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File size: 1,129 Bytes
cb7157e 6d6dbdb ce27aee 6d6dbdb cb7157e b454d73 ce27aee b454d73 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | from dotenv import load_dotenv
import os
from pathlib import Path
load_dotenv()
PROJECT_NAME = os.getenv("PROJECT_NAME", "Sentiment Sleuth")
PROJECT_DESCRIPTION = os.getenv(
"PROJECT_DESCRIPTION", "ML-Powered Amazon Review Sentiment Analysis"
)
# Hugging Face / asset settings
HF_ASSETS_REPO = os.getenv("HF_ASSETS_REPO", "")
HF_ASSETS_REPO_TYPE = os.getenv("HF_ASSETS_REPO_TYPE", "")
# Default asset paths (kept here so settings is authoritative)
ASSET_PATHS = [
'data/vectorizers/tfidf_vectorizer.joblib',
'data/models/05_logistic_regression_classifier.joblib',
'data/models/06_naive_bayes_classifier.joblib',
'data/models/07_ft_svm_classifier.joblib',
'data/models/07_linear_svm_classifier.joblib',
'data/models/08_knn_classifier.joblib',
'data/models/09_decision_tree_classifier.joblib',
'data/models/10_random_forest_classifier.joblib',
'data/models/11_stochastic_gradient_descent_classifier.joblib',
'data/models/12_xgboost_classifier.joblib',
'data/models/13_lightgbm_classifier.joblib',
]
# Cache directory for downloaded assets
ASSET_CACHE_DIR = Path(os.getenv("ASSET_CACHE_DIR", "data/remote_cache"))
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