Update src/inference.py

src/inference.py

@@ -1,17 +1,18 @@
 import os
-from src.preprocessing import clean_text
-from src.features import create_features
-from src.model import load_model
-from src.entity_extraction import extract_entities
 import numpy as np
 import joblib
 import scipy.sparse
 from textblob import TextBlob
 
-# ✅ Correct path to model files
-BASE_PATH = os.path.join(os.path.dirname(__file__), 'models')
+from src.preprocessing import clean_text
+from src.features import create_features
+from src.model import load_model
+from src.entity_extraction import extract_entities
+
+# Set BASE_PATH to the absolute path of the models directory relative to this file
+BASE_PATH = os.path.join(os.path.dirname(__file__), '..', 'models')
 
-# ✅ Load models from correct location
+# Load models & tfidf vectorizer from models directory
 model_issue = load_model(os.path.join(BASE_PATH, 'model_issue_type.pkl'))
 model_urgency = load_model(os.path.join(BASE_PATH, 'model_urgency_level.pkl'))
 tfidf = joblib.load(os.path.join(BASE_PATH, 'tfidf.pkl'))
@@ -22,6 +23,7 @@ def predict_ticket(ticket_text):
     ticket_length = len(clean.split())
     sentiment = TextBlob(clean).sentiment.polarity
     
+    # Combine features: tfidf + ticket length + sentiment
     X_features = scipy.sparse.hstack([
         X_tfidf,
         np.array([[ticket_length]]),