Preventing Feature Skipping in Lovable Code Generation

 
Creating the Main Application File
 

Create a new file named main.js in your Lovable project. This file will initialize your application and later include the code that ensures your honor prompt details are processed correctly.

• Open or create main.js and insert the following code, which initializes your application once the document is fully loaded:

  
  document.addEventListener('DOMContentLoaded', function() {
      // Your application initialization code goes here
      console.log("Application loaded!");
  });
      

 
Inserting the Lovable Honors Prompt Logic
 

Add code in main.js to handle and display your honor prompt details. This snippet validates the prompt details and displays them on the page.

• Copy and paste the following code into main.js below the initialization code:

  
  function processHonorPrompt(promptDetails) {
      // Validate the prompt details ensuring they are not empty
      if (promptDetails && promptDetails.trim() !== "") {
          console.log("Honor Prompt processed:", promptDetails);
          // Display the prompt details on the screen
          displayHonorPrompt(promptDetails);
      } else {
          console.error("Invalid prompt details provided");
      }
  }
  
  function displayHonorPrompt(prompt) {
      // Find the HTML element that will display the prompt
      var displayArea = document.getElementById("honorPromptArea");
      if (displayArea) {
          displayArea.textContent = prompt;
      } else {
          console.error("Display area for honor prompt not found!");
      }
  }
  // Example usage of the function with your prompt details
  processHonorPrompt("Your Honor Prompt Details Here");
      

  
  

 
Updating Your HTML File to Display the Prompt
 

Create or update your main HTML file (for example, index.html) to include an area where the honor prompt details will be displayed. This file will also load the JavaScript code.

• Create or open index.html and add the following content:

 
Including Dependencies Directly in Code
 

Since Lovable does not have a terminal for installing dependencies, any external libraries you need should be added directly as files in your project. For example, if you require a part of the Lodash library, you can include its code manually.

• Create a new file named lodash.js and paste the following sample code. This code provides a simple implementation of a utility function similar to Lodash's functionality:

  
  /_ Sample implementation of a Lodash-like chunk method _/
  function chunk(array, size) {
      var results = [];
      for (var i = 0; i < array.length; i += size) {
          results.push(array.slice(i, i + size));
      }
      return results;
  }
      

• Next, update your index.html file to load lodash.js before main.js:

 
Finalizing and Testing Your Integration
 

After updating the files:

• Save all the changes in your Lovable project.
• Use the Lovable preview feature to open index.html and verify that the honor prompt details are correctly processed and displayed.
• If the prompt does not appear as expected, use the browser console (if available) to review any error messages and adjust the code as needed.

 
Configuring the Detailed Logger
 

• In your Lovable project, create a new file named logger\_config.py in your project’s main folder. This file will set up the detailed logging that will help you get a clear view of what’s happening in your application.
• Copy and paste the following code snippet into logger\_config.py. This code uses Python’s built-in logging and an optional dependency named coloredlogs for better output formatting. Since Lovable doesn’t have a terminal, the snippet includes code to install the dependency automatically if it isn’t found.

  
  import logging
  
  try:
      import coloredlogs
  except ImportError:
      import os
      os.system("pip install coloredlogs")
      import coloredlogs
  def setup_logger(logger_name='LovableDetailedLogger'):
      logger = logging.getLogger(logger_name)
      logger.setLevel(logging.DEBUG)  # Set logging to capture all details
      coloredlogs.install(level='DEBUG', logger=logger, fmt='%(asctime)s %(levelname)s %(message)s')
      return logger
  if name == "main":
      setup_logger()
      print("Detailed logger is configured.")
      

  
  


• This file configures the logger with the DEBUG level, meaning every detail is captured. The format prints the time, severity level, and the actual message so you can easily troubleshoot and understand what is happening in your application.

 
Integrating the Logger into Your Main Code
 

• In your main application file (for example, app.py or main.py), you need to import the logger from logger\_config.py so that you can use detailed output in your code.
• Add the following code snippet at the very top of your main file to set up the logger:

  
  from logger_config import setup_logger
  
  logger = setup_logger()
  Start of your application code
  def some_function():
      logger.debug("Starting some_function processing.")
      try:
          # Your operation goes here
          result = "Performing important tasks."
          logger.info("Operation successful with result: %s", result)
      except Exception as e:
          logger.error("An error occurred in some_function: %s", str(e))
  some_function()
      

  
  


• This addition ensures that every step in your main file uses the detailed logger for debugging and information.

 
Enhancing Error Handling with Detailed Logging
 

• For portions of your code where errors are most likely to occur, add try-except blocks paired with detailed logging. This means when an error happens, the logger will output all useful information to help troubleshoot the issue.
• Insert the following snippet around any critical or risky operation in your code:

  
  try:
      # Perform a risky operation
      result = some_risky_operation()
      logger.debug("Result from risky operation: %s", result)
  except Exception as error:
      logger.exception("Exception caught in risky operation:")
      

• This code logs not only the error message but also the traceback, which provides detailed context for troubleshooting.

 
Using Detailed Output for Troubleshooting
 

• Throughout your Lovable project, anywhere you perform an operation, add appropriate logger calls. Use logger.debug() for fine-grained informational events, logger.info() for standard operation messages, logger.warning() for potential issues, and logger.error() or logger.exception() when exceptions occur.
• This practice will help you see exactly where issues are arising and understand the sequence of application events, making it easier to diagnose and resolve problems.
• Remember: all changes are made directly in your code files (like logger\_config.py and your main file). There is no separate terminal-based installation; the code handles any dependency setup automatically.