app.py

import gradio as gr
import joblib

# Charger le modèle
model = joblib.load('salary_prediction_model.joblib')

# Définir l'interface Gradio
def predict_salary(age, gender, education, job_title, years_experience, country, race):
    # Préparer les données d'entrée
    input_data = [[age, gender, education, job_title, years_experience, country, race]]
    # Faire la prédiction
    prediction = model.predict(input_data)
    return prediction[0]

# Créer l'interface
iface = gr.Interface(
    fn=predict_salary,
    inputs=[
        gr.inputs.Number(label="Age"),
        gr.inputs.Dropdown(choices=["Male", "Female"], label="Gender"),
        gr.inputs.Dropdown(choices=["Bachelor's", "Master's", "PhD"], label="Education Level"),
        gr.inputs.Textbox(label="Job Title"),
        gr.inputs.Number(label="Years of Experience"),
        gr.inputs.Dropdown(choices=["USA", "UK", "Canada"], label="Country"),
        gr.inputs.Dropdown(choices=["White", "Hispanic", "Asian"], label="Race")
    ],
    outputs="number",
    title="Salary Prediction Model",
    description="Predict salary based on various factors."
)

# Lancer l'interface
iface.launch()