新增tracker&视频封面实时模糊（未启用）&搜索页面改进

.gitignore

@@ -1,6 +1,6 @@
 /.nyc_output
 /coverage
-/node_modules
+**/node_modules/
 /sign
 /dist
 /build

package.json

@@ -55,6 +55,7 @@
   },
   "dependencies": {
     "dayjs": "^1.11.13",
+    "jpeg-js": "^0.4.4",
     "semver": "^7.6.3"
   }
 }

prototype/image-color-pick-gen/index.ts

@@ -0,0 +1,422 @@
+import * as fs from 'fs';
+import * as jpeg from 'jpeg-js';
+
+/** 
+ * 用于表示像素的 RGB 颜色 
+ * [r, g, b] 每个范围 0~255
+ */
+type Color = [number, number, number];
+
+/*************************************************************************
+ * 1. 使用 jpeg-js 解码 JPG，并抽取像素用于 K-means
+ *************************************************************************/
+
+/**
+ * 从指定文件读取并解码 JPG 得到原始 RGBA 像素数据。
+ * @param filePath 
+ * @returns { data: Uint8Array; width: number; height: number }
+ */
+function decodeJpg(filePath: string) {
+  const jpgBuffer = fs.readFileSync(filePath);
+  // jpeg.decode 返回 { data: Buffer, width, height }
+  // data 是 RGBA (width * height * 4)
+  const decoded = jpeg.decode(jpgBuffer, { useTArray: true });
+  return {
+    data: decoded.data,   // Uint8Array，顺序 RGBA
+    width: decoded.width,
+    height: decoded.height,
+  };
+}
+
+/**
+ * 计算两种颜色(RGB)的欧几里得距离
+ */
+function distance(c1: Color, c2: Color): number {
+  const dr = c1[0] - c2[0];
+  const dg = c1[1] - c2[1];
+  const db = c1[2] - c2[2];
+  return Math.sqrt(dr * dr + dg * dg + db * db);
+}
+
+/*************************************************************************
+ * 2. K-means 聚类核心
+ *************************************************************************/
+
+/**
+ * 对给定像素集合执行 K-means 聚类，返回聚类中心（颜色）。
+ * @param pixels  所有像素的 RGB 数组
+ * @param k       聚类数量
+ * @param maxIterations 迭代次数上限
+ * @param tolerance     判断收敛的距离阈值
+ * @returns {Color[]} k 个聚类中心（RGB）
+ */
+function kMeansCluster(
+  pixels: Color[], 
+  k: number, 
+  maxIterations = 50, 
+  tolerance = 1.0
+): Color[] {
+  // 1. 随机初始化 k 个聚类中心 (从像素中随机选 k 个)
+  const centers: Color[] = [];
+  for (let i = 0; i < k; i++) {
+    const randomIndex = Math.floor(Math.random() * pixels.length);
+    centers.push([...pixels[randomIndex]] as Color);
+  }
+
+  // 用于存储每次迭代时每个像素的所属聚类
+  let assignments: number[] = new Array(pixels.length).fill(-1);
+
+  for (let iter = 0; iter < maxIterations; iter++) {
+    // 记录旧中心，用于判断收敛
+    const oldCenters = centers.map((c) => [...c]) as Color[];
+
+    // 2.1 为每个像素找到离自己最近的中心
+    for (let pIndex = 0; pIndex < pixels.length; pIndex++) {
+      let minDist = Infinity;
+      let clusterIndex = 0;
+      for (let cIndex = 0; cIndex < k; cIndex++) {
+        const dist = distance(pixels[pIndex], centers[cIndex]);
+        if (dist < minDist) {
+          minDist = dist;
+          clusterIndex = cIndex;
+        }
+      }
+      assignments[pIndex] = clusterIndex;
+    }
+
+    // 2.2 重新计算每个聚类的中心(将同一个 cluster 里的所有像素平均值作为新的中心)
+    const sums: Color[] = new Array(k).fill([0, 0, 0]).map(() => [0, 0, 0]);
+    const counts: number[] = new Array(k).fill(0);
+
+    for (let pIndex = 0; pIndex < pixels.length; pIndex++) {
+      const clusterIndex = assignments[pIndex];
+      sums[clusterIndex][0] += pixels[pIndex][0];
+      sums[clusterIndex][1] += pixels[pIndex][1];
+      sums[clusterIndex][2] += pixels[pIndex][2];
+      counts[clusterIndex]++;
+    }
+
+    for (let cIndex = 0; cIndex < k; cIndex++) {
+      if (counts[cIndex] > 0) {
+        centers[cIndex][0] = sums[cIndex][0] / counts[cIndex];
+        centers[cIndex][1] = sums[cIndex][1] / counts[cIndex];
+        centers[cIndex][2] = sums[cIndex][2] / counts[cIndex];
+      }
+    }
+
+    // 2.3 判断是否收敛：新旧中心之间的最大移动距离 < tolerance
+    let maxShift = 0;
+    for (let cIndex = 0; cIndex < k; cIndex++) {
+      const shift = distance(centers[cIndex], oldCenters[cIndex]);
+      if (shift > maxShift) {
+        maxShift = shift;
+      }
+    }
+    if (maxShift < tolerance) {
+      // 收敛
+      break;
+    }
+  }
+
+  // 返回最终的 k 个聚类中心(颜色分量取整)
+  return centers.map(c => [
+    Math.round(c[0]),
+    Math.round(c[1]),
+    Math.round(c[2])
+  ] as Color);
+}
+
+/**
+ * 提取 3 个主要颜色主流程：
+ *   1. 读取并解码图片 -> RGBA
+ *   2. 抽取 (R,G,B) 像素
+ *   3. 用 K-means 求得 3 个主要颜色
+ */
+function extractTop3Colors(filePath: string): Color[] {
+  console.log(`[INFO] decoding JPG: ${filePath}`);
+  const { data, width, height } = decodeJpg(filePath);
+
+  // data: RGBA，(width * height * 4)
+  const sampleStep = Math.max(1, Math.floor((width * height) / 20000));
+
+  const pixels: Color[] = [];
+  for (let i = 0; i < width * height; i += sampleStep) {
+    const r = data[i * 4 + 0];
+    const g = data[i * 4 + 1];
+    const b = data[i * 4 + 2];
+    // alpha 通常忽略
+    pixels.push([r, g, b]);
+  }
+
+  console.log(`[INFO] Running K-means for 3 clusters (sample size = ${pixels.length})...`);
+  const k = 3;
+  const centers = kMeansCluster(pixels, k);
+
+  return centers;
+}
+
+/*************************************************************************
+ * 3. 在新图上绘制 3 个「从圆心色 -> 背景透明」的圆，并保存为 JPG
+ *************************************************************************/
+
+/** 画布大小 */
+const CANVAS_WIDTH = 430;
+const CANVAS_HEIGHT = 250;
+
+/** 背景颜色 */
+const BACKGROUND_COLOR: [number, number, number, number] = [0, 0, 0, 255];
+
+/**
+ * 圆心/半径的范围，可自行修改：
+ *   - 圆心距离画布边缘至少 MARGIN 
+ *   - 半径范围 [MIN_RADIUS, MAX_RADIUS]
+ */
+const MARGIN = 2;
+const MIN_RADIUS = 80;
+const MAX_RADIUS = 110;
+
+/**
+ * 圆与圆之间的最小距离（基于圆心与圆心之间的距离减去半径之和）。
+ * 如果希望**完全不重叠**，可令:
+ *   distanceBetweenCenters >= (r1 + r2 + MIN_GAP_BETWEEN_CIRCLES).
+ */
+const MIN_GAP_BETWEEN_CIRCLES = 20;
+
+/**
+ * 新增：圆心颜色亮度因子 (0~1)，用于降低圆心过亮
+ * 例如：0.8 -> 稍微暗一点；0.5 -> 明显暗
+ */
+const COLOR_BRIGHTNESS_FACTOR = 0.62;
+
+/**
+ * 对 RGBA 像素进行 alpha 混合：
+ *   outA = srcA + dstA * (1 - srcA)
+ *   outRGB = (srcRGB * srcA + dstRGB * dstA * (1 - srcA)) / outA
+ *
+ * data 数组中每像素 4 通道：R, G, B, A，值范围 [0,255]
+ * alpha 范围 [0,1]
+ */
+function alphaBlendPixel(
+  data: Uint8Array, 
+  x: number, 
+  y: number, 
+  width: number, 
+  color: Color, 
+  alpha: number
+) {
+  const offset = (y * width + x) * 4;
+  const dstR = data[offset + 0];
