import { app, ipcMain, shell } from "electron";
import { mkdir, stat } from "fs/promises";
import { db } from "../../core/db";
import log from "electron-log";
import path from "node:path";
import { getMetadata, getTotalScanLength } from "../../core/pacs";
import { InferStructuralEnum } from "../../core/alg.type";
import { readFileSync, statSync } from "fs";

export const registerCommonHandler = () => {
  ipcMain.handle("output:open", async (_event, SeriesInstanceUID) => {
    await db.read();
    const optPath = db.data.setting.outputPath;
    const resolvedPath = path.join(optPath, SeriesInstanceUID);
    try {
      // 检查路径是否存在
      const stats = await stat(resolvedPath);
      if (stats.isDirectory()) shell.openPath(resolvedPath);
    } catch (error) {
      log.error(error);
      await mkdir(resolvedPath, { recursive: true });
      shell.openPath(resolvedPath);
    }
  });

  ipcMain.handle("measure:excel", async (_event, SeriesInstanceUID) => {
    const excelPath = path.join(
      app.getPath("userData"),
      "output",
      SeriesInstanceUID
    );
    try {
      if (statSync(excelPath).isDirectory()) {
        shell.openPath(excelPath);
        return { code: 1 };
      }
    } catch (error) {
      return { code: 0, msg: "请先进行AI推理" };
    }
  });

  ipcMain.handle("measure:json", async (_event, SeriesInstanceUID) => {
    // 读取测量json
    const physicalLength = await getTotalScanLength(SeriesInstanceUID);
    const module =
      physicalLength && physicalLength < 200
        ? InferStructuralEnum.AORTA
        : InferStructuralEnum.PERI;
    // 获取metadata
    if (module !== InferStructuralEnum.AORTA)
      return { code: 0, msg: "仅开放根部测量报告" };
    const tags = await getMetadata(SeriesInstanceUID);
    const rootPath = path.join(
      app.getPath("userData"),
      "output",
      SeriesInstanceUID
    );
    const measurementPath = path.join(rootPath, module, "measurement.json");
    if (statSync(measurementPath).isFile()) {
      const measurement = readFileSync(measurementPath, "utf-8");
      return { measurement: JSON.parse(measurement), tags };
    } else {
      return { code: 0, msg: "请先进行AI推理" };
    }
  });
};