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How to build Feedback collection tool with Lovable?

Discover how to build a powerful feedback tool with Lovable. Our guide shows you how to design, integrate, and customize it to capture real user insights.

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How to build Feedback collection tool with Lovable?

 
Setting Up Your Lovable Project
 
Create a new project within Lovable. Once logged into your Lovable account, start a new project by clicking the “New Project” button. Name your project “Feedback Collection Tool” and save it. This project will hold all your files for both the front-end and back-end of your feedback tool.

 
Creating the Feedback Form UI
 
Inside your Lovable project, add a new file named feedback.html. This file will contain the HTML code for the feedback form. Insert the following snippet into feedback.html:


<!DOCTYPE html>
<html lang="en">
  <head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Feedback Form</title>
    <style>
      body { font-family: Arial, sans-serif; margin: 20px; }
      .feedback-form { max-width: 500px; margin: auto; }
      .feedback-form input, .feedback-form textarea { width: 100%; margin-bottom: 10px; padding: 8px; }
      .feedback-form button { padding: 10px 20px; }
    </style>
  </head>
  <body>
    <div class="feedback-form">
      <h2>We Value Your Feedback</h2>
      <form id="feedbackForm" action="/submit-feedback" method="POST">
        <input type="text" name="name" placeholder="Your Name" required>
        <input type="email" name="email" placeholder="Your Email" required>
        <textarea name="feedback" placeholder="Enter your feedback" required></textarea>
        <button type="submit">Submit Feedback</button>
      </form>
    </div>
  </body>
</html>

This HTML page creates a simple feedback form that collects the user’s name, email, and feedback message. The action attribute in the form is set to /submit-feedback, which is the endpoint you will create to handle the submitted data.

 
Configuring Dependencies Without a Terminal
 
Since Lovable does not include a terminal, you need to manage dependencies by adding a package.json file in your project. Create a new file named package.json and insert the following content. This file tells Lovable which modules to install automatically:


{
  "name": "feedback-tool",
  "version": "1.0.0",
  "description": "A Feedback Collection Tool built with Lovable",
  "main": "server.js",
  "scripts": {
    "start": "node server.js"
  },
  "dependencies": {
    "express": "^4.18.2",
    "body-parser": "^1.20.2"
  }
}

Lovable will detect the package.json file and install the stated dependencies automatically.

 
Building the Server-Side API to Handle Feedback
 
Create a new file named server.js in your Lovable project. This file will contain Node.js code using Express to process the feedback submission from the form. Insert the following code into server.js:


const express = require('express');
const bodyParser = require('body-parser');
const app = express();
const port = process.env.PORT || 3000;

// Middleware to parse form data
app.use(bodyParser.urlencoded({ extended: true }));
app.use(bodyParser.json());

// Serve the feedback form
app.get('/', (req, res) => {
  res.sendFile(\_\_dirname + '/feedback.html');
});

// Handle feedback form submission
app.post('/submit-feedback', (req, res) => {
  const { name, email, feedback } = req.body;
  
  // For demonstration, simply log the feedback to the console.
  console.log('Feedback Received:');
  console.log('Name:', name);
  console.log('Email:', email);
  console.log('Feedback:', feedback);
  
  // Send a thank-you response
  res.send('<h2>Thank You for Your Feedback!</h2><p>We appreciate you taking the time to help us improve.</p>');
});

// Start the server
app.listen(port, () => {
  console.log(`Feedback tool running on port ${port}`);
});

This code sets up an Express server that:
• Serves the feedback.html page when a user visits the root URL.
• Listens for POST requests at /submit-feedback to capture form submissions.
• Logs the submitted feedback to the console and returns a thank-you message to the user.

 
Linking the Feedback Form to the API
 
The feedback form in feedback.html already includes the action="/submit-feedback" attribute. This ensures that when the form is submitted, the data is sent to the API endpoint you created in server.js. No further changes are necessary, but make sure both files are saved in the same project directory.

