mirror of
https://wget.la/https://github.com/Wxw-Gu/WechatExplorer
synced 2026-10-03 18:33:14 +08:00
feat: 新增 Windows 本地图片文字识别能力
This commit is contained in:
电摇小子
@@ -19,6 +19,8 @@ asarUnpack:
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- node_modules/silk-wasm/**
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- node_modules/sherpa-onnx-node/**
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- node_modules/sherpa-onnx-*/**
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- node_modules/@napi-rs/system-ocr/**
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- node_modules/@napi-rs/system-ocr-*/**
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extraResources:
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# Keep the updater provider in every packaged Windows app. electron-builder also
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# regenerates this file during publish, using the same release configuration.
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@@ -16,7 +16,7 @@ export default defineConfig({
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output: {
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entryFileNames: '[name].js'
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},
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external: ['koffi', 'sherpa-onnx-node']
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external: ['koffi', 'sherpa-onnx-node', '@napi-rs/system-ocr']
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}
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}
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},
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@@ -79,6 +79,8 @@
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"@electron-toolkit/preload": "^3.0.2",
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"@electron-toolkit/utils": "^4.0.0",
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"@koromix/koffi-win32-x64": "3.1.0",
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"@napi-rs/system-ocr": "1.2.0",
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"@napi-rs/system-ocr-win32-x64-msvc": "1.2.0",
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"@radix-ui/react-alert-dialog": "^1.1.23",
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"@radix-ui/react-checkbox": "^1.3.11",
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"@radix-ui/react-dialog": "^1.1.23",
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Generated
+42
@@ -12,6 +12,8 @@ specifiers:
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'@electron-toolkit/tsconfig': ^2.0.0
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'@electron-toolkit/utils': ^4.0.0
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'@koromix/koffi-win32-x64': 3.1.0
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'@napi-rs/system-ocr': 1.2.0
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'@napi-rs/system-ocr-win32-x64-msvc': 1.2.0
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'@playwright/test': ^1.62.1
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'@radix-ui/react-alert-dialog': ^1.1.23
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'@radix-ui/react-checkbox': ^1.3.11
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@@ -86,6 +88,8 @@ dependencies:
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'@electron-toolkit/preload': 3.0.2_electron@43.1.0
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'@electron-toolkit/utils': 4.0.0_electron@43.1.0
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'@koromix/koffi-win32-x64': 3.1.0
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'@napi-rs/system-ocr': 1.2.0
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'@napi-rs/system-ocr-win32-x64-msvc': 1.2.0
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'@radix-ui/react-alert-dialog': 1.1.23_eijghdl4n2x4hz6j4cg7ctgbuu
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'@radix-ui/react-checkbox': 1.3.11_eijghdl4n2x4hz6j4cg7ctgbuu
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'@radix-ui/react-dialog': 1.1.23_eijghdl4n2x4hz6j4cg7ctgbuu
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@@ -1685,6 +1689,44 @@ packages:
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- supports-color
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dev: true
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/@napi-rs/system-ocr/1.2.0:
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resolution: {integrity: sha512-r0f2xNH6U+sth44qF+lUP+2WuHSGUBAry5KSCNuaLDGRbgslFqeROr/qJJ/fb6AjBp3Ov+CJP5MdrOWoaoM3cw==}
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engines: {node: '>= 10'}
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optionalDependencies:
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'@napi-rs/system-ocr-darwin-arm64': 1.2.0
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'@napi-rs/system-ocr-darwin-x64': 1.2.0
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'@napi-rs/system-ocr-win32-arm64-msvc': 1.2.0
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'@napi-rs/system-ocr-win32-x64-msvc': 1.2.0
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dev: false
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/@napi-rs/system-ocr-darwin-arm64/1.2.0:
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resolution: {integrity: sha512-cK8dcDBEl3P4A04xmFJSHEJQxfDytaAIFyDCLqavTp92FVU5plESttWzZsqtTkS81/kzKiBfHyPQffSIndfWbQ==}
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cpu: [arm64]
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os: [darwin]
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engines: {node: '>= 10'}
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dev: false
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/@napi-rs/system-ocr-darwin-x64/1.2.0:
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resolution: {integrity: sha512-u3TBvBGrhmT5Os6AfaxbUEg6VHe8lvrFJNPgThJgshJHyRXUx/wCfTyOroJ22KdVCP5AE4GpwS5tFHMb6p6iaQ==}
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cpu: [x64]
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os: [darwin]
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engines: {node: '>= 10'}
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dev: false
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/@napi-rs/system-ocr-win32-arm64-msvc/1.2.0:
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resolution: {integrity: sha512-7ej8uMvmXomw3NXo5gZ5p2Nl6UKsHI+VRU3ELv0mhcxR0sJ6wFifYTu5bJrM1TGcz1/RsaX+TjWMmsDq8vriKQ==}
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cpu: [arm64]
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os: [win32]
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engines: {node: '>= 10'}
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dev: false
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/@napi-rs/system-ocr-win32-x64-msvc/1.2.0:
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resolution: {integrity: sha512-oOoCj3FPWDVctTxx98vMBiMI6m51U+w7SMmMefvmtpcpLelzZ/zYTqdwtWZFAjShaHO+RdaKkcpeVcQuBQiVbA==}
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cpu: [x64]
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os: [win32]
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engines: {node: '>= 10'}
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dev: false
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/@nodelib/fs.scandir/2.1.5:
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resolution: {integrity: sha512-vq24Bq3ym5HEQm2NKCr3yXDwjc7vTsEThRDnkp2DK9p1uqLR+DHurm/NOTo0KG7HYHU7eppKZj3MyqYuMBf62g==}
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engines: {node: '>= 8'}
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+54
-4
@@ -78,6 +78,44 @@ function validateSherpaRuntime(runtimeResources, platform, arch) {
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}
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}
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/**
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* System OCR 用 native package（@napi-rs/system-ocr）。它是 external + asarUnpack，
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* 打包后必须以 unpacked 形式存在，否则运行时会 MODULE_NOT_FOUND / native binding missing。
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* 本轮只有 Windows 是 supported target，所以只在 Windows 上做硬校验。
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*/
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function systemOcrTarget(platform, arch) {
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return platform === 'win32' ? `${platform}-${arch}-msvc` : `${platform}-${arch}`
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}
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function validateSystemOcrRuntime(runtimeResources, platform, arch) {
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if (platform !== 'win32') return
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const target = systemOcrTarget(platform, arch)
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const basePath = path.join(
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runtimeResources,
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'app.asar.unpacked',
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'node_modules',
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'@napi-rs',
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'system-ocr'
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)
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const nativePath = path.join(
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runtimeResources,
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'app.asar.unpacked',
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'node_modules',
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'@napi-rs',
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`system-ocr-${target}`
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)
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const requiredFiles = [
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path.join(basePath, 'package.json'),
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path.join(basePath, 'index.js'),
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path.join(nativePath, 'package.json'),
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path.join(nativePath, `system-ocr.${target}.node`)
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]
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const missingFiles = requiredFiles.filter((filePath) => !existsSync(filePath))
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if (missingFiles.length > 0) {
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throw new Error(`Missing unpacked System OCR runtime: ${missingFiles.join(', ')}`)
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}
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}
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function normalizeBuilderArch(arch) {
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if (typeof arch === 'string') return arch
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return { 0: 'ia32', 1: 'x64', 2: 'armv7l', 3: 'arm64', 4: 'universal' }[arch] || String(arch)
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@@ -152,16 +190,24 @@ function validateReaderSkillRuntime(runtimeResources) {
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* The loaders pick their package from process.platform/arch, so the siblings
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* are dead weight — drop them.
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*/
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// 每个条目返回 platform package 的**完整后缀**（不含 package 前缀与连字符）。
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const NATIVE_RUNTIME_PACKAGES = [
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{
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modules: [],
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prefix: 'sherpa-onnx',
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platformName: (platform) => (platform === 'win32' ? 'win' : platform)
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platformName: (platform, arch) => `${platform === 'win32' ? 'win' : platform}-${arch}`
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},
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{
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modules: ['@koromix'],
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prefix: 'koffi',
