497 lines
16 KiB
TypeScript
497 lines
16 KiB
TypeScript
import { BrowserWindow, ipcMain, dialog as dialogBox, app } from 'electron'
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import { captureScreen, closeScreenshot, getCapturedImage, getCapturedBase64, clearCapturedImage, startScreenshot } from './screenshot'
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import { getMainWindow, openDialogWindow } from './window'
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import * as fs from 'fs'
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import * as path from 'path'
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import log from 'electron-log'
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let store: any = null
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function getStore() {
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if (!store) {
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const Store = require('electron-store').default
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store = new Store({
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defaults: {
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apiKey: '',
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baseUrl: 'https://api.siliconflow.cn/v1',
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model: 'gpt-4o',
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shortcut: 'Alt+Q',
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theme: 'light',
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fontSize: 14,
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proxy: '',
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timeout: 120,
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screenshotSavePath: ''
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}
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})
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// migrate old low timeout values
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const t = store.get('timeout') as number | undefined
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if (t !== undefined && t < 60) store.set('timeout', 120)
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}
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return store
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}
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let db: any = null
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function getDb() {
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if (!db) {
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const Database = require('better-sqlite3')
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const dbPath = require('path').join(app.getPath('userData'), 'grading.db')
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db = new Database(dbPath)
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db.prepare(`CREATE TABLE IF NOT EXISTS history (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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question_id INTEGER,
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image_path TEXT,
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student_answer TEXT,
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ai_score REAL,
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teacher_score REAL,
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confidence REAL,
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created_at DATETIME DEFAULT CURRENT_TIMESTAMP
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)`).run()
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db.prepare(`CREATE TABLE IF NOT EXISTS exam (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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name TEXT,
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course TEXT,
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created_at DATETIME DEFAULT CURRENT_TIMESTAMP
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)`).run()
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db.prepare(`CREATE TABLE IF NOT EXISTS question (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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exam_id INTEGER,
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title TEXT,
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max_score INTEGER,
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rubric TEXT
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)`).run()
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db.prepare(`CREATE TABLE IF NOT EXISTS rubric (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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question_title TEXT NOT NULL DEFAULT '',
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max_score REAL NOT NULL DEFAULT 100,
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reference_answer TEXT NOT NULL DEFAULT '',
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rubric TEXT NOT NULL DEFAULT '',
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sort_order INTEGER NOT NULL DEFAULT 0,
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reference_answer_image TEXT NOT NULL DEFAULT ''
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)`).run()
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// migrate: add column for existing DBs
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try { db.prepare('ALTER TABLE rubric ADD COLUMN reference_answer_image TEXT NOT NULL DEFAULT \'\'').run() } catch (_) {}
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}
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return db
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}
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export function setupIpc(win: BrowserWindow): void {
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ipcMain.handle('window:dragMove', (_event, { deltaX, deltaY }: { deltaX: number; deltaY: number }) => {
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const [x, y] = win.getPosition()
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win.setPosition(x + deltaX, y + deltaY)
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})
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ipcMain.handle('window:dragEnd', (_event, { x, y }: { x: number; y: number }) => {
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win.setPosition(x, y)
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})
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ipcMain.handle('window:resizeMain', (_event, width: number) => {
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const [wx, wy] = win.getPosition()
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win.setBounds({ x: wx, y: wy, width: Math.max(200, Math.min(width, 1200)), height: 64 })
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})
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ipcMain.handle('screenshot:start', () => {
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log.info('IPC: screenshot:start')
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startScreenshot(win)
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})
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ipcMain.handle('screenshot:capture', async (_event, region: { x: number; y: number; width: number; height: number }) => {
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log.info('IPC: screenshot:capture', region)
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const base64 = await captureScreen(region)
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closeScreenshot()
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setTimeout(() => {
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const mainWin = getMainWindow()
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if (mainWin) {
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mainWin.show()
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mainWin.webContents.send('screenshot:completed', base64)
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}
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require('./shortcut').enableShortcut()
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}, 100)
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return base64
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})
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ipcMain.handle('screenshot:getLastImage', () => {
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return getCapturedBase64()
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})
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ipcMain.handle('screenshot:cancel', () => {
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log.info('IPC: screenshot:cancel')
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closeScreenshot()
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setTimeout(() => {
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const mainWin = getMainWindow()
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if (mainWin) mainWin.show()
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require('./shortcut').enableShortcut()
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}, 100)
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})
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ipcMain.handle('ai:grade', async (_event, { imageBase64, rubric, apiConfig, maxScore, referenceAnswer, questionTitle, referenceAnswerImage }: {
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imageBase64: string
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rubric: string
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apiConfig: { apiKey: string; baseUrl: string; model: string }
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maxScore?: number
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referenceAnswer?: string
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questionTitle?: string
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referenceAnswerImage?: string
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}) => {
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log.info('IPC: ai:grade')
