feat: interview review module with whisper.cpp ASR + AI analysis + frontend page

New backend module 'interview-review' provides: - Audio upload (50MB limit, MP3/M4A/WAV/AAC/OGG/MP4/WebM) - Text transcript submission - whisper.cpp local ASR integration (tiny + base models) - AI analysis (4-dimension scoring: logic/expression/professionalism/stability) - Speech analysis (filler words detection, pace, duration) - Async processing pipeline with status polling - Graceful fallback to mock ASR when whisper unavailable New frontend page 'pages/review/review.vue' with 3 modes: - List mode: review history with status indicators - Upload mode: audio file upload or text paste - Report mode: score radar, dimension bars, analysis details Docs updated: PROJECT-STATUS.md v4.4, FEATURE-LIST.md v4.2, ROADMAP.md v4.2
2026-06-16 18:32:25 +08:00
parent 96c367e0f8
commit 4cd889c081
16 changed files with 1771 additions and 80 deletions
@@ -0,0 +1,302 @@
+import { Injectable, Logger, HttpException, HttpStatus } from '@nestjs/common'
+import { InjectModel } from '@nestjs/mongoose'
+import { Model } from 'mongoose'
+import { InterviewReview, InterviewReviewDocument } from './interview-review.schema'
+import { AiService } from '../ai/ai.service'
+import { AsrService } from './asr.service'
+import { analyzeSpeech } from '../../common/utils/filler-words'
+import * as fs from 'fs'
+import * as path from 'path'
+
+@Injectable()
+export class InterviewReviewService {
+  private readonly logger = new Logger(InterviewReviewService.name)
+
+  constructor(
+    @InjectModel(InterviewReview.name) private reviewModel: Model<InterviewReviewDocument>,
+    private aiService: AiService,
+    private asrService: AsrService,
+  ) {}
+
+  async create(
+    userId: string,
+    position: string,
+    company?: string,
+    audioFile?: any,
+  ) {
+    let audioInfo: any = undefined
+    if (audioFile) {
+      const crypto = await import('crypto')
+      const hash = crypto.createHash('md5').update(audioFile.buffer).digest('hex')
+      audioInfo = {
+        hash,
+        filePath: audioFile.path,
+        duration: 0,
+        size: audioFile.size,
+        mimeType: audioFile.mimetype,
+      }
+    }
+
+    const review = new this.reviewModel({
+      userId,
+      position,
+      company: company || '',
+      status: 'processing',
+      audioFile: audioInfo,
+    })
+
+    const saved = await review.save()
+
+    // Start async processing (non-blocking)
+    this.processReview(saved._id.toString()).catch((err) => {
+      this.logger.error(`Review ${saved._id} processing failed: ${err.message}`)
+    })
+
+    return {
+      id: saved._id.toString(),
+      status: 'processing',
+      estimatedTime: 120,
+    }
+  }
+
+  /** Create from text transcript (skip ASR, go straight to analysis) */
+  async createFromText(
+    userId: string,
+    position: string,
+    text: string,
+    company?: string,
+  ) {
+    const review = new this.reviewModel({
+      userId,
+      position,
+      company: company || '',
+      status: 'processing',
+      transcript: {
+        fullText: text,
+        segments: [{
+          startTime: 0,
+          endTime: Math.max(text.length / 3.5, 10),
+          speaker: 'candidate',
+          text,
+        }],
+      },
+    })
+
+    const saved = await review.save()
+
+    this.processReview(saved._id.toString()).catch((err) => {
+      this.logger.error(`Review ${saved._id} processing failed: ${err.message}`)
+    })
+
+    return {
+      id: saved._id.toString(),
+      status: 'processing',
+      estimatedTime: 60,
+    }
+  }
+
+  async processReview(reviewId: string) {
+    const review = await this.reviewModel.findById(reviewId)
+    if (!review) {
+      throw new Error('Review not found')
+    }
+
+    try {
+      // Step 1: ASR (if audio file exists and no transcript yet)
+      let transcript = review.transcript
+      if (!transcript && review.audioFile?.filePath) {
+        const asrResult = await this.asrService.transcribe(
+          review.audioFile.filePath,
+          review.audioFile.mimeType,
+        )
+        transcript = {
+          fullText: asrResult.fullText,
+          segments: asrResult.segments.map(s => ({
+            startTime: s.startTime,
+            endTime: s.endTime,
+            speaker: s.speaker as 'interviewer' | 'candidate',
+            text: s.text,
+          })),
+        }
+        await this.reviewModel.findByIdAndUpdate(reviewId, { transcript })
+      }
+
+      const transcriptText = transcript?.fullText || ''
+
+      // Step 2: Speech analysis (filler words)
+      const speechResult = analyzeSpeech(transcriptText)
+      let pace = '适中'
+      const rate = speechResult.speechRate
+      if (rate > 5) pace = '偏快'
+      else if (rate < 2.5) pace = '偏慢'
+
+      const speechAnalysis = {
+        fillerWords: speechResult.fillerWords,
+        fillerScore: speechResult.fillerScore,
+        fillerDensity: speechResult.fillerDensity,
+        pace,
+        totalDuration: speechResult.estimatedDurationSec,
+        totalChars: speechResult.totalChars,
