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feat(S2-02b): Implement AssemblyAI external transcription with speaker diarization
- Add assembly.ts module for REST API transcription via AssemblyAI
- Implement 5-step pipeline: upload → create job → poll status → download → save
- Enable speaker_labels for diarization (Speaker A, B, C...)
- Add millisecond-precision timestamps for each utterance
- Store JSON transcripts in storage/transcripts/{session_id}.json
- Add axios, dotenv dependencies
- Add transcribeLatest.ts helper for quick testing
User Story: S2-02b - Externe Transkription per REST API
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// services/pipeline/jobs/transcribeLatest.ts
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import path from 'path';
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import fs from 'fs';
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import assembly from '../../modules/transcription/assembly';
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/**
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* Finds the most recently modified .wav file in storage/audio/
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*/
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function getLatestWav(): string {
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const audioDir = path.join(process.cwd(), 'storage', 'audio');
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const files = fs.readdirSync(audioDir).filter(f => f.toLowerCase().endsWith('.wav'));
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if (files.length === 0) throw new Error('⚠️ No .wav file found in storage/audio');
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const newest = files
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.map(f => ({ f, t: fs.statSync(path.join(audioDir, f)).mtimeMs }))
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.sort((a, b) => b.t - a.t)[0].f;
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return path.join(audioDir, newest);
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}
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/**
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* Full transcription pipeline according to the defined workflow:
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* 1. Audio Upload → AssemblyAI
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* 2. Job Creation (transcript_id)
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* 3. Polling Status (queued → processing → completed)
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* 4. Download Transcript JSON
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* 5. Storage: /transcripts/{session_id}.json
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*/
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async function main() {
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const audioPath = getLatestWav();
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console.log('1️⃣ Audio Upload → AssemblyAI');
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console.log(' Source:', audioPath);
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console.log('2️⃣ Job Creation (transcript_id)');
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console.log('3️⃣ Polling Status (queued → processing → completed)');
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console.log('4️⃣ Download Transcript JSON');
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console.log('5️⃣ Storage: /transcripts/{session_id}.json');
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// Execute the transcription process via the AssemblyAI module
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const result = await assembly.run(audioPath);
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console.log('✅ Transcription completed successfully');
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console.log('🆔 Transcript ID:', result.id);
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console.log('📁 Transcript file saved under: storage/transcripts/');
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}
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// Entry point
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main().catch((err) => {
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console.error('❌ Transcription pipeline failed:', err.message || err);
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process.exit(1);
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});
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