utils/model_inference.py

import tensorflow as tf
import joblib
import pandas as pd

def load_lstm_model(path="models/lstm_forex_model.h5"):
    return tf.keras.models.load_model(path)

def load_sac_model(path="models/reconstructed_sac_forex_trading_model.zip"):
    return joblib.load(path)

def generate_forex_signals(capital, risk_level):
    # Logic to combine LSTM and SAC predictions
    # Return currency pair, entry/exit times, ROI, signal strength
    return {
        "currency_pair": "EUR/USD",
        "entry_time": "10:15 AM",
        "exit_time": "2:45 PM",
        "roi": 15.6,
        "signal_strength": "High"
    }