import gradio as gr
import pandas as pd
import pickle

# 모델 로딩 함수
def load_model():
    with open("model.pkl", "rb") as file:
        loaded_pipeline = pickle.load(file)
    return loaded_pipeline

# 예측 함수 정의
def predict(construction_type, underground_floors, aboveground_floors, total_area, 
            land_area, building_area, landscape_area, parking_lot_count, order_year, 
            order_month, construction_period, location, building_purpose):
            
    new_project = {
        '구조': [construction_type],
        '지하층수': [underground_floors],
        '지상층수': [aboveground_floors],
        '연면적': [total_area],
        '대지면적': [land_area],
        '건축면적': [building_area],
        '조경면적': [landscape_area],
        '주차수': [parking_lot_count],
        '발주년': [order_year],  
        '발주월': [order_month],  
        '공사기간': [construction_period],
        '현장위치': [location],
        '건축법상용도': [building_purpose],
    }
    
    model = load_model()
    prediction = model.predict(pd.DataFrame.from_dict(new_project))
    return prediction[0].tolist()

# Gradio 인터페이스 생성
iface = gr.Interface(
    fn=predict,
    inputs=[
        gr.Textbox(label="구조"),
        gr.Number(label="지하층수"),
        gr.Number(label="지상층수"),
        gr.Number(label="연면적(m2)"),
        gr.Number(label="대지면적(m2)"),
        gr.Number(label="건축면적(m2)"),
        gr.Number(label="조경면적(m2)"),
        gr.Number(label="주차대수"),
        gr.Number(label="발주년도"),
        gr.Dropdown(range(1, 13), label="발주월"),
        gr.Number(label="공사기간(일))"),
        gr.Textbox(label="현장위치(도/시)"),
        gr.Textbox(label="건축법상용도")
    ],
    outputs=[
        gr.Textbox(label="건축공사비"),
        gr.Textbox(label="기계공사비"),
        gr.Textbox(label="전기공사비"),
        gr.Textbox(label="통신공사비"),
        gr.Textbox(label="토목공사비"),
        gr.Textbox(label="조경공사비")
    ]
)

# Gradio 앱을 실행합니다.
iface.launch()