+  const dstG = data[offset + 1];
+  const dstB = data[offset + 2];
+  const dstA = data[offset + 3] / 255; // 转为 0~1
+
+  const srcR = color[0];
+  const srcG = color[1];
+  const srcB = color[2];
+  const srcA = alpha;
+
+  const outA = srcA + dstA * (1 - srcA);
+  if (outA > 0) {
+    const outR = (srcR * srcA + dstR * dstA * (1 - srcA)) / outA;
+    const outG = (srcG * srcA + dstG * dstA * (1 - srcA)) / outA;
+    const outB = (srcB * srcA + dstB * dstA * (1 - srcA)) / outA;
+
+    data[offset + 0] = Math.round(outR);
+    data[offset + 1] = Math.round(outG);
+    data[offset + 2] = Math.round(outB);
+    data[offset + 3] = Math.round(outA * 255);
+  } else {
+    // outA=0 -> 全透明
+    data[offset + 0] = 0;
+    data[offset + 1] = 0;
+    data[offset + 2] = 0;
+    data[offset + 3] = 0;
+  }
+}
+
+/**
+ * 在 data 上绘制一个「从 centerColor->背景透明」的径向渐变圆
+ * @param data  画布（RGBA）
+ * @param width, height  画布尺寸
+ * @param cx, cy 圆心坐标
+ * @param radius 半径
+ * @param centerColor 圆心处的颜色 (RGB)
+ */
+function drawRadialGradientCircle(
+  data: Uint8Array, 
+  width: number,
+  height: number,
+  cx: number, 
+  cy: number,
+  radius: number,
+  centerColor: Color
+) {
+  // 仅在圆的外接矩形范围内绘制
+  const minX = Math.max(0, cx - radius);
+  const maxX = Math.min(width - 1, cx + radius);
+  const minY = Math.max(0, cy - radius);
+  const maxY = Math.min(height - 1, cy + radius);
+
+  for (let y = minY; y <= maxY; y++) {
+    for (let x = minX; x <= maxX; x++) {
+      const dx = x - cx;
+      const dy = y - cy;
+      const dist = Math.sqrt(dx * dx + dy * dy);
+      if (dist <= radius) {
+        // 根据距离，计算该点的 alpha：
+        //   圆心 dist=0 -> alpha=1
+        //   半径 dist=radius -> alpha=0
+        const alpha = 1 - dist / radius;
+        alphaBlendPixel(data, x, y, width, centerColor, alpha);
+      }
+    }
+  }
+}
+
+/** 
+ * 工具函数：判断新圆 (cx, cy, r) 与已放置的圆数组 placedCircles
+ * 是否满足“互不重叠”，即： 
+ *   distanceBetweenCenters >= (r + oldCircle.r + MIN_GAP_BETWEEN_CIRCLES)
+ */
+function canPlaceCircle(
+  cx: number, 
+  cy: number, 
+  r: number, 
+  placedCircles: { cx: number, cy: number, r: number }[],
+  minGap: number
+): boolean {
+  for (const c of placedCircles) {
+    const dist = Math.sqrt((cx - c.cx) ** 2 + (cy - c.cy) ** 2);
+    // 如果距离 < 两个半径和 + minGap，就判定为重叠
+    if (dist < (r + c.r + minGap)) {
+      return false;
+    }
+  }
+  return true;
+}
+
+/**
+ * 生成画布并绘制 3 个不会彼此重叠的渐变圆
+ * @param colors 3 个原始颜色 (RGB)
+ */
+function generateCirclesImage(colors: Color[]): { data: Uint8Array; width: number; height: number } {
+  const width = CANVAS_WIDTH;
+  const height = CANVAS_HEIGHT;
+
+  // 1. 创建画布并填充背景
+  const data = new Uint8Array(width * height * 4);
+  for (let i = 0; i < width * height; i++) {
+    data[i * 4 + 0] = BACKGROUND_COLOR[0];
+    data[i * 4 + 1] = BACKGROUND_COLOR[1];
+    data[i * 4 + 2] = BACKGROUND_COLOR[2];
+    data[i * 4 + 3] = BACKGROUND_COLOR[3];
+  }
+
+  // 2. 依次为 3 个颜色生成圆，确保不重叠
+  const placedCircles: { cx: number; cy: number; r: number }[] = [];
+  for (let i = 0; i < 3; i++) {
+    let circlePlaced = false;
+
+    // 最多尝试多次，若都无法放置，就跳过
+    const MAX_TRIES = 100;
+
+    const radius = randInt(MIN_RADIUS, MAX_RADIUS);
+    var cx = 0;
+    var cy = 0;
+    for (let attempt = 0; attempt < MAX_TRIES; attempt++) {
+      cx = randInt(radius + MARGIN, width - radius - MARGIN);
+      cy = randInt(radius + MARGIN, height - radius - MARGIN);
+
+      if (canPlaceCircle(cx, cy, radius, placedCircles, MIN_GAP_BETWEEN_CIRCLES)) {
+        // 找到不重叠的位置了
+        placedCircles.push({ cx, cy, r: radius });
+        circlePlaced = true;
+        break;
+      }
+    }
+
+    if (!circlePlaced) {
+      console.warn(
+        `[WARN] 无法在 ${MAX_TRIES} 次随机尝试中给第${i + 1}个圆找到合适位置，但仍然绘制。`
+      );
+      placedCircles.push({ cx, cy, r: radius });
+    }
+  }
+
+  // 3. 把成功放置的圆绘制到画布
+  //    在这里应用 COLOR_BRIGHTNESS_FACTOR，降低每个圆心的RGB
+  placedCircles.forEach((c, idx) => {
+    // 取对应颜色(若 idx>=colors.length，可加保护)
+    const origColor = colors[idx] || [255, 255, 255];
+    // 调整亮度
+    const adjustedColor: Color = [
+      Math.min(255, Math.max(0, origColor[0] * COLOR_BRIGHTNESS_FACTOR)),
+      Math.min(255, Math.max(0, origColor[1] * COLOR_BRIGHTNESS_FACTOR)),
+      Math.min(255, Math.max(0, origColor[2] * COLOR_BRIGHTNESS_FACTOR)),
+    ];
+
+    console.log(
+      `[INFO] Circle #${idx + 1}: center=(${c.cx},${c.cy}), radius=${c.r}, color=${adjustedColor}`
+    );
+    drawRadialGradientCircle(data, width, height, c.cx, c.cy, c.r, adjustedColor);
+  });
+
+  return { data, width, height };
+}
+
+/**
+ * 将 RGBA 数据保存为 JPG 文件
+ */
+function saveAsJpeg(data: Uint8Array, width: number, height: number, outPath: string) {
+  const rawImageData = {
+    data: Buffer.from(data), // jpeg-js 需要 Buffer 类型
+    width,
+    height,
+  };
+  // 设定 jpg 质量
+  const jpegImageData = jpeg.encode(rawImageData, 80);
+  fs.writeFileSync(outPath, jpegImageData.data);
+  console.log(`[INFO] Saved: ${outPath}`);
+}
+
+/**
+ * 工具函数：在 [min, max] 范围内随机整数
+ */
+function randInt(min: number, max: number): number {
+  return Math.floor(Math.random() * (max - min + 1)) + min;
+}
+
+/*************************************************************************
+ * 4. 主函数：读取命令行参数并执行
+ *************************************************************************/
+
+function main() {
+  const args = process.argv.slice(2);
+  if (args.length < 1) {
+    console.log(`用法: node kmeans-colors.js <jpg文件路径>`);
+    process.exit(1);
+  }
+  const filePath = args[0];
+  if (!fs.existsSync(filePath)) {
+    console.error(`[ERROR] 文件不存在: ${filePath}`);
+    process.exit(2);
+  }
+
+  // 1) 提取 3 个主色
+  const top3Colors = extractTop3Colors(filePath);
+  console.log(`\n[RESULT] 主要颜色 (RGB):`);
+  top3Colors.forEach((c, idx) => {
+    console.log(`  #${idx + 1}: R=${c[0]}, G=${c[1]}, B=${c[2]}`);
+  });
+
+  // 2) 用这 3 个颜色在 400×400 的画布上绘制不重叠的渐变圆
+  const { data, width, height } = generateCirclesImage(top3Colors);
+
+  // 3) 保存结果为 JPG
+  const outPath = 'output-circles.jpg';
+  saveAsJpeg(data, width, height, outPath);
+}
+
+if (require.main === module) {
+  main();
+}

