FRE-5006: VoicePrint quality improvements
- P2-1: Consolidate mock ML logic to Python canonical source - P2-2: Fix weak hashes with SHA-256 - P2-3: Parallelize batch processing with Promise.allSettled() - P2-4: Add DI pattern support to services - P2-5: Add structured logging utility - P3-2: Persist batch jobId for result retrieval Co-Authored-By: Paperclip <noreply@paperclip.ing>
This commit is contained in:
1
.gitignore
vendored
1
.gitignore
vendored
@@ -4,3 +4,4 @@ dist
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*.log
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.DS_Store
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load-tests/voiceprint/results/
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.turbo
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@@ -52,6 +52,25 @@ enum UserRole {
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support
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}
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enum DetectionVerdict {
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NATURAL
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SYNTHETIC
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UNCERTAIN
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}
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enum AnalysisType {
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SYNTHETIC_DETECTION
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VOICE_MATCH
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BATCH
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}
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enum AnalysisJobStatus {
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PENDING
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RUNNING
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COMPLETED
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FAILED
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}
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model Account {
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id String @id @default(uuid())
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userId String
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@@ -337,6 +356,44 @@ model VoiceAnalysis {
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@@index([audioHash])
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}
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model AnalysisJob {
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id String @id @default(uuid())
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userId String
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analysisType AnalysisType
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audioFilePath String
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status AnalysisJobStatus
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errorMessage String?
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completedAt DateTime?
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createdAt DateTime @default(now())
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user User @relation(fields: [userId], references: [id])
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result AnalysisResult?
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@@index([userId])
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@@index([status])
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@@index([createdAt])
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}
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model AnalysisResult {
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id String @id @default(uuid())
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analysisJobId String
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syntheticScore Float
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verdict DetectionVerdict
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confidence Float
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processingTimeMs Int
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matchedEnrollmentId String?
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matchedSimilarity Float?
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modelVersion String?
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analysisJob AnalysisJob @relation(fields: [analysisJobId], references: [id])
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createdAt DateTime @default(now())
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@@index([analysisJobId])
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@@index([syntheticScore])
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@@index([verdict])
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}
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// ============================================
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// SpamShield Models (Spam Detection)
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// ============================================
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20
pnpm-lock.yaml
generated
20
pnpm-lock.yaml
generated
@@ -490,9 +490,15 @@ importers:
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'@shieldai/types':
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specifier: workspace:*
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version: link:../../packages/types
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'@types/uuid':
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specifier: ^11.0.0
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version: 11.0.0
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node-cache:
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specifier: ^5.1.2
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version: 5.1.2
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uuid:
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specifier: ^14.0.0
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version: 14.0.0
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devDependencies:
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'@vitest/coverage-v8':
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specifier: ^4.1.5
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@@ -2748,6 +2754,10 @@ packages:
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'@types/tough-cookie@4.0.5':
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resolution: {integrity: sha512-/Ad8+nIOV7Rl++6f1BdKxFSMgmoqEoYbHRpPcx3JEfv8VRsQe9Z4mCXeJBzxs7mbHY/XOZZuXlRNfhpVPbs6ZA==}
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'@types/uuid@11.0.0':
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resolution: {integrity: sha512-HVyk8nj2m+jcFRNazzqyVKiZezyhDKrGUA3jlEcg/nZ6Ms+qHwocba1Y/AaVaznJTAM9xpdFSh+ptbNrhOGvZA==}
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deprecated: This is a stub types definition. uuid provides its own type definitions, so you do not need this installed.
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'@types/ws@8.18.1':
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resolution: {integrity: sha512-ThVF6DCVhA8kUGy+aazFQ4kXQ7E1Ty7A3ypFOe0IcJV8O/M511G99AW24irKrW56Wt44yG9+ij8FaqoBGkuBXg==}
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@@ -5552,6 +5562,10 @@ packages:
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deprecated: uuid@10 and below is no longer supported. For ESM codebases, update to uuid@latest. For CommonJS codebases, use uuid@11 (but be aware this version will likely be deprecated in 2028).
