Update ATS_score.py

ATS_score.py

@@ -1,17 +1,11 @@
-#find ats score 
-from sklearn.feature_extraction.text import TfidfVectorizer 
-from sklearn.metrics.pairwise import cosine_similarity 
-from sklearn.feature_extraction import _stop_words 
-from convert import ExtractPDFText
-
-def calculateATSscore(resume_data, job_description):
-    stopwords = list(_stop_words.ENGLISH_STOP_WORDS) 
-    vectorizer = TfidfVectorizer(stop_words=stopwords) 
-    vectors = vectorizer.fit_transform([job_description, resume_data])
-    similarity_value = cosine_similarity(vectors)
-    print(similarity_value)
-    # return similarity_value[0,1]
-    return similarity_value[0,1]
+from sentence_transformers import SentenceTransformer, util
+
+def calculateATSscore_with_bert(resume_data, job_description):
+    model = SentenceTransformer('paraphrase-MiniLM-L6-v2')  # Pre-trained BERT model
+    resume_embedding = model.encode(resume_data)
+    job_desc_embedding = model.encode(job_description)
+    similarity_value = util.cos_sim(resume_embedding, job_desc_embedding)
+    return similarity_value.item()