0d72d70f5d
- main.py: 4 helper funcs (_persist_to_s3, _ensure_local, _delete_from_s3, _ffmpeg_then_persist) - no-op fallback when S3 creds missing - save_job(): mirror metadata JSON to S3 - process_job(): mirror YT download + render output + analysis/srt/ass to S3 - upload_video(): mirror direct uploads to S3 - _precache_edit_assets(): Popen->threaded with S3 sync after ffmpeg - read endpoints (download, preview, source_video, waveform, preview_clip, get_transcript, recut_job): _ensure_local() fallback fetch from S3 - delete_job(): cascade delete to S3 (mirror unlink) - cleanup.py: NEW module, deletes local files >48h that exist in S3. Verified by S3 head_object + size match. NOT YET ACTIVATED in cron. Backward compat: lokalna mapa ostane primary. Brez env vars S3_* vsi helperji vrnejo False (no-op). Production behavior identičen, dokler ne dobi S3 creds.
2440 lines
101 KiB
Python
2440 lines
101 KiB
Python
"""
|
||
reels.biba.live — FastAPI backend.
|
||
|
||
Endpoints:
|
||
GET / — frontend HTML
|
||
POST /api/upload — naloži video file
|
||
POST /api/youtube — submit YouTube URL
|
||
POST /api/process/{id} — start processing job
|
||
GET /api/jobs — list vseh jobov
|
||
GET /api/jobs/{id} — status job-a
|
||
GET /api/stream/{id} — SSE progress stream
|
||
GET /api/download/{id} — download finalni reel
|
||
GET /api/preview/{id} — preview video stream
|
||
DELETE /api/jobs/{id} — pobriši job + datoteke
|
||
"""
|
||
import asyncio
|
||
import json
|
||
import os
|
||
import secrets
|
||
import shutil
|
||
import subprocess
|
||
import threading
|
||
import time
|
||
import uuid
|
||
from pathlib import Path
|
||
from typing import Optional
|
||
|
||
from fastapi import (
|
||
FastAPI, UploadFile, File, Form, HTTPException, Depends,
|
||
BackgroundTasks, Request, status
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||
)
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||
from fastapi.responses import (
|
||
FileResponse, HTMLResponse, StreamingResponse, JSONResponse, Response
|
||
)
|
||
from fastapi.staticfiles import StaticFiles
|
||
from fastapi.security import HTTPBasic, HTTPBasicCredentials
|
||
from pydantic import BaseModel
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────
|
||
# Config
|
||
# ────────────────────────────────────────────────────────────────
|
||
DATA_DIR = Path(os.environ.get("DATA_DIR", "/data"))
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||
UPLOAD_DIR = DATA_DIR / "uploads"
|
||
OUTPUT_DIR = DATA_DIR / "outputs"
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||
JOBS_DIR = DATA_DIR / "jobs"
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||
QNET_DIR = DATA_DIR / "qnet"
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||
SCRIPTS_DIR = Path(__file__).parent.parent / "scripts"
|
||
|
||
UPLOAD_DIR.mkdir(parents=True, exist_ok=True)
|
||
OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
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||
JOBS_DIR.mkdir(parents=True, exist_ok=True)
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||
QNET_DIR.mkdir(parents=True, exist_ok=True)
|
||
|
||
# Qnet song match — povezava z MB player bazami
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os.environ.setdefault("QNET_LOOKUP_PATH", str(QNET_DIR / "songs_lookup.json"))
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from app import qnet_match # noqa: E402
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# S3 storage mirror — uploads/outputs/jobs gredo tudi v s3://folxspeed/reels-app/
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# Lokalna mapa ostane primary, S3 je replica/cache.
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from app import s3_storage # noqa: E402
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||
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||
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||
def _persist_to_s3(local_path, kind: str) -> bool:
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"""Mirror local file to S3 after producing it (best-effort).
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|
||
kind: 'upload' for uploads/, 'output' for outputs/, 'job_meta' for jobs/
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Silent no-op when S3 not configured. Never raises.
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"""
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try:
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||
if not s3_storage.is_enabled():
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||
return False
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||
p = Path(local_path)
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||
if not p.exists() or p.stat().st_size == 0:
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||
return False
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||
return s3_storage.upload_job_file("", kind, p)
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||
except Exception as e:
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print(f"⚠️ S3 mirror failed for {local_path}: {e}", flush=True)
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return False
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||
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def _ensure_local(local_path, kind: str) -> bool:
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"""Make sure file is on disk; if missing, fetch from S3.
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Returns True if file is ready locally after the call.
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kind: 'upload' or 'output'
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"""
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p = Path(local_path)
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if p.exists() and p.stat().st_size > 0:
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return True
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if not s3_storage.is_enabled():
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return False
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folder = {"upload": "uploads", "output": "outputs", "job_meta": "jobs"}.get(kind, kind)
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key = f"{folder}/{p.name}"
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print(f"📥 Local missing, fetching from S3: {key}", flush=True)
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return s3_storage.download(key, p)
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|
||
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def _delete_from_s3(filename: str, kind: str) -> bool:
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"""Delete object from S3 (mirror local delete). Best-effort, no raise."""
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try:
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if not s3_storage.is_enabled():
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return False
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folder = {"upload": "uploads", "output": "outputs", "job_meta": "jobs"}.get(kind, kind)
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return s3_storage.delete(f"{folder}/{filename}")
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except Exception:
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return False
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||
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||
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def _ffmpeg_then_persist(cmd, out_path, kind: str = "output", timeout: int = 600):
|
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"""Run ffmpeg in background thread, then mirror result to S3.
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Drop-in replacement for subprocess.Popen() when we want S3 sync after.
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"""
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def runner():
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try:
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subprocess.run(
|
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cmd,
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stdout=subprocess.DEVNULL,
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stderr=subprocess.DEVNULL,
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timeout=timeout,
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)
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_persist_to_s3(out_path, kind)
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except Exception as e:
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print(f"⚠️ ffmpeg/persist failed for {out_path}: {e}", flush=True)
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threading.Thread(target=runner, daemon=True).start()
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# Dedup DB — sledi že obdelanim/naloženim komadom
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DEDUP_DB = DATA_DIR / "processed.db"
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def _normalize_filename(filename: str) -> str:
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"""Normaliziraj filename za dedup primerjavo.
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||
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'BRAJDE (Official Video).mp4' → 'brajde'
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'Brajde (HD).mxf' → 'brajde'
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"""
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import re
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name = Path(filename).stem.lower()
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||
# Odstrani pogoste suffix-e
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name = re.sub(r'\b(official|video|hd|4k|lyric|audio|music|mv|live|cover|version|remix)\b', '', name)
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# Odstrani parentheses content
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name = re.sub(r'\([^)]*\)', '', name)
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name = re.sub(r'\[[^\]]*\]', '', name)
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# Whitespace normalize
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name = re.sub(r'\s+', ' ', name).strip()
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# Odstrani pogoste ločila
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name = re.sub(r'[-_.]+', ' ', name).strip()
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return name
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def _dedup_init():
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"""Ustvari SQLite tabelo če ne obstaja."""
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import sqlite3
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conn = sqlite3.connect(str(DEDUP_DB))
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conn.execute("""
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CREATE TABLE IF NOT EXISTS processed_videos (
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normalized_name TEXT NOT NULL,
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tv_station TEXT NOT NULL,
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filename_orig TEXT NOT NULL,
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job_id TEXT NOT NULL,
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||
nextcloud_url TEXT,
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file_size_mb REAL,
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uploaded_at REAL NOT NULL,
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PRIMARY KEY (normalized_name, tv_station)
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)
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""")
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conn.execute("CREATE INDEX IF NOT EXISTS idx_norm ON processed_videos(normalized_name)")
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conn.commit()
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conn.close()
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def dedup_check(filename: str, tv_station: str) -> Optional[dict]:
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"""Vrne dict z info o že obdelanem komadu, ali None."""
