from typing import List, Dict
import pandas as pd
import numpy as np
import joblib

scaler = joblib.load("scaler.joblib")
models = {
    "processing": joblib.load("svm_model_processing.joblib"),
    "perception": joblib.load("svm_model_perception.joblib"),
    "input": joblib.load("svm_model_input.joblib"),
    "understanding": joblib.load("svm_model_understanding.joblib"),
}

class Model:
    def __init__(self):
        self.scaler = scaler
        self.models = models

    def __call__(self, inputs: List[List[float]]) -> List[Dict[str, float]]:
        feature_names = [
            "course overview", "reading file", "abstract materiale", 
            "concrete material", "visual materials", "self-assessment", 
            "exercises submit", "quiz submitted", "playing", "paused", 
            "unstarted", "buffering"
        ]
        outputs = []
        for features in inputs:
            input_df = pd.DataFrame([features], columns=feature_names)
            scaled_input = self.scaler.transform(input_df)
            predictions = {}
            for target, model in self.models.items():
                predictions[target] = model.predict(scaled_input)[0]
            outputs.append(predictions)
        return outputs

model = Model()