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hasBin: true
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uuid@14.0.0:
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resolution: {integrity: sha512-Qo+uWgilfSmAhXCMav1uYFynlQO7fMFiMVZsQqZRMIXp0O7rR7qjkj+cPvBHLgBqi960QCoo/PH2/6ZtVqKvrg==}
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hasBin: true
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uuid@8.3.2:
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resolution: {integrity: sha512-+NYs2QeMWy+GWFOEm9xnn6HCDp0l7QBD7ml8zLUmJ+93Q5NF0NocErnwkTkXVFNiX3/fpC6afS8Dhb/gz7R7eg==}
|
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deprecated: uuid@10 and below is no longer supported. For ESM codebases, update to uuid@latest. For CommonJS codebases, use uuid@11 (but be aware this version will likely be deprecated in 2028).
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@@ -8450,6 +8464,10 @@ snapshots:
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'@types/tough-cookie@4.0.5':
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optional: true
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'@types/uuid@11.0.0':
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dependencies:
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uuid: 14.0.0
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'@types/ws@8.18.1':
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dependencies:
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'@types/node': 25.6.0
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@@ -11809,6 +11827,8 @@ snapshots:
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uuid@10.0.0: {}
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uuid@14.0.0: {}
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uuid@8.3.2: {}
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uuid@9.0.1: {}
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@@ -10,14 +10,16 @@
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"lint": "eslint src/"
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},
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"dependencies": {
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"@shieldai/correlation": "workspace:*",
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"@shieldai/db": "workspace:*",
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"@shieldai/types": "workspace:*",
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"@shieldai/correlation": "workspace:*",
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"node-cache": "^5.1.2"
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"@types/uuid": "^11.0.0",
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"node-cache": "^5.1.2",
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"uuid": "^14.0.0"
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},
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"devDependencies": {
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"vitest": "^4.1.5",
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"@vitest/coverage-v8": "^4.1.5"
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"@vitest/coverage-v8": "^4.1.5",
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"vitest": "^4.1.5"
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},
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"exports": {
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".": "./src/index.ts"
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@@ -6,9 +6,11 @@ import {
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AnalysisType,
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AnalysisResultOutput,
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} from "@shieldai/types";
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import { logger } from "../logger";
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export class BatchAnalysisService {
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private analysisService: AnalysisService;
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private readonly maxConcurrency = 5;
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constructor() {
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this.analysisService = new AnalysisService();
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@@ -19,43 +21,56 @@ export class BatchAnalysisService {
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userId: string
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): Promise<BatchResult> {
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const batchId = `batch_${Date.now()}_${Math.random().toString(36).slice(2, 8)}`;
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logger.info("Starting batch analysis", { batchId, userId, totalFiles: input.audioBuffers.length });
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const results: AnalysisResultOutput[] = [];
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const errors: Array<{ name: string; error: string }> = [];
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for (const audioInput of input.audioBuffers) {
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try {
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const result = await this.analysisService.analyze(
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{
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audioBuffer: audioInput.buffer,
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sampleRate: audioInput.sampleRate,
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analysisType: input.analysisType || AnalysisType.SYNTHETIC_DETECTION,
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},
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userId
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);
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results.push(result);
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} catch (err) {
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const message = err instanceof Error ? err.message : "Analysis failed";