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import sqlite3
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_dedup_init()
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norm = _normalize_filename(filename)
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if not norm:
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return None
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conn = sqlite3.connect(str(DEDUP_DB))
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conn.row_factory = sqlite3.Row
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row = conn.execute(
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"SELECT * FROM processed_videos WHERE normalized_name = ? AND tv_station = ?",
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(norm, tv_station)
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).fetchone()
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conn.close()
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if row:
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return dict(row)
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return None
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||
|
||
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def dedup_record(filename: str, tv_station: str, job_id: str, nextcloud_url: str = None, file_size_mb: float = None):
|
||
"""Zabeleži uspešno obdelan + naložen komad."""
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import sqlite3
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||
_dedup_init()
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norm = _normalize_filename(filename)
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if not norm:
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return
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conn = sqlite3.connect(str(DEDUP_DB))
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conn.execute("""
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||
INSERT OR REPLACE INTO processed_videos
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(normalized_name, tv_station, filename_orig, job_id, nextcloud_url, file_size_mb, uploaded_at)
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VALUES (?, ?, ?, ?, ?, ?, ?)
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""", (norm, tv_station, filename, job_id, nextcloud_url, file_size_mb, time.time()))
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conn.commit()
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||
conn.close()
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||
print(f"📒 Dedup: zabeležen {norm} → {tv_station} (job {job_id})", flush=True)
|
||
|
||
|
||
def dedup_remove(filename: str, tv_station: str):
|
||
"""Izbriši zapis (npr. če uporabnik želi re-narediti)."""
|
||
import sqlite3
|
||
_dedup_init()
|
||
norm = _normalize_filename(filename)
|
||
if not norm:
|
||
return
|
||
conn = sqlite3.connect(str(DEDUP_DB))
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||
conn.execute("DELETE FROM processed_videos WHERE normalized_name = ? AND tv_station = ?", (norm, tv_station))
|
||
conn.commit()
|
||
conn.close()
|
||
|
||
|
||
AUTH_USER = os.environ.get("AUTH_USER", "sebastjan")
|
||
AUTH_PASS = os.environ.get("AUTH_PASS", "change-me-in-coolify-env")
|
||
|
||
MAX_UPLOAD_MB = int(os.environ.get("MAX_UPLOAD_MB", "2000"))
|
||
|
||
# Nextcloud upload (folxspeed/REELS/)
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NEXTCLOUD_URL = os.environ.get("NEXTCLOUD_URL", "https://nextcloud.folx.tv")
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||
NEXTCLOUD_USER = os.environ.get("NEXTCLOUD_USER", "admin")
|
||
NEXTCLOUD_PASS = os.environ.get("NEXTCLOUD_PASS", "")
|
||
NEXTCLOUD_FOLDER = os.environ.get("NEXTCLOUD_FOLDER", "folxspeed/REELS")
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────
|
||
# Auth
|
||
# ────────────────────────────────────────────────────────────────
|
||
security = HTTPBasic()
|
||
|
||
|
||
def check_auth(creds: HTTPBasicCredentials = Depends(security)):
|
||
correct_user = secrets.compare_digest(creds.username, AUTH_USER)
|
||
correct_pass = secrets.compare_digest(creds.password, AUTH_PASS)
|
||
if not (correct_user and correct_pass):
|
||
raise HTTPException(
|
||
status_code=status.HTTP_401_UNAUTHORIZED,
|
||
detail="Napačno geslo",
|
||
headers={"WWW-Authenticate": "Basic"},
|
||
)
|
||
return creds.username
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────
|
||
# Artist + title parsing iz filename / YouTube title
|
||
# ────────────────────────────────────────────────────────────────
|
||
import re
|
||
|
||
_NOISE_PATTERNS = [
|
||
# Variacije "official" z možnimi tipkarskimi napakami (offiicial, offical, oficial, ...)
|
||
# Match liberalno: "off" + 0-3 dodatnih črk + "icial" + "video"/"audio" + opcijsko številka
|
||
r"\(Off[a-z]*icial\s+(?:Music\s+|HD\s+|4K\s+)?(?:Video|Audio)\s*\)",
|
||
r"\(Off[a-z]*icia[lk]\s+(?:Music\s+|HD\s+|4K\s+)?(?:Video|Audio)\)",
|
||
r"\bOff[a-z]*icial\s+(?:Music\s+|HD\s+|4K\s+)?(?:Video|Audio)\b",
|
||
|
||
# Nemške variacije
|
||
r"\(Offizielles?\s+(?:Musik)?[Vv]ideo\)",
|
||
r"\bOffizielles?\s+(?:Musik)?[Vv]ideo\b",
|
||
|
||
# Lyric videos
|
||
r"\(Lyric[s]?\s+Video\)",
|
||
r"\bLyric[s]?\s+Video\b",
|
||
|
||
# Audio quality / version markers
|
||
r"\(Audio\)",
|
||
r"\(HD\)", r"\(HQ\)", r"\(4K\)", r"\(8K\)", r"\(1080p?\)",
|
||
r"\(Live\)", r"\(Remix\)", r"\(Cover\)", r"\(Acoustic\)",
|
||
r"\(Remastered\)", r"\(Remaster(?:ed)?\s*\d{0,4}\)",
|
||
r"\(Extended(?:\s+Mix)?\)",
|
||
r"\(Radio(?:\s+Edit)?\)",
|
||
r"\(Clean(?:\s+Version)?\)",
|
||
r"\(Explicit\)",
|
||
|
||
# Square brackets variations
|
||
r"\[Official[^\]]*\]",
|
||
r"\[Music[^\]]*\]",
|
||
r"\[Audio[^\]]*\]",
|
||
r"\[HD\]", r"\[HQ\]", r"\[4K\]",
|
||
r"\[Lyric[s]?[^\]]*\]",
|
||
|
||
# Bare words (without brackets)
|
||
r"\boriginal\s+(?:video|audio)\b",
|
||
r"\bMV\b",
|
||
r"\b(?:4K|HD|HQ|8K|1080p|720p|4k|hd|hq)\s*$", # trailing 4K/HD brez oklepajev
|
||
|
||
# Trailing year in parens (npr. "(2024)")
|
||
r"\(\d{4}\)\s*$",
|
||
|
||
# Trailing 2-4 digit number na koncu (verjetno leto: "23", "2023", "33"):
|
||
# POMEMBNO: samo če je ZADNJA stvar v stringu in ne del besede
|
||
# NE odstrani '33 točk' ampak DA odstrani 'Naslov 33'
|
||
# Pred številko: presledek/oklepaji/ničesar
|
||
r"\s+\d{2,4}\s*$",
|
||
|
||
# Prazni / dummy oklepaji: "( )", "( )", "( - )", "(-)", "(.)"
|
||
r"\(\s*[-–—._]*\s*\)",
|
||
|
||
# Catch-all: oklepaji z "video"/"audio"/"version"/"mix"/"edit"/"remix"
|
||
# (široko match — če oklepaji vsebujejo te besede, so verjetno noise)
|
||
r"\([^)]*\b(?:video|audio|version|mix|edit|remix|cover|live|hd|hq|4k|8k|remaster(?:ed)?|extended|clean|explicit|radio|lyric[s]?|official|offizielles?|musik)\b[^)]*\)",
|
||
|
||
# Catch-all: oglati oklepaji z noise besedami
|
||
r"\[[^\]]*\b(?:video|audio|version|mix|edit|remix|cover|live|hd|hq|4k|official|musik)\b[^\]]*\]",
|
||
|
||
# Avtor/feat. v oklepajih: "(prod. by X)", "(feat. Y)", "(ft. Z)"
|
||
r"\(\s*(?:prod\.?(?:uced)?\s+by|feat\.?(?:uring)?|ft\.?)\s+[^)]+\)",
|
||
|
||
# Trailing številke ki označujejo verzije: "33" na koncu (npr. "Modrijani - X 33")
|
||
# POZOR: zelo previdno, ker so lahko legit (npr. del naslova)
|
||
# — Ne dodam splošnega trailing številk pattern-a, ker bi razbil legitime
|
||
]
|
||
|
||
def parse_artist_title(filename_or_title):
|
||
"""Iz imena datoteke / YouTube naslova ekstrahira (artist, title).
