import os

# Model paths
BAIL_BERT_MODEL_PATH = "./models/bert/saved_bail_bert_model"
FAIRNESS_BERT_MODEL_PATH = "./models/bert/saved_fairness_bert_model"

BAIL_LOGREG_MODEL_PATH = "./models/logreg/bail_outcome/logreg_bail_outcome_model.joblib"
BAIL_TFIDF_PATH = "./models/logreg/bail_outcome/tfidf_vectorizer.joblib"
BAIL_SCALER_PATH = "./models/logreg/bail_outcome/feature_scaler.joblib"

FAIRNESS_LOGREG_MODEL_PATH = "./models/logreg/fairness/fairness_logreg_best_model.joblib"
FAIRNESS_TFIDF_PATH = "./models/logreg/fairness/fairness_tfidf_vectorizer.joblib"
FAIRNESS_SCALER_PATH = "./models/logreg/fairness/fairness_feature_scaler.joblib"
FAIRNESS_ENCODERS_PATH = "./models/logreg/fairness/fairness_label_encoders.joblib"

FAIRNESS_XGB_MODEL_PATH = "./models/xgboost/fairness/fairness_xgb_best_model.joblib"
FAIRNESS_XGB_TFIDF_PATH = "./models/xgboost/fairness/fairness_xgb_tfidf_vectorizer.joblib"
FAIRNESS_XGB_SCALER_PATH = "./models/xgboost/fairness/fairness_xgb_feature_scaler.joblib"
FAIRNESS_XGB_ENCODERS_PATH = "./models/xgboost/fairness/fairness_xgb_label_encoders.joblib"

# Dataset path
DATASET_PATH = "./indian_bail_judgments.json"

# App configuration
MAX_TEXT_LENGTH = 512
DEFAULT_CONFIDENCE_THRESHOLD = 0.5

# Model labels
BAIL_OUTCOME_LABELS = ["Rejected", "Granted"]
FAIRNESS_LABELS = ["Fair", "Potentially Biased"]

# Feature options
CRIME_TYPES = [
    "Attempt to Murder", 
    "Cyber Crime", 
    "Domestic Violence", 
    "Dowry Harassment", 
    "Extortion", 
    "Fraud or Cheating", 
    "Kidnapping", 
    "Murder", 
    "Narcotics", 
    "Others", 
    "Sexual Offense", 
    "Theft or Robbery"
]
BAIL_TYPES = ["Regular", "Anticipatory", "Interim", "Transit", "Default"]
GENDERS = ["Male", "Female", "Unknown", "Transgender"]
REGIONS = ["Unknown", "North India", "South India", "East India", "West India", "Central India", "Northeast India"]