Spaces:
Running
on
CPU Upgrade
Running
on
CPU Upgrade
chore: update
Browse files
app.py
CHANGED
@@ -115,12 +115,12 @@ def get_features_fn(*checked_symptoms: Tuple[str]) -> Dict:
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print("Provide at least 5 symptoms.")
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return {
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error_box1: gr.update(visible=True, value="⚠️ Provide at least 5 symptoms"),
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-
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}
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return {
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error_box1: gr.update(visible=False),
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-
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visible=False,
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value=get_user_symptoms_from_checkboxgroup(pretty_print(checked_symptoms)),
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),
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@@ -217,7 +217,7 @@ def encrypt_fn(user_symptoms: np.ndarray, user_id: str) -> None:
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return {
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error_box3: gr.update(visible=False),
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-
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enc_vect_box: gr.update(visible=True, value=encrypted_quantized_user_symptoms_shorten_hex),
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}
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@@ -435,19 +435,19 @@ def decrypt_fn(
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top3_diseases = np.argsort(output.flatten())[-3:][::-1]
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top3_proba = output[0][top3_diseases]
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if (
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(top3_proba[0] < threshold)
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or (np.sum(top3_proba) < threshold)
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or (abs(top3_proba[0] - top3_proba[1]) < threshold)
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):
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-
out = "⚠️ The prediction appears uncertain; including more symptoms may improve the results
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-
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-
else:
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out = ""
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out = (
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-
f"{out}"
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-
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"Here are the top3 predictions:\n\n"
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f"1. « {get_disease_name(top3_diseases[0])} » with a probability of {top3_proba[0]:.2%}\n"
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f"2. « {get_disease_name(top3_diseases[1])} » with a probability of {top3_proba[1]:.2%}\n"
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@@ -467,18 +467,18 @@ def reset_fn():
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clean_directory()
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return {
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-
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-
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user_id_box: gr.update(visible=False, value=None),
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-
one_hot_vector: None,
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default_symptoms: gr.update(visible=True, value=None),
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-
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-
quant_vect_box: gr.update(visible=False, value=None),
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-
enc_vect_box: gr.update(visible=True, value=None),
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key_box: gr.update(visible=True, value=None),
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key_len_box: gr.update(visible=False, value=None),
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fhe_execution_time_box: gr.update(visible=True, value=None),
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decrypt_box: None,
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error_box7: gr.update(visible=False),
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error_box1: gr.update(visible=False),
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error_box2: gr.update(visible=False),
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@@ -570,24 +570,24 @@ if __name__ == "__main__":
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with gr.Row():
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with gr.Column(scale=2):
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-
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with gr.Column(scale=5):
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default_symptoms = gr.Textbox(label="Related Symptoms:", visible=False)
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# User vector symptoms encoded in oneHot representation
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-
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# Submit botton
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submit_btn = gr.Button("Submit")
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# Clear botton
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clear_button = gr.Button("Reset Space 🔁", visible=False)
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-
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-
fn=display_default_symptoms_fn, inputs=[
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)
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submit_btn.click(
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fn=get_features_fn,
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inputs=[*check_boxes],
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-
outputs=[
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)
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# ------------------------- Step 2 -------------------------
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@@ -611,7 +611,7 @@ if __name__ == "__main__":
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gen_key_btn.click(
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key_gen_fn,
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-
inputs=
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outputs=[
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key_box,
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user_id_box,
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@@ -628,15 +628,15 @@ if __name__ == "__main__":
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with gr.Row():
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with gr.Column():
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-
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with gr.Column():
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enc_vect_box = gr.Textbox(label="Encrypted Vector:", max_lines=10)
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encrypt_btn.click(
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encrypt_fn,
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-
inputs=[
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outputs=[
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-
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enc_vect_box,
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error_box3,
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],
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@@ -655,7 +655,7 @@ if __name__ == "__main__":
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send_input_btn.click(
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send_input_fn,
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inputs=[user_id_box,
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outputs=[error_box4, srv_resp_send_data_box],
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)
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@@ -698,7 +698,7 @@ if __name__ == "__main__":
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get_output_btn.click(
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get_output_fn,
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inputs=[user_id_box,
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outputs=[srv_resp_retrieve_data_box, error_box6],
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)
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@@ -710,7 +710,7 @@ if __name__ == "__main__":
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decrypt_btn.click(
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decrypt_fn,
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inputs=[user_id_box,
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outputs=[decrypt_box, error_box7, submit_btn],
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)
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@@ -734,10 +734,9 @@ if __name__ == "__main__":
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clear_button.click(
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reset_fn,
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outputs=[
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-
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-
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submit_btn,
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-
# disease_box,
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error_box1,
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error_box2,
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error_box3,
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@@ -745,7 +744,7 @@ if __name__ == "__main__":
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error_box5,
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error_box6,
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error_box7,
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-
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default_symptoms,
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user_id_box,
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key_len_box,
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print("Provide at least 5 symptoms.")