 
Testing Your Feedback Collection Tool
 
Lovable provides a built-in preview feature to test your project. Click the “Run” or “Preview” button in Lovable. The application will start the Express server using server.js and open your browser to display the feedback form. Fill out the form and submit your feedback. Check your Lovable project’s console for the logged data to verify that the submission is working correctly.

 
Deploying Your Feedback Collection Tool
 
Every time you make changes to feedback.html, server.js, or package.json, save the files in Lovable. The preview updates automatically when you click “Run.” When you are satisfied with your changes, share the project URL provided by Lovable with users to start collecting feedback.

 
Sharing and Managing Feedback Data
 
Currently, feedback submissions are logged to the console in server.js. For production purposes, you might consider extending this tool to save data in a database or send it via email. To do this, you can integrate additional libraries by updating package.json and modifying server.js accordingly. Lovable will use the updated package.json to install any new dependencies.

 

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How to build a Feedback Collection API with Lovable?


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

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

const feedbackSchema = new mongoose.Schema({
  userId: { type: String, required: true },
  rating: { type: Number, required: true, min: 1, max: 5 },
  comment: { type: String },
  createdAt: { type: Date, default: Date.now }
});

const Feedback = mongoose.model('Feedback', feedbackSchema);

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

app.post('/api/feedback', async (req, res) => {
  try {
    const { userId, rating, comment } = req.body;
    if (!userId || !rating) {
      return res.status(400).json({ error: 'Missing required fields (userId, rating)' });
    }
    const feedback = new Feedback({ userId, rating, comment });
    await feedback.save();
    res.status(201).json({ message: 'Feedback saved successfully' });
  } catch (error) {
    res.status(500).json({ error: 'Failed to save feedback' });
  }
});

app.get('/api/feedback', async (req, res) => {
  try {
    const feedbacks = await Feedback.find().sort({ createdAt: -1 });
    res.json(feedbacks);
  } catch (error) {
    res.status(500).json({ error: 'Failed to fetch feedbacks' });
  }
});

app.get('/api/feedback/stats', async (req, res) => {
  try {
    const stats = await Feedback.aggregate([
      {
        $group: {
          \_id: null,
          averageRating: { $avg: '$rating' },
          totalFeedbacks: { $sum: 1 }
        }
      }
    ]);
    res.json(stats[0] || {});
  } catch (error) {
    res.status(500).json({ error: 'Failed to fetch stats' });
  }
});

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

How to Build a Feedback Collection Tool with Lovable's Sentiment Analysis


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

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

const SENTIMENT_API_URL = process.env.SENTIMENT_API_URL || 'https://api.lovablesentiment.com/analyze';
const API_KEY = process.env.SENTIMENT_API_KEY || 'your_api_key_here';

app.post('/api/feedback/with-analysis', async (req, res) => {
  try {
    const { userId, rating, comment } = req.body;
    if (!userId || !rating || !comment) {
      return res.status(400).json({ error: 'userId, rating, and comment are required.' });
    }
    
    const sentimentResponse = await axios.post(SENTIMENT_API_URL, { text: comment }, {
      headers: { 'Authorization': `Bearer ${API_KEY}` }
    });
    
    const sentimentScore = sentimentResponse.data.score;
    
    // Simulated saving to a database
    const feedbackRecord = {
      id: Math.floor(Math.random() \* 1e6),
      userId,
      rating,
      comment,
      sentimentScore,
      createdAt: new Date()
    };
    
    res.status(201).json({ message: 'Feedback processed with sentiment analysis', feedback: feedbackRecord });
  } catch (err) {
    res.status(500).json({ error: 'Error processing feedback', details: err.message });
  }
});

app.listen(3001, () => {
  console.log('Feedback Analysis API running on port 3001');
});

How to Build a Rate-Limited Feedback Collection API for Lovable


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

const client = redis.createClient({ host: '127.0.0.1', port: 6379 });
client.on('error', (err) => console.error('Redis error:', err));