prototype/image-color-pick-gen/package-lock.json

@@ -0,0 +1,21 @@
+{
+  "name": "image-color-pick-gen",
+  "version": "1.0.0",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "name": "image-color-pick-gen",
+      "version": "1.0.0",
+      "license": "ISC",
+      "dependencies": {
+        "jpeg-js": "^0.4.4"
+      }
+    },
+    "node_modules/jpeg-js": {
+      "version": "0.4.4",
+      "resolved": "https://registry.npmjs.org/jpeg-js/-/jpeg-js-0.4.4.tgz",
+      "integrity": "sha512-WZzeDOEtTOBK4Mdsar0IqEU5sMr3vSV2RqkAIzUEV2BHnUfKGyswWFPFwK5EeDo93K3FohSHbLAjj0s1Wzd+dg=="
+    }
+  }
+}

prototype/image-color-pick-gen/package.json

@@ -0,0 +1,14 @@
+{
+  "name": "image-color-pick-gen",
+  "version": "1.0.0",
+  "description": "",
+  "main": "index.js",
+  "scripts": {
+    "test": "echo \"Error: no test specified\" && exit 1"
+  },
+  "author": "",
+  "license": "ISC",
+  "dependencies": {
+    "jpeg-js": "^0.4.4"
+  }
+}

prototype/image-color-pick-gen/test.ts

@@ -0,0 +1 @@
+console.log("1")

quickapp.config.js

@@ -33,6 +33,7 @@ module.exports = {
         },
         resolve: {
             alias: {
+                '@src': path.resolve(__dirname, 'src'),
                 '@components': path.resolve(__dirname, 'src/components'),
                 '@less': path.resolve(__dirname, 'src/less'),
                 '@protobuf': path.resolve(__dirname, 'src/protobuf'),

src/app.ux

@@ -13,6 +13,7 @@ import * as jumpcheck from "./jumpcheck"
 import * as htmlparser from "./htmlparser"
 import * as savedcontent from "./savedcontent"
 import * as bgimg from "./bgimg"
+import * as usertracker from "./usertracker"
 import logger from "./logger/logger"
 export default {
   dayjs: dayjs,

