Update app.py (#1)

- Update app.py (0bcfca3df9752a308ef79d01d38a48a8414c7fca)


Co-authored-by: Yoann Poupart <Xmaster6y@users.noreply.huggingface.co>

app.py

@@ -7,11 +7,11 @@ from typing import List
 # Define the COLUMN_MIN_MAX as provided
 COLUMN_MIN_MAX = {
     "Age": (18, 100),
-    "Blood_Glucose_Level": (0, 3),
-    "Blood_Pressure_Systolic": (0, 3),
-    "Blood_Pressure_Diastolic": (0, 3),
-    "BMI": (0, 3),
-    "Condition_Severity": (0, 3),
+    "Blood_Glucose_Level": (0, 300),
+    "Blood_Pressure_Systolic": (80, 200),
+    "Blood_Pressure_Diastolic": (40, 120),
+    "BMI": (10, 50),
+    "Condition_Severity": (1, 10),
     "Gender": (0, 2),
     "Ethnicity": (0, 5),
     "Geographic_Location": (0, 6),
@@ -33,7 +33,7 @@ additional_categories = {
     "Ethnicity": ["White", "Black or African American", "Asian", "American Indian or Alaska Native", "Native Hawaiian or Other Pacific Islander", "Other"],
     "Geographic_Location": ["North America", "South America", "Europe", "Asia", "Africa", "Australia", "Antarctica"],
     "Smoking_Status": ["Never", "Former", "Current"],
-    "Diagnoses_ICD10": ["E11.9", "I10", "J45.909", "M54.5", "F32.9", "K21.9"],
+    "Diagnoses_ICD10": ["Actinic keratosis", "Melanoma", "Dermatofibroma", "Vascular lesion","None"],
     "Medications": ["Metformin", "Lisinopril", "Atorvastatin", "Amlodipine", "Omeprazole", "Simvastatin", "Levothyroxine", "None"],
     "Allergies": ["Penicillin", "Peanuts", "Shellfish", "Latex", "Bee stings", "None"],
     "Previous_Treatments": ["Chemotherapy", "Radiation Therapy", "Surgery", "Physical Therapy", "Immunotherapy", "None"],
@@ -48,39 +48,39 @@ additional_categories = {
 min_age_input = gr.Number(label="Minimum Age", value=18, minimum=COLUMN_MIN_MAX["Age"][0], maximum=COLUMN_MIN_MAX["Age"][1])
 max_age_input = gr.Number(label="Maximum Age", value=100, minimum=COLUMN_MIN_MAX["Age"][0], maximum=COLUMN_MIN_MAX["Age"][1])
 
-gender_input = gr.CheckboxGroup(choices=additional_categories["Gender"], label="Gender")
-ethnicity_input = gr.CheckboxGroup(choices=additional_categories["Ethnicity"], label="Ethnicity")
-geographic_location_input = gr.CheckboxGroup(choices=additional_categories["Geographic_Location"], label="Geographic Location")
-diagnoses_icd10_input = gr.CheckboxGroup(choices=additional_categories["Diagnoses_ICD10"], label="Diagnoses (ICD-10)")
-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")
+gender_input = gr.CheckboxGroup(choices=additional_categories["Gender"], label="Gender", value=["Male"])
+ethnicity_input = gr.CheckboxGroup(choices=additional_categories["Ethnicity"], label="Ethnicity", value=["White"])
+geographic_location_input = gr.CheckboxGroup(choices=additional_categories["Geographic_Location"], label="Geographic Location", value=["North America"])
+diagnoses_icd10_input = gr.CheckboxGroup(choices=additional_categories["Diagnoses_ICD10"], label="Skin Diagnosis", value=["Actinic keratosis"])
+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"])
 
 min_blood_glucose_level_input = gr.Number(label="Minimum Blood Glucose Level", value=0, minimum=COLUMN_MIN_MAX["Blood_Glucose_Level"][0], maximum=COLUMN_MIN_MAX["Blood_Glucose_Level"][1])
 max_blood_glucose_level_input = gr.Number(label="Maximum Blood Glucose Level", value=3, minimum=COLUMN_MIN_MAX["Blood_Glucose_Level"][0], maximum=COLUMN_MIN_MAX["Blood_Glucose_Level"][1])
+blood_glucose_level_input = gr.Number(label="Blood Glucose Level", value=100, minimum=COLUMN_MIN_MAX["Blood_Glucose_Level"][0], maximum=COLUMN_MIN_MAX["Blood_Glucose_Level"][1])
 