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return {
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error_box1: gr.update(visible=True, value="⚠️ Provide at least 5 symptoms"),
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+
one_hot_vect: None,
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}
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return {
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error_box1: gr.update(visible=False),
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+
one_hot_vect: gr.update(
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visible=False,
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value=get_user_symptoms_from_checkboxgroup(pretty_print(checked_symptoms)),
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),
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return {
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error_box3: gr.update(visible=False),
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+
one_hot_vect_box: gr.update(visible=True, value=user_symptoms),
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enc_vect_box: gr.update(visible=True, value=encrypted_quantized_user_symptoms_shorten_hex),
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}
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top3_diseases = np.argsort(output.flatten())[-3:][::-1]
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top3_proba = output[0][top3_diseases]
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+
out = ""
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+
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if (
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(top3_proba[0] < threshold)
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or (np.sum(top3_proba) < threshold)
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or (abs(top3_proba[0] - top3_proba[1]) < threshold)
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):
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+
out = "⚠️ The prediction appears uncertain; including more symptoms may improve the results."
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out = (
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+
f"{out}\n"
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"Given the symptoms you provided: "
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f"{pretty_print(checked_symptoms, case_conversion=str.capitalize, delimiter=', ')}\n\n"
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"Here are the top3 predictions:\n\n"
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f"1. « {get_disease_name(top3_diseases[0])} » with a probability of {top3_proba[0]:.2%}\n"
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f"2. « {get_disease_name(top3_diseases[1])} » with a probability of {top3_proba[1]:.2%}\n"
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clean_directory()
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return {
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+
one_hot_vect: None,
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+
one_hot_vect_box: None,
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+
enc_vect_box: gr.update(visible=True, value=None),
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+
quant_vect_box: gr.update(visible=False, value=None),
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user_id_box: gr.update(visible=False, value=None),
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default_symptoms: gr.update(visible=True, value=None),
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default_disease_box: gr.update(visible=True, value=None),
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key_box: gr.update(visible=True, value=None),
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key_len_box: gr.update(visible=False, value=None),
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fhe_execution_time_box: gr.update(visible=True, value=None),
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decrypt_box: None,
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submit_btn: gr.update(value="Submit"),
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error_box7: gr.update(visible=False),
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error_box1: gr.update(visible=False),
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error_box2: gr.update(visible=False),
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with gr.Row():
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with gr.Column(scale=2):
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+
default_disease_box = gr.Dropdown(sorted(diseases), label="Diseases", visible=False)
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with gr.Column(scale=5):
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default_symptoms = gr.Textbox(label="Related Symptoms:", visible=False)
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# User vector symptoms encoded in oneHot representation
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+
one_hot_vect = gr.Textbox(visible=False)
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# Submit botton
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submit_btn = gr.Button("Submit")
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# Clear botton
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clear_button = gr.Button("Reset Space 🔁", visible=False)
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+
default_disease_box.change(
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fn=display_default_symptoms_fn, inputs=[default_disease_box], outputs=[default_symptoms]
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)
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submit_btn.click(
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fn=get_features_fn,
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inputs=[*check_boxes],
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+
outputs=[one_hot_vect, error_box1, submit_btn],
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)
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# ------------------------- Step 2 -------------------------
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gen_key_btn.click(
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key_gen_fn,
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+
inputs=one_hot_vect,
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outputs=[
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key_box,
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user_id_box,
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with gr.Row():
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with gr.Column():
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+
one_hot_vect_box = gr.Textbox(label="User Symptoms Vector:", max_lines=10)
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with gr.Column():
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enc_vect_box = gr.Textbox(label="Encrypted Vector:", max_lines=10)
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encrypt_btn.click(
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encrypt_fn,
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+
inputs=[one_hot_vect, user_id_box],
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outputs=[
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+
one_hot_vect_box,
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enc_vect_box,
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error_box3,
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],
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send_input_btn.click(
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send_input_fn,
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+
inputs=[user_id_box, one_hot_vect],
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outputs=[error_box4, srv_resp_send_data_box],
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)
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get_output_btn.click(
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get_output_fn,
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+
inputs=[user_id_box, one_hot_vect],
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outputs=[srv_resp_retrieve_data_box, error_box6],
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)
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decrypt_btn.click(
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decrypt_fn,
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+
inputs=[user_id_box, one_hot_vect, *check_boxes],
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outputs=[decrypt_box, error_box7, submit_btn],
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)
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clear_button.click(
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reset_fn,
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outputs=[
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+
one_hot_vect_box,
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+
one_hot_vect,
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submit_btn,
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error_box1,
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error_box2,
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error_box3,
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error_box5,
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error_box6,
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error_box7,
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+
default_disease_box,
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default_symptoms,
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user_id_box,
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key_len_box,
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