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How to build Directory service with Lovable?

Discover how to build a robust directory service with Lovable. Follow our step-by-step guide for setup, best practices, and expert tips for success.

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How to build Directory service with Lovable?

 
Creating a New Lovable Project
 

  • Log into your Lovable account and create a new project by clicking the Create Project button.
  • Give your project a name such as "DirectoryService" and choose the default programming language (for this example, we use Python).
  • Lovable automatically creates a project workspace where you will add new files and code.

 
Configuring Dependencies via Code
 

  • Since Lovable does not have a terminal for installing packages, you must add a dependency configuration file.
  • Create a new file named lovable.json in the root of your project.
  • Add the following code snippet to lovable.json to specify that your project depends on Flask:
    • 
      {
        "dependencies": {
          "Flask": "2.0.3"
        }
      }
            
  • This file instructs Lovable to “install” or load the Flask dependency when your project runs.

 
Creating the Main Server File
 

  • Create a new file named main.py in your project’s root directory. This file will host your server logic.
  • Copy and paste the following code into main.py:
    • 
      from flask import Flask, jsonify, request
      from directory import Directory
      
      

      app = Flask(name)
      directory = Directory()

      Endpoint to list all contacts in the directory

      @app.route('/directory', methods=['GET'])
      def get_directory():
      return jsonify(directory.get_all_contacts())

      Endpoint to add a new contact to the directory

      @app.route('/directory', methods=['POST'])
      def add_contact():
      contact = request.get_json()
      directory.add_contact(contact)
      return jsonify({'message': 'Contact added successfully!'}), 201

      if name == "main":
      # Lovable will run this file as the entry point; it listens on all IPs using port 8080.
      app.run(host="0.0.0.0", port=8080)




  • This file sets up a simple web server with two endpoints: one for retrieving all directory contacts and one for adding a new entry.

 
Creating the Directory Module
 

  • Create a new file named directory.py in the project’s root folder. This module will contain the logic for managing directory contacts.
  • Add the following code snippet to directory.py:
    • 
      class Directory:
          def **init**(self):
              # Using a simple list to store contacts in memory
              self.contacts = []
      
      
      def get_all_contacts(self):
          return self.contacts
      
      def add\_contact(self, contact):
          # Append the contact (a dictionary with contact details) to the contacts list.
          self.contacts.append(contact)
        </code></pre>
      </li>
      
  • This module defines a Directory class with methods to return all contacts and add new contacts.

 
Configuring and Running Your Directory Service App
 

  • Ensure that all files (lovable.json, main.py, and directory.py) are saved in your project’s root directory.
  • Lovable automatically detects the lovable.json configuration and loads Flask as specified.
  • Your project’s entry point is main.py; when you click the Run button in Lovable, the web server will start listening on port 8080.

 
Testing and Interacting with Your Directory Service
 

  • After clicking Run, Lovable displays a web view with your application URL.
  • You can test the GET endpoint by navigating to /directory in your browser; an empty list should be returned initially.
  • To add a new contact, simulate a POST request by using Lovable’s API testing tools or by adding temporary code in your project to send a request to /directory with a JSON payload.
  • For example, you can temporarily add a code snippet to main.py that sends a POST request when your app starts, then remove it once you have verified functionality.

 
Updating and Maintaining Your Directory Service
 

  • Each time you need to modify the way data is handled or add more endpoints, update the corresponding files (main.py or directory.py).
  • Save your changes and click Run to see the updates.
  • Because Lovable manages dependencies via the lovable.json configuration, any changes to dependency versions can be made there.

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How to Build a Lovable Directory Service with Express and MongoDB


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

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

const DirectorySchema = new mongoose.Schema({
  name: { type: String, required: true },
  category: { type: String, required: true },
  location: { type: String, required: true },
  lovableScore: { type: Number, default: 0 },
  contact: {
    email: { type: String },
    phone: { type: String }
  },
  metadata: { type: mongoose.Schema.Types.Mixed }
});

const Directory = mongoose.model('Directory', DirectorySchema);