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platformName: (platform) => platform
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platformName: (platform, arch) => `${platform}-${arch}`
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},
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{
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// @napi-rs 的 platform package 目录名带 -msvc 后缀（win32-x64-msvc）。
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modules: ['@napi-rs'],
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prefix: 'system-ocr',
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platformName: (platform, arch) => systemOcrTarget(platform, arch),
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foreignPattern: /^system-ocr-[a-z0-9]+-(arm64|x64|ia32|loong64|riscv64)(-msvc)?$/
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}
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]
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@@ -173,8 +219,10 @@ function pruneForeignArchNativeRuntimes(runtimeResources, platform, arch) {
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for (const runtime of NATIVE_RUNTIME_PACKAGES) {
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const modulesRoot = path.join(unpackedRoot, ...runtime.modules)
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if (!existsSync(modulesRoot)) continue
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const expected = `${runtime.prefix}-${runtime.platformName(platform)}-${arch}`
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const foreign = new RegExp(`^${runtime.prefix}-[a-z0-9]+-(arm64|x64|ia32|loong64|riscv64)$`)
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const expected = `${runtime.prefix}-${runtime.platformName(platform, arch)}`
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const foreign =
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runtime.foreignPattern ||
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new RegExp(`^${runtime.prefix}-[a-z0-9]+-(arm64|x64|ia32|loong64|riscv64)$`)
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for (const entry of readdirSync(modulesRoot, { withFileTypes: true })) {
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if (!entry.isDirectory() || entry.name === expected || !foreign.test(entry.name)) continue
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rmSync(path.join(modulesRoot, entry.name), { recursive: true, force: true })
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@@ -223,6 +271,7 @@ exports.default = async function afterPack(context) {
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'Bundled ffmpeg'
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)
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validateSherpaRuntime(runtimeResources, context.electronPlatformName, arch)
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validateSystemOcrRuntime(runtimeResources, context.electronPlatformName, arch)
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pruneIntelMacKeyTool(runtimeResources, context.electronPlatformName, arch)
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pruneForeignArchConnectors(runtimeResources, context.electronPlatformName, arch)
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pruneForeignArchNativeRuntimes(runtimeResources, context.electronPlatformName, arch)
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@@ -258,6 +307,7 @@ exports.validateReaderSkillRuntime = validateReaderSkillRuntime
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exports.validateFfmpegRuntime = validateFfmpegRuntime
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exports.validateSilkWasmRuntime = validateSilkWasmRuntime
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exports.validateSherpaRuntime = validateSherpaRuntime
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exports.validateSystemOcrRuntime = validateSystemOcrRuntime
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exports.pruneIntelMacKeyTool = pruneIntelMacKeyTool
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exports.pruneForeignArchConnectors = pruneForeignArchConnectors
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exports.pruneForeignArchNativeRuntimes = pruneForeignArchNativeRuntimes
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@@ -114,7 +114,11 @@ function getFfmpegCandidates(selectedPath = loadSettings().ffmpegPath): FfmpegCa
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)
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}
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function resolveFfmpegExecutable(): string {
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/**
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* 解析可用的 ffmpeg 可执行文件。除图片解密自身使用外，也供 System OCR 的
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* 图片归一化（GIF/BMP/WebP/TIFF → PNG）复用，避免重复一套路径探测逻辑。
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*/
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export function resolveFfmpegExecutable(): string {
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for (const candidate of getFfmpegCandidates()) {
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const pathLike = candidate.executable.includes('/') || candidate.executable.includes('\\')
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if (pathLike) {
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@@ -29,6 +29,7 @@ import {
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ImageDecryptService,
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inspectImageDecoderExecutable,
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inspectImageDecoderStatus,
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resolveFfmpegExecutable,
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type DecodedImage
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} from './image-decrypt-service'
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import {
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@@ -64,6 +65,7 @@ import { apiTokenStore } from './api-token-store'
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import { ImageKeyConfigService } from './services/image-key-config-service'
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import { AIProviderService } from './services/ai-provider-service'
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import { imageInsightService } from './services/image-insight-service'
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import { systemOcrService } from './services/system-ocr-service'
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import type {
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ImageAnalysisRequest,
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ImageAnalysisResponse,
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@@ -71,6 +73,7 @@ import type {
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ImageCandidateQuery,
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ImageInsight
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} from '../shared/image-insight'
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import type { SystemOcrCapability, SystemOcrRequest, SystemOcrResult } from '../shared/system-ocr'
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import { KeyServiceMac } from './key-service-mac'
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import { KeyService as KeyServiceWin } from './key-service-win'
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import * as chat from './services/chat-service'
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@@ -1814,6 +1817,13 @@ app.whenReady().then(async () => {
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}
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})
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// System OCR 是独立的本地 Runtime（不是 AI Provider）：只注入项目统一的 ffmpeg
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// 解析逻辑（GIF/BMP/WebP/TIFF → PNG 归一化）和系统 locale（OCR 语言包探测）。
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systemOcrService.bind({
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resolveFfmpegExecutable,
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locale: () => app.getLocale()
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})
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/** 日报入口:取会话 Top N 热点图片 + 已缓存的 Insight */
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ipcMain.handle(
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'image:listCandidates',
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@@ -1885,6 +1895,26 @@ app.whenReady().then(async () => {
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}
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)
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// ============================================================
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// 本地图片文字识别（System OCR / Windows System OCR Runtime）
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// ============================================================
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// 这是本地 Runtime，不是 AI Vision Provider：
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// - 不联网、不上传原图；
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// - 不读写 AI Provider / Vision 模型配置；
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// - 结果不落库（派生内容，本轮只做内存级闭环）。
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ipcMain.handle('system-ocr:getCapability', async (): Promise<SystemOcrCapability> => {
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return imageInsightService.getSystemOcrCapability()
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})
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ipcMain.handle(
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'system-ocr:recognize',
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async (_, request: SystemOcrRequest): Promise<SystemOcrResult> => {
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// 日志只记录结构性信息，不记录 base64、不记录识别正文。
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console.log('[IPC] system-ocr:recognize hash=%s', request?.imageHash || 'auto')
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return imageInsightService.extractLocalText(request)
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}
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)
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ipcMain.handle('db:getSticker', async (_, cdnUrl?: string, md5?: string) => {
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if (!stickerService) {
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stickerService = new StickerService(chat.getChatDb()?.getWcdb4Client())
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@@ -27,6 +27,8 @@ import {
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isFreshImageInsight,
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isHotImageCandidate
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} from '../../shared/image-insight'
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import type { SystemOcrCapability, SystemOcrRequest, SystemOcrResult } from '../../shared/system-ocr'
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import { systemOcrService } from './system-ocr-service'
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/**
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* 单张图片的最小信息(由 renderer 从已加载的 messages 中提取并传入 main)。
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@@ -312,6 +314,35 @@ class ImageInsightService {
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listBySession(sessionId: string, limit?: number): ImageInsight[] {
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return imageInsightsStore.listBySession(sessionId, limit)
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}
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// ============================================================
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// 本地图片文字识别（System OCR）
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// ============================================================
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//
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// 与 Vision 路径的关系：
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// ImageInsightService 是统一编排入口，下面挂两条互不干扰的运行时——
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// - Vision Model Runtime（AIProviderService，走 AI Provider，可能联网）