src/asyncapi/file.ts

@@ -0,0 +1,187 @@
+import { file } from '../tsimports'
+
+interface FileMoveOptions {
+    srcUri: string;
+    dstUri: string;
+}
+
+interface FileCopyOptions {
+    srcUri: string;
+    dstUri: string;
+}
+
+interface FileListOptions {
+    uri: string;
+}
+
+interface FileGetOptions {
+    uri: string;
+    recursive?: boolean;
+}
+
+interface FileDeleteOptions {
+    uri: string;
+}
+
+interface FileWriteTextOptions {
+    uri: string;
+    text: string;
+    encoding?: string;
+    append?: boolean;
+}
+
+interface FileWriteArrayBufferOptions {
+    uri: string;
+    buffer: Uint8Array;
+    position?: number;
+    append?: boolean;
+}
+
+interface FileReadTextOptions {
+    uri: string;
+    encoding?: string;
+}
+
+interface FileReadArrayBufferOptions {
+    uri: string;
+    position?: number;
+    length?: number;
+}
+
+interface FileAccessOptions {
+    uri: string;
+}
+
+interface FileMkdirOptions {
+    uri: string;
+    recursive?: boolean;
+}
+
+interface FileRmdirOptions {
+    uri: string;
+    recursive?: boolean;
+}
+
+class FileAPI {
+    async move(options: FileMoveOptions): Promise<string> {
+        return new Promise((resolve, reject) => {
+            file.move({
+                ...options,
+                success: (uri: string) => resolve(uri),
+                fail: (_, code: number) => reject(new Error(`Move failed with code ${code}`)),
+            });
+        });
+    }
+
+    async copy(options: FileCopyOptions): Promise<string> {
+        return new Promise((resolve, reject) => {
+            file.copy({
+                ...options,
+                success: (uri: string) => resolve(uri),
+                fail: (_, code: number) => reject(new Error(`Copy failed with code ${code}`)),
+            });
+        });
+    }
+
+    async list(options: FileListOptions): Promise<{ fileList: { uri: string; lastModifiedTime: number; length: number }[] }> {
+        return new Promise((resolve, reject) => {
+            file.list({
+                ...options,
+                success: (data: { fileList: { uri: string; lastModifiedTime: number; length: number }[] }) => resolve(data),
+                fail: (_, code: number) => reject(new Error(`List failed with code ${code}`)),
+            });
+        });
+    }
+
+    async get(options: FileGetOptions): Promise<{ uri: string; length: number; lastModifiedTime: number; type: string; subFiles?: any[] }> {
+        return new Promise((resolve, reject) => {
+            file.get({
+                ...options,
+                success: (data: any) => resolve(data),
+                fail: (_, code: number) => reject(new Error(`Get failed with code ${code}`)),
+            });
+        });
+    }
+
+    async delete(options: FileDeleteOptions): Promise<void> {
+        return new Promise((resolve, reject) => {
+            file.delete({
+                ...options,
+                success: () => resolve(),
+                fail: (_, code: number) => reject(new Error(`Delete failed with code ${code}`)),
+            });
+        });
+    }
+
+    async writeText(options: FileWriteTextOptions): Promise<void> {
+        return new Promise((resolve, reject) => {
+            file.writeText({
+                ...options,
+                success: () => resolve(),
+                fail: (_, code: number) => reject(new Error(`WriteText failed with code ${code}`)),
+            });
+        });
+    }
+
+    async writeArrayBuffer(options: FileWriteArrayBufferOptions): Promise<void> {
+        return new Promise((resolve, reject) => {
+            file.writeArrayBuffer({
+                ...options,
+                success: () => resolve(),
+                fail: (_, code: number) => reject(new Error(`WriteArrayBuffer failed with code ${code}`)),
+            });
+        });
+    }
+
+    async readText(options: FileReadTextOptions): Promise<string> {
+        return new Promise((resolve, reject) => {
+            file.readText({
+                ...options,
+                success: (data: { text: string }) => resolve(data.text),
+                fail: (_, code: number) => reject(new Error(`ReadText failed with code ${code}`)),
+            });
+        });
+    }
+
+    async readArrayBuffer(options: FileReadArrayBufferOptions): Promise<Uint8Array> {
+        return new Promise((resolve, reject) => {
+            file.readArrayBuffer({
+                ...options,
+                success: (data: { buffer: Uint8Array }) => resolve(data.buffer),
+                fail: (_, code: number) => reject(new Error(`ReadArrayBuffer failed with code ${code}`)),
+            });
+        });
+    }
+
+    async access(options: FileAccessOptions): Promise<boolean> {
+        return new Promise((resolve, reject) => {
+            file.access({
+                ...options,
+                success: () => resolve(true),
+                fail: (_, code: number) => reject(new Error(`Access failed with code ${code}`)),
+            });
+        });
+    }
+
+    async mkdir(options: FileMkdirOptions): Promise<void> {
+        return new Promise((resolve, reject) => {
+            file.mkdir({
+                ...options,
+                success: () => resolve(),
+                fail: (_, code: number) => reject(new Error(`Mkdir failed with code ${code}`)),
+            });
+        });
+    }
+
+    async rmdir(options: FileRmdirOptions): Promise<void> {
+        return new Promise((resolve, reject) => {
+            file.rmdir({
+                ...options,
+                success: () => resolve(),
+                fail: (_, code: number) => reject(new Error(`Rmdir failed with code ${code}`)),
+            });
+        });
+    }
+}
+
+export const asyncFile = new FileAPI();

src/asyncapi/storage.ts

@@ -0,0 +1,58 @@
+import { storage } from "../tsimports";
+
+interface StorageGetOptions {
+    key: string;
+    default?: string;
+}
+
+interface StorageSetOptions {
+    key: string;
+    value: string;
+}
+
+interface StorageDeleteOptions {
+    key: string;
+}
+
+class StorageAPI {
+    async get(options: StorageGetOptions): Promise<string> {
+        return new Promise((resolve, reject) => {
+            storage.get({
+                ...options,
+                success: (data: string) => resolve(data),
+                fail: (_, code: number) => reject(new Error(`Get failed with code ${code}`)),
+            });
+        });
+    }
+
+    async set(options: StorageSetOptions): Promise<void> {
+        return new Promise((resolve, reject) => {
+            storage.set({
+                ...options,
+                success: () => resolve(),
+                fail: (_, code: number) => reject(new Error(`Set failed with code ${code}`)),
+            });
+        });
+    }
+
+    async clear(): Promise<void> {
+        return new Promise((resolve, reject) => {
+            storage.clear({
+                success: () => resolve(),
+                fail: (_, code: number) => reject(new Error(`Clear failed with code ${code}`)),
+            });
+        });
+    }
+
+    async delete(options: StorageDeleteOptions): Promise<void> {
+        return new Promise((resolve, reject) => {
+            storage.delete({
+                ...options,
+                success: () => resolve(),
+                fail: (_, code: number) => reject(new Error(`Delete failed with code ${code}`)),
+            });
+        });
+    }
+}
+
+export const asyncStorage = new StorageAPI();

src/components/BetterOnlineImage/BetterOnlineImage.ux

@@ -85,6 +85,9 @@ export default {
                     token: data.token,
                     success: (data) => {
                         global.logger.log("[BetterOnlineImage] Image Saved in: " + data.uri)
+                        this.$emit('loaded', {
+                            uri: data.uri
+                        })
                         this.localsrc = data.uri
                         this.show_loading = false
                         this.show_image = true