|
||
|
||
Podpira pogoste vzorce:
|
||
- "Artist - Title.mp4"
|
||
- "Artist - Title (Official Music Video).mp4"
|
||
- "Artist – Title" (em-dash)
|
||
- "Artist | Title"
|
||
|
||
Vrne (artist, title) ali (None, None) če ni razvidno.
|
||
"""
|
||
if not filename_or_title:
|
||
return (None, None)
|
||
|
||
# Odstrani extension
|
||
name = Path(filename_or_title).stem if "." in filename_or_title else filename_or_title
|
||
|
||
# Odstrani noise patterns
|
||
for pat in _NOISE_PATTERNS:
|
||
name = re.sub(pat, "", name, flags=re.IGNORECASE)
|
||
|
||
# Normaliziraj presledke
|
||
name = re.sub(r"\s+", " ", name).strip()
|
||
|
||
# Probaj različne separatorje
|
||
for sep in [" - ", " – ", " — ", " | ", " : "]:
|
||
if sep in name:
|
||
parts = name.split(sep, 1)
|
||
artist = parts[0].strip()
|
||
title = parts[1].strip()
|
||
# Strip trailing/leading puncutation
|
||
artist = re.sub(r'^[\s\-–—|.:_]+|[\s\-–—|.:_]+$', '', artist)
|
||
title = re.sub(r'^[\s\-–—|.:_]+|[\s\-–—|.:_]+$', '', title)
|
||
if artist and title and len(artist) <= 80 and len(title) <= 100:
|
||
return (artist, title)
|
||
|
||
return (None, None)
|
||
|
||
|
||
def safe_filename(s, max_len=80):
|
||
"""Naredi varno ime datoteke (brez znakov ki bi razbili FS)."""
|
||
if not s:
|
||
return ""
|
||
# Replace problematic chars with safe alternative
|
||
s = re.sub(r'[<>:"/\\|?*\x00-\x1f]', '', s)
|
||
s = re.sub(r'\s+', ' ', s).strip()
|
||
return s[:max_len]
|
||
|
||
|
||
def clean_noise(s):
|
||
"""Odstrani 'noise' (Official Video itd.) iz besedila - tudi že-parsed values."""
|
||
if not s:
|
||
return s
|
||
cleaned = s
|
||
for pat in _NOISE_PATTERNS:
|
||
cleaned = re.sub(pat, "", cleaned, flags=re.IGNORECASE)
|
||
cleaned = re.sub(r"\s+", " ", cleaned).strip()
|
||
cleaned = re.sub(r'^[\s\-–—|.:_]+|[\s\-–—|.:_]+$', '', cleaned)
|
||
return cleaned
|
||
|
||
|
||
def build_download_filename(job):
|
||
"""Sestavi pravilno ime download datoteke iz job metadata."""
|
||
# Najprej probaj job-shranjene parsed values
|
||
artist = clean_noise(job.get("parsed_artist"))
|
||
title = clean_noise(job.get("parsed_title"))
|
||
|
||
# Fallback: parse from filename
|
||
if not artist or not title:
|
||
source = job.get("filename") or job.get("youtube_title") or ""
|
||
parsed_artist, parsed_title = parse_artist_title(source)
|
||
artist = artist or parsed_artist
|
||
title = title or parsed_title
|
||
|
||
if artist and title:
|
||
return f"{safe_filename(artist)} - {safe_filename(title)} - REEL.mp4"
|
||
if title:
|
||
return f"{safe_filename(title)} - REEL.mp4"
|
||
# Last resort: job ID (vendar to bi se moralo preprečiti že ob upload-u)
|
||
return f"reel_{job['id']}.mp4"
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────
|
||
# Job state (filesystem-based, persistent prek restartov)
|
||
# ────────────────────────────────────────────────────────────────
|
||
def job_path(job_id):
|
||
return JOBS_DIR / f"{job_id}.json"
|
||
|
||
|
||
def load_job(job_id):
|
||
p = job_path(job_id)
|
||
if not p.exists():
|
||
return None
|
||
return json.loads(p.read_text())
|
||
|
||
|
||
def save_job(job):
|
||
p = job_path(job["id"])
|
||
p.write_text(json.dumps(job, ensure_ascii=False, indent=2))
|
||
_persist_to_s3(p, "job_meta")
|
||
|
||
|
||
def update_job(job_id, **kwargs):
|
||
job = load_job(job_id)
|
||
if not job:
|
||
return None
|
||
job.update(kwargs)
|
||
job["updated_at"] = time.time()
|
||
save_job(job)
|
||
return job
|
||
|
||
|
||
def _clean_job_titles(job):
|
||
"""Očisti 'Official Video' ipd. iz parsed_title v real-time (brez perzistiranja)."""
|
||
if not job:
|
||
return job
|
||
if job.get("parsed_title"):
|
||
cleaned = clean_noise(job["parsed_title"])
|
||
if cleaned and cleaned != job["parsed_title"]:
|
||
job["parsed_title"] = cleaned
|
||
if job.get("parsed_artist"):
|
||
cleaned = clean_noise(job["parsed_artist"])
|
||
if cleaned and cleaned != job["parsed_artist"]:
|
||
job["parsed_artist"] = cleaned
|
||
return job
|
||
|
||
|
||
def list_jobs():
|
||
out = []
|
||
for f in sorted(JOBS_DIR.glob("*.json"), reverse=True):
|
||
try:
|
||
out.append(_clean_job_titles(json.loads(f.read_text())))
|
||
except Exception:
|
||
pass
|
||
return out
|
||
|
||
|
||
def generate_srt_from_segments(segments, clip_start, clip_end, output_path):
|
||
"""Generira SRT samo za dele, ki spadajo v [clip_start, clip_end].
|
||
|
||
Timestamp-i so re-mapirani na 0-based (kot je v trim-anem videu).
|
||
Razdeli dolge segmente (>2.5s) na enake kose za hiter pacing v reels stilu.
|
||
Vse besedilo VELIKE TISKANE ČRKE.
|
||
"""
|
||
MAX_CHUNK_DURATION = 2.5
|
||
|
||
def fmt_ts(s):
|
||
h = int(s // 3600)
|
||
m = int((s % 3600) // 60)
|
||
sec = s % 60
|
||
return f"{h:02d}:{m:02d}:{sec:06.3f}".replace(".", ",")
|
||
|
||
lines = []
|
||
idx = 1
|
||
|
||
for seg in segments:
|
||
s_start = float(seg["start"])
|
||
s_end = float(seg["end"])
|
||
text = str(seg["text"]).strip()
|
||
words = seg.get("words", []) or []
|
||
|
||
# Filter v range
|
||
if s_end <= clip_start or s_start >= clip_end:
