Update app.py

app.py

@@ -5,6 +5,7 @@ import json
 import pandas as pd
 import folium
 from streamlit_folium import folium_static
+import matplotlib.pyplot as plt
 
 # Function to call the Together AI model
 def call_ai_model(all_message):
@@ -48,27 +49,16 @@ air_quality_index = st.number_input("Air Quality Index:", min_value=0, max_value
 precipitation = st.number_input("Precipitation (mm):", min_value=0.0, max_value=500.0, value=10.0)
 atmospheric_pressure = st.number_input("Atmospheric Pressure (hPa):", min_value=900, max_value=1100, value=1013)
 
-# Geographic location
+# Geographic location input
 latitude = st.number_input("Latitude:", min_value=-90.0, max_value=90.0, value=0.0)
 longitude = st.number_input("Longitude:", min_value=-180.0, max_value=180.0, value=0.0)
 
-# Athlete-specific data
-age = st.number_input("Athlete Age:", min_value=0, max_value=100, value=25)
-sport = st.selectbox("Select Sport:", ["Running", "Cycling", "Swimming", "Football", "Basketball"])
-performance_history = st.text_area("Athlete Performance History:")
-
-# Infrastructure characteristics
-facility_type = st.selectbox("Facility Type:", ["Stadium", "Gymnasium", "Outdoor Field"])
-facility_age = st.number_input("Facility Age (years):", min_value=0, max_value=100, value=10)
-materials_used = st.text_input("Materials Used in Construction:")
-
 if st.button("Generate Prediction"):
     all_message = (
         f"Assess the impact on sports performance and infrastructure based on climate conditions: "
         f"Temperature {temperature}°C, Humidity {humidity}%, Wind Speed {wind_speed} km/h, UV Index {uv_index}, "
         f"Air Quality Index {air_quality_index}, Precipitation {precipitation} mm, Atmospheric Pressure {atmospheric_pressure} hPa. "
-        f"Location: Latitude {latitude}, Longitude {longitude}. "
-        f"Athlete (Age: {age}, Sport: {sport}), Facility (Type: {facility_type}, Age: {facility_age}, Materials: {materials_used})."
+        f"Location: Latitude {latitude}, Longitude {longitude}."
     )
 
     try:
@@ -107,6 +97,13 @@ if st.button("Generate Prediction"):
             st.markdown("**Predicted Impact on Performance and Infrastructure:**")
             st.markdown(generated_text.strip())
 
+            # Generate a simple chart
+            fig, ax = plt.subplots()
+            ax.bar(results_data['Condition'], results_data['Value'])
+            ax.set_ylabel('Values')
+            ax.set_title('Climate Conditions Impact')
+            st.pyplot(fig)
+
             # Generate static map using Folium
             map_center = [latitude, longitude]
             sport_map = folium.Map(location=map_center, zoom_start=12)