Update app.py

app.py

@@ -84,6 +84,8 @@ if 'username' not in st.session_state:
     st.session_state.username = ''
 if 'current_page' not in st.session_state:
     st.session_state.current_page = 'login'
+if 'employee_submitted' not in st.session_state:
+    st.session_state.employee_submitted = False
 
 # Page styling
 st.markdown("""
@@ -223,9 +225,9 @@ def reset_password_page():
             elif not new_password or not re_password:
                 st.error("Enter all the credentials.")
             elif len(new_password) <= 3:
-                st.error("Password too short. Must be at least 4 characters.")
+                st.error("Password too short. Enter a longer password.")
             elif new_password != re_password:
-                st.error("Passwords do not match. Please re-enter.")
+                st.error("Passwords do not match! Please re-enter.")
             else:
                 reset_password(username, new_password)
                 st.success("Password has been reset successfully! Please login with your new password.")
@@ -245,48 +247,54 @@ def home_page():
     # Sidebar for inputting employee details
     st.sidebar.header("Enter Employee Details")
     employee_name = st.sidebar.text_input("Employee Name")
-    employee_id = st.sidebar.number_input("Employee ID", min_value=1, max_value=1000, value=1)
+    employee_id = st.sidebar.text_input("Employee ID")
     employee_age = st.sidebar.number_input("Employee Age", min_value=18, max_value=65, value=30)
     employee_join_date = st.sidebar.date_input("Joining Date", value=datetime.date(2020, 1, 1))
     employee_appraisal_date = st.sidebar.date_input("Last Appraisal Date", value=datetime.date(2023, 1, 1))
     
     if st.sidebar.button("Submit"):
+        st.session_state.employee_submitted = True
         st.sidebar.success(f"Employee {employee_name} (ID: {employee_id}, Age: {employee_age}) details submitted successfully!")
 
     # Main dashboard area
     st.title("Performance Prediction Dashboard")
     
-    col1, col2 = st.columns(2)
-    
-    with col1:
-        st.subheader("Employee Performance Score")
-        performance_score = np.random.randint(60, 100)
-        st.metric("Predicted Performance", f"{performance_score}%", "4%")
+    if st.session_state.employee_submitted:
+        tab1, tab2 = st.tabs(["Overview", "Performance Insights"])
         
-        st.subheader("Key Factors Influencing Performance")
-        factors = pd.DataFrame({
-            'Factor': ['Experience', 'Training', 'Projects', 'Teamwork'],
-            'Impact': [0.3, 0.25, 0.28, 0.17]
-        })
-        fig = px.bar(factors, x='Impact', y='Factor', orientation='h', color='Factor',
-                     color_discrete_sequence=px.colors.qualitative.Bold)
-        st.plotly_chart(fig)
-
-    with col2:
-        st.subheader("Performance Trend")
-        dates = pd.date_range(start="2023-01-01", end="2023-12-31", freq="M")
-        performance = np.random.randint(70, 100, size=len(dates))
-        trend_data = pd.DataFrame({"Date": dates, "Performance": performance})
-        fig = px.line(trend_data, x="Date", y="Performance", title='Performance Over Time',
-                      line_shape='spline', render_mode='svg', color_discrete_sequence=['#1E88E5'])
-        st.plotly_chart(fig)
-        
-    st.subheader("Performance Insights")
-    st.write(f"Based on the analysis for Employee ID {employee_id}:")
-    st.write(f"- Current performance is {'above' if performance_score > 80 else 'below'} average")
-    st.write(f"- Key area for improvement: {'Training' if performance_score < 80 else 'Project Management'}")
-    st.write(f"- Recommended action: {'Enroll in advanced skills program' if performance_score < 80 else 'Take on leadership role in upcoming project'}")
-
+        with tab1:
+            col1, col2 = st.columns(2)
+            
+            with col1:
+                st.subheader("Employee Performance Score")
+                performance_score = np.random.randint(60, 100)
+                st.metric("Predicted Performance", f"{performance_score}%", "4%")
+                
+                st.subheader("Key Factors Influencing Performance")
+                factors = pd.DataFrame({
+                    'Factor': ['Experience', 'Training', 'Projects', 'Teamwork'],
+                    'Impact': [0.3, 0.25, 0.28, 0.17]
+                })
+                fig = px.bar(factors, x='Impact', y='Factor', orientation='h', color='Factor',
+                             color_discrete_sequence=px.colors.qualitative.Bold)
+                st.plotly_chart(fig)
+
+            with col2:
+                st.subheader("Performance Trend")
+                dates = pd.date_range(start="2023-01-01", end="2023-12-31", freq="M")
+                performance = np.random.randint(70, 100, size=len(dates))
+                trend_data = pd.DataFrame({"Date": dates, "Performance": performance})
+                fig = px.line(trend_data, x="Date", y="Performance", title='Performance Over Time',
+                              line_shape='spline', render_mode='svg', color_discrete_sequence=['#1E88E5'])
+                st.plotly_chart(fig)
+                
+        with tab2:
+            st.subheader("Performance Insights")
+            st.write(f"Based on the analysis for Employee ID {employee_id}:")
+            st.write(f"- Current performance is {'above' if performance_score > 80 else 'below'} average")
+            st.write(f"- Key area for improvement: {'Training' if performance_score < 80 else 'Project Management'}")
+            st.write(f"- Recommended action: {'Enroll in advanced skills program' if performance_score < 80 else 'Take on leadership role in upcoming project'}")
+    
     if st.button("Logout"):
         st.session_state.login_successful = False
         st.session_state.username = ''
@@ -294,9 +302,6 @@ def home_page():
         st.experimental_rerun()
 
 # Main app logic
-if 'current_page' not in st.session_state:
-    st.session_state.current_page = 'login'
-
 if st.session_state.current_page == 'login':
     login()
 elif st.session_state.current_page == 'sign_up':