Update app.py

app.py

@@ -5,11 +5,10 @@ import numpy as np
 
 # Load the model and unique brand values
 model = joblib.load('model.joblib')
-unique_values = joblib.load('unique_values.joblib')
-college_values = unique_values['college']
+
 
 # Define the prediction function
-def predict(college,conf,year_drafted,qb_num_picked,rd_picked,num_picked,coach_tenure,height,weight,drafted_team_winpr,drafted_team_ppg_rk,conf_str,p_cmp,p_att,cmp_pct,p_yds,p_ypa,p_adj_ypa,ints,rate,r_att,r_yds,r_avg,r_tds):
+def predict(year_drafted,qb_num_picked,rd_picked,num_picked,coach_tenure,height,weight,drafted_team_winpr,drafted_team_ppg_rk,conf_str,p_cmp,p_att,cmp_pct,p_yds,p_ypa,p_adj_ypa,ints,rate,r_att,r_yds,r_avg,r_tds):
     # Convert inputs to appropriate types
     year_drafted = int(year_drafted) 
     qb_num_picked = int(qb_num_picked)
@@ -36,8 +35,6 @@ def predict(college,conf,year_drafted,qb_num_picked,rd_picked,num_picked,coach_t
     
     # Prepare the input array for prediction
     input_data = pd.DataFrame({
-        'college': college,
-        'conf': conf,
         'year_drafted': year_drafted,
         'qb_num_picked': qb_num_picked,
         'rd_picked': rd_picked,
@@ -72,7 +69,6 @@ def predict(college,conf,year_drafted,qb_num_picked,rd_picked,num_picked,coach_t
 interface = gr.Interface(
     fn=predict,
     inputs=[
-        gr.Dropdown(choices=college_values, label="College"),
         gr.Textbox(label="Year Drafted"),
         gr.Textbox(label="QB Number Picked"),
         gr.Textbox(label="Round Picked"),