src/image/jpegkmeans.ts

@@ -0,0 +1,419 @@
+import * as jpeg from 'jpeg-js';
+import { asyncFile } from '../asyncapi/file';
+
+/** 
+ * 用于表示像素的 RGB 颜色 
+ * [r, g, b] 每个范围 0~255
+ */
+type Color = [number, number, number];
+
+/*************************************************************************
+ * 1. 使用 jpeg-js 解码 JPG，并抽取像素用于 K-means
+ *************************************************************************/
+
+/**
+ * 从指定文件读取并解码 JPG 得到原始 RGBA 像素数据。
+ * @param filePath 
+ * @returns { data: Uint8Array; width: number; height: number }
+ */
+async function decodeJpg(filePath: string) {
+  global.logger.log(`[INFO] JPG读取中`);
+  const jpgBuffer = await asyncFile.readArrayBuffer({ uri: filePath });
+  // jpeg.decode 返回 { data: Buffer, width, height }
+  // data 是 RGBA (width * height * 4)
+  global.logger.log(`[INFO] 调用JPEG库解码JPG`);
+  const decoded = jpeg.decode(jpgBuffer, { useTArray: true });
+  return {
+    data: decoded.data,   // Uint8Array，顺序 RGBA
+    width: decoded.width,
+    height: decoded.height,
+  };
+}
+
+/**
+ * 计算两种颜色(RGB)的欧几里得距离
+ */
+function distance(c1: Color, c2: Color): number {
+  const dr = c1[0] - c2[0];
+  const dg = c1[1] - c2[1];
+  const db = c1[2] - c2[2];
+  return Math.sqrt(dr * dr + dg * dg + db * db);
+}
+
+/*************************************************************************
+ * 2. K-means 聚类核心
+ *************************************************************************/
+
+/**
+ * 对给定像素集合执行 K-means 聚类，返回聚类中心（颜色）。
+ * @param pixels  所有像素的 RGB 数组
+ * @param k       聚类数量
+ * @param maxIterations 迭代次数上限
+ * @param tolerance     判断收敛的距离阈值
+ * @returns {Color[]} k 个聚类中心（RGB）
+ */
+function kMeansCluster(
+  pixels: Color[],
+  k: number,
+  maxIterations = 50,
+  tolerance = 1.0
+): Color[] {
+  // 1. 随机初始化 k 个聚类中心 (从像素中随机选 k 个)
+  const centers: Color[] = [];
+  for (let i = 0; i < k; i++) {
+    const randomIndex = Math.floor(Math.random() * pixels.length);
+    centers.push([...pixels[randomIndex]] as Color);
+  }
+
+  // 用于存储每次迭代时每个像素的所属聚类
+  let assignments: number[] = new Array(pixels.length).fill(-1);
+
+  for (let iter = 0; iter < maxIterations; iter++) {
+    // 记录旧中心，用于判断收敛
+    const oldCenters = centers.map((c) => [...c]) as Color[];
+
+    // 2.1 为每个像素找到离自己最近的中心
+    for (let pIndex = 0; pIndex < pixels.length; pIndex++) {
+      let minDist = Infinity;
+      let clusterIndex = 0;
+      for (let cIndex = 0; cIndex < k; cIndex++) {
+        const dist = distance(pixels[pIndex], centers[cIndex]);
+        if (dist < minDist) {
+          minDist = dist;
+          clusterIndex = cIndex;
+        }
+      }
+      assignments[pIndex] = clusterIndex;
+    }
+
+    // 2.2 重新计算每个聚类的中心(将同一个 cluster 里的所有像素平均值作为新的中心)
+    const sums: Color[] = new Array(k).fill([0, 0, 0]).map(() => [0, 0, 0]);
+    const counts: number[] = new Array(k).fill(0);
+
+    for (let pIndex = 0; pIndex < pixels.length; pIndex++) {
+      const clusterIndex = assignments[pIndex];
+      sums[clusterIndex][0] += pixels[pIndex][0];
+      sums[clusterIndex][1] += pixels[pIndex][1];
+      sums[clusterIndex][2] += pixels[pIndex][2];
+      counts[clusterIndex]++;
+    }
+
+    for (let cIndex = 0; cIndex < k; cIndex++) {
+      if (counts[cIndex] > 0) {
+        centers[cIndex][0] = sums[cIndex][0] / counts[cIndex];
+        centers[cIndex][1] = sums[cIndex][1] / counts[cIndex];
+        centers[cIndex][2] = sums[cIndex][2] / counts[cIndex];
+      }
+    }
+
+    // 2.3 判断是否收敛：新旧中心之间的最大移动距离 < tolerance
+    let maxShift = 0;
+    for (let cIndex = 0; cIndex < k; cIndex++) {
+      const shift = distance(centers[cIndex], oldCenters[cIndex]);
+      if (shift > maxShift) {
+        maxShift = shift;
+      }
+    }
+    if (maxShift < tolerance) {
+      // 收敛
+      break;
+    }
+  }
+
+  // 返回最终的 k 个聚类中心(颜色分量取整)
+  return centers.map(c => [
+    Math.round(c[0]),
+    Math.round(c[1]),
+    Math.round(c[2])
+  ] as Color);
+}
+
+/**
+ * 提取 3 个主要颜色主流程：
+ *   1. 读取并解码图片 -> RGBA
+ *   2. 抽取 (R,G,B) 像素
+ *   3. 用 K-means 求得 3 个主要颜色
+ */
+async function extractTop3Colors(filePath: string): Promise<Color[]> {
+  global.logger.log(`[INFO] decoding JPG: ${filePath}`);
+  const { data, width, height } = await decodeJpg(filePath);
+
+  // data: RGBA，(width * height * 4)
+  const sampleStep = Math.max(1, Math.floor((width * height) / 20000));
+
+  const pixels: Color[] = [];
+  for (let i = 0; i < width * height; i += sampleStep) {
+    const r = data[i * 4 + 0];
+    const g = data[i * 4 + 1];
+    const b = data[i * 4 + 2];
+    // alpha 通常忽略
+    pixels.push([r, g, b]);
+  }
+
+  global.logger.log(`[INFO] Running K-means for 3 clusters (sample size = ${pixels.length})...`);
+  const k = 3;
+  const centers = kMeansCluster(pixels, k);
+
+  return centers;
+}
+
+/*************************************************************************
+ * 3. 在新图上绘制 3 个「从圆心色 -> 背景透明」的圆，并保存为 JPG
+ *************************************************************************/
+
+/** 画布大小 */
+const CANVAS_WIDTH = 430;
+const CANVAS_HEIGHT = 250;
+
+/** 背景颜色 */
+const BACKGROUND_COLOR: [number, number, number, number] = [0, 0, 0, 255];
+
+/**
+ * 圆心/半径的范围，可自行修改：
+ *   - 圆心距离画布边缘至少 MARGIN 
+ *   - 半径范围 [MIN_RADIUS, MAX_RADIUS]
+ */
+const MARGIN = 2;
+const MIN_RADIUS = 80;
+const MAX_RADIUS = 110;
+
+/**
+ * 圆与圆之间的最小距离（基于圆心与圆心之间的距离减去半径之和）。
+ * 如果希望**完全不重叠**，可令:
+ *   distanceBetweenCenters >= (r1 + r2 + MIN_GAP_BETWEEN_CIRCLES).
+ */
+const MIN_GAP_BETWEEN_CIRCLES = 20;
+
+/**
+ * 新增：圆心颜色亮度因子 (0~1)，用于降低圆心过亮
+ * 例如：0.8 -> 稍微暗一点；0.5 -> 明显暗
+ */
+const COLOR_BRIGHTNESS_FACTOR = 0.62;
+
+/**
+ * 对 RGBA 像素进行 alpha 混合：
+ *   outA = srcA + dstA * (1 - srcA)
+ *   outRGB = (srcRGB * srcA + dstRGB * dstA * (1 - srcA)) / outA
+ *
+ * data 数组中每像素 4 通道：R, G, B, A，值范围 [0,255]
+ * alpha 范围 [0,1]
+ */
+function alphaBlendPixel(
+  data: Uint8Array,
+  x: number,
+  y: number,
+  width: number,
+  color: Color,
+  alpha: number
+) {
+  const offset = (y * width + x) * 4;
+  const dstR = data[offset + 0];
+  const dstG = data[offset + 1];