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errors.push({ name: audioInput.name, error: message });
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const processWithConcurrency = async (limit: number) => {
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for (let i = 0; i < input.audioBuffers.length; i += limit) {
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const chunk = input.audioBuffers.slice(i, i + limit);
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const promises = chunk.map(async (audioInput: { name: string; buffer: Buffer; sampleRate?: number }) => {
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try {
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const result = await this.analysisService.analyze(
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{
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audioBuffer: audioInput.buffer,
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sampleRate: audioInput.sampleRate,
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analysisType: input.analysisType || AnalysisType.SYNTHETIC_DETECTION,
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},
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userId
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);
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return { success: true, result, name: audioInput.name };
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} catch (err) {
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const message = err instanceof Error ? err.message : "Analysis failed";
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return { success: false, error: message, name: audioInput.name };
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}
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});
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const outcomes = await Promise.allSettled(promises);
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for (const outcome of outcomes) {
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if (outcome.status === 'fulfilled') {
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if (outcome.value.success && outcome.value.result) {
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results.push(outcome.value.result);
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} else if (!outcome.value.success && outcome.value.name) {
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errors.push({ name: outcome.value.name, error: outcome.value.error || "Analysis failed" });
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}
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}
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}
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}
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}
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};
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const batchJob = await prisma.analysisJob.create({
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data: {
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userId,
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analysisType: AnalysisType.BATCH,
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audioFilePath: `voiceprint/${userId}/${batchId}`,
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status: errors.length === input.audioBuffers.length
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? AnalysisJobStatus.FAILED
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: AnalysisJobStatus.COMPLETED,
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errorMessage:
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errors.length > 0 ? `${errors.length} of ${input.audioBuffers.length} files failed` : undefined,
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completedAt: new Date(),
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},
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await processWithConcurrency(this.maxConcurrency);
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logger.info("Batch analysis completed", {
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batchId,
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successfulResults: results.length,
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failedCount: errors.length
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});
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return {
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batchId,
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jobId: batchJob.id,
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jobId: `batch_${batchId}`,
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totalFiles: input.audioBuffers.length,
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successfulResults: results.length,
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failedCount: errors.length,
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@@ -1,10 +1,14 @@
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import { spawn } from "child_process";
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import { v4 as uuidv4 } from "uuid";
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import { logger } from "../logger";
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const EMBEDDING_DIM = 192;
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const MODEL_VERSION = "ecapa-tdnn-0.1.0-mock";
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export class EmbeddingService {
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private mlServiceUrl: string;
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private readonly maxRetries = 3;
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private readonly retryDelay = 1000;
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constructor() {
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this.mlServiceUrl = process.env.VOICEPRINT_ML_URL || "http://localhost:8001";
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@@ -14,20 +18,34 @@ export class EmbeddingService {
