feat: add defaults

app.py

@@ -39,24 +39,24 @@ additional_categories = {
 }
 
 # Define the input components for the form
-age_input = gr.Slider(minimum=18, maximum=100, label="Age ", step=1)
-gender_input = gr.Radio(choices=additional_categories["Gender"], label="Gender")
-ethnicity_input = gr.Radio(choices=additional_categories["Ethnicity"], label="Ethnicity")
-geographic_location_input = gr.Radio(choices=additional_categories["Geographic_Location"], label="Geographic Location")
-medications_input = gr.CheckboxGroup(choices=additional_categories["Medications"], label="Medications")
-allergies_input = gr.CheckboxGroup(choices=additional_categories["Allergies"], label="Allergies")
-previous_treatments_input = gr.CheckboxGroup(choices=additional_categories["Previous_Treatments"], label="Previous Treatments")
-blood_glucose_level_input = gr.Slider(minimum=0, maximum=300, label="Blood Glucose Level", step=1)
-blood_pressure_systolic_input = gr.Slider(minimum=80, maximum=200, label="Blood Pressure (Systolic)", step=1)
-blood_pressure_diastolic_input = gr.Slider(minimum=40, maximum=120, label="Blood Pressure (Diastolic)", step=1)
-bmi_input = gr.Slider(minimum=10, maximum=50, label="BMI ", step=1)
-smoking_status_input = gr.Radio(choices=additional_categories["Smoking_Status"], label="Smoking Status")
-alcohol_consumption_input = gr.Radio(choices=additional_categories["Alcohol_Consumption"], label="Alcohol Consumption")
-exercise_habits_input = gr.Radio(choices=additional_categories["Exercise_Habits"], label="Exercise Habits")
-diet_input = gr.Radio(choices=additional_categories["Diet"], label="Diet")
-condition_severity_input = gr.Slider(minimum=1, maximum=10, label="Condition Severity", step=1)
-functional_status_input = gr.Radio(choices=additional_categories["Functional_Status"], label="Functional Status")
-previous_trial_participation_input = gr.Radio(choices=additional_categories["Previous_Trial_Participation"], label="Previous Trial Participation")
+age_input = gr.Slider(minimum=18, maximum=100, label="Age ", step=1, value=30)
+gender_input = gr.Radio(choices=additional_categories["Gender"], label="Gender", value="Male")
+ethnicity_input = gr.Radio(choices=additional_categories["Ethnicity"], label="Ethnicity", value="White")
+geographic_location_input = gr.Radio(choices=additional_categories["Geographic_Location"], label="Geographic Location", value="North America")
+medications_input = gr.CheckboxGroup(choices=additional_categories["Medications"], label="Medications", value=["Metformin"])
+allergies_input = gr.CheckboxGroup(choices=additional_categories["Allergies"], label="Allergies", value=["Peanuts"])
+previous_treatments_input = gr.CheckboxGroup(choices=additional_categories["Previous_Treatments"], label="Previous Treatments", value=["None"])
+blood_glucose_level_input = gr.Slider(minimum=0, maximum=300, label="Blood Glucose Level", step=1, value=100)
+blood_pressure_systolic_input = gr.Slider(minimum=80, maximum=200, label="Blood Pressure (Systolic)", step=1, value=120)
+blood_pressure_diastolic_input = gr.Slider(minimum=40, maximum=120, label="Blood Pressure (Diastolic)", step=1, value=80)
+bmi_input = gr.Slider(minimum=10, maximum=50, label="BMI ", step=1, value=20)
+smoking_status_input = gr.Radio(choices=additional_categories["Smoking_Status"], label="Smoking Status", value="Never")
+alcohol_consumption_input = gr.Radio(choices=additional_categories["Alcohol_Consumption"], label="Alcohol Consumption", value="None")
+exercise_habits_input = gr.Radio(choices=additional_categories["Exercise_Habits"], label="Exercise Habits", value="Sedentary")
+diet_input = gr.Radio(choices=additional_categories["Diet"], label="Diet", value="Omnivore")
+condition_severity_input = gr.Slider(minimum=1, maximum=10, label="Condition Severity", step=1, value=5)
+functional_status_input = gr.Radio(choices=additional_categories["Functional_Status"], label="Functional Status", value="Independent")
+previous_trial_participation_input = gr.Radio(choices=additional_categories["Previous_Trial_Participation"], label="Previous Trial Participation", value="No")
 
 
 # def encrypt_array(user_symptoms: np.ndarray, user_id: str) -> bytes: