Update app.py

app.py

@@ -103,25 +103,23 @@ for i in range(1, 51):  # Looping for 2 applicants
 
 
 st.divider()
-
-
 st.subheader("Visualise", divider="blue")
+
 if 'upload_count' not in st.session_state:
     st.session_state['upload_count'] = 0
-    
-max_attempts = 3
+    max_attempts = 3
+
 if st.session_state['upload_count'] < max_attempts:
-    uploaded_files = st.file_uploader("Upload Applicant's resume", type="pdf", key = "applicant 1")
-if uploaded_files:
-    st.session_state['upload_count'] += 1
-
-    with st.spinner("Wait for it...", show_time=True):
-        time.sleep(2)
-        pdf_reader = PdfReader(uploaded_files)
-        text_data = ""
-        for page in pdf_reader.pages:
-            text_data += page.extract_text()
-            
+    uploaded_files = st.file_uploader("Upload Applicant's resume", type="pdf", key="applicant 1")
+    if uploaded_files:
+        st.session_state['upload_count'] += 1
+        with st.spinner("Wait for it...", show_time=True):
+            time.sleep(2)
+            pdf_reader = PdfReader(uploaded_files)
+            text_data = ""
+            for page in pdf_reader.pages:
+                text_data += page.extract_text()
+
             data = pd.Series(text_data, name='Text')
             frames = [job, data]
             result = pd.concat(frames)
@@ -132,25 +130,22 @@ if uploaded_files:
             fig = px.treemap(entities, path=[px.Constant("all"), 'text', 'label'],
                              values='score', color='label')
             fig.update_layout(margin=dict(t=50, l=25, r=25, b=25))
-            st.plotly_chart(fig, key = "figure 1")
-
+            st.plotly_chart(fig, key="figure 1")
             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)
 
-            
             fig = px.imshow(cosine_sim_df, text_auto=True,
                             labels=dict(x="Keyword similarity", y="Resumes", color="Productivity"),
                             x=['Resume', 'Jon Description'],
                             y=['Resume', 'Job Description'])
             st.plotly_chart(fig, key="figure 2")
- 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).")
-
+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).")