 min_blood_pressure_systolic_input = gr.Number(label="Minimum Blood Pressure (Systolic)", value=0, minimum=COLUMN_MIN_MAX["Blood_Pressure_Systolic"][0], maximum=COLUMN_MIN_MAX["Blood_Pressure_Systolic"][1])
 max_blood_pressure_systolic_input = gr.Number(label="Maximum Blood Pressure (Systolic)", value=3, minimum=COLUMN_MIN_MAX["Blood_Pressure_Systolic"][0], maximum=COLUMN_MIN_MAX["Blood_Pressure_Systolic"][1])
+blood_pressure_systolic_input = gr.Number(label="Blood Pressure (Systolic)", value=120, minimum=COLUMN_MIN_MAX["Blood_Pressure_Systolic"][0], maximum=COLUMN_MIN_MAX["Blood_Pressure_Systolic"][1])
 
 min_blood_pressure_diastolic_input = gr.Number(label="Minimum Blood Pressure (Diastolic)", value=0, minimum=COLUMN_MIN_MAX["Blood_Pressure_Diastolic"][0], maximum=COLUMN_MIN_MAX["Blood_Pressure_Diastolic"][1])
 max_blood_pressure_diastolic_input = gr.Number(label="Maximum Blood Pressure (Diastolic)", value=3, minimum=COLUMN_MIN_MAX["Blood_Pressure_Diastolic"][0], maximum=COLUMN_MIN_MAX["Blood_Pressure_Diastolic"][1])
+blood_pressure_diastolic_input = gr.Number(label="Blood Pressure (Diastolic)", value=80, minimum=COLUMN_MIN_MAX["Blood_Pressure_Diastolic"][0], maximum=COLUMN_MIN_MAX["Blood_Pressure_Diastolic"][1])
 
 min_bmi_input = gr.Number(label="Minimum BMI", value=0, minimum=COLUMN_MIN_MAX["BMI"][0], maximum=COLUMN_MIN_MAX["BMI"][1])
 max_bmi_input = gr.Number(label="Maximum BMI", value=3, minimum=COLUMN_MIN_MAX["BMI"][0], maximum=COLUMN_MIN_MAX["BMI"][1])
-
-smoking_status_input = gr.CheckboxGroup(choices=additional_categories["Smoking_Status"], label="Smoking Status")
-alcohol_consumption_input = gr.CheckboxGroup(choices=additional_categories["Alcohol_Consumption"], label="Alcohol Consumption")
-exercise_habits_input = gr.CheckboxGroup(choices=additional_categories["Exercise_Habits"], label="Exercise Habits")
-diet_input = gr.CheckboxGroup(choices=additional_categories["Diet"], label="Diet")
-
-min_condition_severity_input = gr.Number(label="Minimum Condition Severity", value=0, minimum=COLUMN_MIN_MAX["Condition_Severity"][0], maximum=COLUMN_MIN_MAX["Condition_Severity"][1])
-max_condition_severity_input = gr.Number(label="Maximum Condition Severity", value=3, minimum=COLUMN_MIN_MAX["Condition_Severity"][0], maximum=COLUMN_MIN_MAX["Condition_Severity"][1])
-
-functional_status_input = gr.CheckboxGroup(choices=additional_categories["Functional_Status"], label="Functional Status")
-previous_trial_participation_input = gr.CheckboxGroup(choices=additional_categories["Previous_Trial_Participation"], label="Previous Trial Participation")
-
+bmi_input = gr.Number(label="BMI", value=20, minimum=COLUMN_MIN_MAX["BMI"][0], maximum=COLUMN_MIN_MAX["BMI"][1])
+
+smoking_status_input = gr.CheckboxGroup(choices=additional_categories["Smoking_Status"], label="Smoking Status", value=["Never"])
+alcohol_consumption_input = gr.CheckboxGroup(choices=additional_categories["Alcohol_Consumption"], label="Alcohol Consumption", value=["None"])
+exercise_habits_input = gr.CheckboxGroup(choices=additional_categories["Exercise_Habits"], label="Exercise Habits", value=["Sedentary"])
+diet_input = gr.CheckboxGroup(choices=additional_categories["Diet"], label="Diet", value=["Omnivore"])
+condition_severity_input = gr.Number(label="Condition Severity", value=5, minimum=0, maximum=10)
+functional_status_input = gr.CheckboxGroup(choices=additional_categories["Functional_Status"], label="Functional Status", value=["Independent"])
+previous_trial_participation_input = gr.CheckboxGroup(choices=additional_categories["Previous_Trial_Participation"], label="Previous Trial Participation", value=["No"])
 # Define the server's URL
-SERVER_URL = "http://127.0.0.1:7860/api/predict"  # Ensure this is the correct endpoint
+SERVER_URL = "https://affordable-prot-bind-clarke.trycloudflare.com/requirements/create"  # Ensure this is the correct endpoint
 
 def encode_categorical_data(data: List[str], category_name: str) -> List[int]:
     """Encodes a list of categorical values into their corresponding indices based on additional_categories."""
@@ -189,7 +189,7 @@ def process_researcher_data(
 
     # Construct the payload as a regular dictionary
     payload = {
-        "model_name": "fhe_model_v1",
+        "model_name": "second_model",
         "requirements": requirements
     }