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// - Windows System OCR Runtime（SystemOcrService，纯本地，不联网）
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//
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// 边界与约束：
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// 1. 本地 OCR 结果属于 **派生内容**，原始消息始终是权威来源；
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// 本轮不落库、不写 Knowledge、不做历史图片 backfill。
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// 2. 本地 OCR 结果 **不会** 写入 image-insights.json——那是 Vision 结果的缓存，
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// 两者的缓存键空间也不同（见 buildSystemOcrCacheKey）。
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// 3. 这里不读取也绝不修改 AI Vision Provider / 模型配置。
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/** 本机是否支持本地图片文字识别（Windows System OCR）。 */
|
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getSystemOcrCapability(): Promise<SystemOcrCapability> {
|
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return systemOcrService.getCapability()
|
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}
|
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/**
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* 只做「把图片里的文字读出来」。不发网络请求，不动 AI Provider 配置。
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* 失败不抛，返回带 errorCode 的结果。
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*/
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extractLocalText(request: SystemOcrRequest): Promise<SystemOcrResult> {
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return systemOcrService.recognize(request)
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||||
}
|
||||
}
|
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export const imageInsightService = new ImageInsightService()
|
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@@ -0,0 +1,558 @@
|
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// src/main/services/system-ocr-service.ts
|
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//
|
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// System OCR Runtime（本地图片文字识别）。
|
||||
//
|
||||
// 职责边界（只做这些事）：
|
||||
// 1. capability detection
|
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// 2. image normalization / preparation
|
||||
// 3. OCR execution
|
||||
// 4. result normalization
|
||||
// 5. runtime metadata
|
||||
// 6. error mapping
|
||||
//
|
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// 明确不做：
|
||||
// - 不伪装成 AI Provider / Vision Model；不读写 AIVisionRuntimeConfig；
|
||||
// - 不发任何网络请求；不上传原图；
|
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// - 不遍历历史图片、不做 backfill、不写 Knowledge；
|
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// - 不把 OCR 文本写进 image-insights.json（那是 Vision 结果的缓存）。
|
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//
|
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// Windows 后端：Windows.Media.Ocr.OcrEngine（经 @napi-rs/system-ocr）。
|
||||
// 已实测的引擎行为（@napi-rs/system-ocr 1.2.0 / Electron 43 / Windows x64）：
|
||||
// - Buffer 输入只接受 PNG；JPEG / WEBP / BMP 会被判为不可识别，
|
||||
// 所以本服务在边界上统一归一化成 PNG 字节再调用（不落盘）。
|
||||
// - preferredLangs 只使用第一个语言；语言包缺失时引擎创建失败，
|
||||
// 抛出的错误是 `Windows error 操作成功完成。 (0x00000000)`（HRESULT 为 S_OK）。
|
||||
// - 空白图不会报错，返回空文本 → 映射成 OCR_EMPTY_RESULT。
|
||||
// - CJK 字符之间会被引擎插入空格，结果里做归一化。
|
||||
|
||||
import crypto from 'node:crypto'
|
||||
import { spawn } from 'node:child_process'
|
||||
import {
|
||||
SYSTEM_OCR_CACHE_TTL_MS,
|
||||
SYSTEM_OCR_ENGINE,
|
||||
SYSTEM_OCR_PROBE_PNG_BASE64,
|
||||
buildSystemOcrCacheKey,
|
||||
detectSystemOcrImageFormat,
|
||||
mapSystemOcrNativeError,
|
||||
normalizeSystemOcrText,
|
||||
parseImageDataUrl,
|
||||
resolveSystemOcrLanguageTag
|
||||
} from '../../shared/system-ocr'
|
||||
import type {
|
||||
SystemOcrCapability,
|
||||
SystemOcrErrorCode,
|
||||
SystemOcrImageFormat,
|
||||
SystemOcrLine,
|
||||
SystemOcrRequest,
|
||||
SystemOcrResult
|
||||
} from '../../shared/system-ocr'
|
||||
|
||||
const NATIVE_PACKAGE = '@napi-rs/system-ocr'
|
||||
const MAX_CACHE_ENTRIES = 32
|
||||
const FFMPEG_TIMEOUT_MS = 10_000
|
||||
|
||||
interface NativeLine {
|
||||
text: string
|
||||
confidence: number
|
||||
boundingBox: { x: number; y: number; width: number; height: number }
|
||||
}
|
||||
|
||||
interface NativeResult {
|
||||
text: string
|
||||
confidence: number
|
||||
lines: NativeLine[]
|
||||
}
|
||||
|
||||
interface NativeRuntime {
|
||||
version: string | null
|
||||
recognize: (image: Uint8Array, accuracy?: number, languages?: string[]) => Promise<NativeResult>
|
||||
}
|
||||
|
||||
export interface SystemOcrServiceDeps {
|
||||
/** 加载 native 运行时；不可用时返回 null（不允许抛） */
|
||||
loadRuntime?: () => NativeRuntime | null
|
||||
/** 把输入图片转成 PNG 字节；失败返回 null */
|
||||
toPngBytes?: (input: {
|
||||
buffer: Buffer
|
||||
format: SystemOcrImageFormat
|
||||
}) => Promise<Buffer | null>
|
||||
/**
|
||||
* ffmpeg 可执行文件解析器。只用于 GIF/BMP/WebP/TIFF → PNG 的兜底归一化。
|
||||
* main/index.ts 会注入项目统一的解析逻辑（与图片解密共用一套候选路径）。
|
||||
*/
|
||||
resolveFfmpegExecutable?: () => string
|
||||
platform?: NodeJS.Platform
|
||||
arch?: string
|
||||
/** 系统 locale（如 zh-CN），用于推导 OCR 语言标签 */
|
||||
locale?: () => string
|
||||
}
|
||||
|
||||
/** 未被显式注入时的兜底：环境变量 → 打包内 ffmpeg-static → PATH。 */
|
||||
const defaultResolveFfmpegExecutable = (): string => {
|
||||
const fromEnvironment = String(process.env['FFMPEG_BIN'] || '').trim()
|
||||
if (fromEnvironment) return fromEnvironment
|
||||
try {
|
||||
const bundled = require('ffmpeg-static') as string | null
|
||||
if (bundled) return bundled
|
||||
} catch {
|
||||
// 忽略：退回到 PATH 上的 ffmpeg
|
||||
}
|
||||
return process.platform === 'win32' ? 'ffmpeg.exe' : 'ffmpeg'
|
||||
}
|
||||
|
||||
const toLines = (lines: NativeLine[] | undefined): SystemOcrLine[] =>
|
||||
Array.isArray(lines)
|
||||
? lines.map((line) => ({
|
||||
text: normalizeSystemOcrText(line.text),
|
||||
confidence: typeof line.confidence === 'number' ? line.confidence : 1,
|
||||
boundingBox: {
|
||||
x: Number(line.boundingBox?.x ?? 0),
|
||||
y: Number(line.boundingBox?.y ?? 0),
|
||||
width: Number(line.boundingBox?.width ?? 0),
|
||||
height: Number(line.boundingBox?.height ?? 0)
|
||||
}
|
||||
}))
|
||||
: []
|
||||
|
||||
const failure = (
|
||||
errorCode: SystemOcrErrorCode,
|
||||
error: string,
|
||||
startedAt: number
|
||||
): SystemOcrResult => ({
|
||||
success: false,
|
||||
text: '',
|
||||
lines: [],
|
||||
language: null,
|
||||
engine: SYSTEM_OCR_ENGINE,
|
||||
durationMs: Date.now() - startedAt,
|
||||
errorCode,
|
||||
error
|
||||
})
|
||||
|
||||
/** 把任意容器（gif/bmp/webp/tiff）用 ffmpeg 走内存管道转成 PNG。不落盘。 */
|
||||
const convertWithFfmpeg = (buffer: Buffer, executable: string): Promise<Buffer | null> =>
|
||||
new Promise((resolve) => {
|
||||
let settled = false
|
||||
const finish = (value: Buffer | null): void => {
|
||||
if (settled) return
|
||||
settled = true
|
||||
resolve(value)
|
||||
}
|
||||
let child: ReturnType<typeof spawn>
|
||||
try {
|
||||
child = spawn(
|
||||
executable,
|
||||
[
|
||||
'-hide_banner',
|
||||
'-loglevel',
|
||||
'error',
|
||||
'-i',
|
||||
'pipe:0',
|
||||
'-frames:v',
|
||||
'1',
|
||||
'-f',
|
||||
'image2pipe',
|
||||
'-vcodec',
|
||||
'png',
|
||||
'pipe:1'
|
||||
],
|
||||
{ windowsHide: true }
|
||||
)
|
||||
} catch {
|
||||
finish(null)
|
||||
return
|
||||
}
|
||||
const chunks: Buffer[] = []
|
||||
const timeout = setTimeout(() => {
|
||||
try {
|
||||
child.kill()
|
||||
} catch {
|
||||
// best-effort
|
||||
}
|
||||
finish(null)
|
||||
}, FFMPEG_TIMEOUT_MS)
|
||||
child.stdout?.on('data', (chunk: Buffer) => chunks.push(chunk))
|
||||
child.on('error', () => {
|
||||
clearTimeout(timeout)
|
||||
finish(null)
|
||||
})
|
||||
child.on('close', (code) => {
|
||||
clearTimeout(timeout)
|
||||
finish(code === 0 && chunks.length > 0 ? Buffer.concat(chunks) : null)
|
||||
})
|
||||
child.stdin?.on('error', () => undefined)
|
||||
child.stdin?.end(buffer)
|
||||
})
|
||||
|
||||
class SystemOcrService {
|
||||
private runtime: NativeRuntime | null = null
|
||||
private runtimeLoaded = false
|
||||
private capability: SystemOcrCapability | null = null
|
||||
private capabilityPromise: Promise<SystemOcrCapability> | null = null
|
||||
private readonly cache = new Map<string, { value: SystemOcrResult; expireAt: number }>()
|
||||
private deps: SystemOcrServiceDeps = {}
|
||||
|
||||
constructor(deps: SystemOcrServiceDeps = {}) {
|
||||
this.deps = deps
|
||||
}
|
||||
|
||||
/** 由 main/index.ts 在 app ready 后调用（可选，用于注入 app.getLocale 等）。 */
|
||||
bind(deps: SystemOcrServiceDeps): void {
|
||||
this.deps = { ...this.deps, ...deps }
|
||||
this.runtime = null
|
||||
this.runtimeLoaded = false
|
||||
this.capability = null
|
||||
this.capabilityPromise = null
|
||||
}
|
||||
|
||||
/** 仅测试用：清空探测与缓存状态。 */
|
||||
reset(): void {
|
||||
this.runtime = null
|
||||
this.runtimeLoaded = false
|
||||
this.capability = null
|
||||
this.capabilityPromise = null
|
||||
this.cache.clear()
|
||||
}
|
||||
|
||||
private get platform(): NodeJS.Platform {
|
||||
return this.deps.platform ?? process.platform
|
||||
}
|
||||
|
||||
private get arch(): string {
|
||||
return this.deps.arch ?? process.arch
|
||||
}
|
||||
|
||||
private get locale(): string {
|
||||
if (this.deps.locale) {
|
||||
try {
|
||||
return this.deps.locale()
|
||||
} catch {
|
||||
return ''
|
||||
}
|
||||
}
|
||||
try {
|
||||
const { app } = require('electron') as typeof import('electron')
|
||||
return app?.getLocale?.() ?? ''
|
||||
} catch {
|
||||
return ''
|
||||
}
|
||||
}
|
||||
|
||||
private loadRuntime(): NativeRuntime | null {
|
||||
if (this.runtimeLoaded) return this.runtime
|
||||
this.runtimeLoaded = true
|
||||
if (this.deps.loadRuntime) {
|
||||
this.runtime = this.deps.loadRuntime()
|
||||
return this.runtime
|
||||
}
|
||||
if (this.platform !== 'win32') {
|
||||
this.runtime = null
|
||||
return this.runtime
|
||||
}
|
||||
try {
|
||||
// 原生模块必须在打包时 external + asarUnpack，否则这里会 MODULE_NOT_FOUND。
|
||||
const nativeModule = require(NATIVE_PACKAGE) as {
|
||||
recognize: NativeRuntime['recognize']
|
||||
}
|
||||
let version: string | null = null
|
||||
try {
|
||||
version = (require(`${NATIVE_PACKAGE}/package.json`) as { version?: string }).version ?? null
|
||||
} catch {
|
||||
version = null
|
||||
}
|
||||
this.runtime =
|
||||
nativeModule && typeof nativeModule.recognize === 'function'
|
||||
? { version, recognize: nativeModule.recognize.bind(nativeModule) }
|
||||
: null
|
||||
} catch (error) {
|
||||
console.warn(
|
||||
'[SystemOcrService] native runtime unavailable engine=%s platform=%s reason=%s',
|
||||
SYSTEM_OCR_ENGINE,
|
||||
this.platform,
|
||||
error instanceof Error ? error.message.split('\n')[0] : String(error)
|
||||
)
|
||||
this.runtime = null
|
||||
}
|
||||
return this.runtime
|
||||
}
|
||||
|
||||
private async toPngBytes(
|
||||
buffer: Buffer,
|
||||
format: SystemOcrImageFormat
|
||||
): Promise<Buffer | null> {
|
||||
if (this.deps.toPngBytes) return this.deps.toPngBytes({ buffer, format })
|
||||
if (format === 'png') return buffer
|
||||
if (format === 'jpeg') {
|
||||
// 项目内已有的进程内解码能力，优先于 ffmpeg（更快、无子进程）。
|
||||
try {
|
||||
const { nativeImage } = require('electron') as typeof import('electron')
|
||||
const image = nativeImage.createFromBuffer(buffer)
|
||||
if (!image.isEmpty()) {
|
||||
const png = image.toPNG()
|
||||
if (png && png.length > 0) return png
|
||||
}
|
||||
} catch {
|
||||
// 继续走 ffmpeg 兜底
|
||||
}
|
||||
}
|
||||
try {
|
||||
const resolveFfmpeg = this.deps.resolveFfmpegExecutable ?? defaultResolveFfmpegExecutable
|
||||
const png = await convertWithFfmpeg(buffer, resolveFfmpeg())
|
||||
return png
|
||||
} catch {
|
||||
return null
|
||||
}
|
||||
}
|
||||
|
||||
/** capability 探测：平台 → native 运行时 → 至少一个可用 OCR 语言。 */
|
||||
async getCapability(force = false): Promise<SystemOcrCapability> {
|
||||
if (!force && this.capability) return this.capability
|
||||
if (!force && this.capabilityPromise) return this.capabilityPromise
|
||||
this.capabilityPromise = this.detectCapability()
|
||||
try {
|
||||
this.capability = await this.capabilityPromise
|
||||
} finally {
|
||||
this.capabilityPromise = null
|
||||
}
|
||||
return this.capability
|
||||
}
|
||||
|
||||
private async detectCapability(): Promise<SystemOcrCapability> {
|
||||
const base: Pick<
|
||||
SystemOcrCapability,
|
||||
'engine' | 'platform' | 'arch' | 'runtimeVersion' | 'language'
|
||||
> = {
|
||||
engine: SYSTEM_OCR_ENGINE,
|
||||
platform: this.platform,
|
||||
arch: this.arch,
|
||||
runtimeVersion: null,
|
||||
language: null
|
||||
}
|
||||
