Update app.py

app.py

@@ -104,82 +104,81 @@ for i in range(1, 51):  # Looping for 2 applicants
 
 st.divider()
 
-col1, col2 = st.columns(2)
-
-with col1:
-    st.subheader("Visualise Applicant's Profile", divider="blue")
-    if 'upload_count' not in st.session_state:
-        st.session_state['upload_count'] = 0
-        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()
+
+st.subheader("Visualise Applicant's Profile", divider="blue")
+if 'upload_count' not in st.session_state:
+    st.session_state['upload_count'] = 0
+    
+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()
             
-                data = pd.Series(text_data, name='Text')
-                frames = [job, data]
-                result = pd.concat(frames)
-                model = GLiNER.from_pretrained("urchade/gliner_base")
-                labels = ["person", "country", "organization", "role", "skills"]
-                entities = model.predict_entities(text_data, labels)
-                df = pd.DataFrame(entities)
-                fig = px.treemap(entities, path=[px.Constant("all"), 'text', 'label'],
+            data = pd.Series(text_data, name='Text')
+            frames = [job, data]
+            result = pd.concat(frames)
+            model = GLiNER.from_pretrained("urchade/gliner_base")
+            labels = ["person", "country", "organization", "role", "skills"]
+            entities = model.predict_entities(text_data, labels)
+            df = pd.DataFrame(entities)
+            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")
-    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).")
-
-
-
-with col2:
-    st.subheader("Visualise Similarity", divider="blue")
-    if 'upload_count' not in st.session_state:
-        st.session_state['upload_count'] = 0
-        max_attempts = 3
-    if st.session_state['upload_count'] < max_attempts:
-        uploaded_files = st.file_uploader("Upload Applicant's resume", type="pdf", key = "applicant 2")
-    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()
+            fig.update_layout(margin=dict(t=50, l=25, r=25, b=25))
+            st.plotly_chart(fig, key = "figure 1")
+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).")
+
+
+
+
+st.subheader("Visualise Similarity", divider="blue")
+if 'upload_count' not in st.session_state:
+    st.session_state['upload_count'] = 0
+max_attempts = 3
+if st.session_state['upload_count'] < max_attempts:
+    uploaded_files = st.file_uploader("Upload Applicant's resume", type="pdf", key = "applicant 2")
+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)
+            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)
+            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,
+            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")
+            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).")