Update app.py

app.py

@@ -4,7 +4,7 @@ import os
 import json
 import pandas as pd
 import matplotlib.pyplot as plt
-import numpy as np
+from PIL import Image
 
 # Function to call the Together API with the provided model
 def call_ai_model(all_message):
@@ -96,22 +96,19 @@ if st.button("Generate Prediction"):
             st.markdown(f"**Impact Summary:** {generated_text.strip()}")
             st.markdown("**Conclusion:** Tailoring strategies based on these climate conditions can significantly enhance performance and infrastructure resilience.")
 
-            # Data Visualization
-            st.subheader("Climate Condition Impacts Visualization")
-            # Example: Displaying data in a table
+            # Displaying a table of input data
             data = {
                 'Condition': ['Temperature', 'Humidity', 'Wind Speed', 'UV Index', 'Air Quality Index', 'Precipitation', 'Atmospheric Pressure'],
                 'Value': [temperature, humidity, wind_speed, uv_index, air_quality_index, precipitation, atmospheric_pressure]
             }
             df = pd.DataFrame(data)
+            st.subheader("Input Data Overview")
             st.table(df)
 
-            # Plotting a bar chart for climate variables
-            fig, ax = plt.subplots()
-            ax.bar(data['Condition'], data['Value'], color=['blue', 'green', 'orange', 'red', 'purple', 'gray', 'cyan'])
-            ax.set_ylabel('Value')
-            ax.set_title('Climate Condition Impacts')
-            st.pyplot(fig)
+            # Display an infographic
+            infographics_path = 'path_to_your_infographic_image.jpg'  # Replace with your image path
+            infographic = Image.open(infographics_path)
+            st.image(infographic, caption='Climate Impact Infographic', use_column_width=True)
 
     except ValueError as ve:
         st.error(f"Configuration error: {ve}")