|
||
continue
|
||
|
||
# ── HALLUCINATION FILTER ──
|
||
# STT (Scribe, Whisper) občasno halucinira pri dolgih instrumentalih:
|
||
# vrne segment 60-100s z 1-2 besedama. Tak segment ne smemo dati v SRT.
|
||
# Pravilo: če je segment > 15s IN ima < 5 besed (ali words array < 5),
|
||
# je verjetno halucinacija.
|
||
seg_dur = s_end - s_start
|
||
word_count = len(words) if words else len(text.split())
|
||
if seg_dur > 15 and word_count < 5:
|
||
print(f"[SRT] Preskočil halucinacijski segment [{s_start:.1f}-{s_end:.1f}] "
|
||
f"({seg_dur:.1f}s, {word_count} besed): {text[:50]!r}", flush=True)
|
||
continue
|
||
|
||
# Pripravi words_in_clip vedno (če imamo word-level timestampe)
|
||
# Uporabili ga bomo tako za segment trim kot za chunk boundaries
|
||
words_in_clip = None
|
||
if words:
|
||
words_in_clip = []
|
||
for w in words:
|
||
w_start = float(w.get("start", 0))
|
||
w_end = float(w.get("end", 0))
|
||
w_text = w.get("text", "").strip()
|
||
if not w_text:
|
||
continue
|
||
if w_end > clip_start and w_start < clip_end:
|
||
words_in_clip.append({
|
||
"start": max(w_start, clip_start),
|
||
"end": min(w_end, clip_end),
|
||
"text": w_text,
|
||
})
|
||
|
||
# Če segment delno štrli iz clip range-a IN imamo word-level timestampe,
|
||
# uporabi samo tiste besede ki dejansko padejo v clip range
|
||
if words_in_clip and (s_start < clip_start or s_end > clip_end):
|
||
if not words_in_clip:
|
||
continue
|
||
|
||
# Reconstruiraj segment z dejanskim word-level timing-om
|
||
text = " ".join(w["text"] for w in words_in_clip)
|
||
s_start = words_in_clip[0]["start"]
|
||
s_end = words_in_clip[-1]["end"]
|
||
else:
|
||
# Klipni segment začetek/konec na clip range
|
||
s_start = max(s_start, clip_start)
|
||
s_end = min(s_end, clip_end)
|
||
|
||
if s_end - s_start < 0.2:
|
||
continue
|
||
|
||
# Re-mapraj na 0-based
|
||
rel_start = s_start - clip_start
|
||
rel_end = s_end - clip_start
|
||
|
||
if not text:
|
||
continue
|
||
text_upper = text.upper()
|
||
|
||
# Razdeli na chunk-e če je predolg
|
||
duration = rel_end - rel_start
|
||
if duration <= MAX_CHUNK_DURATION:
|
||
lines.append(f"{idx}\n{fmt_ts(rel_start)} --> {fmt_ts(rel_end)}\n{text_upper}\n")
|
||
idx += 1
|
||
else:
|
||
# ── WORD-LEVEL CHUNKING ──
|
||
# Če imamo word-level timestampe (Soniox/Scribe), uporabi DEJANSKE čase besed
|
||
# za chunk boundaries (NE enake time chunks, ker pevec ne poje enakomerno).
|
||
|
||
if words_in_clip and len(words_in_clip) >= 2:
|
||
# Group besede v chunke z max trajanjem MAX_CHUNK_DURATION
|
||
# Pravila:
|
||
# 1. Vsak chunk traja max MAX_CHUNK_DURATION (2.5s)
|
||
# 2. NE začni novega chunka če bi prejšnji ostal kratek (<3 besede ali <12 znakov)
|
||
# 3. NE pusti zadnji chunk siroto z 1 kratko besedo (<3 znakov) — združi nazaj
|
||
MIN_CHUNK_WORDS = 3
|
||
MIN_CHUNK_CHARS = 12
|
||
chunks = []
|
||
current_chunk = [words_in_clip[0]]
|
||
for w in words_in_clip[1:]:
|
||
chunk_start_time = current_chunk[0]["start"]
|
||
chunk_dur_so_far = w["end"] - chunk_start_time
|
||
|
||
# Bi začeli nov chunk?
|
||
if chunk_dur_so_far > MAX_CHUNK_DURATION:
|
||
# Preveri ali bi current_chunk ostal "siroto kratek"
|
||
current_text = " ".join(c["text"] for c in current_chunk)
|
||
too_short = (len(current_chunk) < MIN_CHUNK_WORDS
|
||
or len(current_text) < MIN_CHUNK_CHARS)
|
||
if too_short:
|
||
# Daj še to besedo zraven (raje malo predolg chunk kot siroto kratek)
|
||
current_chunk.append(w)
|
||
else:
|
||
chunks.append(current_chunk)
|
||
current_chunk = [w]
|
||
else:
|
||
current_chunk.append(w)
|
||
if current_chunk:
|
||
# Če zadnji chunk ima samo 1-2 kratki besedi, združi z zadnjim chunkom
|
||
last_text = " ".join(c["text"] for c in current_chunk)
|
||
if (chunks and
|
||
(len(current_chunk) < 2 or len(last_text) < 5)):
|
||
chunks[-1].extend(current_chunk)
|
||
else:
|
||
chunks.append(current_chunk)
|
||
|
||
# Generiraj SRT iz chunks (z dejanskimi word timestampi)
|
||
for chunk in chunks:
|
||
cs = chunk[0]["start"] - clip_start
|
||
ce = chunk[-1]["end"] - clip_start
|
||
chunk_text = " ".join(w["text"] for w in chunk).upper().strip()
|
||
if not chunk_text:
|
||
continue
|
||
lines.append(f"{idx}\n{fmt_ts(cs)} --> {fmt_ts(ce)}\n{chunk_text}\n")
|
||
idx += 1
|
||
else:
|
||
# Fallback: brez word-level timestampov, razdeli enako
|
||
n_parts = int(duration / MAX_CHUNK_DURATION) + 1
|
||
words_split = text_upper.split()
|
||
words_per_part = max(1, len(words_split) // n_parts)
|
||
chunk_dur = duration / n_parts
|
||
for i in range(n_parts):
|
||
cs = rel_start + i * chunk_dur
|
||
ce = rel_start + (i + 1) * chunk_dur
|
||
wstart = i * words_per_part
|
||
wend = (i + 1) * words_per_part if i < n_parts - 1 else len(words_split)
|
||
chunk_text = " ".join(words_split[wstart:wend]) if wstart < len(words_split) else text_upper
|
||
if not chunk_text.strip():
|
||
chunk_text = text_upper
|
||
lines.append(f"{idx}\n{fmt_ts(cs)} --> {fmt_ts(ce)}\n{chunk_text.strip()}\n")
|
||
idx += 1
|
||
|
||
with open(output_path, "w", encoding="utf-8") as f:
|
||
f.write("\n".join(lines))
|
||
return output_path
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────
|
||
# Pipeline runner (background task)
|
||
# ────────────────────────────────────────────────────────────────
|
||
def run_subprocess_logged(cmd, job_id, step_name):
|
||
"""Pokliče subprocess, logi gredo v job."""
|
||
update_job(job_id, current_step=step_name, status="processing")
|
||
proc = subprocess.run(cmd, capture_output=True, text=True)
|
||
if proc.returncode != 0:
|
||
# Combine stdout + stderr za diagnostiko
|
||
err_msg = (proc.stderr or "") + "\n" + (proc.stdout or "")
|
||
update_job(
|
||
job_id,
|
||
status="failed",
|
||
error=f"{step_name}: {err_msg[-800:].strip()}",
|
||
)
|
||
return False
|
||
# Tudi pri success-u beleži stderr za diagnostiko (samo zadnji del)
|
||
if proc.stderr and proc.stderr.strip():
|
||
update_job(job_id, last_step_log=proc.stderr[-500:].strip())
|
||
return True
|
||
|
||
|
||
def _precache_edit_assets(job_id: str, src_path: str):
|
||
"""Generira low-q source video + waveform PNG za Edit modal.
|
||
|
||
Tečeta v ozadju (subprocess), ne blokira pipeline-a.
|
||
Če Edit modal je odprt, te assete dobi instant.