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

const RATE_LIMIT_DURATION = 600; // seconds (10 minutes)

// Middleware: limit feedback submissions per IP address
app.use('/api/feedback', (req, res, next) => {
  const userIp = req.ip;
  client.get(`feedback:${userIp}`, (err, record) => {
    if (err) {
      return res.status(500).json({ error: 'Internal server error' });
    }
    if (record) {
      return res.status(429).json({ error: 'You have recently submitted feedback. Please wait a while before submitting again.' });
    }
    client.setex(`feedback:${userIp}`, RATE_LIMIT_DURATION, 'submitted', (err) => {
      if (err) console.error('Redis set error:', err);
    });
    next();
  });
});

app.post('/api/feedback', async (req, res) => {
  const { userId, rating, comment } = req.body;
  if (!userId || !rating || rating < 1 || rating > 5) {
    return res.status(400).json({ error: 'Invalid feedback data.' });
  }
  
  // Forward feedback asynchronously to Lovable backend for further processing
  axios.post('https://api.lovable.com/v1/feedback', { userId, rating, comment }, {
    headers: { 'Authorization': 'Bearer YOUR_LOVABLE_API\_KEY' }
  })
  .then(response => {
    res.status(201).json({ message: 'Feedback submitted successfully', details: response.data });
  })
  .catch(error => {
    res.status(500).json({ error: 'Error processing feedback with Lovable', details: error.message });
  });
});

app.listen(4000, () => console.log('Feedback API with rate limiting running on port 4000'));

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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

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

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Best Practices for Building a Feedback collection tool with AI Code Generators

 
Introduction
 

  • This guide walks you through best practices for building a feedback collection tool enhanced with AI code generators.
  • It is designed for non-technical users, explaining both design concepts and sample code to integrate AI features.
  • The focus is on collecting user feedback, processing it with AI, and iterating for better user experience.

 
Prerequisites
 

  • A basic computer that can access the internet.
  • A web browser to interact with the feedback tool.
  • Familiarity with simple concepts of web forms and data submission.
  • Access to an AI code generator service (most platforms provide simple integration guides).
  • Optional: A basic understanding of the Python programming language if handling server-side features.

 
Setting Up Your Project Environment
 

  • Decide on a platform to host your tool; this could be a local development environment or a cloud-based service.
  • Create a new project folder where all your files will reside.
  • If available, use a no-code or low-code platform that simplifies back-end integrations and API calls.
  • The essential components are an HTML form for feedback and a backend processor which can be enhanced with AI.

 
Building the Feedback Collection Form
 

  • Create a simple HTML form to capture user feedback as shown in the example below:
    •
  • This form keeps the design minimal, encouraging users to share their thoughts without distraction.

 
Integrating AI Code Generators
 

  • The AI code generator helps enhance your tool by assisting in code generation for processing and analyzing feedback.
  • Include an event listener on your form that captures the submission and sends it to the backend for AI processing.
  • Use the JavaScript example below to establish this functionality:
    • 
document.getElementById("feedbackForm").addEventListener("submit", function(event) {
  event.preventDefault();
  const feedback = document.getElementById("feedback").value;
  // Integrate with AI code generator by sending the feedback to the server
  fetch("/process-feedback", {
    method: "POST",
    body: JSON.stringify({ feedback: feedback }),
    headers: {
      "Content-Type": "application/json"
    }
  })
  .then(response => response.json())
  .then(data => {
    console.log("AI processed feedback:", data);
  });
});
  • This snippet demonstrates capturing form data and preparing it for AI processing, all without complex coding.

 
Processing the Feedback with AI on the Server
 

  • Set up a server to receive and process feedback. A popular choice is a simple Flask server.
  • The example below illustrates how to receive data, call an AI service (or simulate one), and return the results:
    • 
from flask import Flask, request, jsonify
app = Flask(**name**)


    @app.route('/process-feedback', methods=['POST'])
    def process_feedback():

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