Understanding the Problem
 

• This guide explains how to fix skipped features that occur when a prompt is ambiguous in version 0 of your project. The goal is to detect ambiguous words or phrases in user input and either request further clarification or use a default safe path.
• The fix involves modifying your prompt processing code so that it checks for ambiguous keywords before executing features. If ambiguity is detected, the feature is skipped and an informative response is returned.

 
Creating a Prompt Ambiguity Handler
 

• Create a new file in your project folder named promptHandler.js. In this file, you will write functions to handle ambiguous prompts.
• Insert the following code into promptHandler.js. This code defines a function that looks for ambiguous words in the prompt:

function resolveAmbiguity(prompt) {
    // List of ambiguous keywords to check in the prompt
    const ambiguousKeywords = ["maybe", "possibly", "unclear", "ambiguous"];
    const lowerPrompt = prompt.toLowerCase();
    
    // Loop through keywords and check if any exist in the prompt
    for (let keyword of ambiguousKeywords) {
        if (lowerPrompt.includes(keyword)) {
            // Log a warning and indicate ambiguity
            console.warn("Ambiguous prompt detected. Requesting clarification...");
            return null;
        }
    }
    // If no ambiguity is found, return the original prompt
    return prompt;
}

• This function will later be called to either proceed with the feature or return a message asking for more clarification.

 
Updating the Feature Processing Function
 

• Open your main JavaScript file where prompt-based features are executed. This file might be named app.js or similar.
• Modify your feature processing function to use the new ambiguity handler. Locate the part of your code that deals with the incoming prompt and insert the following code snippet:

function processFeature(prompt) {
    // Use the ambiguity resolver to check the prompt
    const resolvedPrompt = resolveAmbiguity(prompt);
    
    // If the prompt is ambiguous, skip feature execution
    if (resolvedPrompt === null) {
        // Return a clear message for the user or fallback handling
        return "Feature skipped due to ambiguous prompt. Please provide more details.";
    }
    
    // Proceed with the normal feature execution using the unambiguous prompt
    return executeFeature(resolvedPrompt);
}

• Make sure that your function executeFeature (or similar) exists and contains the logic to run the feature when the prompt is clear.

 
Integrating the New Handler into Your Application
 

• Ensure that your main HTML file (or entry point) includes the newly created promptHandler.js so that its functions are available. Insert the following <script> tag in your HTML file, typically before your main application script:

<script src="promptHandler.js"></script>
<script src="app.js"></script>

• If your application does not support terminal commands (as is the case with Lovable), no separate dependency installation is required. The code snippets provided here do not use external modules; they rely solely on built-in JavaScript functionality.

 
Wrapping Up and Testing the Changes
 

• After making these changes, test your application by using prompts that contain ambiguous words like "maybe" or "possibly" to see if the feature is skipped with the proper message.
• Test with clear prompts to ensure that the application processes them correctly and proceeds with feature execution.
• The clear separation of ambiguity resolution in promptHandler.js and the integration within your main processing function makes it easier to update or expand this functionality in the future.

 
Understanding Feature Skipping in v0 Generation
 

• Feature skipping happens when parts of your code activated by certain conditions are ignored. This can make your v0 generation incomplete. The primary goal is to ensure that every intended feature-specific section is reached and executed. To do this, you need checks that confirm whether a feature is enabled before its execution.
• Best practices include clear configuration settings, organized code separation, and robust testing to ensure no feature is accidentally bypassed.

 
Organizing Your Code for Clarity
 

• Place your feature-related functions and checks in a separate file. For example, create a file named feature\_controller.py. This file will manage feature flags and the logic needed to determine when a feature should run.
• Insert the following snippet in feature\_controller.py to set up a basic feature flag system:

  
  # Define your feature flags. Set them to True to enable a feature or False to disable.
  FEATURE\_FLAGS = {
      "new\_ui": True,
      "advanced\_search": False,
      "beta\_notifications": True
  }
  
  def is_feature_enabled(feature_name):
      """
      Check if a particular feature is enabled.
      """
      return FEATURE_FLAGS.get(feature_name, False)
      

  
  


• This approach centralizes your feature control, making it easier to verify if each feature should run in your generation process.

 
Integrating Feature Checks in Your Main Code
 

• Now modify your main generation code to include checks that prevent feature skipping. Suppose your main file is named main.py. You need to import and use the feature controller.
• Add this snippet at the beginning of main.py:

  
  # Import the feature controller functions
  from feature_controller import is_feature\_enabled
      

• Wrap each feature block in an if-statement that uses is_feature_enabled to determine if that block should be executed:

  
  # Example: Running new UI code
  if is_feature_enabled("new\_ui"):
      # Place the new UI generation code here
      def generate_new_ui():
          print("Generating the new UI feature...")
      generate_new_ui()
  else:
      # A fallback to the current UI or a warning message
      print("New UI feature is skipped as it is disabled.")
      

• This ensures each feature is explicitly checked before running, preventing any accidental omission.

 
Establishing Automated Dependency Installation Without Terminal Access
 

• Since Lovable does not allow terminal installations, include installation instructions directly in your code. Suppose you require an external library like requests for some feature callouts. Add a snippet at the top of your main.py that checks for the module and provides guidance if it's missing:

  
  try:
      import requests
  except ImportError:
      print("The 'requests' library is missing. Please add the following code snippet at the top of your project to simulate dependency installation:")
      print("import os; os.system('pip install requests')")
      # Note: In Lovable, you might simulate pip installations differently.
      

• This snippet helps ensure that anyone reading or using the code knows exactly what dependency is missing and how to add it through code.

 
Implementing Thorough Testing for Feature Integrity
 

• It is important to test each feature separately. Create a file test\_features.py where you write simple tests to confirm whether a feature is executed. For non-tech users, these tests act as a checklist.
• Include the following snippet in test\_features.py to test a feature:

  
  from feature_controller import is_feature\_enabled
  
  def test_new_ui_feature():
      if is_feature_enabled("new_ui"):
          print("Test Passed: New UI is enabled.")
      else:
          print("Test Skipped: New UI is disabled as expected.")
  Run tests
  if name == "main":
      test_new_ui_feature()
      

  
  


• This way, every time you run your code, you have a built-in method to verify which features are active and ensure that none are skipped accidentally.

 
Maintaining Clear Documentation and Comments
 

• Document every feature flag and the corresponding code block. Add friendly comments in your code explaining what each feature does and when it should be activated.
• For example, add comments like the following before your feature block in main.py:

  
  # Feature: Advanced Search
  # This block handles the advanced search functionality when it is enabled.
  if is_feature_enabled("advanced\_search"):
      def run_advanced_search():
          print("Executing advanced search...")
      run_advanced_search()
  else:
      print("Advanced search feature is not active.")
      

• Clear documentation helps anyone reviewing your code to understand why certain features might be skipped if they are turned off deliberately.

 
Final Remarks on Best Practices
 

• Always keep your feature controls centralized and easy to update. This not only prevents unintentional feature skipping but also simplifies future modifications.
• Regularly run your tests in test\_features.py to confirm that all sections of your code behave as expected.
• Make sure every code block related to a feature has an exit path if the feature is turned off, preventing any unexpected behavior.