app.py

import gradio as gr
from churn_analysis import predict
from translator import text_translator_ui
from sentiment import create_sentiment_tab
from financial_analyst import create_financial_tab
from personal_info_identifier import create_personal_info_tab

with gr.Blocks() as app:
    with gr.Tab("Text Translator"):
        text_translator_ui()

    with gr.Tab("Sentiment Analysis"):
        create_sentiment_tab()

    with gr.Tab("Financial Analyst"):
        create_financial_tab()

    with gr.Tab("Personal Info Identifier"):
        gr.Interface.load("models/iiiorg/piiranha-v1-detect-personal-information")  

    with gr.Tab("Churn Analysis"):
        gr.Markdown("Customer Churn Prediction")

        # อธิบายเบื้องต้น
        with gr.Row():
            gr.Markdown("This app predicts the likelihood of a customer to leave or stay with the company.")

        # กำหนด input columns
        with gr.Row():
            with gr.Column():
                input_interface_column_1 = [
                    gr.Radio(['Yes', 'No'], label="Are you a Seniorcitizen?"),
                    gr.Radio(['Yes', 'No'], label='Do you have Partner?'),
                    gr.Radio(['No', 'Yes'], label='Do you have any Dependents?'),
                    gr.Slider(label='Enter length of Tenure in Months', minimum=1, maximum=73, step=1),
                    gr.Radio(['DSL', 'Fiber optic', 'No Internet'], label='What is your Internet Service?'),
                    gr.Radio(['No', 'Yes'], label='Do you have Online Security?'),
                    gr.Radio(['No', 'Yes'], label='Do you have Online Backup?'),
                    gr.Radio(['No', 'Yes'], label='Do you have Device Protection?')
                ]

            with gr.Column():
                input_interface_column_2 = [
                    gr.Radio(['No', 'Yes'], label='Do you have Tech Support?'),
                    gr.Radio(['No', 'Yes'], label='Do you have Streaming TV?'),
                    gr.Radio(['No', 'Yes'], label='Do you have Streaming Movies?'),
                    gr.Radio(['Month-to-month', 'One year', 'Two year'], label='What is your Contract Type?'),
                    gr.Radio(['Yes', 'No'], label='Do you prefer Paperless Billing?'),
                    gr.Radio(['Electronic check', 'Mailed check', 'Bank transfer (automatic)', 'Credit card (automatic)'], label='Which PaymentMethod do you prefer?'),
                    gr.Slider(label="Enter monthly charges", minimum=18.40, maximum=118.65)
                ]

        # รวม inputs ไว้ในลิสต์เดียว
        input_interface = []
        input_interface.extend(input_interface_column_1)
        input_interface.extend(input_interface_column_2)

        # ปุ่มและผลลัพธ์
        with gr.Row():
            predict_btn = gr.Button('Predict')
            output_interface = gr.Label(label="Churn Prediction Result")

        # คำอธิบายเพิ่มเติม
        with gr.Accordion("Open for information on inputs", open=False):
            gr.Markdown("""
            **Input Descriptions:**
            - SeniorCitizen: Whether a customer is a senior citizen or not
            - Partner: Whether the customer has a partner or not
            - Dependents: Whether the customer has dependents
            - Tenure: Number of months the customer has stayed
            - InternetService, OnlineSecurity, OnlineBackup, DeviceProtection
            - TechSupport, StreamingTV, StreamingMovies
            - Contract: Type of contract (Month-to-month, One year, Two year)
            - PaperlessBilling
            - PaymentMethod
            - MonthlyCharges
            """)

        # เชื่อมปุ่มกับฟังก์ชัน
        predict_btn.click(fn=predict, inputs=input_interface, outputs=output_interface)

app.launch(share=True)