fixed spacy model download

requirements.txt

@@ -5,5 +5,5 @@ supabase
 PyMuPDF
 pytest
 sentence-transformers
-spacy && python -m spacy download en_core_web_sm
+spacy
 fuzzywuzzy

utils.py

@@ -14,11 +14,16 @@ from collections import Counter
 from sklearn.feature_extraction.text import TfidfVectorizer
 import streamlit as st
 from fuzzywuzzy import fuzz
+import subprocess
 
 # These functions will be called in the app.py file
 
 # Load spaCy NLP model
-nlp = spacy.load("en_core_web_sm")
+try:
+    nlp = spacy.load("en_core_web_sm")
+except OSError:
+    subprocess.run(["python", "-m", "spacy", "download", "en_core_web_sm"])
+    nlp = spacy.load("en_core_web_sm")
 
 def evaluate_resumes(uploaded_files, job_description, min_keyword_match=2):
     """Evaluates uploaded resumes, filters by keywords and score, and returns shortlisted candidates."""