if (this.platform !== 'win32') {
|
||||
return {
|
||||
...base,
|
||||
available: false,
|
||||
reason: 'UNSUPPORTED_PLATFORM',
|
||||
message: '本地图片文字识别目前仅支持 Windows。'
|
||||
}
|
||||
}
|
||||
const runtime = this.loadRuntime()
|
||||
if (!runtime) {
|
||||
return {
|
||||
...base,
|
||||
available: false,
|
||||
reason: 'NATIVE_MODULE_MISSING',
|
||||
message: '本地文字识别组件不可用，请重新安装 TraceMemo。'
|
||||
}
|
||||
}
|
||||
const probed = await this.probeLanguage(runtime)
|
||||
if (probed.reason) {
|
||||
return {
|
||||
...base,
|
||||
runtimeVersion: runtime.version,
|
||||
available: false,
|
||||
reason: probed.reason,
|
||||
message: probed.message
|
||||
}
|
||||
}
|
||||
return {
|
||||
...base,
|
||||
runtimeVersion: runtime.version,
|
||||
available: true,
|
||||
language: probed.language,
|
||||
message: probed.language
|
||||
? `本地图片文字识别可用（Windows 系统 OCR，${probed.language}）。`
|
||||
: '本地图片文字识别可用（Windows 系统 OCR，跟随系统语言）。'
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 用一个 64x32 纯白 PNG 探测语言可用性：引擎能创建即说明语言包可用。
|
||||
* 首选「系统 locale 推导出的标签」，失败再退回「系统用户语言配置」。
|
||||
*/
|
||||
private async probeLanguage(
|
||||
runtime: NativeRuntime
|
||||
): Promise<
|
||||
| { language: string | null; reason?: undefined; message?: undefined }
|
||||
| { language: null; reason: 'LANGUAGE_UNAVAILABLE' | 'NATIVE_MODULE_MISSING'; message: string }
|
||||
> {
|
||||
const probeBuffer = Buffer.from(SYSTEM_OCR_PROBE_PNG_BASE64, 'base64')
|
||||
const preferred = resolveSystemOcrLanguageTag(this.locale)
|
||||
const candidates: Array<string | null> = preferred ? [preferred, null] : [null]
|
||||
let lastCode: SystemOcrErrorCode = 'OCR_FAILED'
|
||||
for (const candidate of candidates) {
|
||||
try {
|
||||
await runtime.recognize(
|
||||
probeBuffer,
|
||||
undefined,
|
||||
candidate ? [candidate] : undefined
|
||||
)
|
||||
return { language: candidate }
|
||||
} catch (error) {
|
||||
lastCode = mapSystemOcrNativeError(
|
||||
error instanceof Error ? error.message : String(error)
|
||||
)
|
||||
}
|
||||
}
|
||||
if (lastCode === 'OCR_LANGUAGE_UNAVAILABLE') {
|
||||
return {
|
||||
language: null,
|
||||
reason: 'LANGUAGE_UNAVAILABLE',
|
||||
message:
|
||||
'当前 Windows 未安装可用的 OCR 语言支持，请在系统「语言和区域」里安装简体中文或英文的 OCR 语言包后重试。'
|
||||
}
|
||||
}
|
||||
return {
|
||||
language: null,
|
||||
reason: 'NATIVE_MODULE_MISSING',
|
||||
message: '本地文字识别引擎初始化失败，请重启 TraceMemo 或重新安装。'
|
||||
}
|
||||
}
|
||||
|
||||
private readCache(key: string, startedAt: number): SystemOcrResult | null {
|
||||
const hit = this.cache.get(key)
|
||||
if (!hit) return null
|
||||
if (hit.expireAt <= Date.now()) {
|
||||
this.cache.delete(key)
|
||||
return null
|
||||
}
|
||||
return { ...hit.value, durationMs: Date.now() - startedAt, fromCache: true }
|
||||
}
|
||||
|
||||
private writeCache(key: string, value: SystemOcrResult): void {
|
||||
if (this.cache.size >= MAX_CACHE_ENTRIES) {
|
||||
const oldest = this.cache.keys().next()
|
||||
if (!oldest.done) this.cache.delete(oldest.value)
|
||||
}
|
||||
this.cache.set(key, { value, expireAt: Date.now() + SYSTEM_OCR_CACHE_TTL_MS })
|
||||
}
|
||||
|
||||
/**
|
||||
* 识别一张图片里的文字。
|
||||
* 任意失败都不抛，统一返回 success=false + 产品级 errorCode。
|
||||
*/
|
||||
async recognize(request: SystemOcrRequest): Promise<SystemOcrResult> {
|
||||
const startedAt = Date.now()
|
||||
const parsed = parseImageDataUrl(request.imageDataUrl)
|
||||
if (!parsed) {
|
||||
return failure('UNSUPPORTED_IMAGE', '仅支持 PNG、JPG、JPEG、WebP、GIF、BMP 图片。', startedAt)
|
||||
}
|
||||
let sourceBuffer: Buffer
|
||||
try {
|
||||
sourceBuffer = Buffer.from(parsed.base64, 'base64')
|
||||
} catch {
|
||||
return failure('IMAGE_DECODE_FAILED', '图片数据无法解码。', startedAt)
|
||||
}
|
||||
if (sourceBuffer.length === 0) {
|
||||
return failure('IMAGE_DECODE_FAILED', '图片数据为空。', startedAt)
|
||||
}
|
||||
const format = detectSystemOcrImageFormat(sourceBuffer)
|
||||
if (!format) {
|
||||
return failure('UNSUPPORTED_IMAGE', '无法识别的图片格式。', startedAt)
|
||||
}
|
||||
|
||||
const imageHash =
|
||||
request.imageHash?.trim() ||
|
||||
crypto.createHash('sha256').update(sourceBuffer).digest('hex').slice(0, 32)
|
||||
const requestedLanguage = request.language?.trim() || null
|
||||
|
||||
const capability = await this.getCapability()
|
||||
if (!capability.available) {
|
||||
const errorCode: SystemOcrErrorCode =
|
||||
capability.reason === 'UNSUPPORTED_PLATFORM'
|
||||
? 'UNSUPPORTED_PLATFORM'
|
||||
: capability.reason === 'LANGUAGE_UNAVAILABLE'
|
||||
? 'OCR_LANGUAGE_UNAVAILABLE'
|
||||
: 'SYSTEM_OCR_UNAVAILABLE'
|
||||
return failure(errorCode, capability.message, startedAt)
|
||||
}
|
||||
|
||||
const languageForCache = requestedLanguage ?? capability.language
|
||||
const cacheKey = buildSystemOcrCacheKey({
|
||||
imageHash,
|
||||
language: languageForCache,
|
||||
runtimeVersion: capability.runtimeVersion,
|
||||
platform: capability.platform
|
||||
})
|
||||
if (requestedLanguage === null) {
|
||||
const cached = this.readCache(cacheKey, startedAt)
|
||||
if (cached) return cached
|
||||
}
|
||||
|
||||
const runtime = this.loadRuntime()
|
||||
if (!runtime) {
|
||||
return failure('SYSTEM_OCR_UNAVAILABLE', '本地文字识别组件不可用。', startedAt)
|
||||
}
|
||||
|
||||
const png = await this.toPngBytes(sourceBuffer, format)
|
||||
if (!png || png.length === 0 || !detectSystemOcrImageFormat(png)) {
|
||||
return failure('IMAGE_DECODE_FAILED', '图片解码失败，无法读取这张图片。', startedAt)
|
||||
}
|
||||
|
||||
const candidates: Array<string | null> = requestedLanguage
|
||||
? [requestedLanguage]
|
||||
: capability.language
|
||||
? [capability.language, null]
|
||||
: [null]
|
||||
let lastErrorCode: SystemOcrErrorCode = 'OCR_FAILED'
|
||||
let lastErrorMessage = ''
|
||||
let usedLanguage: string | null = null
|
||||
for (const candidate of candidates) {
|
||||
try {
|
||||
const result = await runtime.recognize(
|
||||
png,
|
||||
undefined,
|
||||
candidate ? [candidate] : undefined
|
||||
)
|
||||
const text = normalizeSystemOcrText(result?.text ?? '')
|
||||
const lines = toLines(result?.lines)
|
||||
usedLanguage = candidate
|
||||
if (!text) {
|
||||
return failure('OCR_EMPTY_RESULT', '没有在这张图片里识别到文字。', startedAt)
|
||||
}
|
||||
const succeeded: SystemOcrResult = {
|
||||
success: true,
|
||||
text,
|
||||
lines,
|
||||
language: usedLanguage,
|
||||
engine: SYSTEM_OCR_ENGINE,
|
||||
durationMs: Date.now() - startedAt
|
||||
}
|
||||
// 生产日志只记录 error code / engine / platform / duration，绝不记录识别正文。
|
||||
console.log(
|
||||
'[SystemOcrService] ok engine=%s platform=%s language=%s chars=%d durationMs=%d',
|
||||
SYSTEM_OCR_ENGINE,
|
||||
capability.platform,
|
||||
usedLanguage ?? 'system-default',
|
||||
text.length,
|
||||
succeeded.durationMs
|
||||
)
|
||||
this.writeCache(cacheKey, succeeded)
|
||||
return succeeded
|
||||
} catch (error) {
|
||||
lastErrorMessage = error instanceof Error ? error.message : String(error)
|
||||
lastErrorCode = mapSystemOcrNativeError(lastErrorMessage)
|
||||
// 语言不可用才值得换下一个候选；其它错误直接结束，避免无意义重试。
|
||||
if (lastErrorCode !== 'OCR_LANGUAGE_UNAVAILABLE') break
|
||||
}
|
||||
}
|
||||
|
||||
console.warn(
|
||||
'[SystemOcrService] failed engine=%s platform=%s errorCode=%s durationMs=%d',
|
||||
SYSTEM_OCR_ENGINE,
|
||||
capability.platform,
|
||||
lastErrorCode,
|
||||
Date.now() - startedAt
|
||||
)
|
||||
return failure(
|
||||
lastErrorCode,
|
||||
lastErrorCode === 'OCR_LANGUAGE_UNAVAILABLE'
|
||||
? '当前 Windows 未安装可用的 OCR 语言支持。'
|
||||
: '本地文字识别失败，请稍后重试。',
|
||||
startedAt
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
export { SystemOcrService }
|
||||
export const systemOcrService = new SystemOcrService()
|
||||
Vendored
+4
@@ -57,6 +57,7 @@ import type {
|
||||
ImageCandidateQuery,
|
||||
ImageInsight
|
||||
} from '../shared/image-insight'
|
||||
import type { SystemOcrCapability, SystemOcrRequest, SystemOcrResult } from '../shared/system-ocr'
|
||||
import type { AgentHubActionResult, AgentHubLogEntry, AgentHubStatus } from '../shared/agent-hub'
|
||||
import type {
|
||||
PersonalWechatGeneratedTtsVoiceRequest,
|
||||
@@ -660,6 +661,9 @@ declare global {
|
||||
sessionId: string,
|
||||
limit?: number
|
||||
) => Promise<{ success: boolean; insights: ImageInsight[] }>
|
||||
// 本地图片文字识别（System OCR，本地 Runtime，非 AI Provider）
|
||||
getSystemOcrCapability: () => Promise<SystemOcrCapability>
|
||||
recognizeLocalImageText: (request: SystemOcrRequest) => Promise<SystemOcrResult>
|
||||
getPersonalWechatSenderStatus: () => Promise<PersonalWechatSenderStatus>
|
||||
getPersonalWechatSendCapability: () => Promise<PersonalWechatSendCapability>
|
||||
getPersonalWechatKeepOneBotProcess: () => Promise<boolean>
|
||||
|
||||
@@ -30,6 +30,7 @@ import type {
|
||||
ImageCandidateQuery,
|
||||
ImageInsight
|
||||
} from '../shared/image-insight'
|
||||
import type { SystemOcrCapability, SystemOcrRequest, SystemOcrResult } from '../shared/system-ocr'
|
||||
import type { AgentHubLogEntry, AgentHubStatus } from '../shared/agent-hub'
|
||||
import type {
|
||||
PersonalWechatGeneratedTtsVoiceRequest,
|
||||
@@ -462,6 +463,11 @@ const api = {
|
||||
limit?: number
|
||||
): Promise<{ success: boolean; insights: ImageInsight[] }> =>
|
||||
ipcRenderer.invoke('image:listInsights', sessionId, limit),
|
||||
// 本地图片文字识别（System OCR，本地 Runtime，非 AI Provider）
|
||||
getSystemOcrCapability: (): Promise<SystemOcrCapability> =>
|
||||
ipcRenderer.invoke('system-ocr:getCapability'),
|
||||
recognizeLocalImageText: (request: SystemOcrRequest): Promise<SystemOcrResult> =>
|
||||
ipcRenderer.invoke('system-ocr:recognize', request),
|
||||
getPersonalWechatSenderStatus: (): Promise<PersonalWechatSenderStatus> =>
|
||||
ipcRenderer.invoke('wechat-personal:getStatus'),
|
||||
getPersonalWechatSendCapability: (): Promise<PersonalWechatSendCapability> =>
|
||||
|
||||
@@ -0,0 +1,255 @@
|
||||
import { useCallback, useEffect, useState } from 'react'
|
||||
import type { SystemOcrCapability, SystemOcrResult } from '../../../../../shared/system-ocr'
|
||||
import { Button } from '../../../components/ui'
|
||||
|
||||
const MAX_FILE_BYTES = 10 * 1024 * 1024
|
||||
|
||||
type LocalOcrStatus = 'idle' | 'reading' | 'ready' | 'running' | 'done' | 'error'
|
||||
|
||||
interface LocalOcrState {
|
||||
status: LocalOcrStatus
|
||||
image?: {
|
||||
dataUrl: string
|
||||
fileName: string
|
||||
size: number
|
||||
}
|
||||
result?: SystemOcrResult
|
||||
error?: string
|
||||
}
|
||||
|
||||
/**
|
||||
* 本地图片文字识别（Windows 系统 OCR）。
|
||||
*
|
||||
* 这是**本地 Runtime**，不是 AI 图片理解：
|
||||
* - 只把图片里的文字读出来；不描述画面、人物、场景，也不做视觉推理；
|
||||
* - 原始图片不会因为这一步发给任何 AI Provider；
|
||||
* - 结果只是派生内容，不会写进本地知识库。
|
||||
*/
|
||||
export function LocalImageTextRecognition(): React.ReactElement {
|
||||
const [capability, setCapability] = useState<SystemOcrCapability | null>(null)
|
||||
const [state, setState] = useState<LocalOcrState>({ status: 'idle' })
|
||||
|
||||
useEffect(() => {
|
||||
let alive = true
|
||||
void window.api
|
||||
.getSystemOcrCapability()
|
||||
.then((value) => {
|
||||
if (alive) setCapability(value)
|
||||
})
|
||||
.catch(() => {
|
||||
if (alive) setCapability(null)
|
||||
})
|
||||
return () => {
|
||||
alive = false
|
||||
}
|
||||
}, [])
|
||||
|
||||
const selectImage = useCallback(async (file: File): Promise<void> => {
|
||||
const extension = file.name.split('.').pop()?.toLowerCase()
|
||||
const inferredType =
|
||||
extension === 'png'
|
||||
? 'image/png'
|
||||
: extension === 'jpg' || extension === 'jpeg'
|
||||
? 'image/jpeg'
|
||||
: extension === 'webp'
|
||||
? 'image/webp'
|
||||
: extension === 'bmp'
|
||||
? 'image/bmp'
|
||||
: extension === 'gif'
|
||||
? 'image/gif'
|
||||
: ''
|
||||
const mimeType = file.type === 'image/jpg' ? 'image/jpeg' : file.type || inferredType
|
||||
const supportedTypes = new Set([
|
||||
'image/png',
|
||||
'image/jpeg',
|
||||
'image/webp',
|
||||
'image/bmp',
|
||||
'image/gif'
|
||||
])
|
||||
if (!supportedTypes.has(mimeType)) {
|
||||
setState({ status: 'error', error: '请选择 PNG、JPG、JPEG、WebP、BMP 或 GIF 图片' })
|
||||
return
|
||||
}
|
||||
if (!file.size || file.size > MAX_FILE_BYTES) {
|
||||
setState({ status: 'error', error: '图片大小必须在 10 MB 以内' })
|
||||
return
|
||||
}
|
||||
setState({ status: 'reading' })
|
||||
try {
|
||||
const rawDataUrl = await readFileAsDataUrl(file)
|
||||
const dataUrl = rawDataUrl.replace(/^data:[^;]*;/, `data:${mimeType};`)
|
||||
setState({
|
||||
status: 'ready',
|
||||
image: { dataUrl, fileName: file.name, size: file.size }
|
||||
})
|
||||
} catch {
|
||||
setState({ status: 'error', error: '图片无法读取，请重新选择' })
|
||||
}
|
||||
}, [])
|
||||
|
||||
const run = useCallback(async (): Promise<void> => {
