Rename aap to app.py

app.py

@@ -0,0 +1,35 @@
+import gradio as gr
+from fastai.tabular.all import *
+import pandas as pd
+
+model = load_learner('learn_model.pkl')
+
+    
+def predict(age, hypertension, heart_disease, avg_glucose_level, bmi, gender, married, work_type, residence_type, smoking_status):
+    
+    columns_df = ['gender', 'age', 'hypertension', 'heart_disease', 'ever_married', 'work_type', 'Residence_type', 'avg_glucose_level', 'bmi','smoking_status']
+    
+    data = [[gender, age, hypertension, heart_disease, married, work_type, residence_type, avg_glucose_level, bmi, smoking_status]]
+    df = pd.Dataframe(data, columns=columns_df)
+    
+    prediction = model.predict(df)
+    return "O paciente tem a seguinte possibilidade de infarto: " + str(predictions[0])
+
+gr.Interface(
+    fn=predict,
+    title="Stroke predict Model",
+    allow_flagging="never",
+    share=True,
+    inputs=[
+        gr.inputs.Number(default=30, label="Age"),
+        gr.Dropdown(["Yes", "No"], label="Hypertension"),
+        gr.Dropdown(["Yes", "No"], label="Heart disease"),
+        gr.inputs.Number(default=100, label="Average glucose level"),
+        gr.inputs.Number(default=28.8, label="Body mass index (BMI)"),
+        gr.inputs.Radio(choices=["Female", "Male", "Other"], default="Female", label="Gender"),
+        gr.Dropdown(["No", "Yes"], label="Married"),
+        gr.Dropdown(["Governamental", "Never worked", "Private", "Self-employed", "Children"], label="Work type"),
+        gr.Dropdown(["Rural", "Urban"],  label="Residence type"),
+        gr.Dropdown(["Unknown", "Formely smoked", "Never smoked", "Smokes"], label="Smoking status"),
+    ],
+    outputs="text").launch()