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const mlAvailable = await this.checkMLService();
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if (mlAvailable) {
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logger.info("Using ML service for embedding extraction", { mlUrl: this.mlServiceUrl });
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return this.extractViaML(audioBuffer);
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}
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return this.extractMock(audioBuffer);
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logger.info("Using mock embedding generation", { audioBufferLength: audioBuffer.length });
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return this.generateMockFromBuffer(audioBuffer);
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}
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async classify(embedding: number[]): Promise<number> {
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const mlAvailable = await this.checkMLService();
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if (mlAvailable) {
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logger.info("Using ML service for classification", { embeddingLength: embedding.length });
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return this.classifyViaML(embedding);
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}
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return this.classifyMock(embedding);
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logger.info("Using mock classification", { embeddingLength: embedding.length });
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const mean = embedding.reduce((s, v) => s + v, 0) / embedding.length;
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const variance = embedding.reduce((s, v) => s + (v - mean) ** 2, 0) / embedding.length;
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const stdDev = Math.sqrt(variance);
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const syntheticIndicators = [
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stdDev < 0.1 ? 0.8 : 0.2,
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Math.abs(mean) > 0.5 ? 0.7 : 0.3,
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this.hasArtifacts(embedding) ? 0.9 : 0.1,
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];
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return syntheticIndicators.reduce((s, v) => s + v, 0) / syntheticIndicators.length;
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}
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getModelVersion(): string {
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@@ -105,26 +123,29 @@ except:
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});
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}
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private async extractMock(audioBuffer: Buffer): Promise<EmbeddingOutput> {
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return this.generateMockFromBuffer(audioBuffer);
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}
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private hasArtifacts(embedding: number[]): boolean {
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const window = 16;
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let artifactCount = 0;
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private async classifyMock(embedding: number[]): Promise<number> {
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const mean = embedding.reduce((s, v) => s + v, 0) / embedding.length;
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const variance = embedding.reduce((s, v) => s + (v - mean) ** 2, 0) / embedding.length;
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const stdDev = Math.sqrt(variance);
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for (let i = 0; i < embedding.length - window; i += window) {
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const slice = embedding.slice(i, i + window);
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const localMean = slice.reduce((s, v) => s + v, 0) / slice.length;
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const localVar = slice.reduce((s, v) => s + (v - localMean) ** 2, 0) / slice.length;
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const syntheticIndicators = [
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stdDev < 0.1 ? 0.8 : 0.2,
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Math.abs(mean) > 0.5 ? 0.7 : 0.3,
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this.hasArtifacts(embedding) ? 0.9 : 0.1,
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];
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if (localVar < 0.001) artifactCount++;
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}
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return syntheticIndicators.reduce((s, v) => s + v, 0) / syntheticIndicators.length;
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return artifactCount > embedding.length / window / 3;
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}
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private generateMockFromBuffer(audioBuffer: Buffer): EmbeddingOutput {
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const seed = this.computeSeed(audioBuffer);
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let hash = 0;
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const sampleSize = Math.min(audioBuffer.length, 1024);
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for (let i = 0; i < sampleSize; i += 4) {
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hash = ((hash << 5) - hash + audioBuffer.readInt32LE(i)) | 0;
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}
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const seed = Math.abs(hash);
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||||
const rng = this.createRNG(seed);
|
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const vector: number[] = [];
|
||||
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@@ -141,22 +162,8 @@ except:
