Update app.py

app.py

@@ -1,41 +1,45 @@
 import streamlit as st
 from sentence_transformers import SentenceTransformer, util
+import re
 
-# Cache the model to load it only once
 @st.cache_resource
 def load_model():
     return SentenceTransformer('sentence-transformers/all-mpnet-base-v2')
 
 model = load_model()
 
-# App title
-st.title("Resume and Job Description Similarity Checker")
+def keyword_match(job_desc, resume):
+    job_keywords = set(re.findall(r'\b\w+\b', job_desc.lower()))
+    resume_keywords = set(re.findall(r'\b\w+\b', resume.lower()))
+    common_keywords = job_keywords.intersection(resume_keywords)
+    match_ratio = len(common_keywords) / len(job_keywords) * 100
+    return match_ratio
+
+st.title("Enhanced Resume and Job Description Similarity Checker")
 
-# Input text areas
 job_description = st.text_area("Paste the job description here:", height=200)
 resume_text = st.text_area("Paste your resume here:", height=200)
 
-# Button to compute similarity
 if st.button("Compare"):
     if job_description.strip() and resume_text.strip():
-        # Encode both the job description and resume
         job_description_embedding = model.encode(job_description)
         resume_embedding = model.encode(resume_text)
-
-        # Calculate cosine similarity
         similarity_score = util.cos_sim(job_description_embedding, resume_embedding).item() * 100
-
-        # Display the similarity score
-        st.write(f"**Similarity Score:** {similarity_score:.2f}%")
-
-        # Provide feedback based on similarity score
-        if similarity_score > 80:
-            st.success("Excellent match! Your resume closely aligns with the job description.")
-        elif similarity_score > 60:
-            st.info("Good match! Your resume has relevant information, but you might want to tailor it further.")
-        elif similarity_score > 40:
-            st.warning("Partial match. Your resume shows some alignment, but consider adding more relevant skills and experiences.")
+        keyword_score = keyword_match(job_description, resume_text)
+        
+        # Combine scores (weighted or simple average)
+        overall_score = (similarity_score * 0.7) + (keyword_score * 0.3)
+        
+        st.write(f"**Similarity Score:** {overall_score:.2f}%")
+        
+        # Adjusted feedback
+        if overall_score > 70:
+            st.success("Great match! Your resume aligns well with the job description.")
+        elif overall_score > 50:
+            st.info("Good match! Your resume has relevant information, but it could be tailored a bit more.")
+        elif overall_score > 30:
+            st.warning("Partial match. Your resume shows some alignment, but consider emphasizing relevant skills and experiences.")
         else:
-            st.error("Low match. Your resume might not align well with the job description. Consider revising it to better reflect the job requirements.")
+            st.error("Low match. Consider revising your resume to better reflect the job requirements.")
     else:
         st.error("Please paste both the job description and your resume to proceed.")