Update app.py

app.py

@@ -40,96 +40,61 @@ with st.sidebar:
 ''')
 
 
+
 st.title("AI Resume Analysis based on Keywords App")
 st.divider()
 
-st.subheader("Job Description", divider="red")
-txt = st.text_area("Paste the job description and then press Ctrl + Enter", key="text 1")
-job = pd.Series(txt, name="Text")
+job = pd.Series(st.text_area("Paste the job description and then press Ctrl + Enter", key="job_desc"), name="Text")
 
-st.subheader("Applicant Resume 1", divider="green")
-if 'upload_count' not in st.session_state:
-    st.session_state['upload_count'] = 0
+if 'applicant_data' not in st.session_state:
+    st.session_state['applicant_data'] = {}
 
 max_attempts = 20
-if st.session_state['upload_count'] < max_attempts:
-    uploaded_files = st.file_uploader("Upload Applicant's 1 resume", type="pdf", key="candidate 1")
-    if uploaded_files:
-        st.session_state['upload_count'] += 1
-        
-        pdf_reader = PdfReader(uploaded_files)
-        text_data = ""
-        for page in pdf_reader.pages:
-            text_data += page.extract_text()
-            with st.expander("See Applicant'1 resume"):
-                st.write(text_data)
-            
-            data = pd.Series(text_data, name='Text')
-            frames = [job, data]
-            result = pd.concat(frames)
-            
-
-            vectorizer = TfidfVectorizer()
-            tfidf_matrix = vectorizer.fit_transform(result)
-            tfidf_df = pd.DataFrame(tfidf_matrix.toarray(), columns=vectorizer.get_feature_names_out())
-            cosine_sim_matrix = cosine_similarity(tfidf_matrix)
-            cosine_sim_df = pd.DataFrame(cosine_sim_matrix)
-
-            for i, similarity_score in enumerate(cosine_sim_matrix[0][1:]):
-                with st.popover("See result"):
-                    st.write(f"Similarity of job description with Applicant's 1 resume based on keywords: {similarity_score:.2f}")
-                    st.info(
-                    "A score closer to 1 (0.80, 0.90) means higher similarity between Applicant's 1 resume and job description. A score closer to 0 (0.20, 0.30) means lower similarity between Applicant's 1 resume and job description.")
-else:
-    st.warning(f"You have reached the maximum upload attempts ({max_attempts}).")
-    if 'upload_count' in st.session_state and st.session_state['upload_count'] > 0:
-        st.info(f"Files uploaded {st.session_state['upload_count']} time(s).")
 
+for i in range(1, 3):  # Looping for 2 applicants
+    st.subheader(f"Applicant Resume {i}", divider="green")
+    applicant_key = f"applicant_{i}"
+    upload_key = f"candidate_{i}"
 
+    if applicant_key not in st.session_state['applicant_data']:
+        st.session_state['applicant_data'][applicant_key] = {'upload_count': 0, 'uploaded_file': None, 'analysis_done': False}
 
+    if st.session_state['applicant_data'][applicant_key]['upload_count'] < max_attempts:
+        uploaded_file = st.file_uploader(f"Upload Applicant's {i} resume", type="pdf", key=upload_key)
 
-st.subheader("Job Description", divider="red")
-txt = st.text_area("Paste the job description and then press Ctrl + Enter", key="text 2")
-job = pd.Series(txt, name="Text")
+        if uploaded_file:
+            st.session_state['applicant_data'][applicant_key]['uploaded_file'] = uploaded_file
+            st.session_state['applicant_data'][applicant_key]['upload_count'] += 1
+            st.session_state['applicant_data'][applicant_key]['analysis_done'] = False # Reset analysis flag
 
-st.subheader("Applicant Resume 2", divider="green")
-if 'upload_count' not in st.session_state:
-    st.session_state['upload_count'] = 0
+        if st.session_state['applicant_data'][applicant_key]['uploaded_file'] and not st.session_state['applicant_data'][applicant_key]['analysis_done']:
+            pdf_reader = PdfReader(st.session_state['applicant_data'][applicant_key]['uploaded_file'])
+            text_data = ""
+            for page in pdf_reader.pages:
+                text_data += page.extract_text()
 
-max_attempts = 20
-if st.session_state['upload_count'] < max_attempts:
-    uploaded_files = st.file_uploader("Upload Applicant's 2 resume", type="pdf", key="candidate 2")
-    if uploaded_files:
-        st.session_state['upload_count'] += 1
-        
-        pdf_reader = PdfReader(uploaded_files)
-        text_data = ""
-        for page in pdf_reader.pages:
-            text_data += page.extract_text()
-            with st.expander("See Applicant'2 resume"):
+            with st.expander(f"See Applicant's {i} resume"):
                 st.write(text_data)
-            
+
             data = pd.Series(text_data, name='Text')
-            frames = [job, data]
-            result = pd.concat(frames)
-            
+            result = pd.concat([job, data])
 
             vectorizer = TfidfVectorizer()
             tfidf_matrix = vectorizer.fit_transform(result)
-            tfidf_df = pd.DataFrame(tfidf_matrix.toarray(), columns=vectorizer.get_feature_names_out())
             cosine_sim_matrix = cosine_similarity(tfidf_matrix)
-            cosine_sim_df = pd.DataFrame(cosine_sim_matrix)
 
-            for i, similarity_score in enumerate(cosine_sim_matrix[0][1:]):
+            st.subheader(f"Similarity Analysis for Applicant {i}")
+            for j, similarity_score in enumerate(cosine_sim_matrix[0][1:]):
                 with st.popover("See result"):
-                    st.write(f"Similarity of job description with Applicant's 2 resume based on keywords: {similarity_score:.2f}")
+                    st.write(f"Similarity based on keyword: {similarity_score:.2f}")
                     st.info(
-                    "A score closer to 1 (0.80, 0.90) means higher similarity between Applicant's 2 resume and job description. A score closer to 0 (0.20, 0.30) means lower similarity between Applicant's 2 resume and job description.")
-else:
-    st.warning(f"You have reached the maximum upload attempts ({max_attempts}).")
-    if 'upload_count' in st.session_state and st.session_state['upload_count'] > 0:
-        st.info(f"Files uploaded {st.session_state['upload_count']} time(s).")
+                        f"A score closer to 1 means higher similarity between Applicant's {i} resume and job description.")
+            st.session_state['applicant_data'][applicant_key]['analysis_done'] = True
 
+    else:
+        st.warning(f"Applicant {i} has reached the maximum upload attempts ({max_attempts}).")
+        if st.session_state['applicant_data'][applicant_key]['upload_count'] > 0:
+            st.info(f"Files uploaded for Applicant {i}: {st.session_state['applicant_data'][applicant_key]['upload_count']} time(s).")