add

app.py

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+import gradio as gr
+import pandas as pd
+from fastai.tabular.all import *
+
+learn = load_learner('model.pkl')
+
+def predict(Gender, SmokingHistory, Age, Hypertension, HeartDisease, BMI, HbLevel, GlucoseLevel):
+
+    data = [[Gender, SmokingHistory, int(Age), int(Hypertension), int(HeartDisease), float(BMI), float(HbLevel), int(GlucoseLevel)]]
+
+    row_df = pd.DataFrame(data,columns=['gender','smoking_history', 'age', 'hypertension', 'heart_disease', 'bmi', 'HbA1c_level', 'blood_glucose_level'])
+    
+    row, clas, probs = learn.predict(row_df.iloc[0])
+    if probs[0] < 0.5:
+        return "Tem diabetes"
+    else:
+        return "Não tem diabetes"
+
+gr.Interface(
+    fn=predict,
+    title="Predict Diabetes",
+    allow_flagging="never",
+    inputs=[
+        gr.inputs.Radio(["Male", "Female"], label="Gender", default="Male"),
+        gr.inputs.Dropdown(
+            ["never", "No info", "current" , "former"], label="SmokingHistory", default="never"
+        ),
+        gr.inputs.Number(default=60, label="Age"),
+        gr.inputs.Radio(["1", "0"], label="HyperTension", default="1"),
+        gr.inputs.Radio(["1", "0"], label="HeartDisease", default="1"),
+        gr.inputs.Number(default=30, label="BMI"),
+        gr.inputs.Number(default=5.1, label="HbLevel"),
+        gr.inputs.Number(default=90, label="GlucoseLevel")
+    ],
+    outputs="text").launch(inline=False)

requirements.txt

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+fastai
+pandas