|
||||
return { vector: normalized, dimension: EMBEDDING_DIM };
|
||||
}
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||||
|
||||
private hasArtifacts(embedding: number[]): boolean {
|
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const window = 16;
|
||||
let artifactCount = 0;
|
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for (let i = 0; i < embedding.length - window; i += window) {
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const slice = embedding.slice(i, i + window);
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const localMean = slice.reduce((s, v) => s + v, 0) / slice.length;
|
||||
const localVar = slice.reduce((s, v) => s + (v - localMean) ** 2, 0) / slice.length;
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||||
|
||||
if (localVar < 0.001) artifactCount++;
|
||||
}
|
||||
|
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return artifactCount > embedding.length / window / 3;
|
||||
}
|
||||
|
||||
private async checkMLService(): Promise<boolean> {
|
||||
logger.info("Checking ML service availability", { mlUrl: this.mlServiceUrl });
|
||||
return new Promise((resolve) => {
|
||||
const proc = spawn("python3", [
|
||||
"-c",
|
||||
@@ -173,15 +180,6 @@ except:
|
||||
});
|
||||
}
|
||||
|
||||
private computeSeed(buffer: Buffer): number {
|
||||
let hash = 0;
|
||||
const sampleSize = Math.min(buffer.length, 1024);
|
||||
for (let i = 0; i < sampleSize; i += 4) {
|
||||
hash = ((hash << 5) - hash + buffer.readInt32LE(i)) | 0;
|
||||
}
|
||||
return Math.abs(hash);
|
||||
}
|
||||
|
||||
private createRNG(seed: number): () => number {
|
||||
return () => {
|
||||
seed = (seed * 1664525 + 1013904223) & 0xffffffff;
|
||||
|
||||
@@ -23,11 +23,13 @@ export class VoiceEnrollmentService {
|
||||
const enrollment = await prisma.voiceEnrollment.create({
|
||||
data: {
|
||||
userId,
|
||||
label: input.label,
|
||||
embeddingVector: embedding.vector,
|
||||
embeddingDim: embedding.dimension,
|
||||
sampleRate: preprocessed.sampleRate,
|
||||
durationSec: preprocessed.durationSec,
|
||||
name: input.label,
|
||||
voiceHash: this.computeVoiceHash(embedding.vector),
|
||||
audioMetadata: {
|
||||
sampleRate: preprocessed.sampleRate,
|
||||
durationSec: preprocessed.durationSec,
|
||||
embeddingDim: embedding.dimension,
|
||||
},
|
||||
},
|
||||
});
|
||||
|
||||
@@ -35,10 +37,10 @@ export class VoiceEnrollmentService {
|
||||
|
||||
return {
|
||||
id: enrollment.id,
|
||||
label: enrollment.label,
|
||||
embeddingDim: enrollment.embeddingDim,
|
||||
sampleRate: enrollment.sampleRate,
|
||||
durationSec: enrollment.durationSec,
|
||||
label: enrollment.name,
|
||||
embeddingDim: preprocessed.sampleRate,
|
||||
sampleRate: preprocessed.sampleRate,
|
||||
durationSec: preprocessed.durationSec,
|
||||
createdAt: enrollment.createdAt,
|
||||
};
|
||||
}
|
||||
|
||||
36
services/voiceprint/src/logger.ts
Normal file
36
services/voiceprint/src/logger.ts
Normal file
@@ -0,0 +1,36 @@
|
||||
import { FastifyLoggerOptions } from 'fastify';
|
||||
|
||||
export interface Logger {
|
||||
info(message: string, context?: Record<string, unknown>): void;
|
||||
warn(message: string, context?: Record<string, unknown>): void;
|
||||
error(message: string, context?: Record<string, unknown>): void;
|
||||
debug(message: string, context?: Record<string, unknown>): void;
|
||||
}
|
||||
|
||||
export class ConsoleLogger implements Logger {
|
||||
info(message: string, context?: Record<string, unknown>): void {
|
||||
const timestamp = new Date().toISOString();
|
||||
const logContext = context ? ` ${JSON.stringify(context)}` : '';
|
||||
console.log(`[${timestamp}] [INFO] ${message}${logContext}`);
|
||||
}
|
||||
|
||||
warn(message: string, context?: Record<string, unknown>): void {
|
||||
const timestamp = new Date().toISOString();
|
||||
const logContext = context ? ` ${JSON.stringify(context)}` : '';
|
||||
console.warn(`[${timestamp}] [WARN] ${message}${logContext}`);
|
||||
}
|
||||
|
||||
error(message: string, context?: Record<string, unknown>): void {
|
||||
const timestamp = new Date().toISOString();
|
||||
const logContext = context ? ` ${JSON.stringify(context)}` : '';
|
||||
console.error(`[${timestamp}] [ERROR] ${message}${logContext}`);
|
||||
}
|
||||
|
||||
debug(message: string, context?: Record<string, unknown>): void {
|
||||
const timestamp = new Date().toISOString();
|
||||
const logContext = context ? ` ${JSON.stringify(context)}` : '';
|
||||
console.debug(`[${timestamp}] [DEBUG] ${message}${logContext}`);
|
||||
}
|
||||
}
|
||||
|
||||
export const logger = new ConsoleLogger();
|
||||
@@ -8,6 +8,7 @@ import {
|
||||
voicePrintFeatureFlags,
|
||||
} from './voiceprint.config';
|
||||
import { checkFlag } from './voiceprint.feature-flags';
|
||||
import { createHash } from 'crypto';
|
||||
|
||||
// Audio preprocessing service
|
||||
export class AudioPreprocessor {
|
||||
@@ -197,12 +198,10 @@ export class VoiceEnrollmentService {
|
||||
}
|
||||
|
||||
private computeEmbeddingHash(embedding: number[]): string {
|
||||
let hash = 0;
|
||||
for (let i = 0; i < embedding.length; i++) {
|
||||
hash = ((hash << 5) - hash) + embedding[i];
|
||||
hash |= 0;
|
||||
}
|
||||
return `vp_${Math.abs(hash).toString(16)}_${embedding.length}`;
|
||||
const hash = createHash('sha256')
|
||||
.update(JSON.stringify(embedding))
|
||||
.digest('hex');
|
||||
return `vp_${hash.substring(0, 16)}_${embedding.length}`;
|
||||
}
|
||||
}
|
||||
|
||||
@@ -287,13 +286,10 @@ export class AnalysisService {
|
||||
}
|
||||
|
||||
private computeAudioHash(buffer: Buffer): string {
|
||||
let hash = 0;
|
||||
const sampleSize = Math.min(buffer.length, 1024);
|
||||
for (let i = 0; i < sampleSize; i += 8) {
|
||||
hash = ((hash << 5) - hash) + buffer.readUInt8(i);
|
||||
hash |= 0;
|
||||
}
|
||||
return `audio_${Math.abs(hash).toString(16)}`;
|
||||
const hash = createHash('sha256')
|
||||
.update(buffer)
|
||||
.digest('hex');
|
||||
return `audio_${hash.substring(0, 16)}`;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
Reference in New Issue
Block a user