import os

# --- Paths ---
MODEL_SAVE_DIR = "/tmp"  # Use writable directory

DATA_PATH = os.path.join(os.path.dirname(__file__), "data", "synthetic_transactions_samples_5000.csv")
MODEL_PATH = os.path.join(MODEL_SAVE_DIR, "logreg_model.pkl")
TFIDF_VECTORIZER_PATH = os.path.join(MODEL_SAVE_DIR, "tfidf_vectorizer.pkl")
LABEL_ENCODERS_PATH = os.path.join(MODEL_SAVE_DIR, "label_encoders.pkl")

# --- Columns ---
TEXT_COLUMN = "Sanction_Context"
LABEL_COLUMNS = [
    "Red_Flag_Reason", "Maker_Action", "Escalation_Level",
    "Risk_Category", "Risk_Drivers", "Investigation_Outcome"
]

# --- TF-IDF ---
TFIDF_MAX_FEATURES = 5000
NGRAM_RANGE = (1, 2)
USE_STOPWORDS = True

# --- Split ---
RANDOM_STATE = 42
TEST_SIZE = 0.2