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try {
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const result = await callAiApi(imageBase64, rubric, apiConfig, { maxScore, referenceAnswer, questionTitle, referenceAnswerImage })
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return result
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} catch (err: any) {
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log.error('AI grade failed:', err)
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throw new Error(err.message || 'AI grading failed')
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}
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})
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ipcMain.handle('settings:get', () => {
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return getStore().store
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})
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ipcMain.handle('settings:set', (_event, settings: Record<string, unknown>) => {
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const s = getStore()
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for (const [key, value] of Object.entries(settings)) {
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s.set(key, value)
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}
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return true
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})
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ipcMain.handle('settings:selectDirectory', async () => {
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const result = await dialogBox.showOpenDialog({
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properties: ['openDirectory']
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})
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if (result.canceled || result.filePaths.length === 0) return null
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return result.filePaths[0]
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})
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ipcMain.handle('history:list', () => {
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try {
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return getDb().prepare('SELECT * FROM history ORDER BY created_at DESC LIMIT 100').all()
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} catch (err) {
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log.error('history:list error:', err)
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return []
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}
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})
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ipcMain.handle('history:delete', (_event, id: number) => {
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try {
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getDb().prepare('DELETE FROM history WHERE id = ?').run(id)
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return true
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} catch {
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return false
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}
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})
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ipcMain.handle('grading:submit', (_event, data: {
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questionId: number
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imagePath: string
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aiScore: number
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teacherScore: number
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confidence: number
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studentAnswer?: string
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}) => {
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try {
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getDb().prepare(`INSERT INTO history (question_id, image_path, student_answer, ai_score, teacher_score, confidence)
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VALUES (?, ?, ?, ?, ?, ?)`).run(
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data.questionId || 0,
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data.imagePath || '',
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data.studentAnswer || '',
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data.aiScore,
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data.teacherScore,
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data.confidence
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)
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return true
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} catch (err) {
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log.error('grading:submit error:', err)
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return false
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}
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})
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ipcMain.handle('template:list', () => {
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try {
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const db = getDb()
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const exams = db.prepare('SELECT * FROM exam ORDER BY created_at DESC').all()
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return exams
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} catch {
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return []
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}
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})
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ipcMain.handle('template:save', (_event, data: { name: string; course: string }) => {
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try {
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const db = getDb()
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const result = db.prepare('INSERT INTO exam (name, course) VALUES (?, ?)').run(data.name, data.course)
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return result.lastInsertRowid
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} catch (err) {
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log.error('template:save error:', err)
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return null
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}
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})
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// --- Dialog child windows ---
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ipcMain.handle('dialog:open', (_event, { type, data }: { type: string; data?: any }) => {
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log.info('IPC: dialog:open', type)
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if (data !== undefined) {
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dialogPayloads[type] = data
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}
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openDialogWindow(type)
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})
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ipcMain.on('dialog:close', (_event) => {
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const w = BrowserWindow.fromWebContents(_event.sender)
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if (w) w.close()
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})
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ipcMain.handle('dialog:getPayload', (_event, type: string) => {
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const data = dialogPayloads[type]
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delete dialogPayloads[type]
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return data
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})
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// --- Open image file from disk ---
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ipcMain.handle('dialog:openImage', async () => {
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const result = await dialogBox.showOpenDialog({
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properties: ['openFile'],
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filters: [{ name: '图片', extensions: ['png', 'jpg', 'jpeg', 'bmp', 'gif', 'webp'] }]
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})
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if (result.canceled || result.filePaths.length === 0) return null
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const filePath = result.filePaths[0]
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const ext = path.extname(filePath).toLowerCase().replace('.', '')
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const mime = ext === 'jpg' ? 'jpeg' : ext
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const buffer = fs.readFileSync(filePath)
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return { base64: buffer.toString('base64'), mime, filePath }
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})
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// --- Rubric data bridge (toolbar ↔ rubric window), persisted to DB ---
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ipcMain.handle('rubric:storeData', (_event, data: any) => {
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const d = getDb()
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const questions = data?.questions || []
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log.info(`rubric:storeData: ${questions.length} questions`, JSON.stringify(questions.map((q: any) => ({ title: q.questionTitle, rubricLen: q.rubric?.length }))))
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if (questions.length === 0) return
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d.prepare('DELETE FROM rubric').run()
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const insert = d.prepare('INSERT INTO rubric (question_title, max_score, reference_answer, rubric, sort_order, reference_answer_image) VALUES (?, ?, ?, ?, ?, ?)')
