Upload app.py

app.py

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+# -*- coding: utf-8 -*-
+"""app.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1I-y23tTTs_aMjSYwPa3Fk8Ywz8H8ZUgl
+
+#**GRADIO**
+"""
+
+import gradio as gr
+import joblib as jb
+
+def predict(sex, age, hypertension, heart_disease, ever_married, work_type, Residence_type, avg_glucose_level, bmi, smoking_status):
+    model = jb.load('model.pkl')
+    sex = str(sex)
+    age = int(age)
+    hypertension = str(hypertension)
+    heart_disease = str(heart_disease)
+    ever_married = str(ever_married)
+    work_type = str(work_type)
+    Residence_type = int(Residence_type)
+    avg_glucose_level   = float(avg_glucose_level  )
+    bmi = float(bmi)
+    smoking_status = str(smoking_status)
+
+
+    p = model.predict({{sex, age, hypertension, heart_disease, ever_married, work_type, Residence_type, avg_glucose_level, bmi, smoking_status}})[0]
+
+    return {"Não terá AVC": p[0], "Terá AVC": p[1]}
+
+demo = gr.Interface(fn=predict,
+                   inputs=[gr.Dropdown(choices=["female", "male"], type="index"),
+                          "number",
+                           gr.Dropdown(choices=["Não Hipertenso", "Hipertenso"], type="index"),
+                           gr.Dropdown(choices=["Não doença cardíaca", "Possui doença cardíaca"], type="index"),
+                           gr.Dropdown(choices=["Não casado(a)", "Casado(a)"], type="index"),
+                           gr.Dropdown(choices=["Nunca trabalhou", "filhos", "Emprego público", "Autônomo", "Privado"], type="index"),
+                           gr.Dropdown(choices=["Rural", "Urbana"], type="index"),
+                           "number",
+                           "number",
+                           gr.Dropdown(choices=["Nunca fumou", "Fuma"], type="index"),
+                          ],
+                    outputs="label")
+
+
+demo.launch()