#!/usr/bin/env python3
"""
Mobile VLA 사용 예제
"""

import torch
from transformers import AutoTokenizer, AutoProcessor
from PIL import Image
import numpy as np

def load_mobile_vla_model(model_name="minuum/mobile-vla"):
    """Mobile VLA 모델 로드"""
    
    # 여기서 실제 모델 로딩 로직 구현
    print(f"Loading Mobile VLA model: {model_name}")
    
    # 실제 구현에서는 MobileVLATrainer를 사용
    # from robovlms.train.mobile_vla_trainer import MobileVLATrainer
    # model = MobileVLATrainer.from_pretrained(model_name)
    
    return None  # 플레이스홀더

def predict_action(model, image_path, task_description):
    """액션 예측"""
    
    # 이미지 로드
    image = Image.open(image_path).convert("RGB")
    
    # 전처리 (실제 구현에서는 mobile_vla_collate_fn 사용)
    # processed = preprocess_image(image)
    
    # 예측 (플레이스홀더)
    dummy_action = [0.5, 0.2, 0.1]  # [linear_x, linear_y, angular_z]
    
    return dummy_action

def main():
    """메인 실행 함수"""
    
    print("🚀 Mobile VLA 예제 실행")
    
    # 모델 로드
    model = load_mobile_vla_model()
    
    # 예제 예측
    task = "Navigate around obstacles to track the target cup"
    action = predict_action(model, "example_image.jpg", task)
    
    print(f"Task: {task}")
    print(f"Predicted Action: {action}")
    print(f"  - Linear X (forward/backward): {action[0]:.3f}")
    print(f"  - Linear Y (left/right): {action[1]:.3f}")
    print(f"  - Angular Z (rotation): {action[2]:.3f}")

if __name__ == "__main__":
    main()