document.createElement('tr');

      const nameCell = document.createElement('td');
      nameCell.textContent = item.name;
      row.appendChild(nameCell);

      const quantityCell = document.createElement('td');
      quantityCell.textContent = item.quantity;
      row.appendChild(quantityCell);

      const priceCell = document.createElement('td');
      priceCell.textContent = item.price.toFixed(2);
      row.appendChild(priceCell);

      tableBody.appendChild(row);
    });
  }

  // Event listener for form submission
  form.addEventListener('submit', function(e) {
    e.preventDefault();
    const nameInput = document.getElementById('item-name');
    const quantityInput = document.getElementById('item-quantity');
    const priceInput = document.getElementById('item-price');

    // Create an item object from form values
    const newItem = {
      name: nameInput.value.trim(),
      quantity: parseInt(quantityInput.value, 10),
      price: parseFloat(priceInput.value)
    };

    // Add new item to the inventory list
    inventory.push(newItem);

    // Clear input fields
    nameInput.value = '';
    quantityInput.value = '';
    priceInput.value = '';

    // Re-render the inventory table
    renderInventory();
  });

});
  • This script uses basic DOM manipulation to capture user input, add items to an inventory array, and update the HTML table automatically.

 
Testing Your Inventory Tracking Platform
 

  • Once you have added all the files and code snippets, save your changes in Lovable.
  • Click on the "Run" or preview button provided by Lovable to launch your platform in the browser.
  • Test by adding inventory items. They should appear in the table below the form as you add them.

 
Making Enhancements and Future Improvements
 

  • You can extend this project by using localStorage to persist data across page reloads. Insert additional methods in script.js to save and load the inventory array from localStorage.
  • For further improvements, consider adding edit and delete functionality using additional buttons and event listeners for each inventory row.
  • If your project needs more advanced features in the future, you can integrate a backend by adding API endpoint calls within the JavaScript code, provided Lovable supports HTTP requests.

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How to add a bulk inventory update API endpoint using Lovable


const express = require('express');
const bodyParser = require('body-parser');
const mongoose = require('mongoose');

mongoose.connect('mongodb://localhost:27017/lovable\_inventory', { useNewUrlParser: true, useUnifiedTopology: true });

const InventorySchema = new mongoose.Schema({
  name: { type: String, required: true },
  sku: { type: String, required: true, unique: true },
  quantity: { type: Number, default: 0 },
  location: {
    warehouse: String,
    aisle: String,
    shelf: String
  },
  lastUpdated: { type: Date, default: Date.now }
});

const Inventory = mongoose.model('Inventory', InventorySchema);

const app = express();
app.use(bodyParser.json());

// Complex API endpoint: Bulk update inventory quantities with upsert capabilities
app.put('/api/inventory/bulk-update', async (req, res) => {
  try {
    const updates = req.body.updates; // Expects [{ sku: 'SKU123', quantity: 10 }, ...]
    if (!Array.isArray(updates)) {
      return res.status(400).json({ message: 'Invalid updates format' });
    }
    const bulkOps = updates.map(item => ({
      updateOne: {
        filter: { sku: item.sku },
        update: { $inc: { quantity: item.quantity }, $set: { lastUpdated: new Date() } },
        upsert: true
      }
    }));
    const result = await Inventory.bulkWrite(bulkOps);
    res.json({ message: 'Bulk update successful', result });
  } catch (error) {
    res.status(500).json({ error: error.message });
  }
});

app.listen(3000, () => console.log('Inventory API running on port 3000'));

How to sync your supplier's inventory data with Lovable?