|
||||
const image = state.image
|
||||
if (!image) return
|
||||
if (!capability?.available) {
|
||||
setState((current) => ({
|
||||
...current,
|
||||
status: 'error',
|
||||
error: capability?.message || '本机当前不支持本地图片文字识别'
|
||||
}))
|
||||
return
|
||||
}
|
||||
setState((current) => ({ ...current, status: 'running', result: undefined, error: undefined }))
|
||||
try {
|
||||
const result = await window.api.recognizeLocalImageText({ imageDataUrl: image.dataUrl })
|
||||
setState((current) =>
|
||||
result.success
|
||||
? { ...current, status: 'done', result, error: undefined }
|
||||
: { ...current, status: 'error', result: undefined, error: localOcrErrorMessage(result) }
|
||||
)
|
||||
} catch {
|
||||
setState((current) => ({
|
||||
...current,
|
||||
status: 'error',
|
||||
result: undefined,
|
||||
error: '本地文字识别调用失败，请重试'
|
||||
}))
|
||||
}
|
||||
}, [capability, state.image])
|
||||
|
||||
const clear = useCallback(() => setState({ status: 'idle' }), [])
|
||||
|
||||
const running = state.status === 'running'
|
||||
const result = state.result
|
||||
|
||||
return (
|
||||
<section className="settings-card local-ocr-test">
|
||||
<header>
|
||||
<div>
|
||||
<h2>本地图片文字识别</h2>
|
||||
<p>使用 Windows 系统 OCR 在本机读取图片中的文字，原始图片无需发送给 AI Provider。</p>
|
||||
</div>
|
||||
<span className={`local-ocr-capability ${capability?.available ? 'supported' : ''}`}>
|
||||
{capability ? (capability.available ? '本机可用' : '本机不可用') : '检测中…'}
|
||||
</span>
|
||||
</header>
|
||||
|
||||
{capability && !capability.available ? (
|
||||
<p className="local-ocr-notice">{capability.message}</p>
|
||||
) : null}
|
||||
{capability?.available ? (
|
||||
<p className="local-ocr-runtime">
|
||||
引擎：Windows 系统 OCR
|
||||
{capability.runtimeVersion ? ` · 组件 ${capability.runtimeVersion}` : ''}
|
||||
{capability.language ? ` · 语言 ${capability.language}` : ' · 语言跟随系统'}
|
||||
</p>
|
||||
) : null}
|
||||
|
||||
<label className={`local-ocr-upload ${state.image ? 'has-image' : ''}`}>
|
||||
<input
|
||||
type="file"
|
||||
accept=".png,.jpg,.jpeg,.webp,.bmp,.gif,image/png,image/jpeg,image/webp,image/bmp,image/gif"
|
||||
onChange={(event) => {
|
||||
const file = event.currentTarget.files?.[0]
|
||||
if (file) void selectImage(file)
|
||||
event.currentTarget.value = ''
|
||||
}}
|
||||
/>
|
||||
{state.image ? (
|
||||
<>
|
||||
<img src={state.image.dataUrl} alt="本地文字识别测试预览" />
|
||||
<div>
|
||||
<strong>{state.image.fileName}</strong>
|
||||
<small>{formatFileSize(state.image.size)} · 仅保存在内存中</small>
|
||||
</div>
|
||||
</>
|
||||
) : (
|
||||
<div>
|
||||
<strong>{state.status === 'reading' ? '正在读取图片…' : '选择本地图片'}</strong>
|
||||
<small>支持 PNG、JPG、JPEG、WebP、BMP、GIF，最大 10 MB</small>
|
||||
</div>
|
||||
)}
|
||||
</label>
|
||||
|
||||
<p className="local-ocr-privacy">
|
||||
使用本地 OCR 时，原始图片无需发送给 AI Provider，也不会写入本地缓存或知识库。如果后续继续使用云端
|
||||
AI 分析，提取出的文字可能按当前 Provider 配置发送。
|
||||
</p>
|
||||
|
||||
{state.error ? <p className="local-ocr-error">{state.error}</p> : null}
|
||||
|
||||
{result?.success ? (
|
||||
<div className="local-ocr-result">
|
||||
<h3>识别结果</h3>
|
||||
<dl>
|
||||
<div>
|
||||
<dt>引擎</dt>
|
||||
<dd>Windows 系统 OCR</dd>
|
||||
</div>
|
||||
<div>
|
||||
<dt>语言</dt>
|
||||
<dd>{result.language || '跟随系统'}</dd>
|
||||
</div>
|
||||
<div>
|
||||
<dt>耗时</dt>
|
||||
<dd>{Math.round(result.durationMs)} ms</dd>
|
||||
</div>
|
||||
</dl>
|
||||
<pre className="local-ocr-text">{result.text}</pre>
|
||||
<p className="local-ocr-hint">
|
||||
本地文字识别只读取图片中的文字内容，不会描述画面、人物或场景。
|
||||
</p>
|
||||
</div>
|
||||
) : null}
|
||||
|
||||
<footer>
|
||||
{state.image ? (
|
||||
<Button variant="outline" onClick={clear}>
|
||||
移除图片
|
||||
</Button>
|
||||
) : null}
|
||||
<Button
|
||||
disabled={!state.image || running || !capability?.available}
|
||||
onClick={() => void run()}
|
||||
>
|
||||
{running ? '识别中…' : '本地文字识别'}
|
||||
</Button>
|
||||
</footer>
|
||||
</section>
|
||||
)
|
||||
}
|
||||
|
||||
function localOcrErrorMessage(result: SystemOcrResult): string {
|
||||
switch (result.errorCode) {
|
||||
case 'UNSUPPORTED_PLATFORM':
|
||||
return '本地图片文字识别目前仅支持 Windows。'
|
||||
case 'SYSTEM_OCR_UNAVAILABLE':
|
||||
return '本地文字识别组件不可用，请重新安装 TraceMemo。'
|
||||
case 'OCR_LANGUAGE_UNAVAILABLE':
|
||||
return '当前 Windows 未安装可用的 OCR 语言支持，请在系统「语言和区域」中安装中文或英文语言包。'
|
||||
case 'UNSUPPORTED_IMAGE':
|
||||
return '这张图片的格式暂不支持本地文字识别。'
|
||||
case 'IMAGE_DECODE_FAILED':
|
||||
return '图片解码失败，无法读取这张图片。'
|
||||
case 'OCR_EMPTY_RESULT':
|
||||
return '没有在这张图片里识别到文字。'
|
||||
default:
|
||||
return result.error || '本地文字识别失败，请重试。'
|
||||
}
|
||||
}
|
||||
|
||||
function formatFileSize(bytes: number): string {
|
||||
return bytes < 1024 * 1024
|
||||
? `${Math.max(1, Math.round(bytes / 1024))} KB`
|
||||
: `${(bytes / 1024 / 1024).toFixed(1)} MB`
|
||||
}
|
||||
|
||||
function readFileAsDataUrl(file: File): Promise<string> {
|
||||
return new Promise((resolve, reject) => {
|
||||
const reader = new FileReader()
|
||||
reader.addEventListener('load', () =>
|
||||
typeof reader.result === 'string' ? resolve(reader.result) : reject(new Error('invalid image'))
|
||||
)
|
||||
reader.addEventListener('error', () => reject(reader.error || new Error('read failed')))
|
||||
reader.readAsDataURL(file)
|
||||
})
|
||||
}
|
||||
@@ -4,6 +4,7 @@ import { Button } from '../../../components/ui'
|
||||
import { AIProviderCard } from '../ai-model/AIProviderCard'
|
||||
import { AIProviderEditor } from '../ai-model/AIProviderEditor'
|
||||
import { AIImageUnderstandingTest } from '../ai-model/AIImageUnderstandingTest'
|
||||
import { LocalImageTextRecognition } from '../ai-model/LocalImageTextRecognition'
|
||||
import { useAIModelSettingsController } from '../ai-model/useAIModelSettingsController'
|
||||
|
||||
export function AIModelPage({
|
||||
@@ -68,6 +69,7 @@ export function AIModelPage({
|
||||
onTest={() => void controller.runVisionTest()}
|
||||
onClear={controller.clearVisionImage}
|
||||
/>
|
||||
<LocalImageTextRecognition />
|
||||
{controller.state.error ? (
|
||||
<p className="ai-model-page-error">{controller.state.error}</p>
|
||||
) : null}
|
||||
|
||||
@@ -1605,6 +1605,167 @@
|
||||
justify-content: flex-end;
|
||||
}
|
||||
|
||||
/* 本地图片文字识别（System OCR，本地 Runtime，与 AI 图片理解刻意区分） */
|
||||
.local-ocr-test {
|
||||
display: grid;
|
||||
gap: 16px;
|
||||
}
|
||||
|
||||
.local-ocr-test > header,
|
||||
.local-ocr-test > footer {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: space-between;
|
||||
gap: 16px;
|
||||
}
|
||||
|
||||
.local-ocr-test h2,
|
||||
.local-ocr-test h3,
|
||||
.local-ocr-test p {
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
.local-ocr-test h2 {
|
||||
color: var(--wxex-text-primary);
|
||||
font-size: 15px;
|
||||
}
|
||||
|
||||
.local-ocr-test header p,
|
||||
.local-ocr-runtime,
|
||||
.local-ocr-upload small,
|
||||
.local-ocr-hint {
|
||||
margin-top: 4px;
|
||||
color: var(--wxex-text-secondary);
|
||||
font-size: 12px;
|
||||
}
|
||||
|
||||
.local-ocr-capability {
|
||||
border-radius: 999px;
|
||||
padding: 5px 9px;
|
||||
background: var(--wxex-bg-sidebar);
|
||||
color: var(--wxex-text-secondary);
|
||||
white-space: nowrap;
|
||||
font-size: 12px;
|
||||
}
|
||||
|
||||
.local-ocr-capability.supported {
|
||||
background: var(--wxex-brand-soft);
|
||||
color: var(--wxex-brand);
|
||||
}
|
||||
|
||||
.local-ocr-notice {
|
||||
border-left: 3px solid var(--wxex-danger);
|
||||
padding: 9px 11px;
|
||||
background: color-mix(in srgb, var(--wxex-danger) 12%, transparent);
|
||||
color: var(--wxex-danger);
|
||||
font-size: 12px;
|
||||
line-height: 1.6;
|
||||
}
|
||||
|
||||
.local-ocr-upload {
|
||||
display: flex;
|
||||
min-height: 112px;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
gap: 14px;
|
||||
border: 1px dashed var(--wxex-border);
|
||||
border-radius: var(--wxex-radius-md);
|
||||
padding: 14px;
|
||||
background: var(--wxex-bg-sidebar);
|
||||
color: var(--wxex-text-primary);
|
||||
text-align: center;
|
||||
cursor: pointer;
|
||||
}
|
||||
|
||||
.local-ocr-upload:hover {
|
||||
border-color: var(--wxex-brand);
|
||||
background: var(--wxex-brand-soft);
|
||||
}
|
||||
|
||||
.local-ocr-upload input {
|
||||
display: none;
|
||||
}
|
||||
|
||||
.local-ocr-upload.has-image {
|
||||
justify-content: flex-start;
|
||||
text-align: left;
|
||||
}
|
||||
|
||||
.local-ocr-upload img {
|
||||
width: 112px;
|
||||
height: 82px;
|
||||
flex: 0 0 auto;
|
||||
border-radius: 8px;
|
||||
object-fit: cover;
|
||||
}
|
||||
|
||||
.local-ocr-upload strong,
|
||||
.local-ocr-upload small {
|
||||
display: block;
|
||||
}
|
||||
|
||||
.local-ocr-privacy {
|
||||
color: var(--wxex-text-secondary);
|
||||
font-size: 12px;
|
||||
line-height: 1.6;
|
||||
}
|
||||
|
||||
.local-ocr-error {
|
||||
border-left: 3px solid var(--wxex-danger);
|
||||
padding: 9px 11px;
|
||||
background: color-mix(in srgb, var(--wxex-danger) 12%, transparent);
|
||||
color: var(--wxex-danger);
|
||||
font-size: 12px;
|
||||
}
|
||||
|
||||
.local-ocr-result {
|
||||
display: grid;
|
||||
gap: 12px;
|
||||
border: 1px solid var(--wxex-border);
|
||||
border-radius: var(--wxex-radius-md);
|
||||
padding: 14px;
|
||||
background: var(--wxex-bg-sidebar);
|
||||
}
|
||||
|
||||
.local-ocr-result dl {
|
||||
display: grid;
|
||||
grid-template-columns: repeat(3, minmax(0, 1fr));
|
||||
gap: 12px;
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
.local-ocr-result dt {
|
||||
color: var(--wxex-text-muted);
|
||||
font-size: 11px;
|
||||
}
|
||||
|
||||
.local-ocr-result dd {
|
||||
margin: 4px 0 0;
|
||||
color: var(--wxex-text-primary);
|
||||
font-size: 12px;
|
||||
font-weight: 600;
|
||||
}
|
||||
|
||||
.local-ocr-text {
|
||||
max-height: 240px;
|
||||
overflow: auto;
|
||||
margin: 0;
|
||||
border: 1px solid var(--wxex-border);
|
||||
border-radius: 8px;
|
||||
padding: 12px;
|
||||
background: var(--wxex-bg-app);
|
||||
color: var(--wxex-text-primary);
|
||||
font-family: inherit;
|
||||
font-size: 13px;
|
||||
line-height: 1.7;
|
||||
white-space: pre-wrap;
|
||||
word-break: break-word;
|
||||
}
|
||||
|
||||
.local-ocr-test > footer {
|
||||
justify-content: flex-end;
|
||||
}
|
||||
|
||||
.report-history-sidebar {
|
||||
display: flex;
|
||||
min-width: 0;
|
||||
|
||||
@@ -0,0 +1,266 @@
|
||||
// src/shared/system-ocr.ts
|
||||
//
|
||||
// 本地系统 OCR（System OCR）共享契约。
|
||||
//
|
||||
// 架构边界（不要混淆）：
|
||||
// - System OCR 是**本地 Runtime**，不是 AI Provider，也不是 Vision Model。
|
||||
// 它不占用 AIVisionRuntimeConfig.source，也不产生任何网络请求。
|
||||
// - 能力边界：只把图片里的文字读出来。它不等于「理解人物 / 理解场景 /
|
||||
// 描述照片 / 理解表情包语义 / 视觉推理」——那些仍然属于 Vision Model。
|
||||
// - Windows 后端为 Windows.Media.Ocr.OcrEngine（经 @napi-rs/system-ocr 调用）。
|
||||
// macOS 本轮只保留架构位置，未实现；Linux 不支持。
|
||||
//
|
||||
// 数据边界（本轮不做）：
|
||||
// - 不做历史图片全量 OCR、不做 Knowledge 回填、不把 OCR 文字伪装成原始聊天文字。
|
||||
// 原始消息始终是权威来源，OCR 文字只是派生内容（本轮仅存在于内存）。
|
||||
|
||||
/** System OCR 引擎标识。这是本地 Runtime，不是 provider id。 */
|
||||
export const SYSTEM_OCR_ENGINE = 'windows-system-ocr'
|
||||
|
||||
/** 本地 OCR 结果在内存中的缓存时长。 */
|
||||
export const SYSTEM_OCR_CACHE_TTL_MS = 10 * 60 * 1000
|
||||
|
||||
/**
|
||||
* 产品级错误码。用户可见文案由 error 字段承载，任何 native 堆栈 / HRESULT
|
||||
* 都不会直接透出到 Renderer。
|
||||
*/
|
||||
export type SystemOcrErrorCode =
|
||||
/** 运行时不可用（native binding 缺失 / 加载失败） */
|
||||
| 'SYSTEM_OCR_UNAVAILABLE'
|
||||
/** 当前平台不支持（Linux，或非 Windows 平台） */
|
||||
| 'UNSUPPORTED_PLATFORM'
|
||||
/** 图片格式不在支持范围内 */
|
||||
| 'UNSUPPORTED_IMAGE'
|
||||
/** 图片解码失败（格式可识别但内容损坏或无法转成 PNG） */
|
||||
| 'IMAGE_DECODE_FAILED'
|
||||
/** 当前 Windows 未安装对应的 OCR 语言支持 */
|
||||
| 'OCR_LANGUAGE_UNAVAILABLE'
|
||||
/** 引擎执行失败 */
|
||||
| 'OCR_FAILED'
|
||||
/** 识别成功执行，但图里没有文字 */
|
||||
| 'OCR_EMPTY_RESULT'
|
||||
|
||||
export type SystemOcrUnavailableReason =
|
||||
| 'UNSUPPORTED_PLATFORM'
|
||||
| 'NATIVE_MODULE_MISSING'
|
||||
| 'LANGUAGE_UNAVAILABLE'
|
||||
|
||||
/** 本机 System OCR 能力。UI 只用它决定是否展示「本地文字识别」入口。 */
|
||||
export interface SystemOcrCapability {
|
||||
/** 本机当前是否真的可以识别图片文字 */
|
||||
available: boolean
|
||||
engine: typeof SYSTEM_OCR_ENGINE
|
||||
platform: NodeJS.Platform
|
||||
arch: string
|
||||
/** @napi-rs/system-ocr 运行时版本；无法读取时为 null */
|
||||
runtimeVersion: string | null
|
||||
/** 实际可用的 OCR 语言标签（对应 Windows 语言包）；null 表示走系统用户语言 */
|
||||
language: string | null
|
||||
reason?: SystemOcrUnavailableReason
|
||||
/** 面向用户的中文说明，可直接展示 */
|
||||
message: string
|
||||
}
|
||||
|
||||
export interface SystemOcrBoundingBox {
|
||||
/** 归一化到 0..1，原点在左上角 */
|
||||
x: number
|
||||
y: number
|
||||
width: number
|
||||
height: number
|
||||
}
|
||||
