inference.py

from sklearn.model_selection import train_test_split
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.svm import LinearSVC
from sklearn.preprocessing import LabelEncoder
from sklearn.metrics import classification_report
import joblib

loaded_model = joblib.load("svm.joblib")
loaded_vectorizer = joblib.load("vectorizer.joblib")
loaded_label_encoder = joblib.load("label_encoder.joblib")

# Step 8: Predict for a new input
new_input = ["User Eve uploaded a malicious script"]  # You can replace this with any input
new_input_tfidf = loaded_vectorizer.transform(new_input)
prediction = loaded_model.predict(new_input_tfidf)

# Decode label
predicted_severity = loaded_label_encoder.inverse_transform(prediction)
print(f"Predicted severity: {predicted_severity[0]}")