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Create model_inference.py
Browse files- utils/model_inference.py +20 -0
utils/model_inference.py
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import tensorflow as tf
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import joblib
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import pandas as pd
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def load_lstm_model(path="models/lstm_forex_model.h5"):
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return tf.keras.models.load_model(path)
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def load_sac_model(path="models/reconstructed_sac_forex_trading_model.zip"):
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return joblib.load(path)
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def generate_forex_signals(capital, risk_level):
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# Logic to combine LSTM and SAC predictions
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# Return currency pair, entry/exit times, ROI, signal strength
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return {
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"currency_pair": "EUR/USD",
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"entry_time": "10:15 AM",
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"exit_time": "2:45 PM",
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"roi": 15.6,
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"signal_strength": "High"
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}
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