|
||||
export interface SystemOcrLine {
|
||||
text: string
|
||||
/** Windows 恒为 1.0 */
|
||||
confidence: number
|
||||
boundingBox: SystemOcrBoundingBox
|
||||
}
|
||||
|
||||
/** 本地 OCR 结果。不包含任何 Windows handle / native 内部对象。 */
|
||||
export interface SystemOcrResult {
|
||||
success: boolean
|
||||
/** 归一化后的文本（去掉 CJK 字符之间的引擎伪空格） */
|
||||
text: string
|
||||
lines: SystemOcrLine[]
|
||||
/** 实际使用的 OCR 语言标签；null 表示由系统用户语言决定 */
|
||||
language: string | null
|
||||
engine: typeof SYSTEM_OCR_ENGINE
|
||||
durationMs: number
|
||||
/** 命中内存缓存时为 true */
|
||||
fromCache?: boolean
|
||||
errorCode?: SystemOcrErrorCode
|
||||
error?: string
|
||||
}
|
||||
|
||||
export interface SystemOcrRequest {
|
||||
/** data URL（data:image/png;base64,...）。base64 只在 main 内部流转，不回传 Renderer。 */
|
||||
imageDataUrl: string
|
||||
/** 调用方已经算好的图片内容哈希；未传时由 main 内部计算 */
|
||||
imageHash?: string
|
||||
/** 指定 OCR 语言标签；默认按系统语言解析 */
|
||||
language?: string
|
||||
}
|
||||
|
||||
/**
|
||||
* 缓存 key 组合。刻意与 ImageInsight 的 `imageHash` 保持不同的键空间，
|
||||
* 保证远端 Vision 的旧结果永远不会被当成"本地 OCR 结果"复用，
|
||||
* 也保证 System OCR 运行时升级后不会永远命中旧结果。
|
||||
*/
|
||||
export const buildSystemOcrCacheKey = (input: {
|
||||
imageHash: string
|
||||
language: string | null
|
||||
runtimeVersion: string | null
|
||||
platform?: string
|
||||
}): string =>
|
||||
[
|
||||
input.imageHash,
|
||||
SYSTEM_OCR_ENGINE,
|
||||
input.platform ?? 'unknown',
|
||||
input.language ?? 'auto',
|
||||
input.runtimeVersion ?? 'unknown'
|
||||
].join('|')
|
||||
|
||||
const CJK_CHAR =
|
||||
/[\u3000-\u303f\u3040-\u30ff\u3400-\u4dbf\u4e00-\u9fff\uf900-\ufaff\uff00-\uffef\uac00-\ud7af]/
|
||||
|
||||
/**
|
||||
* Windows OCR 会在每个 CJK 字符之间插入空格（"本 地 图 片"）。
|
||||
* 这里只删除 **两侧都是 CJK** 的空格，保留 "TraceMemo 本地图片文字识别" 里的真实分隔。
|
||||
*/
|
||||
export const normalizeSystemOcrText = (value: string): string => {
|
||||
const source = String(value ?? '')
|
||||
if (!source) return ''
|
||||
let result = ''
|
||||
for (let index = 0; index < source.length; index += 1) {
|
||||
const char = source[index]
|
||||
if (char === ' ' || char === '\u3000') {
|
||||
const previous = result[result.length - 1]
|
||||
let next = ''
|
||||
for (let lookahead = index + 1; lookahead < source.length; lookahead += 1) {
|
||||
if (source[lookahead] !== ' ' && source[lookahead] !== '\u3000') {
|
||||
next = source[lookahead]
|
||||
break
|
||||
}
|
||||
}
|
||||
if (previous && next && CJK_CHAR.test(previous) && CJK_CHAR.test(next)) continue
|
||||
}
|
||||
result += char
|
||||
}
|
||||
return result.trim()
|
||||
}
|
||||
|
||||
/** 把系统 locale（如 zh-CN / en-US）映射成 Windows OCR 语言标签。 */
|
||||
const LANGUAGE_TAG_BY_LOCALE: Record<string, string> = {
|
||||
zh: 'zh-Hans-CN',
|
||||
'zh-cn': 'zh-Hans-CN',
|
||||
'zh-hans': 'zh-Hans-CN',
|
||||
'zh-hans-cn': 'zh-Hans-CN',
|
||||
'zh-sg': 'zh-Hans-CN',
|
||||
'zh-tw': 'zh-Hant-TW',
|
||||
'zh-hant': 'zh-Hant-TW',
|
||||
'zh-hant-tw': 'zh-Hant-TW',
|
||||
'zh-hk': 'zh-Hant-HK',
|
||||
'zh-hant-hk': 'zh-Hant-HK',
|
||||
'zh-mo': 'zh-Hant-MO',
|
||||
'zh-hant-mo': 'zh-Hant-MO',
|
||||
en: 'en-US',
|
||||
'en-us': 'en-US',
|
||||
'en-gb': 'en-GB',
|
||||
'en-au': 'en-AU',
|
||||
'en-ca': 'en-CA',
|
||||
ja: 'ja-JP',
|
||||
'ja-jp': 'ja-JP',
|
||||
ko: 'ko-KR',
|
||||
'ko-kr': 'ko-KR',
|
||||
fr: 'fr-FR',
|
||||
'fr-fr': 'fr-FR',
|
||||
de: 'de-DE',
|
||||
'de-de': 'de-DE',
|
||||
es: 'es-ES',
|
||||
'es-es': 'es-ES',
|
||||
it: 'it-IT',
|
||||
'it-it': 'it-IT',
|
||||
pt: 'pt-BR',
|
||||
'pt-br': 'pt-BR',
|
||||
ru: 'ru-RU',
|
||||
'ru-ru': 'ru-RU'
|
||||
}
|
||||
|
||||
export const resolveSystemOcrLanguageTag = (
|
||||
locale: string | null | undefined
|
||||
): string | null => {
|
||||
const normalized = String(locale ?? '')
|
||||
.trim()
|
||||
.toLowerCase()
|
||||
.replace(/_/g, '-')
|
||||
if (!normalized) return null
|
||||
if (LANGUAGE_TAG_BY_LOCALE[normalized]) return LANGUAGE_TAG_BY_LOCALE[normalized]
|
||||
const primary = normalized.split('-')[0]
|
||||
return LANGUAGE_TAG_BY_LOCALE[primary] ?? null
|
||||
}
|
||||
|
||||
/**
|
||||
* 把 native 错误映射成产品级错误码。
|
||||
*
|
||||
* 已确认的 Windows 行为（1.2.0）：
|
||||
* - 语言包缺失 / 引擎无法创建：`Windows error 操作成功完成。 (0x00000000)`
|
||||
* —— TryCreateFromLanguage 返回 null 引擎但 HRESULT 是 S_OK，非常容易误判。
|
||||
* - 送给解码器的字节不是可识别的图片：`Windows error Could not recognize file (0x80070005)`
|
||||
*/
|
||||
export const mapSystemOcrNativeError = (message: string): SystemOcrErrorCode => {
|
||||
const detail = String(message ?? '')
|
||||
if (!detail) return 'OCR_FAILED'
|
||||
if (/Cannot find native binding|Failed to load native binding|MODULE_NOT_FOUND/i.test(detail)) {
|
||||
return 'SYSTEM_OCR_UNAVAILABLE'
|
||||
}
|
||||
if (/\(0x00000000\)/.test(detail)) return 'OCR_LANGUAGE_UNAVAILABLE'
|
||||
if (/Could not recognize file/i.test(detail)) return 'IMAGE_DECODE_FAILED'
|
||||
if (/Could not open file/i.test(detail)) return 'IMAGE_DECODE_FAILED'
|
||||
return 'OCR_FAILED'
|
||||
}
|
||||
|
||||
/** 解析 data URL；只接受图片 MIME。 */
|
||||
export const parseImageDataUrl = (
|
||||
dataUrl: string
|
||||
): { mimeType: string; base64: string } | null => {
|
||||
const matched = /^data:(image\/[a-z0-9.+-]+);base64,(.+)$/i.exec(String(dataUrl ?? '').trim())
|
||||
if (!matched) return null
|
||||
return { mimeType: matched[1].toLowerCase(), base64: matched[2] }
|
||||
}
|
||||
|
||||
export type SystemOcrImageFormat = 'png' | 'jpeg' | 'gif' | 'bmp' | 'webp' | 'tiff'
|
||||
|
||||
/** 按魔数识别格式。返回 null 表示不在支持范围内。 */
|
||||
export const detectSystemOcrImageFormat = (buffer: Uint8Array): SystemOcrImageFormat | null => {
|
||||
if (!buffer || buffer.length < 4) return null
|
||||
const byte = (index: number): number => buffer[index]
|
||||
if (byte(0) === 0x89 && byte(1) === 0x50 && byte(2) === 0x4e && byte(3) === 0x47) return 'png'
|
||||
if (byte(0) === 0xff && byte(1) === 0xd8 && byte(2) === 0xff) return 'jpeg'
|
||||
if (byte(0) === 0x47 && byte(1) === 0x49 && byte(2) === 0x46) return 'gif'
|
||||
if (byte(0) === 0x42 && byte(1) === 0x4d) return 'bmp'
|
||||
if (
|
||||
byte(0) === 0x52 &&
|
||||
byte(1) === 0x49 &&
|
||||
byte(2) === 0x46 &&
|
||||
byte(3) === 0x46 &&
|
||||
buffer.length > 11 &&
|
||||
byte(8) === 0x57 &&
|
||||
byte(9) === 0x45 &&
|
||||
byte(10) === 0x42 &&
|
||||
byte(11) === 0x50
|
||||
) {
|
||||
return 'webp'
|
||||
}
|
||||
if ((byte(0) === 0x49 && byte(1) === 0x49) || (byte(0) === 0x4d && byte(1) === 0x4d)) {
|
||||
return 'tiff'
|
||||
}
|
||||
return null
|
||||
}
|
||||
|
||||
/**
|
||||
* 64x32 纯白 PNG。仅用于 language capability 探测：
|
||||
* 引擎能创建 → 该语言包可用；引擎创建失败 → 语言不可用。
|
||||
* 探测耗时量级为个位数毫秒。
|
||||
*/
|
||||
export const SYSTEM_OCR_PROBE_PNG_BASE64 =
|
||||
'iVBORw0KGgoAAAANSUhEUgAAAEAAAAAgCAIAAAAt/+nTAAAANUlEQVR42u3PAQkAAAgDMLV/59tCELYG6yT12dRzAgICAgICAgICAgICAgICAgICAgICAvcWMisDPdIJjMIAAAAASUVORK5CYII='
|
||||
@@ -6,6 +6,7 @@ import { AIProviderCard } from '../../src/renderer/src/features/settings/ai-mode
|
||||
import { AIModelPage } from '../../src/renderer/src/features/settings/pages/AIModelPage'
|
||||
import type { AIProviderSummary, AIRuntimeModelConfig } from '../../src/shared/ai-provider'
|
||||
import type { AIVisionTestState } from '../../src/renderer/src/features/settings/ai-model/types'
|
||||
import type { SystemOcrCapability } from '../../src/shared/system-ocr'
|
||||
|
||||
const runtime: AIRuntimeModelConfig = {
|
||||
providerName: 'Not configured',
|
||||
@@ -15,6 +16,16 @@ const runtime: AIRuntimeModelConfig = {
|
||||
status: 'untested'
|
||||
}
|
||||
|
||||
const systemOcrCapability: SystemOcrCapability = {
|
||||
available: true,
|
||||
engine: 'windows-system-ocr',
|
||||
platform: 'win32',
|
||||
arch: 'x64',
|
||||
runtimeVersion: '1.2.0',
|
||||
language: 'zh-Hans-CN',
|
||||
message: '本地图片文字识别可用（Windows 系统 OCR，zh-Hans-CN）。'
|
||||
}
|
||||
|
||||
const provider: AIProviderSummary = {
|
||||
id: 'fixture-provider',
|
||||
name: '本地假服务',
|
||||
@@ -56,7 +67,8 @@ describe('AI model settings', () => {
|
||||
})
|
||||
window.api = {
|
||||
listAIProviders: vi.fn().mockResolvedValue({ success: true, providers: [] }),
|
||||
getAIRuntimeConfig: vi.fn().mockResolvedValue(runtime)
|
||||
getAIRuntimeConfig: vi.fn().mockResolvedValue(runtime),
|
||||
getSystemOcrCapability: vi.fn().mockResolvedValue(systemOcrCapability)
|
||||
} as typeof window.api
|
||||
})
|
||||
|
||||
|
||||
@@ -0,0 +1,107 @@
|
||||
import { fireEvent, render, screen, waitFor } from '@testing-library/react'
|
||||
import { beforeEach, describe, expect, it, vi } from 'vitest'
|
||||
import { LocalImageTextRecognition } from '../../src/renderer/src/features/settings/ai-model/LocalImageTextRecognition'
|
||||
import type { SystemOcrCapability, SystemOcrResult } from '../../src/shared/system-ocr'
|
||||
|
||||
const availableCapability: SystemOcrCapability = {
|
||||
available: true,
|
||||
engine: 'windows-system-ocr',
|
||||
platform: 'win32',
|
||||
arch: 'x64',
|
||||
runtimeVersion: '1.2.0',
|
||||
language: 'zh-Hans-CN',
|
||||
message: '本地图片文字识别可用（Windows 系统 OCR，zh-Hans-CN）。'
|
||||
}
|
||||
|
||||
const unavailableCapability: SystemOcrCapability = {
|
||||
available: false,
|
||||
engine: 'windows-system-ocr',
|
||||
platform: 'win32',
|
||||
arch: 'x64',
|
||||
runtimeVersion: '1.2.0',
|
||||
language: null,
|
||||
reason: 'LANGUAGE_UNAVAILABLE',
|
||||
message: '当前 Windows 未安装可用的 OCR 语言支持。'
|
||||
}
|
||||
|
||||
const successResult: SystemOcrResult = {
|
||||
success: true,
|
||||
text: 'TraceMemo 本地文字识别',
|
||||
lines: [],
|
||||
language: 'zh-Hans-CN',
|
||||
engine: 'windows-system-ocr',
|
||||
durationMs: 42
|
||||
}
|
||||
|
||||
const emptyResult: SystemOcrResult = {
|
||||
success: false,
|
||||
text: '',
|
||||
lines: [],
|
||||
language: 'zh-Hans-CN',
|
||||
engine: 'windows-system-ocr',
|
||||
durationMs: 12,
|
||||
errorCode: 'OCR_EMPTY_RESULT',
|
||||
error: '没有在这张图片里识别到文字。'
|
||||
}
|
||||
|
||||
const selectImage = (): void => {
|
||||
const input = document.querySelector<HTMLInputElement>('input[type="file"]')
|
||||
if (!input) throw new Error('file input missing')
|
||||
const file = new File([new Uint8Array([0x89, 0x50, 0x4e, 0x47])], 'fixture.png', {
|
||||
type: 'image/png'
|
||||
})
|
||||
fireEvent.change(input, { target: { files: [file] } })
|
||||
}
|
||||
|
||||
describe('LocalImageTextRecognition', () => {
|
||||
beforeEach(() => {
|
||||
window.api = {
|
||||
getSystemOcrCapability: vi.fn().mockResolvedValue(availableCapability),
|
||||
recognizeLocalImageText: vi.fn().mockResolvedValue(successResult)
|
||||
} as typeof window.api
|
||||
})
|
||||
|
||||
it('shows local availability without requiring any AI provider', async () => {
|
||||
render(<LocalImageTextRecognition />)
|
||||
expect(await screen.findByText('本机可用')).toBeInTheDocument()
|
||||
expect(screen.getByText(/组件 1\.2\.0/)).toBeInTheDocument()
|
||||
expect(screen.getByRole('button', { name: '本地文字识别' })).toBeDisabled()
|
||||
})
|
||||
|
||||
it('recognizes text locally and renders the extracted text', async () => {
|
||||
render(<LocalImageTextRecognition />)
|
||||
await screen.findByText('本机可用')
|
||||
|
||||
selectImage()
|
||||
const button = await screen.findByRole('button', { name: '本地文字识别' })
|
||||
await waitFor(() => expect(button).toBeEnabled())
|
||||
fireEvent.click(button)
|
||||
|
||||
expect(await screen.findByText('TraceMemo 本地文字识别')).toBeInTheDocument()
|
||||
expect(window.api.recognizeLocalImageText).toHaveBeenCalledWith({
|
||||
imageDataUrl: expect.stringContaining('data:image/png;base64,')
|
||||
})
|
||||
})
|
||||
|
||||
it('surfaces an empty OCR result as a product message, not a native error', async () => {
|
||||
vi.mocked(window.api.recognizeLocalImageText).mockResolvedValue(emptyResult)
|
||||
render(<LocalImageTextRecognition />)
|
||||
await screen.findByText('本机可用')
|
||||
|
||||
selectImage()
|
||||
const button = await screen.findByRole('button', { name: '本地文字识别' })
|
||||
await waitFor(() => expect(button).toBeEnabled())
|
||||
fireEvent.click(button)
|
||||
|
||||
expect(await screen.findByText('没有在这张图片里识别到文字。')).toBeInTheDocument()
|
||||
})
|
||||
|
||||
it('keeps the entry disabled and explains why when the language pack is missing', async () => {
|
||||
vi.mocked(window.api.getSystemOcrCapability).mockResolvedValue(unavailableCapability)
|
||||
render(<LocalImageTextRecognition />)
|
||||
|
||||
expect(await screen.findByText('本机不可用')).toBeInTheDocument()
|
||||
expect(screen.getByText('当前 Windows 未安装可用的 OCR 语言支持。')).toBeInTheDocument()
|
||||
expect(screen.getByRole('button', { name: '本地文字识别' })).toBeDisabled()
|
||||
})
|
||||
})
|
||||
Vendored
BIN
Binary file not shown.
