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