Update app.py

app.py

@@ -2,6 +2,7 @@ import streamlit as st
 from docx import Document
 import pdfplumber
 import re
+from collections import Counter
 
 # Function to extract text from PDF
 def extract_text_from_pdf(pdf_file):
@@ -56,43 +57,87 @@ def check_ats_friendly(text):
 
     return score, suggestions
 
+# Function to calculate job fit score
+def calculate_job_fit_score(resume_text, job_description):
+    resume_words = Counter(resume_text.lower().split())
+    job_words = Counter(job_description.lower().split())
+
+    # Find overlap between resume and job description keywords
+    common_words = resume_words & job_words
+    total_job_words = sum(job_words.values())
+
+    # Calculate match percentage
+    if total_job_words == 0:
+        match_percentage = 0
+    else:
+        match_percentage = sum(common_words.values()) / total_job_words * 100
+
+    suggestions = []
+    if match_percentage < 70:
+        suggestions.append(
+            "Include more relevant keywords from the job description in your resume."
+        )
+
+    return match_percentage, suggestions
+
 # Main App
 def main():
-    st.title("ATS Resume Checker")
-    st.write("Upload your resume to check if it is ATS-friendly and get suggestions for improvement.")
+    st.title("ATS Resume Checker with Job Description Matching")
+    st.write(
+        "Upload your resume to check its ATS-friendliness and compare it with a job description for keyword matching."
+    )
+
+    uploaded_resume = st.file_uploader(
+        "Upload your Resume (PDF or Word):", type=["pdf", "docx"]
+    )
+    job_description = st.text_area("Paste the Job Description:")
 
-    uploaded_file = st.file_uploader("Upload your Resume (PDF or Word):", type=["pdf", "docx"])
-    if uploaded_file:
+    if uploaded_resume:
         # Extract text based on file type
-        if uploaded_file.name.endswith(".pdf"):
-            resume_text = extract_text_from_pdf(uploaded_file)
-        elif uploaded_file.name.endswith(".docx"):
-            resume_text = extract_text_from_docx(uploaded_file)
+        if uploaded_resume.name.endswith(".pdf"):
+            resume_text = extract_text_from_pdf(uploaded_resume)
+        elif uploaded_resume.name.endswith(".docx"):
+            resume_text = extract_text_from_docx(uploaded_resume)
         else:
             st.error("Unsupported file format. Please upload a PDF or Word document.")
             return
 
-        # Display extracted text (optional)
-        st.subheader("Extracted Text:")
-        st.text_area("Resume Content", value=resume_text, height=200)
-
         # Analyze ATS-friendliness
         st.subheader("ATS Analysis")
-        ats_score, suggestions = check_ats_friendly(resume_text)
-
+        ats_score, ats_suggestions = check_ats_friendly(resume_text)
         st.metric("ATS Score", f"{ats_score}/100")
         if ats_score >= 80:
             st.success("Your resume is ATS-friendly!")
         else:
             st.warning("Your resume needs improvement to be ATS-friendly.")
 
-        # Suggestions
-        st.subheader("Suggestions for Improvement")
-        if suggestions:
-            for idx, suggestion in enumerate(suggestions, 1):
+        # Display ATS suggestions
+        st.subheader("Suggestions for ATS Improvement")
+        if ats_suggestions:
+            for idx, suggestion in enumerate(ats_suggestions, 1):
                 st.write(f"{idx}. {suggestion}")
         else:
             st.write("No specific suggestions. Your resume looks great!")
 
+        # Analyze Job Fit
+        if job_description.strip():
+            st.subheader("Job Description Matching")
+            job_fit_score, job_fit_suggestions = calculate_job_fit_score(
+                resume_text, job_description
+            )
+            st.metric("Job Fit Score", f"{job_fit_score:.2f}%")
+            if job_fit_score >= 70:
+                st.success("Your resume matches well with the job description!")
+            else:
+                st.warning("Your resume could be tailored better to match the job description.")
+
+            # Display job fit suggestions
+            st.subheader("Suggestions for Job Matching Improvement")
+            if job_fit_suggestions:
+                for idx, suggestion in enumerate(job_fit_suggestions, 1):
+                    st.write(f"{idx}. {suggestion}")
+            else:
+                st.write("No specific suggestions. Great match!")
+
 if __name__ == "__main__":
     main()