+      }
+
+      // Step 3: AI analysis
+      const analysis = await this.runAiAnalysis(transcriptText, review.position, review.company)
+
+      // Save results
+      await this.reviewModel.findByIdAndUpdate(reviewId, {
+        status: 'completed',
+        analysis,
+        speechAnalysis,
+        'audioFile.duration': speechResult.estimatedDurationSec,
+      })
+    } catch (err: any) {
+      this.logger.error(`Processing failed for review ${reviewId}: ${err.message}`)
+      await this.reviewModel.findByIdAndUpdate(reviewId, {
+        status: 'failed',
+        $inc: { retryCount: 1 },
+      })
+    }
+  }
+
+  private async runAiAnalysis(transcriptText: string, position: string, company: string) {
+    if (!transcriptText.trim()) {
+      return this.emptyAnalysis()
+    }
+
+    const systemPrompt = `你是一位资深的校招面试评估专家。分析以下面试转录内容，输出评估报告。
+
+评估维度（0-100分）：
+1. 逻辑思维(logic)：回答是否结构化、层次分明、有因果关系
+2. 表达能力(expression)：语言是否流畅、用词是否准确、表达是否清晰
+3. 专业度(professionalism)：技术栈掌握程度、行业认知深度、术语使用是否准确
+4. 临场稳定性(stability)：面对问题是否沉着、反应速度、抗压能力
+
+输出格式（严格的 JSON，不要多余内容）：
+{
+  "overallScore": 0-100,
+  "dimensions": { "logic": 0-100, "expression": 0-100, "professionalism": 0-100, "stability": 0-100 },
+  "strengths": ["亮点1", "亮点2"],
+  "weaknesses": ["不足1", "不足2"],
+  "suggestions": ["改进建议1", "改进建议2"],
+  "questionBreakdown": [
+    {
+      "question": "面试官的问题",
+      "answer": "用户的回答摘要",
+      "score": 0-100,
+      "comment": "简短评语",
+      "suggestedAnswer": "参考回答思路"
+    }
+  ]
+}`
+
+    const companyStr = company ? `面试公司: ${company}\n` : ''
+    const userMessage = `面试岗位: ${position}\n${companyStr}\n面试转录:\n${transcriptText}\n\n请评估并输出 JSON 报告。`
+
+    try {
+      const result = await this.aiService.call({
+        systemPrompt,
+        userMessage,
+        temperature: 0.5,
+        maxTokens: 2048,
+      })
+      const parsed = JSON.parse(result)
+
+      // Validate required fields
+      if (!parsed.overallScore || !parsed.dimensions) {
+        return this.emptyAnalysis()
+      }
+
+      return {
+        overallScore: Math.min(100, Math.max(0, Math.round(parsed.overallScore))),
+        dimensions: {
+          logic: Math.min(100, Math.max(0, Math.round(parsed.dimensions.logic || 0))),
+          expression: Math.min(100, Math.max(0, Math.round(parsed.dimensions.expression || 0))),
+          professionalism: Math.min(100, Math.max(0, Math.round(parsed.dimensions.professionalism || 0))),
+          stability: Math.min(100, Math.max(0, Math.round(parsed.dimensions.stability || 0))),
+        },
+        strengths: Array.isArray(parsed.strengths) ? parsed.strengths : [],
+        weaknesses: Array.isArray(parsed.weaknesses) ? parsed.weaknesses : [],
+        suggestions: Array.isArray(parsed.suggestions) ? parsed.suggestions : [],
+        questionBreakdown: Array.isArray(parsed.questionBreakdown) ? parsed.questionBreakdown.slice(0, 10) : [],
+      }
+    } catch {
+      return this.emptyAnalysis()
+    }
+  }
+
+  private emptyAnalysis() {
+    return {
+      overallScore: 60,
+      dimensions: { logic: 60, expression: 60, professionalism: 60, stability: 60 },
+      strengths: ['转录文本为空或 AI 分析异常'],
+      weaknesses: ['请检查音频文件或重新上传'],
+      suggestions: ['确保录音清晰完整后重新提交'],
+      questionBreakdown: [],
+    }
+  }
+
+  async getDetail(reviewId: string, userId: string) {
+    const review = await this.reviewModel.findById(reviewId).lean()
+    if (!review) {
+      throw new HttpException('复盘记录不存在', HttpStatus.NOT_FOUND)
+    }
+    if (review.userId.toString() !== userId) {
+      throw new HttpException('无权访问', HttpStatus.FORBIDDEN)
+    }
+    return this.sanitize(review)
+  }
+
+  async listByUser(userId: string, page = 1, limit = 20) {
+    const skip = (page - 1) * limit
+    const [items, total] = await Promise.all([
+      this.reviewModel
+        .find({ userId })
+        .sort({ createdAt: -1 })
+        .skip(skip)
+        .limit(limit)
+        .select('-transcript.fullText -transcript.segments')
+        .lean(),
+      this.reviewModel.countDocuments({ userId }),
+    ])
+    return {
+      items: items.map(i => this.sanitize(i)),
+      total,
+      page,
+      limit,
+      totalPages: Math.ceil(total / limit),
+    }
+  }
+
+  async delete(reviewId: string, userId: string) {
+    const review = await this.reviewModel.findById(reviewId)
+    if (!review) {
+      throw new HttpException('复盘记录不存在', HttpStatus.NOT_FOUND)
+    }
+    if (review.userId.toString() !== userId) {
+      throw new HttpException('无权删除', HttpStatus.FORBIDDEN)
+    }
+
+    // Delete audio file if exists
+    if (review.audioFile?.filePath) {
+      try {
+        fs.unlinkSync(review.audioFile.filePath)
+      } catch {
+        // ignore
+      }
+    }
+
+    await this.reviewModel.findByIdAndDelete(reviewId)
+    return { success: true }
+  }
+
+  private sanitize(item: any) {
+    if (!item) return item
+    const obj = { ...item }
+    // Remove sensitive fields
+    if (obj.audioFile?.filePath) {
+      obj.audioFile = { ...obj.audioFile }
+      delete obj.audioFile.filePath
+    }
+    return obj
+  }
+}