songsense/BACKEND_COMPLETE.md

SongSense Backend - COMPLETE ✅

All 11 Backend Files Built Successfully

Core Infrastructure

1. ✅ src/lib/store.ts - In-memory job store with Map-based CRUD operations
2. ✅ src/lib/processing/pipeline.ts - Main orchestration pipeline for single songs and albums

Processing Modules

3. ✅ src/lib/processing/download.ts - Audio download (yt-dlp, curl, local files)
4. ✅ src/lib/processing/convert.ts - Audio conversion to 192kbps MP3 (ffmpeg)
5. ✅ src/lib/processing/transcribe.ts - Lyrics transcription (OpenAI Whisper API)
6. ✅ src/lib/processing/analyze.ts - Audio analysis & spectrogram generation (songsee CLI)
7. ✅ src/lib/processing/review.ts - AI review generation (Claude Sonnet 4 API with vision)

API Routes (Next.js 15 App Router)

8. ✅ src/app/api/analyze/route.ts - POST: Start analysis job
9. ✅ src/app/api/status/[jobId]/route.ts - GET: Check job status & progress
10. ✅ src/app/api/review/[jobId]/route.ts - GET: Retrieve completed review
11. ✅ src/app/api/upload/route.ts - POST: Upload audio files

Features Implemented

Download Support

• ✅ YouTube URLs (yt-dlp)
• ✅ SoundCloud URLs (yt-dlp)
• ✅ Direct file URLs (curl)
• ✅ Local file paths
• ✅ File uploads via multipart/form-data

Processing Pipeline

• ✅ Download → Convert → Transcribe → Analyze → Review
• ✅ Progress tracking (0-100%)
• ✅ Status updates at each step
• ✅ Error handling with graceful failures
• ✅ Album support (sequential track processing)

Audio Analysis

• ✅ Spectrogram generation
• ✅ Mel spectrogram
• ✅ Chroma visualization
• ✅ Loudness analysis
• ✅ Tempogram
• ✅ Metadata extraction (duration, sample rate, channels)

AI Review Generation

• ✅ Claude Sonnet 4 API integration
• ✅ Vision API for spectrogram analysis
• ✅ Structured JSON output
• ✅ Production analysis
• ✅ Lyric analysis
• ✅ Vibe & emotional impact
• ✅ 1-10 rating scale
• ✅ Standout lines extraction
• ✅ Instrumental track detection

API Endpoints

POST   /api/analyze        → Start analysis (URL or file upload)
GET    /api/status/:jobId  → Get job status & progress
GET    /api/review/:jobId  → Get completed review
POST   /api/upload         → Upload file (returns path)

Environment Variables Required

OPENAI_API_KEY=sk-...      # For Whisper transcription
ANTHROPIC_API_KEY=sk-...   # For Claude review generation

External Dependencies

• ffmpeg - Audio conversion
• yt-dlp - YouTube/SoundCloud downloads
• songsee - Audio analysis (installed at /opt/homebrew/bin/songsee)
• curl - Direct file downloads

Type Safety

• ✅ All files import from shared src/lib/types.ts
• ✅ TypeScript compilation passes with no errors
• ✅ Proper type annotations throughout

Error Handling

• ✅ Try/catch blocks in all async functions
• ✅ Console logging for debugging
• ✅ Error status updates in job store
• ✅ Graceful degradation (e.g., instrumental detection on transcription failure)

Storage Strategy

• In-memory Map for job storage (MVP - no database)
• Temporary files in /tmp/songsense/{jobId}/
• Uploads in /tmp/songsense/uploads/
• Analysis images in /tmp/songsense/{jobId}/analysis/

Next Steps (for Frontend Builder)

1. Build UI to submit URLs/files to /api/analyze
2. Poll /api/status/:jobId for progress updates
3. Display review from /api/review/:jobId when complete
4. Show spectrograms and visualizations
5. Implement SSE for real-time progress (optional enhancement)

Testing Commands

# Test TypeScript compilation
npx tsc --noEmit

# Start Next.js dev server
npm run dev

# Test API endpoints
curl -X POST http://localhost:3000/api/analyze \
  -H "Content-Type: application/json" \
  -d '{"url": "https://www.youtube.com/watch?v=..."}'

curl http://localhost:3000/api/status/{jobId}
curl http://localhost:3000/api/review/{jobId}

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Backend Status: READY FOR INTEGRATION 🚀

All backend files are built, tested, and ready for the frontend builder to create the UI layer.