+  const dstB = data[offset + 2];
+  const dstA = data[offset + 3] / 255; // 转为 0~1
+
+  const srcR = color[0];
+  const srcG = color[1];
+  const srcB = color[2];
+  const srcA = alpha;
+
+  const outA = srcA + dstA * (1 - srcA);
+  if (outA > 0) {
+    const outR = (srcR * srcA + dstR * dstA * (1 - srcA)) / outA;
+    const outG = (srcG * srcA + dstG * dstA * (1 - srcA)) / outA;
+    const outB = (srcB * srcA + dstB * dstA * (1 - srcA)) / outA;
+
+    data[offset + 0] = Math.round(outR);
+    data[offset + 1] = Math.round(outG);
+    data[offset + 2] = Math.round(outB);
+    data[offset + 3] = Math.round(outA * 255);
+  } else {
+    // outA=0 -> 全透明
+    data[offset + 0] = 0;
+    data[offset + 1] = 0;
+    data[offset + 2] = 0;
+    data[offset + 3] = 0;
+  }
+}
+
+/**
+ * 在 data 上绘制一个「从 centerColor->背景透明」的径向渐变圆
+ * @param data  画布（RGBA）
+ * @param width, height  画布尺寸
+ * @param cx, cy 圆心坐标
+ * @param radius 半径
+ * @param centerColor 圆心处的颜色 (RGB)
+ */
+function drawRadialGradientCircle(
+  data: Uint8Array,
+  width: number,
+  height: number,
+  cx: number,
+  cy: number,
+  radius: number,
+  centerColor: Color
+) {
+  // 仅在圆的外接矩形范围内绘制
+  const minX = Math.max(0, cx - radius);
+  const maxX = Math.min(width - 1, cx + radius);
+  const minY = Math.max(0, cy - radius);
+  const maxY = Math.min(height - 1, cy + radius);
+
+  for (let y = minY; y <= maxY; y++) {
+    for (let x = minX; x <= maxX; x++) {
+      const dx = x - cx;
+      const dy = y - cy;
+      const dist = Math.sqrt(dx * dx + dy * dy);
+      if (dist <= radius) {
+        // 根据距离，计算该点的 alpha：
+        //   圆心 dist=0 -> alpha=1
+        //   半径 dist=radius -> alpha=0
+        const alpha = 1 - dist / radius;
+        alphaBlendPixel(data, x, y, width, centerColor, alpha);
+      }
+    }
+  }
+}
+
+/** 
+ * 工具函数：判断新圆 (cx, cy, r) 与已放置的圆数组 placedCircles
+ * 是否满足“互不重叠”，即： 
+ *   distanceBetweenCenters >= (r + oldCircle.r + MIN_GAP_BETWEEN_CIRCLES)
+ */
+function canPlaceCircle(
+  cx: number,
+  cy: number,
+  r: number,
+  placedCircles: { cx: number, cy: number, r: number }[],
+  minGap: number
+): boolean {
+  for (const c of placedCircles) {
+    const dist = Math.sqrt((cx - c.cx) ** 2 + (cy - c.cy) ** 2);
+    // 如果距离 < 两个半径和 + minGap，就判定为重叠
+    if (dist < (r + c.r + minGap)) {
+      return false;
+    }
+  }
+  return true;
+}
+
+/**
+ * 生成画布并绘制 3 个不会彼此重叠的渐变圆
+ * @param colors 3 个原始颜色 (RGB)
+ */
+function generateCirclesImage(colors: Color[]): { data: Uint8Array; width: number; height: number } {
+  const width = CANVAS_WIDTH;
+  const height = CANVAS_HEIGHT;
+
+  // 1. 创建画布并填充背景
+  const data = new Uint8Array(width * height * 4);
+  for (let i = 0; i < width * height; i++) {
+    data[i * 4 + 0] = BACKGROUND_COLOR[0];
+    data[i * 4 + 1] = BACKGROUND_COLOR[1];
+    data[i * 4 + 2] = BACKGROUND_COLOR[2];
+    data[i * 4 + 3] = BACKGROUND_COLOR[3];
+  }
+
+  // 2. 依次为 3 个颜色生成圆，确保不重叠
+  const placedCircles: { cx: number; cy: number; r: number }[] = [];
+  for (let i = 0; i < 3; i++) {
+    let circlePlaced = false;
+
+    // 最多尝试多次，若都无法放置，就跳过
+    const MAX_TRIES = 100;
+
+    const radius = randInt(MIN_RADIUS, MAX_RADIUS);
+    var cx = 0;
+    var cy = 0;
+    for (let attempt = 0; attempt < MAX_TRIES; attempt++) {
+      cx = randInt(radius + MARGIN, width - radius - MARGIN);
+      cy = randInt(radius + MARGIN, height - radius - MARGIN);
+
+      if (canPlaceCircle(cx, cy, radius, placedCircles, MIN_GAP_BETWEEN_CIRCLES)) {
+        // 找到不重叠的位置了
+        placedCircles.push({ cx, cy, r: radius });
+        circlePlaced = true;
+        break;
+      }
+    }
+
+    if (!circlePlaced) {
+      global.logger.warn(
+        `[WARN] 无法在 ${MAX_TRIES} 次随机尝试中给第${i + 1}个圆找到合适位置，但仍然绘制。`
+      );
+      placedCircles.push({ cx, cy, r: radius });
+    }
+  }
+
+  // 3. 把成功放置的圆绘制到画布
+  //    在这里应用 COLOR_BRIGHTNESS_FACTOR，降低每个圆心的RGB
+  placedCircles.forEach((c, idx) => {
+    // 取对应颜色(若 idx>=colors.length，可加保护)
+    const origColor = colors[idx] || [255, 255, 255];
+    // 调整亮度
+    const adjustedColor: Color = [
+      Math.min(255, Math.max(0, origColor[0] * COLOR_BRIGHTNESS_FACTOR)),
+      Math.min(255, Math.max(0, origColor[1] * COLOR_BRIGHTNESS_FACTOR)),
+      Math.min(255, Math.max(0, origColor[2] * COLOR_BRIGHTNESS_FACTOR)),
+    ];
+
+    global.logger.log(
+      `[INFO] Circle #${idx + 1}: center=(${c.cx},${c.cy}), radius=${c.r}, color=${adjustedColor}`
+    );
+    drawRadialGradientCircle(data, width, height, c.cx, c.cy, c.r, adjustedColor);
+  });
+
+  return { data, width, height };
+}
+
+/**
+ * 将 RGBA 数据保存为 JPG 文件
+ */
+async function saveAsJpeg(data: Uint8Array, width: number, height: number, outPath: string) {
+  const rawImageData = {
+    data: Buffer.from(data), // jpeg-js 需要 Buffer 类型
+    width,
+    height,
+  };
+  // 设定 jpg 质量
+  const jpegImageData = jpeg.encode(rawImageData, 80);
+  await asyncFile.writeArrayBuffer({
+    uri: outPath,
+    buffer: jpegImageData.data
+  });
+  global.logger.log(`[INFO] Saved: ${outPath}`);
+}
+
+/**
+ * 工具函数：在 [min, max] 范围内随机整数
+ */
+function randInt(min: number, max: number): number {
+  return Math.floor(Math.random() * (max - min + 1)) + min;
+}
+
+/**
+ * 使用Kmeans取色并生成最多三个渐变色圆形的blur背景图
+ */
+export async function kmeansCircleGradientImage(imgPath: string) {
+  global.logger.log(`[kmeansCircleGradientImage] 开始处理图片${imgPath}`)
+
+  // 提取 3 个主色
+  const top3Colors = await extractTop3Colors(imgPath);
+  global.logger.log(`\n[kmeansCircleGradientImage] 主要颜色 (RGB):`);
+  top3Colors.forEach((c, idx) => {
+    global.logger.log(`  #${idx + 1}: R=${c[0]}, G=${c[1]}, B=${c[2]}`);
+  });
+
+  global.logger.log(`[kmeansCircleGradientImage] 绘制图片取色模糊...`)
+
+  // 用这 3 个颜色在 400×400 的画布上绘制不重叠的渐变圆
+  const { data, width, height } = generateCirclesImage(top3Colors);
+
+  global.logger.log(`[kmeansCircleGradientImage] 输出result图片...`)
+
+  // 保存结果为 JPG
+  const outPath = 'internal://files/km-gen-tmp.jpg';
+  await saveAsJpeg(data, width, height, outPath);
+
+  global.logger.log(`[kmeansCircleGradientImage] 完成工作`)
+}

