app.py

import gradio as gr
import numpy as np
import joblib
import tensorflow as tf
from huggingface_hub import hf_hub_download

# 1) 허브에서 모델·스케일러 파일 다운로드
model_path = hf_hub_download(repo_id="dklee2013/rc-column-predictor",
                             filename="model0526.keras")
sx_path    = hf_hub_download(repo_id="dklee2013/rc-column-predictor",
                             filename="sx.save")
sy_path    = hf_hub_download(repo_id="dklee2013/rc-column-predictor",
                             filename="sy.save")

model    = tf.keras.models.load_model(model_path)
scaler_X = joblib.load(sx_path)
scaler_y = joblib.load(sy_path)

def predict(f_ck, f_yk, N_Ed, M_Edz, M_Edy, cover, rebar_dia, dc_ratio):
    # 1차 예측
    X1 = np.array([f_ck, f_yk, N_Ed, M_Edz, M_Edy, cover, rebar_dia]).reshape(1,-1)
    Y1 = scaler_y.inverse_transform(model.predict(scaler_X.transform(X1)))
    a  = Y1[0,5]

    # 모멘트 보정
    M_Edz_sc = M_Edz * (1/dc_ratio)**a
    M_Edy_sc = M_Edy * (1/dc_ratio)**a

    # 2차 예측
    X2 = np.array([f_ck, f_yk, N_Ed, M_Edz_sc, M_Edy_sc, cover, rebar_dia]).reshape(1,-1)
    Y2 = scaler_y.inverse_transform(model.predict(scaler_X.transform(X2)))

    # 결과
    b_pred = int(round(Y2[0,0]/50)*50)
    h_pred = int(round(Y2[0,1]/50)*50)
    rr     = float(Y2[0,2])
    rx     = int(round(Y2[0,3]))
    ry     = int(round(Y2[0,4]))
    z1_a   = float(Y2[0,5])
    z2_N   = float(Y2[0,6])
    z3_Mz  = float(Y2[0,7])
    z4_My  = float(Y2[0,8])
    SF     = (M_Edz / z3_Mz)**z1_a + (M_Edy / z4_My)**z1_a

    return (
      b_pred,
      h_pred,
      rr,
      rx,
      ry,
      z1_a,
      z2_N,
      z3_Mz,
      z4_My,
      SF
    )

# 3) Gradio UI 정의
inputs = [
  gr.Number(label="f_ck (MPa) 범위: 30,35,40,45,50", value=40),
  gr.Number(label="f_yk (MPa) 범위: 400, 500, 600", value=600),
  gr.Number(label="N_Ed (N) 범위: 200e3 ~ 800e3", value=455000),
  gr.Number(label="M_Edz (N·mm) 범위: 50e6 ~ 200e6", value=186200000),
  gr.Number(label="M_Edy (N·mm) 범위: 50e6 ~ 200e6", value=126100000),
  gr.Number(label="cover (mm) 고정", value=50),
  gr.Number(label="rebar_dia (mm) 범위: 16,20,25,32,40", value=20),
  gr.Number(label="Safety Factor", value=0.9, precision=2)
]

outputs = [
  gr.Number(label="b_pred (mm)"),
  gr.Number(label="h_pred (mm)"),
  gr.Number(label="reinforcement_ratio"),
  gr.Number(label="rebar_x (개)"),
  gr.Number(label="rebar_y (개)"),
  gr.Number(label="exponent a"),
  gr.Number(label="N_Rd (N)"),
  gr.Number(label="M_Rdz (N·mm)"),
  gr.Number(label="M_Rdy (N·mm)"),
  gr.Number(label="SF")
]

demo = gr.Interface(
    fn=predict,
    inputs=inputs,
    outputs=outputs,
    title="🔧 RC 기둥 단면 설계",
    description="Eurocode 2 기반 ML 모델"
)

if __name__ == "__main__":
    demo.launch()