Update app.py

app.py

@@ -23,8 +23,13 @@ def prediction(price_max,price_step,policy_net):
                 1.,     0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.]
     Q_s = policy_net(to_tensor(sample_state))
     a_opt = Q_s.max(0)[1].detach()
+    plt.figure(figsize=(16, 5))
+    plt.xlabel("Price action ($)")
+    plt.ylabel("Q ($)")
+    plt.bar(price_grid, Q_s.detach().numpy(), color='crimson',  width=6, alpha=0.8)
+    plt.savefig('price.png')    
+    return price_grid[a_opt]
     
-    return price_grid[a_opt],Q_s.detach().numpy()
 def fun():
     st.header("Optimal Price Action")
     st.subheader(str(a))
@@ -33,14 +38,11 @@ def fun():
 st.header("Enter the Specification")
 max_value = st.number_input('Enter the Maximum Value of Price',min_value=50,value = 500,step=1)
 step = st.number_input('Enter the Price step',min_value = 10,value = 10,step=1)
-a,b = prediction(max_value,step,pc2)
+a = prediction(max_value,step,pc2)
 if st.button('Predict'):
     fun()
-    chart_data = pd.DataFrame(a,b,
-    
-    columns=["a", "b"])
-
-    st.bar_chart(chart_data)
+    image = Image.open('price.png')
+    st.image(image,caption = 'Price Optimization',width =1000)