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

app.post('/api/directory', async (req, res) => {
  try {
    const entry = new Directory(req.body);
    await entry.save();
    res.status(201).json(entry);
  } catch (error) {
    res.status(400).json({ error: error.message });
  }
});

app.get('/api/directory/top', async (req, res) => {
  try {
    const { category, location } = req.query;
    const matchFilter = {};
    if (category) matchFilter.category = category;
    if (location) matchFilter.location = location;

    const topEntries = await Directory.aggregate([
      { $match: matchFilter },
      { $sort: { lovableScore: -1 } },
      { $limit: 10 }
    ]);
    res.json(topEntries);
  } catch (error) {
    res.status(500).json({ error: error.message });
  }
});

const PORT = process.env.PORT || 3000;
app.listen(PORT, () => {
  console.log(`Directory service running on port ${PORT}`);
});

How to enrich your directory service with Lovable data?


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

app.use(express.json());

// Endpoint to retrieve a directory entry enriched by data from an external Lovable API
app.get('/api/directory/:id/lovable', async (req, res) => {
  try {
    const { id } = req.params;
    
    // Simulate a local directory entry retrieval (in a real scenario, fetch from your database)
    const localEntry = {
      id,
      name: 'Artisan Cafe',
      category: 'Food & Beverage',
      location: 'Downtown'
    };

    // Connect to external Lovable API service to fetch detailed lovable metrics
    const externalApiUrl = `https://api.lovableinfo.com/ratings/${id}`;
    const externalResponse = await axios.get(externalApiUrl, { timeout: 5000 });
    const externalData = externalResponse.data;

    // Combine local and external data into a cohesive entry
    const enrichedEntry = {
      ...localEntry,
      lovableRating: externalData.rating,
      reviews: externalData.reviews
    };

    res.json(enrichedEntry);
  } catch (error) {
    res.status(500).json({ message: 'Error fetching external data', details: error.message });
  }
});

const PORT = process.env.PORT || 3002;
app.listen(PORT, () => console.log(`Service running on port ${PORT}`));

How to Build a Directory Service with Integrated Lovable Ratings


const express = require('express');
const { graphqlHTTP } = require('express-graphql');
const { GraphQLSchema, GraphQLObjectType, GraphQLString, GraphQLFloat, GraphQLID } = require('graphql');
const axios = require('axios');

const memoryCache = new Map();

const fetchLovableData = async (id) => {
  if (memoryCache.has(id)) {
    return memoryCache.get(id);
  }
  const res = await axios.get(`https://api.lovableinfo.com/ratings/${id}`, { timeout: 5000 });
  const data = res.data;
  memoryCache.set(id, data);
  return data;
};

const directoryData = {
  "1": { id: "1", name: "Sunrise Bakery", category: "Food & Beverage", location: "Midtown" },
  "2": { id: "2", name: "Urban Studio", category: "Art & Design", location: "Downtown" }
};

const DirectoryType = new GraphQLObjectType({
  name: "Directory",
  fields: {
    id: { type: GraphQLID },
    name: { type: GraphQLString },
    category: { type: GraphQLString },
    location: { type: GraphQLString },
    lovableRating: {
      type: GraphQLFloat,
      resolve: async (parent) => {
        const external = await fetchLovableData(parent.id);
        return external.rating;
      }
    },
    reviewCount: {
      type: GraphQLString,
      resolve: async (parent) => {
        const external = await fetchLovableData(parent.id);
        return external.reviews ? external.reviews.length.toString() : "0";
      }
    }
  }
});

const RootQuery = new GraphQLObjectType({
  name: "RootQueryType",
  fields: {
    directory: {
      type: DirectoryType,
      args: { id: { type: GraphQLID } },
      resolve(parent, args) {
        return directoryData[args.id];
      }
    }
  }
});

const schema = new GraphQLSchema({
  query: RootQuery
});

const app = express();
app.use("/graphql", graphqlHTTP({
  schema,
  graphiql: true
}));

const PORT = process.env.PORT || 4000;
app.listen(PORT, () => console.log(`GraphQL service running on port ${PORT}`));

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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.

Best Practices for Building a Directory service with AI Code Generators

 

Prerequisites

 

  • A basic understanding of web applications and RESTful APIs, even if only conceptually.
  • A willingness to follow step-by-step instructions with visual examples.
  • Access to a development environment (like Replit, VSCode, or any code editor), along with a relevant programming language (e.g., Python, Node.js).
  • An account on an AI code generation platform or integrated AI tool (for example, GitHub Copilot, OpenAI Codex, or similar) to assist in code snippet generation.