|
||
"""
|
||
src = Path(src_path)
|
||
if not src.exists():
|
||
return
|
||
|
||
# Low-q source (480p) — za hitro scrubbanje
|
||
low_path = OUTPUT_DIR / f"{job_id}_source_low.mp4"
|
||
if not low_path.exists() or low_path.stat().st_size < 1024:
|
||
if low_path.exists():
|
||
low_path.unlink()
|
||
cmd = [
|
||
"ffmpeg", "-y",
|
||
"-i", str(src),
|
||
"-vf", "scale=854:480:force_original_aspect_ratio=decrease,scale=trunc(iw/2)*2:trunc(ih/2)*2",
|
||
"-c:v", "libx264", "-preset", "veryfast", "-crf", "28",
|
||
"-c:a", "aac", "-b:a", "96k",
|
||
"-movflags", "+faststart",
|
||
"-loglevel", "error",
|
||
str(low_path),
|
||
]
|
||
_ffmpeg_then_persist(cmd, low_path, kind="output")
|
||
print(f"📦 Pre-cache low-q source za {job_id} (background → S3)", flush=True)
|
||
|
||
# Waveform PNG (2400x72 — za zoom)
|
||
wave_path = OUTPUT_DIR / f"{job_id}_waveform_2400x72.png"
|
||
if not wave_path.exists() or wave_path.stat().st_size < 100:
|
||
if wave_path.exists():
|
||
wave_path.unlink()
|
||
cmd = [
|
||
"ffmpeg", "-y",
|
||
"-i", str(src),
|
||
"-filter_complex",
|
||
"[0:a]aformat=channel_layouts=mono,showwavespic=s=2400x72:colors=#ff6b6b:scale=lin:draw=full[wave]",
|
||
"-map", "[wave]",
|
||
"-frames:v", "1",
|
||
"-loglevel", "error",
|
||
str(wave_path),
|
||
]
|
||
_ffmpeg_then_persist(cmd, wave_path, kind="output")
|
||
print(f"📦 Pre-cache waveform za {job_id} (background → S3)", flush=True)
|
||
|
||
|
||
def process_job(job_id):
|
||
"""Glavni pipeline: download (če YT) → find_chorus (če auto) → reframe → subs."""
|
||
job = load_job(job_id)
|
||
if not job:
|
||
return
|
||
|
||
try:
|
||
# ── 1. Source preparation ─────────────────────────────
|
||
if job["source_type"] == "youtube":
|
||
update_job(job_id, status="downloading", current_step="YouTube download")
|
||
input_path = UPLOAD_DIR / f"{job_id}_yt.mp4"
|
||
cmd = [
|
||
"python3", str(SCRIPTS_DIR / "yt_download.py"),
|
||
job["youtube_url"], str(input_path),
|
||
]
|
||
if not run_subprocess_logged(cmd, job_id, "YouTube download"):
|
||
return
|
||
update_job(job_id, input_path=str(input_path))
|
||
# S3 mirror — original video + info.json
|
||
_persist_to_s3(input_path, "upload")
|
||
info_json = input_path.with_suffix(".info.json")
|
||
if info_json.exists():
|
||
_persist_to_s3(info_json, "upload")
|
||
|
||
# Probaj dobiti YT metadata (če še ni iz submit-a) — title, uploader, id, ...
|
||
# Single video submit ali playlist resolve že nastavi metadata, ampak
|
||
# včasih (npr. če je submit fetch failed) je še manjka.
|
||
need_metadata_fetch = not job.get("youtube_title") or not job.get("youtube_uploader")
|
||
if need_metadata_fetch:
|
||
try:
|
||
info_cmd = [
|
||
"python3", str(SCRIPTS_DIR / "yt_download.py"),
|
||
job["youtube_url"], "/dev/null", "--info-only",
|
||
]
|
||
proc = subprocess.run(info_cmd, capture_output=True, text=True, timeout=30)
|
||
if proc.returncode == 0 and proc.stdout:
|
||
info = json.loads(proc.stdout)
|
||
yt_title = info.get("title", "") or ""
|
||
updates = {}
|
||
if yt_title:
|
||
updates["youtube_title"] = yt_title
|
||
if info.get("id"):
|
||
updates["youtube_id"] = info["id"]
|
||
if info.get("uploader") or info.get("channel"):
|
||
updates["youtube_uploader"] = info.get("uploader") or info.get("channel") or ""
|
||
if info.get("duration") is not None:
|
||
updates["youtube_duration"] = info["duration"]
|
||
if info.get("thumbnail"):
|
||
updates["youtube_thumbnail"] = info["thumbnail"]
|
||
if info.get("description"):
|
||
updates["youtube_description"] = info["description"][:2000]
|
||
if info.get("upload_date"):
|
||
updates["youtube_upload_date"] = info["upload_date"]
|
||
if info.get("webpage_url"):
|
||
updates["youtube_webpage_url"] = info["webpage_url"]
|
||
|
||
# Qnet match + parser samo če še nimamo clean name
|
||
if yt_title and not job.get("has_clean_name"):
|
||
qm = qnet_match.match_filename(yt_title)
|
||
if qm["matched"] and qm["confidence"] >= 0.85:
|
||
updates["parsed_artist"] = qm["artist"]
|
||
updates["parsed_title"] = qm["title"]
|
||
updates["has_clean_name"] = True
|
||
updates["qnet_match"] = {
|
||
"method": qm["method"],
|
||
"confidence": qm["confidence"],
|
||
"matched_file": qm["file"],
|
||
"matched_station": qm["station"],
|
||
}
|
||
updates["tv_station"] = qm["station"]
|
||
else:
|
||
a, t = parse_artist_title(yt_title)
|
||
if a: updates["parsed_artist"] = a
|
||
if t: updates["parsed_title"] = t
|
||
updates["has_clean_name"] = bool(a and t)
|
||
|
||
if updates:
|
||
update_job(job_id, **updates)
|
||
# Reload job for downstream use
|
||
job = load_job(job_id)
|
||
except Exception as e:
|
||
print(f"⚠️ Cannot fetch YT metadata: {e}", flush=True)
|
||
else:
|
||
input_path = Path(job["input_path"])
|
||
|
||
# ── 1b. Music recognition (ACRCloud) — če nimamo artist+title ─────
|
||
# Tudi za YouTube jobs lahko naslov ni razviden (npr. iz playliste, "Track 5")
|
||
if not (job.get("parsed_artist") and job.get("parsed_title")):
|
||
update_job(job_id, current_step="Avto-prepoznavam pesem (ACRCloud)")
|
||
try:
|
||
acr_cmd = [
|
||
"python3", str(SCRIPTS_DIR / "acr_recognize.py"),
|
||
str(input_path),
|
||
]
|
||
proc = subprocess.run(acr_cmd, capture_output=True, text=True, timeout=120)
|
||
if proc.returncode == 0 and proc.stdout:
|
||
data = json.loads(proc.stdout)
|
||
a, t = data.get("artist"), data.get("title")
|
||
if a and t:
|
||
update_job(
|
||
job_id,
|
||
parsed_artist=a, parsed_title=t,
|
||
has_clean_name=True,
|
||
recognized_via="acrcloud",
|
||
)
|
||
job = load_job(job_id)
|
||
print(f"✅ ACR prepoznal: {a} - {t}", flush=True)
|
||
else:
|
||
print(f"⚠️ ACR ni prepoznal pesmi", flush=True)
|
||
else:
|
||
print(f"⚠️ ACR exit {proc.returncode}: {proc.stderr[:200]}", flush=True)
|
||
except Exception as e:
|
||
print(f"⚠️ ACR error: {e}", flush=True)
|
||
|
||
# ── 2. Smart analysis (če auto_chorus) ──────────────────────────
|
||
# ÄŒe je custom_clip=True (user-edit mode), preskoÄi analizo
|
||
# in samo posodobi start/duration iz obstojeÄega clip_range v analysis.json
|
||
if job.get("custom_clip"):
|
||
update_job(job_id, current_step="User-edit recut (preskočim analizo)")
|
||
analysis_path = OUTPUT_DIR / f"{job_id}.analysis.json"
|
||
srt_from_claude = None
|
||
if analysis_path.exists():
|
||
try:
|
||
with open(analysis_path, "r", encoding="utf-8") as f:
|
||
analysis = json.load(f)
|
||
cr = analysis["clip_range"]
|
||
fade = analysis.get("fade", {"fade_in": 0.05, "fade_out": 0.5})
