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Self-hosted Opus Clip alternative — reels.biba.live
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Sebastjan Artič 91caf957f2 Auto-route NZ folk-pop directly to Gemini (skip Scribe) 
User feedback: Scribe consistently produces bad transcripts for Slovenian
narodno-zabavna (NZ) folk-pop music:
- 'Saša Avsenik - Žena ME TEPE': hallucinated 'sam sam sam' x14
- 'FEHTARJI - Gorenjska Ljubljena': total hallucination ('finančni moduli')
- 'Ansambel UNIKAT - PA PA': mistranscribed 'mu' as 'vsem'
- 'Ansambel Saša Avsenika - CVETELE SO MALINE': wrong lyrics entirely

Common pattern: all are Slovenian folk-pop with diatonic accordion. Scribe
training data has very little of this genre, so it consistently fails.

Solution: auto-detect NZ songs by filename keywords and route directly
to Gemini 3 Pro (which handles them correctly), skipping Scribe entirely.

is_likely_folk_pop() detects:
- Slovenian: ansambel, avsenik, slak, fehtar, modrijan, atomik, gadi,
  vikend, stil, unikat, korenjaki, gorenjski, štajerski, polka, valček
- Croatian: klapa, thompson, mate bulić
- Serbian/Bosnian: lepa brena, ceca, halid bešlić

When detected:
1. Skip Scribe entirely (it would fail anyway)
2. Go directly to Gemini 3 Pro (~100s, /bin/sh.20)
3. If Gemini fails, fall back to Scribe (rare)

Cost analysis (10 reels/day, 30% NZ):
- Before: 10x Scribe = $0.13/day, ~30% need re-process
- Hybrid (fallback): 10x Scribe + 3x Gemini retry = $0.79/day
- NZ-routing (now): 7x Scribe + 3x Gemini = $0.69/day, FIRST-TRY success

Saves time AND money for NZ-heavy workloads.
2026-04-29 18:58:12 +00:00
app Clean noise patterns more aggressively + clean already-stored values 2026-04-29 18:47:19 +00:00
scripts Auto-route NZ folk-pop directly to Gemini (skip Scribe) 2026-04-29 18:58:12 +00:00
templates Fix: live preview blocks right-side preview buttons 2026-04-29 15:37:51 +00:00
.env.example Initial: reels clipper app 2026-04-28 15:28:22 +00:00
.gitignore Initial: reels clipper app 2026-04-28 15:28:22 +00:00
docker-compose.yml Initial: reels clipper app 2026-04-28 15:28:22 +00:00
Dockerfile Add Deno runtime for yt-dlp YouTube nsig challenge solving 2026-04-28 16:05:09 +00:00
README.md Initial: reels clipper app 2026-04-28 15:28:22 +00:00
requirements.txt ACRCloud auto-recognition: never block uploads, fall back to fingerprinting 2026-04-29 14:24:53 +00:00

README.md

Reels Clipper · biba.live

Self-hosted Opus Clip alternativa za FOLX TV / PTC. Pretvori 16:9 video v 9:16 reels/shorts/tiktok format z auto face tracking, podnapisi (sl/de/en) in avto-detekcijo refrena v glasbenih pesmih.

Features

  • 📤 Drag & drop upload (do 2 GB)
  • 📺 YouTube URL paste (yt-dlp)
  • 🎯 Smart reframe: track (face follow), center, blur (za glasbo)
  • 🎵 Auto-chorus detection (Whisper + energy hibrid)
  • 📝 Burned-in podnapisi (faster-whisper, multi-jezik)
  • 🎨 3 stili podnapisov: reels, yellow (MrBeast), minimal
  • 🔐 HTTP Basic Auth
  • 📊 Real-time progress (Server-Sent Events)
  • 📦 Docker / Coolify ready

Quick start (lokalno)

docker compose up --build
# odpri http://localhost:8000

Default login: sebastjan / nastavi AUTH_PASS v .env.

Coolify deploy

  1. V Coolify ustvari nov projekt → Docker Compose iz tega repoja
  2. Domena: reels.biba.live
  3. Env vars: 
    AUTH_USER=sebastjan
AUTH_PASS=<močno geslo>
MAX_UPLOAD_MB=2000
  4. Volume reels_data se ustvari avtomatsko
  5. Deploy → Coolify postavi Traefik reverse proxy + SSL via Let's Encrypt

Pipeline

Upload / YouTube
       ↓
[ yt_download.py ]    ← samo če YouTube
       ↓
[ find_chorus.py ]    ← samo če auto_chorus=true (Whisper + RMS analiza)
       ↓
[ reframe.py ]        ← 16:9 → 9:16 (track / center / blur)
       ↓
[ subtitle.py ]       ← Whisper transkripcija + burn-in
       ↓
   reel.mp4

API

  • POST /api/upload — multipart file upload, vrne job_id
  • POST /api/youtube — JSON {url, mode, lang, ...}
  • POST /api/process — start processing za uploaded job
  • GET /api/jobs — list vseh
  • GET /api/jobs/{id} — status
  • GET /api/stream/{id} — SSE stream progress
  • GET /api/download/{id} — final reel
  • DELETE /api/jobs/{id} — pobriši

Dependencies

  • FFmpeg (system)
  • faster-whisper (transkripcija)
  • OpenCV (face detection)
  • yt-dlp (YouTube)
  • FastAPI + uvicorn (server)