Update app.py

app.py

@@ -264,45 +264,48 @@ elif page == "Skills Analysis":
         skills = st.multiselect("Select skills to analyze:", 
                                 ["Data Analysis", "Web Development", "Digital Marketing", "Cybersecurity", "Cloud Computing", "AI/Machine Learning", "Mobile App Development", "UI/UX Design"])
         regions = st.multiselect("Select regions:", 
-                                 ["Nairobi", "Mombasa", "Kisumu", "Nakuru", "Eldoret", "Thika", "Malindi", "Kitale", "Kisii", "Nyamira", "Western"])
+                                 ["Nairobi", "Mombasa", "Kisumu", "Nakuru", "Eldoret", "Thika", "Malindi", "Kitale"])
         time_period = st.selectbox("Select time period:", ["Last 3 months", "Last 6 months", "Last year"])
     with col2:
         st_lottie(lottie_skills, height=200, key="skills")
     
     if st.button("Analyze Skills Demand"):
         with st.spinner("Analyzing skills demand..."):
-            # Simulated data generation
-            demand_data = generate_simulated_data(skills)
+            # Simulated data generation (optimized)
+            demand_data = {skill: [random.randint(1, 100) for _ in regions] for skill in skills}
             
-            # Plotting
-            fig = go.Figure()
-            for skill in skills:
-                fig.add_trace(go.Bar(x=regions, y=demand_data[skill], name=skill))
-            fig.update_layout(title="Digital Skills Demand by Region", barmode='group')
-            st.plotly_chart(fig)
+            # Plotting (single chart instead of multiple)
+            df = pd.DataFrame(demand_data, index=regions)
+            fig = px.bar(df, barmode='group', title="Digital Skills Demand by Region")
+            st.plotly_chart(fig, use_container_width=True)
             
-            # AI Insights
-            ai_prompt = f"Analyze the demand for {', '.join(skills)} in {', '.join(regions)} over the {time_period}. Provide insights on trends, gaps, and recommendations for skill development."
-            ai_insights = call_ai_model(ai_prompt)
-            st.markdown("### AI Insights")
-            st.write(ai_insights)
+            # AI Insights (with timeout)
+            ai_prompt = f"Briefly and shortly analyze the demand for {', '.join(skills)} in {', '.join(regions)} over the {time_period}. Provide key insights on trends and gaps."
+            try:
+                with st.spinner("Generating AI insights..."):
+                    ai_insights = call_ai_model(ai_prompt)
+                st.markdown("### AI Insights")
+                st.write(ai_insights)
+            except Exception as e:
+                st.error(f"Failed to generate AI insights: {str(e)}")
             
-            # Word Cloud
-            word_cloud_text = " ".join(skills + regions + ai_insights.split())
-            st.markdown("### Skills Demand Word Cloud")
-            st.pyplot(create_word_cloud(word_cloud_text))
+            # Word Cloud (optional)
+            if st.checkbox("Generate Word Cloud"):
+                word_cloud_text = " ".join(skills + regions + ai_insights.split())
+                st.markdown("### Skills Demand Word Cloud")
+                st.pyplot(create_word_cloud(word_cloud_text))
             
-            # Skills growth projection
+            # Skills growth projection (simplified)
             st.markdown("### Skills Growth Projection")
-            growth_data = {skill: [random.uniform(0, 15) for _ in range(5)] for skill in skills}
-            years = [datetime.now().year + i for i in range(5)]
-            fig = go.Figure()
-            for skill, growth in growth_data.items():
-                fig.add_trace(go.Scatter(x=years, y=growth, mode='lines+markers', name=skill))
-            fig.update_layout(title="Projected Skills Growth (Next 5 Years)", xaxis_title="Year", yaxis_title="Growth Rate (%)")
-            st.plotly_chart(fig)
+            growth_data = {skill: [random.uniform(0, 15) for _ in range(2)] for skill in skills}
+            years = [datetime.now().year, datetime.now().year + 5]
+            df_growth = pd.DataFrame(growth_data, index=years)
+            fig_growth = px.line(df_growth, title="Projected Skills Growth (5 Year Projection)")
+            st.plotly_chart(fig_growth, use_container_width=True)
     
     st.markdown('</div>', unsafe_allow_html=True)
+            
+
 
 elif page == "Program Evaluation":
     animated_progress_bar()