|
After Width: | Height: | Size: 10 KiB |
BIN
Binary file not shown.
|
After Width: | Height: | Size: 20 KiB |
BIN
Binary file not shown.
|
After Width: | Height: | Size: 12 KiB |
Vendored
BIN
Binary file not shown.
|
After Width: | Height: | Size: 14 KiB |
@@ -0,0 +1,96 @@
|
||||
// Windows System OCR native fidelity。
|
||||
//
|
||||
// 这是 capability-gated 的原生冒烟测试：
|
||||
// - 只有在「当前平台支持 + native 运行时可用 + 有可用 OCR 语言包」时才真正跑；
|
||||
// - CI 环境无法保证 Windows OCR 语言包，所以中文识别不作为所有 CI 的硬门槛
|
||||
// （mock 单元测试才是 mandatory，见 tests/unit/system-ocr-service.test.ts）；
|
||||
// - 在 Windows 真机上必须实际通过。
|
||||
//
|
||||
// fixture 全部是 synthetic 图片（tests/fixtures/ocr/*），不含任何真实聊天数据。
|
||||
|
||||
import { readFileSync } from 'node:fs'
|
||||
import { join } from 'node:path'
|
||||
import { describe, expect, it, vi } from 'vitest'
|
||||
import { SYSTEM_OCR_ENGINE } from '../../src/shared/system-ocr'
|
||||
|
||||
vi.mock('../../src/main/image-decrypt-service', () => ({
|
||||
resolveFfmpegExecutable: (): string => 'ffmpeg'
|
||||
}))
|
||||
|
||||
import { systemOcrService } from '../../src/main/services/system-ocr-service'
|
||||
|
||||
const fixtureDirectory = join(__dirname, '..', 'fixtures', 'ocr')
|
||||
|
||||
const toDataUrl = (fileName: string, mimeType: string): string =>
|
||||
`data:${mimeType};base64,${readFileSync(join(fixtureDirectory, fileName)).toString('base64')}`
|
||||
|
||||
/** 只比较"主要 token"，避免系统字体 / 识别微差造成脆弱测试。 */
|
||||
const expectContainsTokens = (text: string, tokens: string[]): void => {
|
||||
const normalized = text.replace(/[\s\u3000]+/g, '').toLowerCase()
|
||||
for (const token of tokens) {
|
||||
expect(normalized).toContain(token.replace(/[\s\u3000]+/g, '').toLowerCase())
|
||||
}
|
||||
}
|
||||
|
||||
const capability = await systemOcrService.getCapability()
|
||||
const nativeGate = capability.available ? it : it.skip
|
||||
|
||||
describe('Windows System OCR native fidelity', () => {
|
||||
it('reports a usable capability on this machine', () => {
|
||||
expect(capability.engine).toBe(SYSTEM_OCR_ENGINE)
|
||||
if (!capability.available) {
|
||||
console.warn(`[integration] System OCR native smoke skipped: ${capability.message}`)
|
||||
}
|
||||
})
|
||||
|
||||
nativeGate('recognizes simplified Chinese text', async () => {
|
||||
const result = await systemOcrService.recognize({
|
||||
imageDataUrl: toDataUrl('system-ocr-zh.png', 'image/png')
|
||||
})
|
||||
expect(result.success).toBe(true)
|
||||
expectContainsTokens(result.text, ['TraceMemo', '本地', '文字', '识别'])
|
||||
// 语言要么是探测到的语言包，要么是"跟随系统用户语言"（null）。
|
||||
if (capability.language) {
|
||||
expect(result.language).toBe(capability.language)
|
||||
} else {
|
||||
expect(result.language).toBeNull()
|
||||
}
|
||||
expect(result.durationMs).toBeGreaterThan(0)
|
||||
})
|
||||
|
||||
nativeGate('recognizes English text', async () => {
|
||||
const result = await systemOcrService.recognize({
|
||||
imageDataUrl: toDataUrl('system-ocr-en.png', 'image/png')
|
||||
})
|
||||
expect(result.success).toBe(true)
|
||||
expectContainsTokens(result.text, ['TraceMemo', 'System', 'OCR'])
|
||||
})
|
||||
|
||||
nativeGate('recognizes mixed Chinese/English text', async () => {
|
||||
const result = await systemOcrService.recognize({
|
||||
imageDataUrl: toDataUrl('system-ocr-mixed.png', 'image/png')
|
||||
})
|
||||
expect(result.success).toBe(true)
|
||||
expectContainsTokens(result.text, ['TraceMemo', '本地', 'OCR', '2026'])
|
||||
})
|
||||
|
||||
/**
|
||||
* 引擎的 Buffer 输入只接受 PNG，所以 JPEG 必须走本服务的归一化路径。
|
||||
* 这条用例就是那个约束的回归保护。
|
||||
*/
|
||||
nativeGate('normalizes a JPEG source before OCR', async () => {
|
||||
const result = await systemOcrService.recognize({
|
||||
imageDataUrl: toDataUrl('system-ocr-mixed.jpg', 'image/jpeg')
|
||||
})
|
||||
expect(result.success).toBe(true)
|
||||
expectContainsTokens(result.text, ['TraceMemo', 'OCR', '2026'])
|
||||
})
|
||||
|
||||
nativeGate('caches an identical repeat request', async () => {
|
||||
const request = { imageDataUrl: toDataUrl('system-ocr-mixed.png', 'image/png') }
|
||||
const first = await systemOcrService.recognize(request)
|
||||
const second = await systemOcrService.recognize(request)
|
||||
expect(first.success).toBe(true)
|
||||
expect(second.fromCache).toBe(true)
|
||||
})
|
||||
})
|
||||
@@ -0,0 +1,349 @@
|
||||
import { readFileSync } from 'node:fs'
|
||||
import { join } from 'node:path'
|
||||
import { beforeEach, describe, expect, it, vi } from 'vitest'
|
||||
import {
|
||||
SYSTEM_OCR_ENGINE,
|
||||
SYSTEM_OCR_PROBE_PNG_BASE64,
|
||||
buildSystemOcrCacheKey,
|
||||
detectSystemOcrImageFormat,
|
||||
mapSystemOcrNativeError,
|
||||
normalizeSystemOcrText,
|
||||
parseImageDataUrl,
|
||||
resolveSystemOcrLanguageTag
|
||||
} from '../../src/shared/system-ocr'
|
||||
|
||||
vi.mock('../../src/main/image-decrypt-service', () => ({
|
||||
resolveFfmpegExecutable: (): string => 'ffmpeg'
|
||||
}))
|
||||
|
||||
const { getByHash, upsert } = vi.hoisted(() => ({
|
||||
getByHash: vi.fn(),
|
||||
upsert: vi.fn()
|
||||
}))
|
||||
|
||||
vi.mock('../../src/main/db/image-insights-store', () => ({
|
||||
imageInsightsStore: {
|
||||
getByHash,
|
||||
upsert,
|
||||
listBySession: vi.fn(() => [])
|
||||
}
|
||||
}))
|
||||
|
||||
import { SystemOcrService } from '../../src/main/services/system-ocr-service'
|
||||
import { imageInsightService } from '../../src/main/services/image-insight-service'
|
||||
|
||||
const PROBE_BYTES = Buffer.from(SYSTEM_OCR_PROBE_PNG_BASE64, 'base64')
|
||||
const FIXTURE_PNG = readFileSync(join(__dirname, '..', 'fixtures', 'ocr', 'system-ocr-zh.png'))
|
||||
const PNG_DATA_URL = `data:image/png;base64,${FIXTURE_PNG.toString('base64')}`
|
||||
const JPEG_DATA_URL = `data:image/jpeg;base64,${Buffer.from([0xff, 0xd8, 0xff, 0xe0, 0x00, 0x10]).toString('base64')}`
|
||||
const GARBAGE_DATA_URL = `data:image/png;base64,${Buffer.from('definitely-not-an-image').toString('base64')}`
|
||||
|
||||
const LANGUAGE_UNAVAILABLE_MESSAGE = 'Windows error 操作成功完成。 (0x00000000)'
|
||||
const DECODE_FAILED_MESSAGE = 'Windows error Could not recognize file (0x80070005)'
|
||||
|
||||
/**
|
||||
* mock 运行时按「探测图字节」区分 capability probe 和业务调用，
|
||||
* 这样 probeError 才能稳定复现「语言包缺失」的场景。
|
||||
*/
|
||||
const createRuntime = (
|
||||
options: {
|
||||
text?: string
|
||||
lines?: Array<{ text: string; confidence?: number }>
|
||||
probeError?: string
|
||||
error?: string
|
||||
version?: string | null
|
||||
} = {}
|
||||
): { version: string | null; recognize: ReturnType<typeof vi.fn> } => {
|
||||
const recognize = vi.fn(
|
||||
async (image: Uint8Array, _accuracy?: number, _languages?: string[]): Promise<unknown> => {
|
||||
if (Buffer.from(image).equals(PROBE_BYTES)) {
|
||||
if (options.probeError) throw new Error(options.probeError)
|
||||
return { text: '', confidence: 1, lines: [] }
|
||||
}
|
||||
if (options.error) throw new Error(options.error)
|
||||
const text = options.text ?? ''
|
||||
return {
|
||||
text,
|
||||
confidence: 1,
|
||||
lines: (options.lines ?? [{ text, confidence: 1 }]).map((line) => ({
|
||||
text: line.text,
|
||||
confidence: line.confidence ?? 1,
|
||||
boundingBox: { x: 0.1, y: 0.2, width: 0.3, height: 0.4 }
|
||||
}))
|
||||
}
|
||||
}
|
||||
)
|
||||
return { version: options.version === undefined ? '1.2.0' : options.version, recognize }
|
||||
}
|
||||
|
||||
const createService = (
|
||||
runtime: { version: string | null; recognize: ReturnType<typeof vi.fn> } | null,
|
||||
overrides: Partial<ConstructorParameters<typeof SystemOcrService>[0]> = {}
|
||||
): SystemOcrService =>
|
||||
new SystemOcrService({
|
||||
platform: 'win32',
|
||||
arch: 'x64',
|
||||
locale: () => 'zh-CN',
|
||||
loadRuntime: () => (runtime ? { ...runtime } : null),
|
||||
toPngBytes: async ({ buffer }) => buffer,
|
||||
...overrides
|
||||
})
|
||||
|
||||
describe('system-ocr shared helpers', () => {
|
||||
it('removes only the engine-inserted spaces between CJK glyphs', () => {
|
||||
expect(normalizeSystemOcrText('TraceMemo 本 地 图 片 文 字 识 别')).toBe(
|
||||
'TraceMemo 本地图片文字识别'
|
||||
)
|
||||
expect(normalizeSystemOcrText('TraceMemo System OCR')).toBe('TraceMemo System OCR')
|
||||
expect(normalizeSystemOcrText(' 本 地 ')).toBe('本地')
|
||||
})
|
||||
|
||||
it('maps system locale onto Windows OCR language tags', () => {
|
||||
expect(resolveSystemOcrLanguageTag('zh-CN')).toBe('zh-Hans-CN')
|
||||
expect(resolveSystemOcrLanguageTag('zh-Hans-CN')).toBe('zh-Hans-CN')
|
||||
expect(resolveSystemOcrLanguageTag('zh_TW')).toBe('zh-Hant-TW')
|
||||
expect(resolveSystemOcrLanguageTag('en-US')).toBe('en-US')
|
||||
expect(resolveSystemOcrLanguageTag('en')).toBe('en-US')
|
||||
expect(resolveSystemOcrLanguageTag('')).toBeNull()
|
||||
expect(resolveSystemOcrLanguageTag('xx-YY')).toBeNull()
|
||||
})
|
||||
|
||||
it('maps native Windows errors onto product error codes', () => {
|
||||
expect(mapSystemOcrNativeError(LANGUAGE_UNAVAILABLE_MESSAGE)).toBe('OCR_LANGUAGE_UNAVAILABLE')
|
||||
expect(mapSystemOcrNativeError(DECODE_FAILED_MESSAGE)).toBe('IMAGE_DECODE_FAILED')
|
||||
expect(mapSystemOcrNativeError('Cannot find native binding.')).toBe('SYSTEM_OCR_UNAVAILABLE')
|
||||
expect(mapSystemOcrNativeError('Failed to load native binding')).toBe('SYSTEM_OCR_UNAVAILABLE')
|
||||
expect(mapSystemOcrNativeError('Windows error something broke (0x80070057)')).toBe('OCR_FAILED')
|
||||
expect(mapSystemOcrNativeError('')).toBe('OCR_FAILED')
|
||||
})
|
||||
|
||||
it('parses image data urls and rejects other payloads', () => {
|
||||
expect(parseImageDataUrl(PNG_DATA_URL)).toMatchObject({ mimeType: 'image/png' })
|
||||
expect(parseImageDataUrl('data:text/plain;base64,aGk=')).toBeNull()
|
||||
expect(parseImageDataUrl('not-a-data-url')).toBeNull()
|
||||
})
|
||||
|
