app.py

import gradio as gr
import numpy as np
import joblib

# Load the trained Naive Bayes model
model_NB = joblib.load('disease_prediction_model_nb.pkl')

# List of symptoms
symptoms = ['itching', 'skin_rash', 'nodal_skin_eruptions', 'continuous_sneezing', 'shivering', 'chills', 'joint_pain', 
            'stomach_pain', 'acidity', 'ulcers_on_tongue', 'muscle_wasting', 'vomiting', 'burning_micturition', 
            'spotting_ urination', 'fatigue', 'weight_gain', 'anxiety', 'cold_hands_and_feets', 'mood_swings', 
            'weight_loss', 'restlessness', 'lethargy', 'patches_in_throat', 'irregular_sugar_level', 'cough', 
            'high_fever', 'sunken_eyes', 'breathlessness', 'sweating', 'dehydration', 'indigestion', 'headache', 
            'yellowish_skin', 'dark_urine', 'nausea', 'loss_of_appetite', 'pain_behind_the_eyes', 'back_pain', 
            'constipation', 'abdominal_pain', 'diarrhoea', 'mild_fever', 'yellow_urine', 'yellowing_of_eyes', 
            'acute_liver_failure', 'swelling_of_stomach', 'swelled_lymph_nodes', 'malaise', 'blurred_and_distorted_vision', 
            'phlegm', 'throat_irritation', 'redness_of_eyes', 'sinus_pressure', 'runny_nose', 'congestion', 'chest_pain', 
            'weakness_in_limbs', 'fast_heart_rate', 'pain_during_bowel_movements', 'pain_in_anal_region', 'bloody_stool', 
            'irritation_in_anus', 'neck_pain', 'dizziness', 'cramps', 'bruising', 'obesity', 'swollen_legs', 
            'swollen_blood_vessels', 'puffy_face_and_eyes', 'enlarged_thyroid', 'brittle_nails', 'swollen_extremeties', 
            'excessive_hunger', 'extra_marital_contacts', 'drying_and_tingling_lips', 'slurred_speech', 'knee_pain', 
            'hip_joint_pain', 'muscle_weakness', 'stiff_neck', 'swelling_joints', 'movement_stiffness', 'spinning_movements', 
            'loss_of_balance', 'unsteadiness', 'weakness_of_one_body_side', 'loss_of_smell', 'bladder_discomfort', 
            'foul_smell_of_urine', 'continuous_feel_of_urine', 'passage_of_gases', 'internal_itching', 'toxic_look_(typhos)', 
            'depression', 'irritability', 'muscle_pain', 'altered_sensorium', 'red_spots_over_body', 'belly_pain', 
            'abnormal_menstruation', 'dischromic _patches', 'watering_from_eyes', 'increased_appetite', 'polyuria', 
            'family_history', 'mucoid_sputum', 'rusty_sputum', 'lack_of_concentration', 'visual_disturbances', 
            'receiving_blood_transfusion', 'receiving_unsterile_injections', 'coma', 'stomach_bleeding', 
            'distention_of_abdomen', 'history_of_alcohol_consumption', 'fluid_overload.1', 'blood_in_sputum', 
            'prominent_veins_on_calf', 'palpitations', 'painful_walking', 'pus_filled_pimples', 'blackheads', 'scurring', 
            'skin_peeling', 'silver_like_dusting', 'small_dents_in_nails', 'inflammatory_nails', 'blister', 
            'red_sore_around_nose', 'yellow_crust_ooze']

# Function for prediction
def predict_disease(*symptom_input):
    input_data = np.array(symptom_input).reshape(1, -1)  # Reshape to fit the model
    prediction = model_NB.predict(input_data)[0]  # Get the prediction
    return prediction

# Create Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("# Disease Prediction App")

    symptom_checkboxes = [gr.Checkbox(label=symptom) for symptom in symptoms]
    predict_button = gr.Button("Predict Disease")

    output = gr.Textbox(label="Predicted Disease")

    predict_button.click(
        predict_disease, 
        inputs=symptom_checkboxes, 
        outputs=output
    )

demo.launch()