predict_success.py

# predict_success.py
import joblib
import numpy as np

model = joblib.load('model.pkl')

def predict_token_success(token_features):
    """
    token_features: dict with keys liquidity, volume, holder_growth, trading_velocity
    """
    features = np.array([
        token_features['liquidity'],
        token_features['volume'],
        token_features['holder_growth'],
        token_features['trading_velocity']
    ]).reshape(1, -1)
    probability = model.predict_proba(features)[0][1]  # Success class probability
    return probability