Updated Code

app.py

@@ -114,14 +114,22 @@ print('Coefficients: \n', modelepw.coef_)
 # The mean squared error
 print("Mean squared error: %.2f" % np.mean((modelepw.predict(X_test) - y_test) ** 2))
 
+#local Testing
+# input = "25,1,10,70,3,3,3,2,3,3,3,3,2,24,2";
+# temp =np.array(input.split(","), dtype=float) 
+# y = model.predict([[temp[0],temp[1],temp[2],temp[3],temp[4],temp[5],temp[6],temp[7],temp[8],temp[9],temp[10],temp[11],temp[12],temp[13],temp[14]]])
+# z = modelepw.predict([[temp[0],temp[1],temp[2],temp[3],temp[4],temp[5],temp[6],temp[7],temp[8],temp[9],temp[10],temp[11],temp[12],temp[13],temp[14]]])
+# print(str(y),",",str(z))
+
+
 def greet(input):
     temp =np.array(input.split(","), dtype=float) 
     y = model.predict([[temp[0],temp[1],temp[2],temp[3],temp[4],temp[5],temp[6],temp[7],temp[8],temp[9],temp[10],temp[11],temp[12],temp[13],temp[14]]])
     z = modelepw.predict([[temp[0],temp[1],temp[2],temp[3],temp[4],temp[5],temp[6],temp[7],temp[8],temp[9],temp[10],temp[11],temp[12],temp[13],temp[14]]])
-    return str(y,",",z)
+    return str(str(y),",",str(z))
 
-textbox_x = gr.Textbox(label="Variable X:", placeholder="10", lines=1)
-textbox_y = gr.Textbox(label="Variable Y:", placeholder ="11", lines=1)
-grIn = gr.Interface(title = "Lineare Regression",fn=greet, inputs=textbox_x, outputs=textbox_y)
+textbox_x = gr.Textbox(label="Enter Input:", placeholder="25,1,10,70,3,3,3,2,3,3,3,3,2,24,2", lines=1)
+textbox_y = gr.Textbox(label="Variable Y:", placeholder ="5.0000000", lines=1)
+grIn = gr.Interface(title = "Your Name Regeression ",fn=greet, inputs=textbox_x, outputs=textbox_y)
 
 grIn.launch()