const express = require('express');
const axios = require('axios');
const mongoose = require('mongoose');

mongoose.connect('mongodb://localhost:27017/lovable\_inventory', { useNewUrlParser: true, useUnifiedTopology: true });

const InventorySchema = new mongoose.Schema({
  sku: { type: String, unique: true },
  name: String,
  quantity: Number,
  supplierData: Object,
  lastSynced: Date
});

const Inventory = mongoose.model('Inventory', InventorySchema);
const app = express();
app.use(express.json());

app.get('/api/inventory/sync-supplier', async (req, res) => {
  try {
    const response = await axios.get('https://api.lovablesupplier.com/v1/inventory', {
      headers: { 'Authorization': 'Bearer YOUR_SUPPLIER_API\_TOKEN' }
    });
    
    const supplierItems = response.data.items;
    const updatePromises = supplierItems.map(item => 
      Inventory.findOneAndUpdate(
        { sku: item.sku },
        { 
          name: item.details.name,
          quantity: item.quantity,
          supplierData: item.details,
          lastSynced: new Date()
        },
        { upsert: true, new: true }
      )
    );
    
    await Promise.all(updatePromises);
    res.json({ message: 'Inventory synced with supplier successfully.' });
  } catch (error) {
    res.status(500).json({ error: error.message });
  }
});

app.listen(3001, () => console.log('Sync API running on port 3001'));

How to build a warehouse stats API with caching using Lovable?


const express = require('express');
const mongoose = require('mongoose');
const redis = require('redis');
const { promisify } = require('util');

mongoose.connect('mongodb://localhost:27017/lovable\_inventory', { useNewUrlParser: true, useUnifiedTopology: true });

const InventorySchema = new mongoose.Schema({
  name: { type: String, required: true },
  sku: { type: String, required: true, unique: true },
  quantity: { type: Number, default: 0 },
  location: {
    warehouse: String,
    aisle: String,
    shelf: String
  },
  lastUpdated: { type: Date, default: Date.now }
});

const Inventory = mongoose.model('Inventory', InventorySchema);

const redisClient = redis.createClient();
const getAsync = promisify(redisClient.get).bind(redisClient);
const setAsync = promisify(redisClient.setex).bind(redisClient);

const app = express();
app.use(express.json());

// Complex API endpoint: Get aggregated inventory statistics per warehouse with Redis caching
app.get('/api/inventory/warehouse-stats', async (req, res) => {
  try {
    const cacheKey = 'warehouse\_stats';
    const cachedResult = await getAsync(cacheKey);
    if (cachedResult) {
      return res.json({ source: 'cache', data: JSON.parse(cachedResult) });
    }
    
    const stats = await Inventory.aggregate([
      {
        $group: {
          \_id: '$location.warehouse',
          totalQuantity: { $sum: '$quantity' },
          itemCount: { $sum: 1 },
          averageQuantity: { $avg: '$quantity' }
        }
      },
      { $sort: { totalQuantity: -1 } }
    ]);
    
    await setAsync(cacheKey, 300, JSON.stringify(stats)); // Cache for 5 minutes
    res.json({ source: 'db', data: stats });
  } catch (error) {
    res.status(500).json({ error: error.message });
  }
});

app.listen(3002, () => console.log('Warehouse Stats API running on port 3002'));

Want to explore opportunities to work with us?

Connect with our team to unlock the full potential of no-code solutions with a no-commitment consultation!

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Matt Graham, CEO of Rapid Developers

Book a call with an Expert

Starting a new venture? Need to upgrade your web app? RapidDev builds application with your growth in mind.

Book a free No-Code consultation

Best Practices for Building a Inventory tracking platform with AI Code Generators

 

Understanding the Project and AI Code Generators

 

  • This project focuses on building an inventory tracking platform that leverages AI code generators to automate segments of code creation, streamline inventory management, and ensure accuracy in tracking items.
  • Inventory tracking involves managing records for products, stock levels, transactions, and alerts for low stock. AI code generators help by suggesting or auto-generating code segments for common tasks such as data entry forms, database queries, and report generation.
  • Before starting, it is important to understand the key components: a user interface, a database back-end, an integration layer that communicates with the AI code generator, and reporting and analytics features.

