import torch
from transformers import AutoModel, AutoTokenizer
from phase6.adjective_complete_model import VisualNarratorModel
import json

# Emotional scene classification dataset
emotional_scenes = [
    {"description": "car chase with explosions", "type": "action", "intensity": 0.9},
    {"description": "romantic sunset on beach", "type": "drama", "intensity": 0.7},
    {"description": "comedic slip on banana", "type": "comedy", "intensity": 0.6},
    {"description": "dark haunted house", "type": "horror", "intensity": 0.8},
    {"description": "nature documentary scene", "type": "documentary", "intensity": 0.4}
]

class EmotionalIntelligenceTrainer:
    def __init__(self):
        self.model = VisualNarratorModel.from_pretrained('phase6/adjective_complete_model')
        self.scene_types = ["action", "drama", "comedy", "horror", "documentary"]
    
    def train_emotional_classification(self):
        print("Starting emotional intelligence training...")
        # Extend current model with emotional tone detection
        # This will enhance our adjective generation with emotional context
        pass

if __name__ == "__main__":
    trainer = EmotionalIntelligenceTrainer()
    trainer.train_emotional_classification()