src/pages/search/searchresult/searchresult.less

@@ -20,7 +20,7 @@
 
 .swipermain {
     width: 100%;
-    height: 100%;
+    height: 97%;
 }
 
 .tiplabel {

src/pages/search/searchresult/searchresult.ux

@@ -25,14 +25,14 @@
             <div class="tiplabel" if="{{comprehensive_status.has_users_result}}">
               <text class="listtip">用户</text>
             </div>
-            <div style="width: 100%; height: 99px; justify-content: center"
+            <div style="width: 100%; justify-content: center"
               if="{{comprehensive_status.has_users_result}}">
               <user user="{{search.users[0]}}"></user>
             </div>
             <div class="tiplabel" style="margin-top: 10px" if="{{comprehensive_status.has_video_result}}">
               <text class="listtip">视频</text>
             </div>
-            <div style="width: 100%; height: 170px; justify-content: center"
+            <div style="width: 100%; justify-content: center"
               if="{{comprehensive_status.has_video_result}}" for="{{search.comprehensive_videos}}">
               <div style="width: 77%; justify-content: center; margin-top: 5px" onclick="OpenVideo({{$item.bvid}})">
                 <videoshow video="{{$item}}"></videoshow>
@@ -43,7 +43,7 @@
         </div>
         <div class="swiper_box">
           <scroll if="{{typebar_if.c2}}" class="swiper_container" scroll-y="true" @scroll="ScrollOverviewCheck">
-            <div style="width: 100%; height: 170px; justify-content: center" for="{{search.videos}}">
+            <div style="width: 100%; justify-content: center" for="{{search.videos}}">
               <div style="width: 77%; justify-content: center; margin-top: 5px" onclick="OpenVideo({{$item.bvid}})">
                 <videoshow video="{{$item}}"></videoshow>
               </div>
@@ -53,7 +53,7 @@
         </div>
         <div class="swiper_box">
           <scroll if="{{typebar_if.c3}}" class="swiper_container" scroll-y="true" @scroll="ScrollOverviewCheck">
-            <div style="width: 100%; height: 99px; justify-content: center; margin-top: 5px" for="{{search.users}}">
+            <div style="width: 100%; justify-content: center; margin-top: 5px" for="{{search.users}}">
               <user user="{{$item}}"></user>
             </div>
             <text style="margin-top: 30px"></text>

src/pages/video/videodetail/videodetail.less

@@ -1,10 +1,3 @@
-.vidpic {
-    border-radius: 20px;
-    width: 320px;
-    height: 150px;
-    margin-top: 31px;
-}
-
 .vidtitle {
     font-size: 20px;
     font-weight: 600;

src/pages/video/videodetail/videodetail.ux

@@ -1,12 +1,13 @@
 <import name="title-bar" src="@components/TitleBar/TitleBar.ux"></import>
 <import name="full-screen-input" src="@components/FullScreenInput/FullScreenInput.ux"></import>
 <import name="default-button" src="@components/DefaultButton/DefaultButton.ux"></import>
+<import name="online-image" src="@components/BetterOnlineImage/BetterOnlineImage.ux"></import>
 
 <template>
   <div class="page">
     <scroll scroll-y="true" class="scroll" bounces="true">
       <title-bar title="video.title"></title-bar>
-      <image src="{{vid.pic}}@319w_150h" alt="/common/grayloading_cn.png" class="vidpic"></image>
+      <online-image if="{{renderingCover}}" src="{{vid.pic}}@319w_150h" margin-top="30px" lock-size="true" width="320px" height="150px" loading-anim="true" @loaded="GenBlur"></online-image>
       <text class="vidtitle">{{ vid.title }}</text>
       <div class="statbar">
         <div class="stat">
@@ -62,6 +63,8 @@
 import router from "@system.router"
 import prompt from "@system.prompt"
 
+import { kmeansCircleGradientImage } from "@src/image/jpegkmeans.ts"
+
 export default {
   public: {
     bvid: 1 // 视频BVID
@@ -74,7 +77,8 @@ export default {
     likesrc: "/common/vidtool_like.png",
     coinsrc: "/common/vidtool_coin.png",
     starsrc: "/common/vidtool_star.png",
-    replymode: false
+    replymode: false,
+    renderingCover: false
   },
   onInit() {
     global.logger.log("[videodetail] load bvid: " + this.bvid);
@@ -88,6 +92,7 @@ export default {
   },
   async GetVideoDetail() {
     this.vid = await global.biliclient.getVideoInfoByBVID(this.bvid)
+    this.renderingCover = true
   },
   async UpdateVideoToolbarStatus() {
     this.stared = await global.biliclient.isVideoStaredByBVID(this.bvid)
@@ -176,6 +181,13 @@ export default {
     prompt.showToast({message})
     this.UpdateVideoToolbarStatus()
   },
+  async GenBlur(evt){
+    // 该Feature在现在任何设备上运行都会卡死，故注释
+    /*
+      global.logger.log(`\n[GenBlur] 开始处理封面取色模糊`);
+      await kmeansCircleGradientImage(evt.detail.uri)
+    */
+  },
   GoReplyArea() {
     router.push({
       uri: "pages/reply/replys",

src/savedcontent.ts

@@ -1,4 +1,4 @@
-import { file } from "./tsimports";
+import { asyncFile } from "./asyncapi/file";
 
