-
Notifications
You must be signed in to change notification settings - Fork 1
Expand file tree
/
Copy pathResume_scanner.py
More file actions
31 lines (25 loc) · 1.11 KB
/
Resume_scanner.py
File metadata and controls
31 lines (25 loc) · 1.11 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
import streamlit as st
from Models import get_HF_embeddings, cosine, get_doc2vec_embeddings
def compare(resume_texts, JD_text, flag='HuggingFace-BERT'):
JD_embeddings = None
resume_embeddings = []
if flag == 'HuggingFace-BERT':
if JD_text is not None:
JD_embeddings = get_HF_embeddings(JD_text)
for resume_text in resume_texts:
resume_embeddings.append(get_HF_embeddings(resume_text))
if JD_embeddings is not None and resume_embeddings is not None:
cos_scores = cosine(resume_embeddings, JD_embeddings)
return cos_scores
# Add logic for other flags like 'Doc2Vec' if necessary
# if flag == 'Doc2Vec':
# if JD_text is not None:
# JD_embeddings = get_doc2vec_embeddings(JD_text)
# for resume_text in resume_texts:
# resume_embeddings.append(get_doc2vec_embeddings(resume_text))
# if JD_embeddings is not None and resume_embeddings is not None:
# cos_scores = cosine(resume_embeddings, JD_embeddings)
# return cos_scores
else:
# Handle other cases
pass