ogegadavis254
commited on
Commit
•
251086d
1
Parent(s):
717bb30
Update app.py
Browse files
app.py
CHANGED
@@ -5,6 +5,7 @@ import json
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import pandas as pd
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import folium
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from streamlit_folium import folium_static
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# Function to call the Together AI model
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def call_ai_model(all_message):
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@@ -48,27 +49,16 @@ air_quality_index = st.number_input("Air Quality Index:", min_value=0, max_value
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precipitation = st.number_input("Precipitation (mm):", min_value=0.0, max_value=500.0, value=10.0)
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atmospheric_pressure = st.number_input("Atmospheric Pressure (hPa):", min_value=900, max_value=1100, value=1013)
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# Geographic location
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latitude = st.number_input("Latitude:", min_value=-90.0, max_value=90.0, value=0.0)
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longitude = st.number_input("Longitude:", min_value=-180.0, max_value=180.0, value=0.0)
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# Athlete-specific data
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age = st.number_input("Athlete Age:", min_value=0, max_value=100, value=25)
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sport = st.selectbox("Select Sport:", ["Running", "Cycling", "Swimming", "Football", "Basketball"])
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performance_history = st.text_area("Athlete Performance History:")
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# Infrastructure characteristics
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facility_type = st.selectbox("Facility Type:", ["Stadium", "Gymnasium", "Outdoor Field"])
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facility_age = st.number_input("Facility Age (years):", min_value=0, max_value=100, value=10)
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materials_used = st.text_input("Materials Used in Construction:")
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if st.button("Generate Prediction"):
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all_message = (
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f"Assess the impact on sports performance and infrastructure based on climate conditions: "
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f"Temperature {temperature}°C, Humidity {humidity}%, Wind Speed {wind_speed} km/h, UV Index {uv_index}, "
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f"Air Quality Index {air_quality_index}, Precipitation {precipitation} mm, Atmospheric Pressure {atmospheric_pressure} hPa. "
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f"Location: Latitude {latitude}, Longitude {longitude}.
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f"Athlete (Age: {age}, Sport: {sport}), Facility (Type: {facility_type}, Age: {facility_age}, Materials: {materials_used})."
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)
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try:
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@@ -107,6 +97,13 @@ if st.button("Generate Prediction"):
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st.markdown("**Predicted Impact on Performance and Infrastructure:**")
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st.markdown(generated_text.strip())
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# Generate static map using Folium
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map_center = [latitude, longitude]
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sport_map = folium.Map(location=map_center, zoom_start=12)
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import pandas as pd
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import folium
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from streamlit_folium import folium_static
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import matplotlib.pyplot as plt
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# Function to call the Together AI model
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def call_ai_model(all_message):
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precipitation = st.number_input("Precipitation (mm):", min_value=0.0, max_value=500.0, value=10.0)
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atmospheric_pressure = st.number_input("Atmospheric Pressure (hPa):", min_value=900, max_value=1100, value=1013)
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# Geographic location input
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latitude = st.number_input("Latitude:", min_value=-90.0, max_value=90.0, value=0.0)
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longitude = st.number_input("Longitude:", min_value=-180.0, max_value=180.0, value=0.0)
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if st.button("Generate Prediction"):
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all_message = (
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f"Assess the impact on sports performance and infrastructure based on climate conditions: "
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f"Temperature {temperature}°C, Humidity {humidity}%, Wind Speed {wind_speed} km/h, UV Index {uv_index}, "
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f"Air Quality Index {air_quality_index}, Precipitation {precipitation} mm, Atmospheric Pressure {atmospheric_pressure} hPa. "
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f"Location: Latitude {latitude}, Longitude {longitude}."
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)
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try:
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st.markdown("**Predicted Impact on Performance and Infrastructure:**")
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st.markdown(generated_text.strip())
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# Generate a simple chart
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fig, ax = plt.subplots()
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ax.bar(results_data['Condition'], results_data['Value'])
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ax.set_ylabel('Values')
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ax.set_title('Climate Conditions Impact')
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st.pyplot(fig)
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# Generate static map using Folium
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map_center = [latitude, longitude]
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sport_map = folium.Map(location=map_center, zoom_start=12)
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