 // 定义文件存储的基本结构
 interface StoredContent {
@@ -15,64 +15,15 @@ let storageIndex: StoredContent[] = [];
 const baseUri = 'internal://files/bilisavedcontent/';
 const indexFileUri = `${baseUri}index.json`; // 存储 storageIndex 的文件
 
-// 封装 file 接口的 Promise 方法
-function fileWrite(uri: string, data: string): Promise<void> {
-  return new Promise((resolve, reject) => {
-    file.writeText({
-      uri,
-      text: data,
-      success: () => resolve(),
-      fail: (data, code) => reject(`Failed to write to ${uri}: ${code}`)
-    });
-  });
-}
-
-function fileRead(uri: string): Promise<string> {
-  return new Promise((resolve, reject) => {
-    file.readText({
-      uri,
-      success: (data) => resolve(data.text),
-      fail: (data, code) => reject(`Failed to read from ${uri}: ${code}`)
-    });
-  });
-}
-
-function fileList(dirUri: string): Promise<any[]> {
-  return new Promise((resolve, reject) => {
-    file.list({
-      uri: dirUri,
-      success: (data) => resolve(data.fileList),
-      fail: (data, code) => reject(`Failed to list files in ${dirUri}: ${code}`)
-    });
-  });
-}
-
-function fileAccess(uri: string): Promise<boolean> {
-  return new Promise((resolve) => {
-    file.access({
-      uri,
-      success: () => resolve(true),
-      fail: () => resolve(false)
-    });
-  });
-}
-
-function fileDelete(uri: string): Promise<void> {
-  return new Promise((resolve, reject) => {
-    file.delete({
-      uri,
-      success: () => resolve(),
-      fail: (data, code) => reject(`Failed to delete ${uri}: ${code}`)
-    });
-  });
-}
-
 // 同步 storageIndex 到本地文件
 async function saveStorageIndex(): Promise<void> {
   try {
     global.logger.log(storageIndex)
     const indexData = JSON.stringify(storageIndex);
-    await fileWrite(indexFileUri, indexData);
+    await asyncFile.writeText({
+      uri: indexFileUri,
+      text: indexData
+    });
   } catch (e) {
     global.logger.error(`[SavedContentManager] saveStorageIndex Error: ${e.toString()}`);
   }
@@ -81,9 +32,9 @@ async function saveStorageIndex(): Promise<void> {
 // 从本地文件加载 storageIndex
 async function loadStorageIndex(): Promise<void> {
   try {
-    const fileExists = await fileAccess(indexFileUri);
+    const fileExists = await asyncFile.access({ uri: indexFileUri });
     if (fileExists) {
-      const indexData = await fileRead(indexFileUri);
+      const indexData = await asyncFile.readText({ uri: indexFileUri });
       storageIndex = JSON.parse(indexData);
     } else {
       storageIndex = [];
@@ -116,7 +67,7 @@ export class SavedContentManager {
       const fileUri = `${baseUri}${id}.txt`;
 
       // 写入文件
-      await fileWrite(fileUri, data);
+      await asyncFile.writeText({ uri: fileUri, text: data });
 
       // 更新 storageIndex 并保存
       storageIndex.push({ id, title, type, fileUri });
@@ -135,10 +86,10 @@ export class SavedContentManager {
       if (!content) return null;
 
       // 读取文件内容
-      const fileExists = await fileAccess(content.fileUri);
+      const fileExists = await asyncFile.access({ uri: content.fileUri });
       if (!fileExists) throw new Error(`File does not exist: ${content.fileUri}`);
 
-      return await fileRead(content.fileUri);
+      return await asyncFile.readText({ uri: content.fileUri });
     } catch (e) {
       global.logger.error(`[SavedContentManager] getContent Error: ${e.toString()}`);
       return null;
@@ -158,7 +109,7 @@ export class SavedContentManager {
 
       // 删除文件
       const fileUri = storageIndex[contentIndex].fileUri;
-      await fileDelete(fileUri);
+      await asyncFile.delete({ uri: fileUri });
 
       // 从 storageIndex 中删除记录并保存
       storageIndex.splice(contentIndex, 1);

src/usertracker.ts

@@ -1,7 +1,8 @@
 import dayjs from "dayjs"
 import { fetch } from "./tsimports"
 
-const TRACKER_URL: string = "https://tracker.hyperbili.astralsight.space/trackreport"
+//const TRACKER_URL: string = "https://tracker.hyperbili.astralsight.space/trackreport"
+const TRACKER_URL: string = "http://192.168.1.247:4080/trackreport"
 const TRACKER_SERVER_PROTOCOL_VERSION = "v1"
 
 interface TrackedInfoUploadPacket {
@@ -78,11 +79,17 @@ function uploadTrack(event: TIUPEvents, payload) {
     if (canUploadTrack()) {
         fetch.fetch({
             url: `${TRACKER_URL}/${TRACKER_SERVER_PROTOCOL_VERSION}/fetch`,
-            data
+            method: "POST",
+            data: JSON.stringify(data),
+            header: {
+                "Content-Type": "application/json"
+            }
         })
     }
 }
 
+setTimeout(() => {
     uploadTrack(TIUPEvents.ON_STARTUP, {
         startTime: dayjs().format()
     })
+}, 3000)

yarn.lock

@@ -5066,6 +5066,11 @@ jest-worker@^27.4.5:
     merge-stream "^2.0.0"
     supports-color "^8.0.0"
 
+jpeg-js@^0.4.4:
+  version "0.4.4"
+  resolved "https://registry.yarnpkg.com/jpeg-js/-/jpeg-js-0.4.4.tgz#a9f1c6f1f9f0fa80cdb3484ed9635054d28936aa"
+  integrity sha512-WZzeDOEtTOBK4Mdsar0IqEU5sMr3vSV2RqkAIzUEV2BHnUfKGyswWFPFwK5EeDo93K3FohSHbLAjj0s1Wzd+dg==
+
 js-tokens@^4.0.0:
   version "4.0.0"
   resolved "https://registry.yarnpkg.com/js-tokens/-/js-tokens-4.0.0.tgz#19203fb59991df98e3a287050d4647cdeaf32499"