Create aiModel.js

Author: KOSASIH

src/space/aiModel.js

@@ -0,0 +1,64 @@
+// src/space/aiModel.js - Ultra Advanced AI Model Module
+
+const tf = require('@tensorflow/tfjs'); // Import TensorFlow.js
+const { logError, logInfo } = require('./logger'); // Import logger for error handling
+
+class AIModel {
+    constructor(modelPath) {
+        this.modelPath = modelPath; // Path to the model
+        this.model = null; // Placeholder for the loaded model
+    }
+
+    async initialize() {
+        try {
+            logInfo('Loading AI model...');
+            this.model = await tf.loadLayersModel(this.modelPath); // Load the model asynchronously
+            logInfo('AI model loaded successfully.');
+        } catch (error) {
+            logError('Error loading AI model:', error);
+            throw new Error('Failed to initialize AI model');
+        }
+    }
+
+    preprocessData(data) {
+        // Implement data preprocessing logic here
+        // For example, normalization, reshaping, etc.
+        logInfo('Preprocessing data...');
+        const tensorData = tf.tensor(data); // Convert data to tensor
+        return tensorData;
+    }
+
+    async analyze(data) {
+        if (!this.model) {
+            throw new Error('AI model is not initialized');
+        }
+
+        try {
+            const processedData = this.preprocessData(data); // Preprocess the input data
+            logInfo('Making predictions...');
+            const predictions = this.model.predict(processedData); // Make predictions
+            const result = await predictions.array(); // Convert predictions to array
+            logInfo('Predictions made successfully.');
+            return result;
+        } catch (error) {
+            logError('Error during analysis:', error);
+            throw new Error('Failed to analyze data');
+        }
+    }
+}
+
+// Example usage
+(async () => {
+    const aiModel = new AIModel('path/to/model.json'); // Specify the model path
+
+    try {
+        await aiModel.initialize(); // Initialize the model
+        const inputData = [[1, 2, 3], [4, 5, 6]]; // Example input data
+        const predictions = await aiModel.analyze(inputData); // Analyze the data
+        console.log('Predictions:', predictions);
+    } catch (error) {
+        console.error('Error:', error.message);
+    }
+})();
+
+module.exports = AIModel;