||||
it('detects supported container formats by magic bytes', () => {
|
||||
expect(detectSystemOcrImageFormat(Buffer.from([0x89, 0x50, 0x4e, 0x47]))).toBe('png')
|
||||
expect(detectSystemOcrImageFormat(Buffer.from([0xff, 0xd8, 0xff, 0xe0]))).toBe('jpeg')
|
||||
expect(detectSystemOcrImageFormat(Buffer.from('GIF89a'))).toBe('gif')
|
||||
expect(detectSystemOcrImageFormat(Buffer.from('BM1234'))).toBe('bmp')
|
||||
expect(
|
||||
detectSystemOcrImageFormat(Buffer.concat([Buffer.from('RIFF'), Buffer.alloc(4), Buffer.from('WEBP')]))
|
||||
).toBe('webp')
|
||||
expect(detectSystemOcrImageFormat(Buffer.from([0x49, 0x49, 0x2a, 0x00]))).toBe('tiff')
|
||||
expect(detectSystemOcrImageFormat(Buffer.from('nope'))).toBeNull()
|
||||
})
|
||||
|
||||
it('keeps the local OCR cache keyspace separate from the vision imageHash', () => {
|
||||
const base = { imageHash: 'a'.repeat(32), language: 'zh-Hans-CN', runtimeVersion: '1.2.0' }
|
||||
const key = buildSystemOcrCacheKey({ ...base, platform: 'win32' })
|
||||
expect(key).not.toBe(base.imageHash)
|
||||
expect(key).toContain(SYSTEM_OCR_ENGINE)
|
||||
expect(key).toContain('zh-Hans-CN')
|
||||
expect(key).toContain('1.2.0')
|
||||
// 语言或运行时版本变化必须换 key，避免复用过期 / 跨引擎结果。
|
||||
expect(buildSystemOcrCacheKey({ ...base, language: 'en-US', platform: 'win32' })).not.toBe(key)
|
||||
expect(
|
||||
buildSystemOcrCacheKey({ ...base, runtimeVersion: '1.3.0', platform: 'win32' })
|
||||
).not.toBe(key)
|
||||
})
|
||||
})
|
||||
|
||||
describe('SystemOcrService capability detection', () => {
|
||||
it('reports available with the probed language on Windows', async () => {
|
||||
const service = createService(createRuntime())
|
||||
const capability = await service.getCapability()
|
||||
expect(capability).toMatchObject({
|
||||
available: true,
|
||||
engine: SYSTEM_OCR_ENGINE,
|
||||
platform: 'win32',
|
||||
arch: 'x64',
|
||||
runtimeVersion: '1.2.0',
|
||||
language: 'zh-Hans-CN'
|
||||
})
|
||||
})
|
||||
|
||||
it('is unavailable on unsupported platforms without loading a runtime', async () => {
|
||||
const loadRuntime = vi.fn(() => null)
|
||||
const service = createService(null, { platform: 'linux', loadRuntime })
|
||||
const capability = await service.getCapability()
|
||||
expect(capability.available).toBe(false)
|
||||
expect(capability.reason).toBe('UNSUPPORTED_PLATFORM')
|
||||
expect(loadRuntime).not.toHaveBeenCalled()
|
||||
})
|
||||
|
||||
it('is unavailable when the native runtime cannot be loaded', async () => {
|
||||
const service = createService(null)
|
||||
const capability = await service.getCapability()
|
||||
expect(capability.available).toBe(false)
|
||||
expect(capability.reason).toBe('NATIVE_MODULE_MISSING')
|
||||
})
|
||||
|
||||
it('reports a missing Windows OCR language pack as LANGUAGE_UNAVAILABLE', async () => {
|
||||
const runtime = createRuntime({ probeError: LANGUAGE_UNAVAILABLE_MESSAGE })
|
||||
const service = createService(runtime)
|
||||
const capability = await service.getCapability()
|
||||
expect(capability.available).toBe(false)
|
||||
expect(capability.reason).toBe('LANGUAGE_UNAVAILABLE')
|
||||
expect(capability.message).toContain('OCR 语言')
|
||||
})
|
||||
})
|
||||
|
||||
describe('SystemOcrService recognition', () => {
|
||||
beforeEach(() => {
|
||||
getByHash.mockReset()
|
||||
getByHash.mockReturnValue(null)
|
||||
upsert.mockReset()
|
||||
})
|
||||
|
||||
it('normalizes a successful result and reports runtime metadata', async () => {
|
||||
const runtime = createRuntime({
|
||||
text: 'TraceMemo 本 地 OCR 2026',
|
||||
lines: [{ text: 'TraceMemo 本 地 OCR 2026' }]
|
||||
})
|
||||
const service = createService(runtime)
|
||||
|
||||
const result = await service.recognize({ imageDataUrl: PNG_DATA_URL })
|
||||
|
||||
expect(result).toMatchObject({
|
||||
success: true,
|
||||
text: 'TraceMemo 本地 OCR 2026',
|
||||
language: 'zh-Hans-CN',
|
||||
engine: SYSTEM_OCR_ENGINE
|
||||
})
|
||||
expect(result.lines[0].boundingBox).toEqual({ x: 0.1, y: 0.2, width: 0.3, height: 0.4 })
|
||||
expect(result.durationMs).toBeGreaterThanOrEqual(0)
|
||||
})
|
||||
|
||||
it('returns OCR_EMPTY_RESULT when the engine finds no text', async () => {
|
||||
const service = createService(createRuntime({ text: '' }))
|
||||
const result = await service.recognize({ imageDataUrl: PNG_DATA_URL })
|
||||
expect(result.success).toBe(false)
|
||||
expect(result.errorCode).toBe('OCR_EMPTY_RESULT')
|
||||
expect(result.text).toBe('')
|
||||
})
|
||||
|
||||
it('returns UNSUPPORTED_PLATFORM on non-Windows platforms', async () => {
|
||||
const service = createService(null, { platform: 'darwin', arch: 'arm64' })
|
||||
const result = await service.recognize({ imageDataUrl: PNG_DATA_URL })
|
||||
expect(result.success).toBe(false)
|
||||
expect(result.errorCode).toBe('UNSUPPORTED_PLATFORM')
|
||||
expect(result.engine).toBe(SYSTEM_OCR_ENGINE)
|
||||
})
|
||||
|
||||
it('returns OCR_LANGUAGE_UNAVAILABLE when no OCR language pack is installed', async () => {
|
||||
const service = createService(createRuntime({ probeError: LANGUAGE_UNAVAILABLE_MESSAGE }))
|
||||
const result = await service.recognize({ imageDataUrl: PNG_DATA_URL })
|
||||
expect(result.success).toBe(false)
|
||||
expect(result.errorCode).toBe('OCR_LANGUAGE_UNAVAILABLE')
|
||||
})
|
||||
|
||||
it('rejects payloads that are not a supported image container', async () => {
|
||||
const runtime = createRuntime()
|
||||
const service = createService(runtime)
|
||||
|
||||
const badUrl = await service.recognize({ imageDataUrl: 'nope' })
|
||||
expect(badUrl.errorCode).toBe('UNSUPPORTED_IMAGE')
|
||||
|
||||
const garbage = await service.recognize({ imageDataUrl: GARBAGE_DATA_URL })
|
||||
expect(garbage.errorCode).toBe('UNSUPPORTED_IMAGE')
|
||||
expect(runtime.recognize).not.toHaveBeenCalled()
|
||||
})
|
||||
|
||||
it('maps an image preparation failure onto IMAGE_DECODE_FAILED', async () => {
|
||||
const runtime = createRuntime()
|
||||
const service = createService(runtime, { toPngBytes: async () => null })
|
||||
const result = await service.recognize({ imageDataUrl: JPEG_DATA_URL })
|
||||
expect(result.success).toBe(false)
|
||||
expect(result.errorCode).toBe('IMAGE_DECODE_FAILED')
|
||||
})
|
||||
|
||||
it('maps a native OCR failure onto a product error code', async () => {
|
||||
const runtime = createRuntime({ error: DECODE_FAILED_MESSAGE })
|
||||
const service = createService(runtime)
|
||||
const result = await service.recognize({ imageDataUrl: PNG_DATA_URL })
|
||||
expect(result.success).toBe(false)
|
||||
expect(result.errorCode).toBe('IMAGE_DECODE_FAILED')
|
||||
expect(result.error).not.toContain('0x80070005')
|
||||
})
|
||||
|
||||
it('caches by image identity + engine + language + runtime version only', async () => {
|
||||
const runtime = createRuntime({ text: 'TraceMemo 本 地' })
|
||||
const service = createService(runtime)
|
||||
|
||||
const first = await service.recognize({ imageDataUrl: PNG_DATA_URL })
|
||||
const callsAfterFirst = runtime.recognize.mock.calls.length
|
||||
const second = await service.recognize({ imageDataUrl: PNG_DATA_URL })
|
||||
|
||||
expect(first.success).toBe(true)
|
||||
expect(second.fromCache).toBe(true)
|
||||
expect(runtime.recognize.mock.calls.length).toBe(callsAfterFirst)
|
||||
|
||||
// 运行时版本升级 → 缓存 key 变化 → 必须重新识别，不能永远吃旧结果。
|
||||
const upgradedRuntime = createRuntime({ text: 'TraceMemo 本 地' })
|
||||
service.bind({
|
||||
loadRuntime: () => ({ version: '1.3.0', recognize: upgradedRuntime.recognize })
|
||||
})
|
||||
const afterUpgrade = await service.recognize({ imageDataUrl: PNG_DATA_URL })
|
||||
|
||||
expect(afterUpgrade.success).toBe(true)
|
||||
expect(afterUpgrade.fromCache).toBeUndefined()
|
||||
expect(upgradedRuntime.recognize).toHaveBeenCalled()
|
||||
})
|
||||
|
||||
it('never reuses a remote Vision insight as a local OCR result', async () => {
|
||||
getByHash.mockReturnValue({
|
||||
imageHash: 'a'.repeat(32),
|
||||
description: '远端 Vision 旧结果',
|
||||
ocrText: '远端 OCR 文本',
|
||||
updatedAt: Date.now()
|
||||
})
|
||||
const runtime = createRuntime({ text: '本地 文 字' })
|
||||
const service = createService(runtime)
|
||||
|
||||
const result = await service.recognize({ imageDataUrl: PNG_DATA_URL })
|
||||
|
||||
expect(result.text).toBe('本地文字')
|
||||
expect(getByHash).not.toHaveBeenCalled()
|
||||
})
|
||||
})
|
||||
|
||||
describe('ImageInsightService local OCR orchestration', () => {
|
||||
beforeEach(() => {
|
||||
getByHash.mockReset()
|
||||
getByHash.mockReturnValue(null)
|
||||
upsert.mockReset()
|
||||
})
|
||||
|
||||
it('exposes capability and never falls back to the remote vision provider', async () => {
|
||||
const analyzeImage = vi.fn(async () => ({ success: true, data: '{}' }))
|
||||
imageInsightService.bind({
|
||||
providerService: {
|
||||
list: () => ({ providers: [], defaultProviderId: 'vision-provider' }),
|
||||
getVisionRuntimeConfig: () => ({
|
||||
providerId: 'vision-provider',
|
||||
providerName: 'OpenAI',
|
||||
model: 'gpt-vision',
|
||||
modelName: 'gpt-vision',
|
||||
configured: true
|
||||
}),
|
||||
analyzeImage
|
||||
},
|
||||
decryptService: {
|
||||
findImageFile: () => null,
|
||||
decryptImageToBase64: () => null
|
||||
}
|
||||
})
|
||||
|
||||
const capability = await imageInsightService.getSystemOcrCapability()
|
||||
expect(capability.engine).toBe(SYSTEM_OCR_ENGINE)
|
||||
|
||||
const result = await imageInsightService.extractLocalText({ imageDataUrl: PNG_DATA_URL })
|
||||
expect(result.engine).toBe(SYSTEM_OCR_ENGINE)
|
||||
// 关键约束：本地 OCR 路径绝不调用远端 Vision Provider。
|
||||
expect(analyzeImage).not.toHaveBeenCalled()
|
||||
// 也不写 Vision 的 insight 缓存。
|
||||
expect(upsert).not.toHaveBeenCalled()
|
||||
})
|
||||
})
|
||||
Reference in New Issue
Block a user