Update app.py

app.py

@@ -7,31 +7,32 @@ import pandas as pd
 with open('model.pkl', 'rb') as f:
     model = pickle.load(f)
     
-def predict(fixedAcidity, volatileAcidity, citricAcid, residualSugar, chlorides, freeSulfurDioxide, totalSulfurDioxide, density, pH, sulphates, alcohol, LogTotalSulfurDioxide):
+def predict(Pregnancies, Glucose, BloodPressure, SkinThickness, Insulin, BMI, DiabetesPedigreeFunction, Age):
 
-    data = [[float(fixedAcidity), float(volatileAcidity), float(citricAcid), float(residualSugar), float(chlorides), float(freeSulfurDioxide), float(totalSulfurDioxide), float(density), float(pH), float(sulphates), float(alcohol), float(LogTotalSulfurDioxide)]]
+    data = [[int(Pregnancies), int(Glucose), int(BloodPressure), int(SkinThickness), int(Insulin), float(BMI), float(DiabetesPedigreeFunction), int(Age)]]
 
-    row_df=pd.DataFrame(data,columns=['fixed acidity','volatile acidity', 'citric acid', 'residual sugar', 'chlorides', 'free sulfur dioxide', 'total sulfur dioxide', 'density', 'pH', 'sulphates', 'alcohol', 'LogTotalSulfurDioxide'])
+    row_df=pd.DataFrame(data,columns=['Pregnancies', 'Glucose', 'BloodPressure', 'SkinThickness','Insulin', 'BMI', 'DiabetesPedigreeFunction', 'Age'])
     
     predictions = model.predict(row_df)
-    return "A nota desse vinho seria: " + str(predictions[0])
+    y_pred = model.predict(row_df)
+    if y_pred[0] == 1:
+        return "Tem diabetes"
+    else:
+        return "Não tem diabetes"
+    return 0
 
 gr.Interface(
     fn=predict,
-    title="Wine Quality Model",
+    title="Predict Diabetes",
     allow_flagging="never",
     inputs=[
-        gr.inputs.Number(default=7.3, label="fixedAcidity"),
-        gr.inputs.Number(default=0.27, label="volatileAcidity"),
-        gr.inputs.Number(default=0.3, label="citricAcid"),
-        gr.inputs.Number(default=1.5, label="residualSugar"),
-        gr.inputs.Number(default=0.08, label="chlorides"),
-        gr.inputs.Number(default=20, label="freeSulfurDioxide"),
-        gr.inputs.Number(default=50, label="totalSulfurDioxide"),
-        gr.inputs.Number(default=0.998, label="density"),
-        gr.inputs.Number(default=3.5, label="pH"),
-        gr.inputs.Number(default=0.6, label="sulphates"),
-        gr.inputs.Number(default=9.5, label="alcohol"),
-        gr.inputs.Number(default=1.6, label="LogTotalSulfurDioxide"),
+        gr.inputs.Number(default=1, label="Pregnancies"),
+        gr.inputs.Number(default=126, label="Glucose"),
+        gr.inputs.Number(default=60, label="BloodPressure"),
+        gr.inputs.Number(default=0, label="SkinThickness"),
+        gr.inputs.Number(default=0, label="Insulin"),
+        gr.inputs.Number(default=30.1, label="BMI"),
+        gr.inputs.Number(default=0.349, label="DiabetesPedigreeFunction"),
+        gr.inputs.Number(default=47, label="Age")
     ],
     outputs="text").launch()