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for (let i = 0; i < questions.length; i++) {
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const q = questions[i]
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insert.run(q.questionTitle || '', q.maxScore ?? 100, q.referenceAnswer || '', q.rubric || '', i, q.referenceAnswerImage || '')
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}
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})
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ipcMain.handle('rubric:getData', () => {
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const d = getDb()
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const rows: any[] = d.prepare('SELECT * FROM rubric ORDER BY sort_order').all()
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log.info(`rubric:getData: ${rows.length} rows`)
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if (rows.length) {
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return {
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questions: rows.map(r => ({
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questionTitle: r.question_title,
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maxScore: r.max_score,
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referenceAnswer: r.reference_answer,
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rubric: r.rubric,
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referenceAnswerImage: r.reference_answer_image || undefined
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})),
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currentIndex: 0
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}
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}
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return null
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})
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ipcMain.handle('rubric:exportJson', async () => {
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const d = getDb()
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const rows: any[] = d.prepare('SELECT * FROM rubric ORDER BY sort_order').all()
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if (!rows.length) throw new Error('暂无评分标准可导出')
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const questions = rows.map(r => ({
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questionTitle: r.question_title,
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maxScore: r.max_score,
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referenceAnswer: r.reference_answer,
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rubric: r.rubric,
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referenceAnswerImage: r.reference_answer_image || undefined
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}))
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const result = await dialogBox.showSaveDialog({
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defaultPath: '评分标准.json',
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filters: [{ name: 'JSON', extensions: ['json'] }]
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})
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if (result.canceled || !result.filePath) return false
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fs.writeFileSync(result.filePath, JSON.stringify(questions, null, 2), 'utf-8')
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return true
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})
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ipcMain.handle('rubric:importJson', async () => {
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const result = await dialogBox.showOpenDialog({
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properties: ['openFile'],
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filters: [{ name: 'JSON', extensions: ['json'] }]
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})
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if (result.canceled || result.filePaths.length === 0) return null
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const content = fs.readFileSync(result.filePaths[0], 'utf-8')
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const questions = JSON.parse(content)
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if (!Array.isArray(questions)) throw new Error('JSON 格式错误：应为数组')
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return { questions, currentIndex: 0 }
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})
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// --- Rubric next question index (persisted between grading cycles) ---
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let rubricNextIndex = 0
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ipcMain.handle('rubric:getNextIndex', () => rubricNextIndex)
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ipcMain.handle('rubric:setNextIndex', (_event, idx: number) => { rubricNextIndex = idx })
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ipcMain.handle('rubric:resetNextIndex', () => { rubricNextIndex = 0 })
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// --- Grading data bridge (toolbar → result window) ---
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ipcMain.handle('grading:storeData', (_event, data: any) => {
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gradingPayload = data
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})
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ipcMain.handle('grading:getData', () => gradingPayload)
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}
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const dialogPayloads: Record<string, any> = {}
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let gradingPayload: any = null
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async function callAiApi(imageBase64: string, rubric: string, config: { apiKey: string; baseUrl: string; model: string }, extras?: { maxScore?: number; referenceAnswer?: string; questionTitle?: string; referenceAnswerImage?: string }): Promise<{
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score: number
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confidence: number
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deductions: string[]
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comment: string
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}> {
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const systemRole = `你是高校阅卷专家，严格按照评分标准逐项评分。只输出JSON，不包含任何其他文字。`
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const hasRefImage = !!extras?.referenceAnswerImage
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const prompt = hasRefImage
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? `${extras?.questionTitle ? `【题目】\n${extras.questionTitle}\n` : ''}【评分标准】
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${rubric || '无'}
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【参考答案】
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${extras?.referenceAnswer || '无'}
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【满分】
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${extras?.maxScore ?? 100}
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图片1：学生答案
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图片2：标准答案
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请按照标准答案（图片2）给学生答案（图片1）评分。
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---
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【评分规则】
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1. 根据评分标准中的各项指标逐项评分，每项给出得分和说明
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2. 各评分项得分之和不得超过满分${extras?.maxScore ?? 100}分