 

Planning Your Directory Service

 

  • Decide on the main purpose of your directory service, e.g., listing businesses, contacts, or resources.
  • Outline the essential features such as search functionality, user authentication, data management, and possibly an admin panel.
  • Sketch the user interface layout on paper or via digital wireframing tools to have a visual guide.
  • Determine how the AI code generator will help. For instance, you might use it to automatically generate boilerplate code, or to help build dynamic queries for search functionality.

 

Designing the Architecture

 

  • Use a client-server model where the front end (user interface) communicates with the back end (server, APIs, and database).
  • The back end should handle the business logic and integrate the AI code generation components, such as generating custom code for specific directory tasks.
  • Choose a database to store directory listings. Options include SQLite for simplicity, or MySQL/PostgreSQL for scalability.
  • Plan for security measures such as authentication and data validation.

 

Setting Up the Development Environment

 

  • Install your chosen development tools and ensure you have the necessary software packages.
  • Create a new project directory on your machine or in your online coding environment.
  • Initialize a version control system like Git to track your progress.
  • If using Python, create a virtual environment to isolate your project’s dependencies.

 

Initializing a Sample Project

 

  • If using Python, start by creating a new main file (e.g., app.py) for your back-end logic.
  • Paste the following code snippet to set up a basic web server using the Flask framework:
    • from flask import Flask, request, jsonify
      
      

      app = Flask(name)

      @app.route('/')
      def home():
      return "Directory Service Home"

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




  • Create a requirements.txt file to list your project dependencies. For example:



    • Flask

      Add any other dependencies as necessary

        </code></pre>
      </li>
      

 

Integrating an AI Code Generator

 

  • Choose an AI code generation tool that fits into your workflow. These tools can suggest code snippets or even generate full functions based on descriptive text.
  • Consider integrating your editor with an AI tool so that when you type comments like "generate a function for listing directory entries," the tool suggests code you can adapt.
  • For example, in a Python project using GitHub Copilot, you might add a comment and let the tool guide you:
    • # Generate a function that returns a JSON of all directory entries from the database
      def get_directory_entries():
          # Your AI tool can help fill in the logic here
          pass
            
  • Review, refine, and test the AI-generated code to ensure it meets your requirements.

 

Implementing Directory Service Functionality

 

  • Create endpoints in your back end to add, update, delete, and query directory information.
  • For example, add an endpoint for listing all entries:
    • @app.route('/entries', methods=['GET'])
      def list\_entries():
          # In a real app, fetch data from a database
          entries = [
              {"name": "Business One", "location": "City A"},
              {"name": "Business Two", "location": "City B"}
          ]
          return jsonify(entries)
            
  • Leverage AI code generators to write repetitive CRUD functions. For instance, by providing clear instructions in comments, the tool can suggest a template for adding a new directory entry.
  • Implement search functionality by creating an API endpoint that processes search queries and returns matching entries.

 >

Testing and Optimization

 

  • Manually test each endpoint using tools like Postman or your browser to ensure responses are correct.
  • Use debugging tools available in your development environment to step through the code if issues arise.
  • Optimize performance by caching frequently requested data and indexing database fields used in search queries.
  • Solicit feedback from non-technical users to validate that the directory service meets usability expectations.

 

Deployment and Security

 

  • Plan to deploy your application on a secure web hosting platform. Options include cloud services like Heroku, AWS, or digital ocean.
  • Ensure you safeguard sensitive data by using environment variables for configuration settings, such as database connection URLs and API keys.
  • Deploy your application using a container-based approach if possible, ensuring consistency between development and production environments.
  • Regularly update both your application and its dependencies for security considerations.

 

Monitoring and Maintenance

 

  • Set up logging to capture errors and performance metrics. This helps in understanding user behavior and troubleshooting issues when they occur.
  • Plan for periodic reviews and maintenance to address any code or system vulnerabilities.
  • Utilize AI tools to assist with code refactoring and performance improvement suggestions as your

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