| import streamlit as st |
| import joblib |
| import os |
|
|
|
|
| @st.cache_resource |
| def load_artifacts(models_path, preprocessor_path): |
| """Загрузка препроцессоров и моделей""" |
| preprocessor = joblib.load(os.path.join(preprocessor_path, 'preprocessor_150.pkl')) |
| scaler = joblib.load(os.path.join(preprocessor_path, 'scaler_150.pkl')) |
|
|
| models = {} |
| model_files = { |
| 'Logistic Regression': 'logreg_150_model.pkl', |
| 'XGBoost': 'xgb_150_model.pkl', |
| 'LightGBM': 'lgbm_150_model.pkl', |
| 'CatBoost': 'catboost_150_model.pkl', |
| 'Random Forest': 'rfc_150_model.pkl' |
| } |
|
|
| for name, filename in model_files.items(): |
| path = os.path.join(models_path, filename) |
| if os.path.exists(path): |
| models[name] = joblib.load(path) |
|
|
| return preprocessor, scaler, models |
