JSFiddle - React, Tailwind, and code Playground

by codemeasandwich

HTML

<style>
#chat-container {
  width: 300px;
  margin: auto;
  border: 1px solid #ccc;
  padding: 10px;
}

#chat-box {
  height: 200px;
  overflow-y: scroll;
  border: 1px solid #ccc;
  padding: 5px;
}

#user-input {
  width: 200px;
}

.user {
  text-align: right;
  color: blue;
}

.bot {
  text-align: left;
  color: green;
}

</style>

<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs"></script>
<script src="https://cdn.polyfill.io/v2/polyfill.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/[email protected]/webcomponents.min.js"></script>
<script src="https://unpkg.com/hyperhtml@latest/min.js"></script>
<script src="https://unpkg.com/hyper-element@latest/source/bundle.js"></script>
<h3>
   Bayesian Network-Based Form Completion Assistant Using TensorFlow.js
</h3>

<form-bot />


<script>


// Load TensorFlow.js model
let model;
(async function() {
  model = await tf.loadLayersModel('path/to/your/model.json');
})();

 function sendMessage() {
  const inputBox = document.getElementById('user-input');
  const userMessage = inputBox.value;
  inputBox.value = '';

  // Display user's message
  displayMessage(userMessage, 'user');

  // Preprocess the user message
  const processedInput = preprocessInput(userMessage);

  // Predict the response using the model
  return  model.predict(tf.tensor([processedInput]))
						   .dataSync()
               .then(response => {
  
    // Postprocess the model output to get the chat response
    const chatResponse = postprocessOutput(response);

    // Display the bot's response
    displayMessage(chatResponse, 'bot');
  
  })
}

function preprocessInput(input) {
  // Implement preprocessing logic (e.g., tokenization, padding)
  return input; // Placeholder
}

function postprocessOutput(output) {
  // Implement postprocessing logic (e.g., converting model output to text)
  return 'This is a response'; // Placeholder
}

function displayMessage(message, sender) {
  const chatBox =...