add user data saving

app.py

@@ -15,11 +15,11 @@ model_dir = model.download()
 model = joblib.load(model_dir + "/diabetes_model.pkl")
 print("Model downloaded")
 
-diabetes_fg = fs.get_feature_group(name="diabetes", version=1)
+diabetes_fg = fs.get_feature_group(name="diabetes_gan", version=1)
 query = diabetes_fg.select_all()
 # feature_view = fs.get_or_create_feature_view(name="diabetes",
 feature_view = fs.get_or_create_feature_view(
-    name="diabetes",
+    name="diabetes_gan",
     version=1,
     description="Read from Diabetes dataset",
     labels=["diabetes"],
@@ -40,11 +40,11 @@ with gr.Blocks() as demo:
             blood_glucose_input = gr.Slider(
                 80, 300, label="blood_glucose_level", info="Blood Glucose Level"
             )
-            gr.Radio(
-                ["yes", "no"],
-                label="if you already know that you have diabetes, select yes, else select no",
+            existent_info_input = gr.Radio(
+                ["yes", "no", "Don't know"],
+                label="Do you already know if you have diabetes? (This will not be used for the prediction)",
             )
-            gr.Checkbox(
+            consent_input = gr.Checkbox(
                 info="I consent that my personal data will be saved and potentially be used for the model training",
                 label="accept",
             )
@@ -53,7 +53,14 @@ with gr.Blocks() as demo:
             output = gr.Text(label="Model prediction")
             plot = gr.Plot()
 
-    def submit_inputs(age_input, bmi_input, hba1c_input, blood_glucose_input):
+    def submit_inputs(
+        age_input,
+        bmi_input,
+        hba1c_input,
+        blood_glucose_input,
+        existent_info_input,
+        consent_input,
+    ):
         df = pd.DataFrame(
             [[age_input, bmi_input, hba1c_input, blood_glucose_input]],
             columns=["age", "bmi", "hba1c_level", "blood_glucose_level"],
@@ -99,11 +106,29 @@ with gr.Blocks() as demo:
         ax.set_xticklabels(categories)
 
         ## save user's data in hopsworks
+        if consent_input == True:
+            user_data_fg = fs.get_or_create_feature_view(
+                name="user_diabetes_data",
+                version=1,
+                primary_key=["age", "bmi", "hba1c_level", "blood_glucose_level"],
+                description="Submitted user data",
+            )
+            user_data_df = df.copy()
+            user_data_df["diabetes"] = existent_info_input
+            user_data_fg.insert(user_data_df)
+            print("inserted new user data to hopsworks", user_data_df)
         return res, fig
 
     btn.click(
         submit_inputs,
-        inputs=[age_input, bmi_input, hba1c_input, blood_glucose_input],
+        inputs=[
+            age_input,
+            bmi_input,
+            hba1c_input,
+            blood_glucose_input,
+            existent_info_input,
+            consent_input,
+        ],
         outputs=[output, plot],
     )