|
||
|
||
# Generiraj nov SRT iz obstoječega transkripta na novem range-u
|
||
if analysis.get("transcript", {}).get("segments") and not job.get("no_subs"):
|
||
srt_path_out = OUTPUT_DIR / f"{job_id}.subtitles.srt"
|
||
try:
|
||
# Če imamo custom_subtitle_segments (user popravil napise)
|
||
segs_to_use = analysis.get("custom_subtitle_segments") or analysis["transcript"]["segments"]
|
||
generate_srt_from_segments(
|
||
segs_to_use,
|
||
cr["start"], cr["end"],
|
||
srt_path_out,
|
||
)
|
||
srt_from_claude = str(srt_path_out)
|
||
except Exception as e:
|
||
print(f"⚠️ Recut SRT generation failed: {e}", flush=True)
|
||
|
||
update_job(
|
||
job_id,
|
||
start=cr["start"],
|
||
duration=cr["duration"],
|
||
fade_in=fade.get("fade_in", 0.05),
|
||
fade_out=fade.get("fade_out", 0.5),
|
||
claude_srt_path=srt_from_claude,
|
||
)
|
||
job = load_job(job_id)
|
||
except Exception as e:
|
||
update_job(job_id, status="failed", error=f"Recut analysis read: {e}")
|
||
return
|
||
else:
|
||
update_job(job_id, status="failed", error="Analysis manjka za recut")
|
||
return
|
||
elif job.get("auto_chorus"):
|
||
update_job(job_id, current_step="Analiza pesmi (transkript + energija)")
|
||
analysis_path = OUTPUT_DIR / f"{job_id}.analysis.json"
|
||
cmd = [
|
||
"python3", str(SCRIPTS_DIR / "analyze.py"),
|
||
str(input_path),
|
||
"--target-duration", str(job.get("duration", 30)),
|
||
"--max-duration", str(job.get("max_duration", 45)),
|
||
"--min-duration", str(job.get("min_duration", 20)),
|
||
"--output", str(analysis_path),
|
||
]
|
||
if job.get("include_prebuild"):
|
||
cmd += ["--include-prebuild"]
|
||
# LLM provider (claude/gemini/auto)
|
||
if job.get("llm_provider"):
|
||
cmd += ["--llm-provider", job["llm_provider"]]
|
||
if job.get("llm_model"):
|
||
cmd += ["--llm-model", job["llm_model"]]
|
||
# Filename hint za Claude/Scribe — preferiraj parsed artist+title (čistejše)
|
||
if job.get("parsed_artist") and job.get("parsed_title"):
|
||
fn_hint = f"{job['parsed_artist']} - {job['parsed_title']}"
|
||
cmd += ["--filename-hint", fn_hint]
|
||
elif job.get("filename"):
|
||
fn_hint = Path(job["filename"]).stem
|
||
cmd += ["--filename-hint", fn_hint]
|
||
# STT provider (elevenlabs = Scribe, local = faster-whisper, auto = preferiraj Scribe)
|
||
# Per-station default routing:
|
||
# FOLX DE / ZWEI (nemške) → Scribe (boljši za nemščino, brez "Mrs. Sadie" halucinacij)
|
||
# FOLX SLO / ONE / ADRIA → Soniox primary (auto = soniox_chain)
|
||
# User lahko v UI override-a (whisper_provider polje).
|
||
station = (job.get("tv_station") or "").upper()
|
||
DE_STATIONS = ("FOLX DE", "ZWEI", "ZWEI MUSIC TV", "FOLX MUSIC TV")
|
||
user_provider = job.get("whisper_provider")
|
||
if user_provider and user_provider not in ("auto", ""):
|
||
# User explicitly chose a provider — respect it
|
||
cmd += ["--whisper-provider", user_provider]
|
||
elif any(s in station for s in DE_STATIONS):
|
||
# Auto-route DE → Scribe
|
||
cmd += ["--whisper-provider", "elevenlabs"]
|
||
print(f"🇩🇪 Auto-routing STT to Scribe za {job.get('tv_station')}", flush=True)
|
||
elif user_provider:
|
||
# auto → analyze.py si izbere (soniox_chain default)
|
||
cmd += ["--whisper-provider", user_provider]
|
||
# lang: če None ali 'auto', pusti analyze.py auto-detect
|
||
if job.get("lang") and job["lang"] not in ("auto", ""):
|
||
cmd += ["--lang", job["lang"]]
|
||
cmd += ["--model", job.get("whisper_model", "large-v3")]
|
||
|
||
proc = subprocess.run(cmd, capture_output=True, text=True)
|
||
srt_from_claude = None # Pot do SRT iz Claude-popravljenega transcript-a
|
||
if proc.returncode == 0 and analysis_path.exists():
|
||
try:
|
||
with open(analysis_path, "r", encoding="utf-8") as f:
|
||
analysis = json.load(f)
|
||
cr = analysis["clip_range"]
|
||
fade = analysis["fade"]
|
||
|
||
# Generiraj SRT iz transcript-a TRIM-ANEGA na clip_range
|
||
# (Claude je morda popravil besedilo — uporabi popravljeno)
|
||
if analysis.get("transcript", {}).get("segments"):
|
||
srt_path_out = OUTPUT_DIR / f"{job_id}.subtitles.srt"
|
||
try:
|
||
generate_srt_from_segments(
|
||
analysis["transcript"]["segments"],
|
||
cr["start"], cr["end"],
|
||
srt_path_out,
|
||
)
|
||
srt_from_claude = str(srt_path_out)
|
||
llm_src = cr.get("source", "LLM")
|
||
print(f"📝 Generated SRT from {llm_src} transcript: {srt_path_out}")
|
||
except Exception as e:
|
||
print(f"⚠️ SRT generation failed: {e}")
|
||
|
||
update_job(
|
||
job_id,
|
||
analysis_summary={
|
||
"language": analysis["language"],
|
||
"language_probability": analysis["language_probability"],
|
||
"instrumental": analysis["instrumental"],
|
||
"clip_range": cr,
|
||
"fade": fade,
|
||
"chorus_preview": analysis["chorus"]["best"]["text_preview"]
|
||
if analysis.get("chorus") and analysis["chorus"].get("best") else None,
|
||
"video_duration": analysis.get("video_duration"),
|
||
"candidates": analysis["chorus"].get("all_candidates", [])[:5]
|
||
if analysis.get("chorus") else [],
|
||
"claude_corrected_text": analysis.get("claude_corrected_text", False),
|
||
},
|
||
# Cel transkript shranimo za UI prikaz
|
||
full_transcript=[
|
||
{"start": s["start"], "end": s["end"], "text": s["text"]}
|
||
for s in analysis.get("transcript", {}).get("segments", [])
|
||
],
|
||
start=cr["start"],
|
||
duration=cr["duration"],
|
||
fade_in=fade["fade_in"],
|
||
fade_out=fade["fade_out"],
|
||
detected_language=analysis["language"],
|
||
is_instrumental=analysis["instrumental"],
|
||
claude_srt_path=srt_from_claude,
|
||
)
|
||
# Auto-disable subs za instrumental
|
||
if analysis["instrumental"] and not job.get("no_subs"):
|
||
update_job(job_id, no_subs=True, auto_disabled_subs=True)
|
||
# Reload local dict
|
||
job = load_job(job_id)
|
||
except (json.JSONDecodeError, KeyError) as e:
|
||
update_job(job_id, chorus_error=f"Analysis parse: {e}")
|
||
else:
|
||
update_job(job_id, chorus_error=(proc.stderr or "")[-500:])
|
||
|
||
# ── 3. Reframe + subtitles (clip.py orchestrator) ─────
|
||
output_path = OUTPUT_DIR / f"{job_id}.mp4"
|
||
update_job(job_id, current_step="Reframe + subtitles")
|
||
|
||
cmd = [
|
||
"python3", str(SCRIPTS_DIR / "clip.py"),
|
||
str(input_path), str(output_path),
|
||
"--mode", job.get("mode", "track"),
|
||
"--quality", job.get("quality", "medium"),
|
||
"--style", job.get("subtitle_style", "reels"),
|
||
]
|
||
if job.get("start") is not None:
|
||
cmd += ["--start", str(job["start"])]
