AI-powered Virtual Assistant with PHP (Simplified Approach)

This guide outlines a basic structure for a Virtual Assistant (VA) using PHP. Due to the complexities of AI and Machine Learning (ML), we’ll focus on a limited set of functionalities and pre-defined responses.

Key Functionalities:

• Natural Language Processing (NLP): Simulate basic understanding of user questions using keyword matching.
• Task Management: Allow users to add, list, and mark tasks as complete.
• Meeting Scheduling (Optional): (Not implemented here) Integrate with a calendar API for scheduling meetings.

Disclaimer: This is a simplified example and doesn’t cover functionalities like complex NLP techniques, intent recognition, dialogue management, or real-time interactions.

Requirements:

• PHP 7.2 or higher

Steps:

1. Code Implementation:

<?php

// Sample task list (replace with database or session storage)
$tasks = [
  'Buy groceries' => false,
  'Write a report' => true,
];

// Function to process user query
function processQuery($query, &$tasks) {
  $response = "I can't assist you with that yet, but I'm still learning.";
  
  // Task Management
  if (strpos(strtolower($query), 'add task') !== false) {
    // Extract task description (replace with more robust parsing)
    $taskDescription = explode('add task:', strtolower($query))[1];
    $tasks[$taskDescription] = false;
    $response = "Task '$taskDescription' added to your list.";
  } elseif (strpos(strtolower($query), 'list tasks') !== false) {
    $response = "Your Tasks:\n";
    foreach ($tasks as $task => $completed) {
      $status = $completed ? 'Completed' : 'Pending';
      $response .= "- $task ($status)\n";
    }
  } elseif (strpos(strtolower($query), 'complete task') !== false) {
    // Extract task description (replace with more robust parsing)
    $taskDescription = explode('complete task:', strtolower($query))[1];
    if (array_key_exists($taskDescription, $tasks)) {
      $tasks[$taskDescription] = true;
      $response = "Task '$taskDescription' marked as completed.";
    } else {
      $response = "Task '$taskDescription' not found in your list.";
    }
  }
  
  return $response;
}

// Get user query (replace with actual user input mechanism)
$userInput = "list tasks"; // Sample query

// Process query and display response
$assistantResponse = processQuery($userInput, $tasks);
echo $assistantResponse;

Code Explanation:

1. Sample Task List:

• The code defines a sample $tasks array to represent a user’s task list.
  • Each element in the array is a key-value pair.
  • The key is the task description (e.g., “Buy groceries”).
  • The value is a boolean (false or true) indicating whether the task is completed or not.
• In a real application, you’d likely replace this with a database or session storage to manage tasks persistently across user interactions.

2. Processing User Queries:

• The processQuery function is the core of the virtual assistant’s interaction with the user.
  • It takes two arguments:
    • $query: This is a string representing the user’s question or command.
    • &$tasks: This is a reference to the $tasks array, allowing the function to modify the task list.
• The function initializes a default response message ("I can't assist you with that yet, but I'm still learning."). This will be used if the user’s query doesn’t match any predefined functionalities.

3. Understanding User Intent (Basic Approach):

• The code utilizes the strpos function for case-insensitive keyword matching within the user’s query converted to lowercase (strtolower($query)).
  • This is a simplified approach to understanding user intent. Real-world virtual assistants employ Natural Language Processing (NLP) techniques to perform more comprehensive intent recognition and extract meaning from the user’s query.

4. Task Management:

• The code checks for specific keywords within the user query:
  • “add task” – If the query contains “add task”, the function assumes the user wants to add a new task to their list.
    • It extracts the task description from the remaining part of the query (replace with more robust parsing in a real application).
    • This parsing is simplified here for demonstration purposes (consider using regular expressions or NLP libraries for more accurate extraction).
    • The extracted task description is then added as a new key-value pair to the $tasks array with a value of false (indicating not completed).
    • The response is updated to inform the user that the task has been added.
  • “list tasks” – If the query contains “list tasks”, the function iterates through the $tasks array.
    • For each task, it retrieves the description and the completion status.
    • It builds a formatted response string listing all tasks and their statuses.
  • “complete task” – If the query contains “complete task”, the function assumes the user wants to mark a task as completed.
    • Similar to adding tasks, it extracts the task description from the remaining part of the query.
    • It checks if the task description exists as a key in the $tasks array.
    • If the task is found, its value (completion status) is changed to true (completed).
    • The response is updated based on whether the task was found or not.

5. Returning Response:

• After processing the user query based on the identified keywords, the function returns the final response message ($assistantResponse).

6. Sample Usage:

• The script assigns a sample query (“list tasks”) to the $userInput variable (replace this with an actual mechanism to capture user input).
• It calls the processQuery function with the $userInput and a reference to the $tasks array.
• The returned response ($assistantResponse) is then displayed, showing the list of tasks and their completion status.

Sample Output:

Your Tasks:
- Buy groceries (Pending)
- Write a report (Completed)

Limitations:

• This is a basic example using simple keyword matching. Real-world virtual assistants use NLP techniques to understand user intent and context.
• The task management functionality is limited. Consider integrating with a task management application for more features.
• Meeting scheduling functionality is not implemented here. Explore calendar APIs for real-time scheduling.