阶段1-rpa-core建包: engine+31个纯Node能力迁入packages/rpa-core, 领域类型单一源化, createEngine工厂收拢模块级状态

- engine/(registry/types/runtime/expression)物理迁入包, 解耦shared/types(域类型归包, 宿主type-only re-export)
- 31个纯Node能力+27个测试迁入包; 宿主留守Electron/浏览器/AI依赖能力, index.ts经@rpa/core/capabilities拉起
- 新增createEngine()/defaultEngine: excel缓存/Excel句柄/db连接/FTP客户端/OCR实例/拟真设置挂引擎实例
- remaining-core子流程依赖改为host-bridge注入, 包内不再import宿主flows
- 宿主main/index.ts启动时注入子流程源; electron-vite/vitest/tsconfig配@rpa/core源码别名
- 验证: typecheck绿, 快照909个id diff为零, 332测试过(2个桌面冒烟因会话无交互SetForegroundWindow被拒, 环境阻塞)

packages/rpa-core/src/capabilities/ocr-caps.ts

@@ -0,0 +1,116 @@
+import path from "node:path";
+import { promises as fs } from "node:fs";
+import { register } from "../engine/registry";
+import { RuntimeError } from "../engine/types";
+import { defaultEngine } from "../engine/engine";
+
+interface OcrWord { text: string; x: number; y: number; width: number; height: number; confidence: number }
+interface RapidOcrLine { text: string; mean: number; box?: number[][] }
+
+async function getOcr(): Promise<{ detect: (image: string) => Promise<{ texts: RapidOcrLine[] }> }> {
+  if (defaultEngine.ocrInstance) return defaultEngine.ocrInstance as { detect: (image: string) => Promise<{ texts: RapidOcrLine[] }> };
+  const mod = await import("@gutenye/ocr-node");
+  const instance = await mod.default.create();
+  defaultEngine.ocrInstance = instance;
+  return instance;
+}
+
+function requireImage(args: Record<string, unknown>, nodeId: string): string {
+  // uiSelector 是 OcrOffline_GetOcrTextNew 目录里唯一的图片字段（P0-1 修复）
+  for (const key of ["image_path", "imagePath", "file_path", "filePath", "path", "image", "pictureSource", "uiSelector"]) {
+    const v = String(args[key] ?? "").trim();
+    if (v) return v;
+  }
+  throw new RuntimeError("validation_error", "图片路径为空", { nodeId, componentId: nodeId, recommendation: "填写本地图片路径（png/jpg/bmp）" });
+}
+
+function boxToRect(box: number[][] | undefined): { x: number; y: number; width: number; height: number } {
+  const points = box ?? [];
+  const xs = points.map(p => p[0]);
+  const ys = points.map(p => p[1]);
+  const minX = Math.min(...(xs.length ? xs : [0]));
+  const minY = Math.min(...(ys.length ? ys : [0]));
+  const maxX = Math.max(...(xs.length ? xs : [0]));
+  const maxY = Math.max(...(ys.length ? ys : [0]));
+  return { x: minX, y: minY, width: maxX - minX, height: maxY - minY };
+}
+
+register("OcrOffline_GetOcrTextNew", async (ctx, node, args) => {
+  const imagePath = requireImage(args, node.id);
+  const ocr = await getOcr();
+  const result = await ocr.detect(imagePath);
+  const text = result.texts.map(t => t.text).join("\n");
+  ctx.log("OCR 识别完成：" + text.length + " 字符 / " + result.texts.length + " 行", "info", node.id);
+  return text;
+});
+
+register("OcrOffline_GetOcrTextPosition", async (ctx, node, args) => {
+  const imagePath = requireImage(args, node.id);
+  const ocr = await getOcr();
+  const result = await ocr.detect(imagePath);
+  const words = result.texts.map(t => {
+    const rect = boxToRect(t.box);
+    return { text: t.text, x: rect.x, y: rect.y, width: rect.width, height: rect.height, confidence: t.mean };
+  });
+  ctx.log("OCR 定位完成：" + words.length + " 行", "info", node.id);
+  return words;
+});
+
+/** 按垂直中心聚类成行（行高 60% 为阈值），行内按 x 排序，返回二维文本表格 */
+function groupOcrRows(words: RapidOcrLine[]): string[][] {
+  const prepared = words
+    .filter((word) => String(word.text ?? "").trim())
+    .map((word) => {
+      const box = word.box ?? [];
+      const xs = box.map((point) => point[0]);
+      const ys = box.map((point) => point[1]);
+      const x = xs.length ? Math.min(...xs) : 0;
+      const y = ys.length ? Math.min(...ys) : 0;
+      const height = ys.length ? Math.max(...ys) - y : 0;
+      return { text: word.text, x, cy: y + height / 2, h: height };
+    })
+    .sort((a, b) => a.cy - b.cy || a.x - b.x);
+  const rows: Array<{ cy: number; h: number; cells: typeof prepared }> = [];
+  let current: (typeof rows)[number] | null = null;
+  for (const item of prepared) {
+    if (!current || Math.abs(item.cy - current.cy) > Math.max(current.h, item.h, 8) * 0.6) {
+      current = { cy: item.cy, h: item.h, cells: [] };
+      rows.push(current);
+    }
+    current.cells.push(item);
+  }
+  return rows.map((row) => row.cells.sort((a, b) => a.x - b.x).map((cell) => cell.text.trim()));
+}
+
+register("OcrOffline_GetOcrTable", async (ctx, node, args) => {
+  const imagePath = requireImage(args, node.id);
+  const ocr = await getOcr();
+  const result = await ocr.detect(imagePath);
+  const rows = groupOcrRows(result.texts);
+  ctx.log("OCR 表格识别完成：" + rows.length + " 行", "info", node.id);
+
+  // showTable=1：写入流程数据表（与 Bivartable 系列组件共享同一份数据簿）
+  if (String(args.showTable ?? "1") === "1") {
+    ctx.vars["__rpaDatabook"] = rows;
+    ctx.log("已写入流程数据表", "info", node.id);
+  }
+
+  // isExcel=1：另存为 Excel 文件
+  let excelFile = "";
+  if (String(args.isExcel ?? "0") === "1") {
+    const ExcelJS = (await import("exceljs")).default;
+    const workbook = new ExcelJS.Workbook();
+    const sheet = workbook.addWorksheet("Sheet1");
+    sheet.addRows(rows);
+    const rawFolder = String(args.excelPath ?? "").trim();
+    // ${res} 流程资源目录占位与空值统一落到运行证据目录
+    const folder = rawFolder && rawFolder !== "${res}" ? rawFolder : ctx.evidenceDir;
+    const fileName = String(args.excelName ?? "表格数据.xlsx").replace(/\$\{randomString\}/g, Math.random().toString(36).slice(2, 8));
+    excelFile = path.resolve(path.isAbsolute(fileName) ? fileName : path.join(folder, fileName));
+    await fs.mkdir(path.dirname(excelFile), { recursive: true });
+    await workbook.xlsx.writeFile(excelFile);
+    ctx.log("已保存 Excel：" + excelFile, "info", node.id);
+  }
+
+  return excelFile ? { rows, excelFile } : rows;
+});