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3. 如果学生答案为空、空白或明显与题目无关，直接给0分
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4. 部分正确时按评分标准酌情给分
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【输出要求】
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只输出以下JSON，不要包含markdown代码块、\`\`\`标记、注释或任何其他文字：
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{
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"score": <总分>,
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"confidence": <置信度0~1>,
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"deductions": ["扣分项说明1", "扣分项说明2"],
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"comment": "总评语及逐项得分说明"
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}`
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: `${extras?.questionTitle ? `【题目】\n${extras.questionTitle}\n` : ''}【评分标准】
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${rubric || '无'}
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【参考答案】
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${extras?.referenceAnswer || '无'}
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【满分】
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${extras?.maxScore ?? 100}
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【学生答案】
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请看图片中的内容。
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---
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【评分规则】
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1. 根据评分标准中的各项指标逐项评分，每项给出得分和说明
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2. 各评分项得分之和不得超过满分${extras?.maxScore ?? 100}分
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3. 如果学生答案为空、空白或明显与题目无关，直接给0分
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4. 部分正确时按评分标准酌情给分
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【输出要求】
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只输出以下JSON，不要包含markdown代码块、\`\`\`标记、注释或任何其他文字：
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{
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"score": <总分>,
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"confidence": <置信度0~1>,
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"deductions": ["扣分项说明1", "扣分项说明2"],
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"comment": "总评语及逐项得分说明"
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}`
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const axios = require('axios')
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const userContent: any[] = hasRefImage
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? [
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{ type: 'text', text: prompt },
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{ type: 'image_url', image_url: { url: `data:image/png;base64,${imageBase64}` } },
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{ type: 'image_url', image_url: { url: `data:image/png;base64,${extras!.referenceAnswerImage}` } }
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]
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: [
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{ type: 'image_url', image_url: { url: `data:image/png;base64,${imageBase64}` } },
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{ type: 'text', text: prompt }
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]
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const response = await axios.post(`${config.baseUrl}/chat/completions`, {
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model: config.model,
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messages: [
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{
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role: 'system',
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content: systemRole
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},
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{
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role: 'user',
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content: userContent
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}
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],
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max_tokens: 4096,
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temperature: 0.3
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}, {
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headers: {
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'Content-Type': 'application/json',
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'Authorization': `Bearer ${config.apiKey}`
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},
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timeout: ((getStore().get('timeout') as number) ?? 120) * 1000
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})
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const content = response.data?.choices?.[0]?.message?.content
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if (!content) {
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log.error('AI API 返回为空或格式异常:', JSON.stringify(response.data).slice(0, 1000))
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throw new Error(`API 返回为空，请检查模型名是否正确 (当前: ${config.model})`)
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}
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const parsed = tryParseJson(content)
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if (!parsed) {
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log.error('AI 返回 JSON 解析失败:', content.slice(0, 500))
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throw new Error(`AI 返回格式异常，无法解析为 JSON。原始返回：\n${content}`)
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}
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return {
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score: parsed.score,
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confidence: parsed.confidence ?? 0.5,
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deductions: parsed.deductions ?? [],
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comment: parsed.comment ?? parsed.commit ?? ''
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}
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}
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function tryParseJson(text: string): any {
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let cleaned = text.trim()
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// remove markdown code fences
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cleaned = cleaned.replace(/```(?:json)?\s*/gi, '').replace(/```\s*/g, '').trim()
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// if there's still non-JSON text, extract the first {...} object
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if (!cleaned.startsWith('{') && !cleaned.startsWith('[')) {
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const match = cleaned.match(/\{[\s\S]*\}/)
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if (match) cleaned = match[0]
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}
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// attempt direct parse
|
|
try {
|
|
return JSON.parse(cleaned)
|
|
} catch {}
|
|
// fix single quotes -> double quotes (but keep escaped ones)
|
|
try {
|
|
const fixed = cleaned
|
|
.replace(/(?<!\\)'/g, '"')
|
|
.replace(/,(\s*[}\]])/g, '$1') // trailing commas
|
|
return JSON.parse(fixed)
|
|
} catch {}
|
|
// fix unquoted keys
|
|
try {
|
|
const fixed = cleaned
|
|
.replace(/([{,]\s*)(\w+)(\s*:)/g, '$1"$2"$3')
|
|
.replace(/,(\s*[}\]])/g, '$1')
|
|
return JSON.parse(fixed)
|
|
} catch {}
|
|
return null
|
|
}
|