|
||
if job.get("duration") is not None:
|
||
cmd += ["--duration", str(job["duration"])]
|
||
if job.get("fade_in", 0) > 0:
|
||
cmd += ["--fade-in", str(job["fade_in"])]
|
||
if job.get("fade_out", 0) > 0:
|
||
cmd += ["--fade-out", str(job["fade_out"])]
|
||
# SRT iz Claude (boljše besedilo) — preda direktno v subtitle.py
|
||
if job.get("claude_srt_path") and Path(job["claude_srt_path"]).exists() and not job.get("no_subs"):
|
||
cmd += ["--srt", job["claude_srt_path"]]
|
||
# lang: prefer detected_language če auto
|
||
chosen_lang = job.get("lang")
|
||
if chosen_lang in (None, "auto", ""):
|
||
chosen_lang = job.get("detected_language")
|
||
if chosen_lang:
|
||
cmd += ["--lang", chosen_lang]
|
||
if job.get("no_subs"):
|
||
cmd += ["--no-subs"]
|
||
cmd += ["--model", job.get("whisper_model", "large-v3")]
|
||
|
||
# DEBUG: zapiši natanko kakšen ukaz se izvede
|
||
update_job(job_id, debug_clip_cmd=" ".join(cmd))
|
||
|
||
if not run_subprocess_logged(cmd, job_id, "Reframe + subtitles"):
|
||
return
|
||
|
||
# ── Done ──────────────────────────────────────────────
|
||
if output_path.exists():
|
||
update_job(
|
||
job_id,
|
||
status="done",
|
||
current_step="Končano",
|
||
output_path=str(output_path),
|
||
output_size_mb=round(output_path.stat().st_size / 1024 / 1024, 2),
|
||
)
|
||
# S3 mirror — final reel + pomožne datoteke (analysis, subtitles)
|
||
_persist_to_s3(output_path, "output")
|
||
for suffix in (".analysis.json", ".subtitles.srt", ".subtitles.ass"):
|
||
aux = OUTPUT_DIR / f"{job_id}{suffix}"
|
||
if aux.exists():
|
||
_persist_to_s3(aux, "output")
|
||
# Telegram obvestilo
|
||
try:
|
||
from app.telegram import notify_job_done
|
||
final_job = load_job(job_id)
|
||
notify_job_done(final_job)
|
||
except Exception as e:
|
||
print(f"⚠️ TG notify_job_done failed: {e}", flush=True)
|
||
|
||
# Pre-cache za Edit modal (instant odpiranje):
|
||
# - low-q source video (480p) za hitro scrubbanje
|
||
# - waveform PNG
|
||
# Ti se bodo zgenerirali tudi on-demand, ampak zdaj so že tu = Edit instant.
|
||
try:
|
||
_precache_edit_assets(job_id, str(input_path))
|
||
except Exception as e:
|
||
print(f"⚠️ Edit precache failed: {e}", flush=True)
|
||
|
||
# Avto-upload v Nextcloud če flag set (npr. po Save/recut)
|
||
try:
|
||
final_job = load_job(job_id)
|
||
if final_job.get("auto_upload_to_nextcloud") and _nextcloud_configured():
|
||
update_job(job_id, nextcloud_status="uploading", nextcloud_error=None)
|
||
download_name = build_download_filename(final_job)
|
||
tv_station = final_job.get("tv_station", "FOLX SLOVENIJA")
|
||
nc_folder = _nextcloud_folder_for_station(tv_station)
|
||
target_subdir = f"folxspeed/REELS/{nc_folder}"
|
||
print(f"☁️ Avto-upload v Nextcloud: /{target_subdir}/{download_name}", flush=True)
|
||
success, result = _nextcloud_upload(str(output_path), download_name, target_subdir=target_subdir)
|
||
if success:
|
||
update_job(
|
||
job_id,
|
||
nextcloud_status="uploaded",
|
||
nextcloud_url=result,
|
||
nextcloud_error=None,
|
||
auto_upload_to_nextcloud=False, # disable da se ne ponovi
|
||
hidden_after_upload=True, # signal za UI da ga skrije
|
||
)
|
||
# Zabeleži v dedup
|
||
try:
|
||
orig_filename = final_job.get("filename") or download_name
|
||
file_mb = final_job.get("output_size_mb") or final_job.get("size_mb")
|
||
dedup_record(orig_filename, tv_station, job_id, nextcloud_url=result, file_size_mb=file_mb)
|
||
except Exception as e:
|
||
print(f"⚠️ Dedup record failed: {e}", flush=True)
|
||
print(f"☁️ Auto-upload OK: /{target_subdir}/{download_name}", flush=True)
|
||
else:
|
||
update_job(job_id, nextcloud_status="error", nextcloud_error=result)
|
||
print(f"⚠️ Auto-upload failed: {result}", flush=True)
|
||
except Exception as e:
|
||
print(f"⚠️ Auto-upload error: {e}", flush=True)
|
||
|
||
# Batch tracking — če je zadnji v batchu, pošlji summary
|
||
_try_finalize_batch(job_id)
|
||
else:
|
||
update_job(
|
||
job_id,
|
||
status="failed",
|
||
error="Output datoteka ne obstaja po obdelavi",
|
||
)
|
||
try:
|
||
from app.telegram import notify_job_failed
|
||
notify_job_failed(load_job(job_id), "Output datoteka ne obstaja")
|
||
except Exception:
|
||
pass
|
||
_try_finalize_batch(job_id)
|
||
except Exception as e:
|
||
update_job(job_id, status="failed", error=str(e))
|
||
try:
|
||
from app.telegram import notify_job_failed
|
||
notify_job_failed(load_job(job_id), str(e))
|
||
except Exception:
|
||
pass
|
||
_try_finalize_batch(job_id)
|
||
|
||
|
||
def _try_finalize_batch(job_id):
|
||
"""Če je job del batch-a, preveri če so vsi zaključili in pošlji summary."""
|
||
try:
|
||
job = load_job(job_id)
|
||
batch_id = job.get("batch_id")
|
||
if not batch_id:
|
||
return
|
||
# Preštej batch jobe
|
||
all_jobs = [load_job(jp.stem) for jp in JOBS_DIR.glob("*.json")]
|
||
batch_jobs = [j for j in all_jobs if j and j.get("batch_id") == batch_id]
|
||
unfinished = [j for j in batch_jobs if j.get("status") not in ("done", "failed")]
|
||
if unfinished:
|
||
return # še niso vsi končani
|
||
# Vsi so končani — pošlji summary
|
||
total = len(batch_jobs)
|
||
succeeded = len([j for j in batch_jobs if j.get("status") == "done"])
|
||
failed = total - succeeded
|
||
try:
|
||
from app.telegram import notify_batch_complete
|
||
notify_batch_complete(batch_id, total, succeeded, failed)
|
||
except Exception as e:
|
||
print(f"⚠️ TG batch summary failed: {e}", flush=True)
|
||
except Exception as e:
|
||
print(f"⚠️ _try_finalize_batch error: {e}", flush=True)
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────
|
||
# FastAPI app
|
||
# ────────────────────────────────────────────────────────────────
|
||
app = FastAPI(title="Reels Clipper")
|
||
app.mount("/static", StaticFiles(directory=Path(__file__).parent.parent / "static"), name="static")
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────
|
||
# Queue worker — procesira queued jobe enega za drugim
|
||
# ────────────────────────────────────────────────────────────────
|
||
import threading
|
||
_queue_lock = threading.Lock()
|
||
# Set ID-jev v obdelavi — omogoča 3 paralelne workerje
|
||
_queue_running = {"jobs_in_progress": set()}
|
||
|
||
# Število paralelnih worker-jev (CPU dovoljena hkratna obdelava)
|
||
NUM_WORKERS = int(os.environ.get("NUM_WORKERS", "3"))
|
||
|
||
|
||
def _queue_worker(worker_id: int):
|
||
"""Background thread ki preverja queued jobe in jih obdeluje paralelno.
