Create tbbot.js

tbbot.js

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+const io = require('socket.io-client');
+const tf = require('@tensorflow/tfjs-node');
+
+// Connect to the existing Socket.IO server
+const socket = io('https://box.km.mk/socket.io'); // Replace with your server URL
+socket.emit("user joined", "AITrainer", "green")
+// Simple in-memory dataset for training
+let trainingData = [];
+let labels = [];
+
+// Listen for incoming messages
+socket.on('data', (data) => {
+    console.log('Received message:', data);
+    processMessage(data); // Process the incoming message
+});
+
+// Function to process incoming messages and prepare them for training
+function processMessage(message) {
+    // Here we assume the message is an object with text and label properties
+    if (message.text && message.label) {
+        trainingData.push(message.text);
+        labels.push(message.label);
+        console.log('Added to training data:', message.text);
+
+        // Optionally train the AI every N messages or on demand
+        if (trainingData.length >= 10) { // Example: train after 10 messages
+            trainAI();
+        }
+    }
+}
+
+// Function to train the AI model
+async function trainAI() {
+    console.log('Training AI with collected data...');
+
+    // Convert texts to tensors (this is a placeholder; implement your own preprocessing)
+    const xs = tf.tensor2d(trainingData.map(text => text.split('').map(char => char.charCodeAt(0))), [trainingData.length, trainingData[0].length]);
+    const ys = tf.tensor2d(labels.map(label => label === 'positive' ? [1] : [0]), [labels.length, 1]); // Binary classification example
+
+    // Define a simple model (this is just an example)
+    const model = tf.sequential();
+    model.add(tf.layers.dense({ units: 5, activation: 'relu', inputShape: [trainingData[0].length] }));
+    model.add(tf.layers.dense({ units: 1, activation: 'sigmoid' }));
+
+    model.compile({ optimizer: 'adam', loss: 'binaryCrossentropy', metrics: ['accuracy'] });
+
+    // Train the model
+    await model.fit(xs, ys, { epochs: 10 });
+
+    console.log('Training complete.');
+
+    // Clear training data after training (optional)
+    trainingData = [];
+    labels = [];
+}
+
+// Handle errors
+socket.on('connect_error', (err) => {
+    console.error('Connection error:', err);
+});
+
+// Keep the process alive indefinitely
+process.on('SIGINT', () => {
+    console.log("Shutting down gracefully...");
+    socket.disconnect();
+    process.exit();
+});
+
+console.log("Listening for messages...");
+
+// This will keep the script running indefinitely.
+setInterval(() => {}, 1000); // Keeps the event loop active