 

Gathering Necessary Tools and Prerequisites

 

  • A basic understanding of web applications and databases.
  • Access to an AI code generator service or platform that suits your needs. Some popular ones include OpenAI Codex, GitHub Copilot, or other similar services.
  • A development environment (this could be a local IDE or an online workspace like Replit).
  • Knowledge of at least one programming language such as Python, JavaScript, or any backend language, although detailed code knowledge is not mandatory for conceptual understanding.

 

Designing the Inventory Tracking Platform

 

  • Plan the overall structure:
    • The user interface where users can add or update inventory.
    • A database to store inventory details like item names, quantities, dates, etc.
    • An integration module that connects with the AI code generator to help produce code for recurring tasks.
  • Create a flow diagram that outlines how data moves through the platform, from input (via forms) to database storage and finally to reporting views.
  • Decide on key functionalities: adding new inventory items, updating stock levels, generating reports, providing automated suggestions for low-stock orders, and tracking historical data.

 

Setting Up the Development Environment

 

  • Create a new project workspace using your chosen development environment. If you are using an online tool, start a new project and select the language you are comfortable with.
  • Set up a virtual environment if you are using a local machine. For example, in Python you can set up a virtual environment: 
    
python -m venv env
source env/bin/activate  # use `env\Scripts\activate` on Windows
  • Install necessary libraries for web development, database operations, and AI integration. For instance, if using Python: 
    
pip install flask sqlalchemy openai

 

Setting Up the Inventory Database

 

  • Choose a database solution (such as SQLite, MySQL, or PostgreSQL) that fits your project’s size and needs.
  • Create the database schema with tables for inventory items, transaction logs, and user details. An example schema for an inventory table might be: 
    
CREATE TABLE Inventory (
    id INTEGER PRIMARY KEY,
    item\_name TEXT NOT NULL,
    stock\_quantity INTEGER DEFAULT 0,
    last_updated DATETIME DEFAULT CURRENT_TIMESTAMP
);
  • Develop a simple script or use an ORM (Object Relational Mapper) to interact with the database.

 

Integrating the AI Code Generator

 

  • Identify parts of the platform where code can be generated automatically. These include generating boilerplate code for forms, database queries, or report templates.
  • Set up API access to the AI code generator. For example, if using an AI service that provides REST APIs, you will typically:
    • Obtain your API key from the service provider.
    • Store the API key securely in your environment configuration or secrets management system.
  • Create a simple module to interact with the AI generator. An example in Python might be: 
    
import requests


    def generate_code(prompt):
        api_key = "YOUR_API_KEY"
        headers = {"Authorization": f"Bearer {api_key}"}
        data = {"prompt": prompt, "max_tokens": 150}
        response = requests.post("https://api.aicodegenerator.com/v1/generate", headers=headers, json=data)
        return response.json().get("code")
    

    Example usage:
    

    code_snippet = generate_code("Generate a Python function to update inventory stock")
    print(code_snippet)

 

Building the User Interface for Inventory Management

 

  • Develop a simple front end where users can enter data, view current inventory levels, and manage orders.
  • If you are using a web framework like Flask, create routes for different pages such as: 
    
from flask import Flask, render\_template, request


    app = Flask(name)
    

    @app.route('/')
    def home():
        # Code to fetch inventory data from database
        return render_template('index.html', inventory=[])
    

    @app.route('/add', methods=['POST'])
    def add_item():
        # Code to add inventory item
        item_name = request.form.get('item_name')
        # insert into database logic
        return "Item added successfully!"
    

    if name == "main":
        app.run(host="0.0.0.0", port=8080)


  • Utilize templating languages (like Jinja2 for Flask) to dynamically display data on the web pages.

 

Automating Code Generation for Repetitive Tasks

 

  • Identify repetitive code that can be generated by the AI, such as CRUD operations for inventory items.
  • Create a process in your development workflow where you provide descriptive prompts to the AI and then review and adjust the generated code.
  • For example, you can start with a prompt like: “Generate a Python SQLAlchemy model for an inventory item with fields for item name, quantity, and update timestamp.”
  • Review the generated output, integrate

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