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```python
# AI Dev Tool: Energy Price Forecast API Integration Wrapper
# Description: A production-ready API integration wrapper for forecasting energy prices
#              using a combination of machine learning models and real-time data from
#              the U.S. Strategic Petroleum Reserve.

import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestRegressor
from sklearn.metrics import mean_squared_error
import requests
import json
from typing import Dict, List

class EnergyPriceForecastAPI:
    """
    A class used to forecast energy prices using a combination of machine learning models
    and real-time data from the U.S. Strategic Petroleum Reserve.

Attributes:
    ----------
    api_key : str
        The API key for accessing the U.S. Strategic Petroleum Reserve data.
    model : RandomForestRegressor
        The machine learning model used for forecasting energy prices.

Methods:
    -------
    get_data()
        Retrieves the latest data from the U.S. Strategic Petroleum Reserve.
    train_model()
        Trains the machine learning model using the retrieved data.
    forecast_price()
        Forecasts the energy price using the trained model.
    """

def __init__(self, api_key: str):
        """
        Initializes the EnergyPriceForecastAPI class

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