app.py.txt

import gradio as gr
import pandas as pd
import joblib

# Charger le modèle pré-entraîné
model = joblib.load('titanic_model.pkl')

def predict_survival(Pclass, Age, SibSp, Parch, Fare, Sex, Embarked):
    # Prétraiter les caractéristiques
    features = {
        'Pclass': [Pclass],
        'Age': [Age],
        'SibSp': [SibSp],
        'Parch': [Parch],
        'Fare': [Fare],
        'Sex': [Sex],
        'Embarked': [Embarked]
    }
    df = pd.DataFrame(features)
    # Faire des prédictions
    prediction = model.predict(df)
    return "Survived" if prediction[0] == 1 else "Not Survived"

# Définir l'interface Gradio
interface = gr.Interface(
    fn=predict_survival,
    inputs=[
        gr.inputs.Number(label="Pclass"),
        gr.inputs.Number(label="Age"),
        gr.inputs.Number(label="SibSp"),
        gr.inputs.Number(label="Parch"),
        gr.inputs.Number(label="Fare"),
        gr.inputs.Textbox(label="Sex"),
        gr.inputs.Textbox(label="Embarked")
    ],
    outputs=gr.outputs.Textbox(label="Survived")
)

# Lancer l'interface
interface.launch()