| import numpy as np |
| import json |
| import os |
| import struct |
| from pathlib import Path |
|
|
| class ReverseAI: |
| def __init__(self, save_dir="ReverseModel"): |
| self.save_dir = Path(save_dir) |
| self.save_dir.mkdir(exist_ok=True) |
| |
| self.char_to_idx = {} |
| self.idx_to_char = {} |
| self.next_idx = 0 |
| |
| self._add_chars("abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ") |
| self._add_chars("0123456789") |
| self._add_chars(" .,!?-:;()[]{}'\"") |
| |
| self.load_model() |
| |
| def _add_chars(self, chars): |
| for c in chars: |
| if c not in self.char_to_idx: |
| self.char_to_idx[c] = self.next_idx |
| self.idx_to_char[self.next_idx] = c |
| self.next_idx += 1 |
| |
| def _ensure_char(self, c): |
| if c not in self.char_to_idx: |
| self.char_to_idx[c] = self.next_idx |
| self.idx_to_char[self.next_idx] = c |
| self.next_idx += 1 |
| |
| def encode(self, text): |
| for c in text: |
| self._ensure_char(c) |
| return np.array([self.char_to_idx[c] for c in text], dtype=np.int32) |
| |
| def decode(self, indices): |
| return ''.join(self.idx_to_char[int(i)] for i in indices) |
| |
| def reverse(self, text): |
| if not text: |
| return "" |
| indices = self.encode(text) |
| reversed_indices = indices[::-1] |
| result = self.decode(reversed_indices) |
| self.save_model() |
| return result |
| |
| def save_model(self): |
| vocab_file = self.save_dir / "vocab.json" |
| with open(vocab_file, 'w', encoding='utf-8') as f: |
| json.dump({ |
| 'char_to_idx': self.char_to_idx, |
| 'idx_to_char': {str(k): v for k, v in self.idx_to_char.items()}, |
| 'vocab_size': self.next_idx |
| }, f, ensure_ascii=False, indent=2) |
| |
| model_file = self.save_dir / "model.bin" |
| with open(model_file, 'wb') as f: |
| f.write(b'RVAI') |
| f.write(struct.pack('I', 1)) |
| f.write(struct.pack('I', self.next_idx)) |
| for idx in range(self.next_idx): |
| char = self.idx_to_char[idx] |
| encoded = char.encode('utf-8') |
| f.write(struct.pack('I', len(encoded))) |
| f.write(encoded) |
| |
| def load_model(self): |
| vocab_file = self.save_dir / "vocab.json" |
| if vocab_file.exists(): |
| try: |
| with open(vocab_file, 'r', encoding='utf-8') as f: |
| data = json.load(f) |
| self.char_to_idx = data['char_to_idx'] |
| self.idx_to_char = {int(k): v for k, v in data['idx_to_char'].items()} |
| self.next_idx = data['vocab_size'] |
| return True |
| except: |
| return False |
| return False |
|
|
| def main(): |
| ai = ReverseAI() |
| |
| print("="*50) |
| print("KrynexAI Reverse Model") |
| print("Type 'exit' to quit") |
| print("="*50) |
| |
| while True: |
| word = input("\n🗣 Enter word: ").strip() |
| |
| if word.lower() in ['exit', 'quit']: |
| print("👋 Goodbye!") |
| break |
| |
| if not word: |
| print("⚠️ Please enter something!") |
| continue |
| |
| result = ai.reverse(word) |
| print(f"🔄 Reversed: {result}") |
|
|
| if __name__ == "__main__": |
| main() |