|
||
|
||
Več worker-jev teče hkrati. Vsak vzame naslednji "queued" job ki ni
|
||
že v obdelavi pri drugem worker-ju. Zaklep poskrbi za atomično vzetje.
|
||
"""
|
||
print(f"🚜 Queue worker #{worker_id} zagnan", flush=True)
|
||
while True:
|
||
try:
|
||
# Najdi naslednjega "queued" joba ki ni že v obdelavi
|
||
with _queue_lock:
|
||
in_progress = _queue_running["jobs_in_progress"]
|
||
queued_jobs = []
|
||
for f in JOBS_DIR.glob("*.json"):
|
||
try:
|
||
j = json.loads(f.read_text())
|
||
jid = j.get("id")
|
||
if j.get("status") == "queued" and jid not in in_progress:
|
||
queued_jobs.append(j)
|
||
except Exception:
|
||
continue
|
||
|
||
if not queued_jobs:
|
||
next_job = None
|
||
else:
|
||
queued_jobs.sort(key=lambda x: x.get("created_at", 0))
|
||
next_job = queued_jobs[0]
|
||
# Atomično rezerviraj
|
||
_queue_running["jobs_in_progress"].add(next_job["id"])
|
||
|
||
if not next_job:
|
||
time.sleep(2)
|
||
continue
|
||
|
||
job_id = next_job["id"]
|
||
print(f"🚜 Worker #{worker_id}: obdelujem {job_id}", flush=True)
|
||
try:
|
||
process_job(job_id)
|
||
except Exception as e:
|
||
print(f"❌ Worker #{worker_id} error pri {job_id}: {e}", flush=True)
|
||
update_job(job_id, status="failed", error=f"Worker #{worker_id}: {e}")
|
||
finally:
|
||
with _queue_lock:
|
||
_queue_running["jobs_in_progress"].discard(job_id)
|
||
except Exception as e:
|
||
print(f"❌ Worker #{worker_id} outer error: {e}", flush=True)
|
||
time.sleep(5)
|
||
|
||
|
||
# Zaženi N worker-jev v ozadju (samo enkrat)
|
||
_worker_threads = []
|
||
def _start_queue_worker():
|
||
global _worker_threads
|
||
if _worker_threads:
|
||
# Preveri da so vsi alive
|
||
alive = [t for t in _worker_threads if t.is_alive()]
|
||
if len(alive) == NUM_WORKERS:
|
||
return
|
||
_worker_threads = []
|
||
for i in range(NUM_WORKERS):
|
||
t = threading.Thread(target=_queue_worker, args=(i+1,), daemon=True)
|
||
t.start()
|
||
_worker_threads.append(t)
|
||
print(f"🚜 Zagnal {NUM_WORKERS} paralelnih worker-jev", flush=True)
|
||
|
||
|
||
@app.on_event("startup")
|
||
async def resume_or_cleanup_jobs():
|
||
"""Ob startu containerja: avto-resume processing jobs ali jih označi kot error.
|
||
|
||
Ko Coolify deploya nov container, prejšnji se ubije sredi obdelave,
|
||
JSON file pa ostane status='processing'.
|
||
|
||
Strategija:
|
||
- Če je analyze.json že narejen (analiza je končana) → resume z reframe+subs
|
||
- Če ni analyze.json → restart pipeline od začetka
|
||
- Po 3 napakah (resume_attempts >= 3) → mark error
|
||
"""
|
||
import asyncio
|
||
print("🔄 Preverjam in obnavljam jobs po restart-u...")
|
||
resumed_count = 0
|
||
error_count = 0
|
||
|
||
for f in JOBS_DIR.glob("*.json"):
|
||
try:
|
||
j = json.loads(f.read_text())
|
||
if j.get("status") != "processing":
|
||
continue
|
||
|
||
job_id = j.get("job_id") or f.stem
|
||
attempts = j.get("resume_attempts", 0)
|
||
|
||
# Po 3 neuspehih nehamo
|
||
if attempts >= 3:
|
||
j["status"] = "error"
|
||
j["current_step"] = "Preveč napak pri ponovnem zagonu"
|
||
j["chorus_error"] = f"Job restartal {attempts} krat — napaka v pipeline-u"
|
||
j["updated_at"] = time.time()
|
||
f.write_text(json.dumps(j, ensure_ascii=False, indent=2))
|
||
error_count += 1
|
||
continue
|
||
|
||
# Preveri ali input file še obstaja
|
||
input_path = UPLOAD_DIR / f"{job_id}.mp4"
|
||
if not input_path.exists():
|
||
j["status"] = "error"
|
||
j["current_step"] = "Vhodna datoteka ne obstaja"
|
||
j["chorus_error"] = f"Upload {job_id}.mp4 ne obstaja po restart-u"
|
||
j["updated_at"] = time.time()
|
||
f.write_text(json.dumps(j, ensure_ascii=False, indent=2))
|
||
error_count += 1
|
||
continue
|
||
|
||
# Resume: status=queued, +1 attempt, in pošlji v background
|
||
j["status"] = "queued"
|
||
j["resume_attempts"] = attempts + 1
|
||
j["current_step"] = f"Avto-resume po restart-u (poskus {attempts + 1}/3)"
|
||
j["last_resume_at"] = time.time()
|
||
j["updated_at"] = time.time()
|
||
f.write_text(json.dumps(j, ensure_ascii=False, indent=2))
|
||
resumed_count += 1
|
||
# Pošlji v background po startup-u (ne smemo blokirati startup)
|
||
asyncio.create_task(_resume_job_async(job_id))
|
||
print(f" 🔁 Resume {job_id} (attempt {attempts + 1}/3)")
|
||
except Exception as e:
|
||
print(f" ⚠️ Napaka pri {f.name}: {e}")
|
||
|
||
print(f" ✅ Resumed: {resumed_count}, Error: {error_count}")
|
||
|
||
# Zaženi queue worker za queued jobe (multi-upload batch)
|
||
_start_queue_worker()
|
||
|
||
|
||
async def _resume_job_async(job_id):
|
||
"""Pomožna funkcija ki zažene process_job v background-u."""
|
||
import asyncio
|
||
# Počakaj kratek čas da je startup končan
|
||
await asyncio.sleep(2)
|
||
try:
|
||
# process_job je sync funkcija, izvedi v thread executor
|
||
loop = asyncio.get_event_loop()
|
||
await loop.run_in_executor(None, process_job, job_id)
|
||
except Exception as e:
|
||
print(f" ❌ Resume failed for {job_id}: {e}")
|
||
|
||
|
||
@app.get("/", response_class=HTMLResponse)
|
||
async def index(user: str = Depends(check_auth)):
|
||
html = (Path(__file__).parent.parent / "templates" / "index.html").read_text()
|
||
return html
|
||
|
||
|
||
@app.get("/healthz")
|
||
async def healthz():
|
||
return {"ok": True}
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────
|
||
# Job models
|
||
# ────────────────────────────────────────────────────────────────
|
||
class YouTubeJobIn(BaseModel):
|
||
url: str
|
||
mode: str = "track"
|
||
lang: Optional[str] = None
|
||
auto_chorus: bool = True
|
||
start: Optional[float] = None
|
||
duration: Optional[float] = 30
|
||
no_subs: bool = False
|
||
subtitle_style: str = "reels"
|
||
whisper_model: str = "large-v3"
|
||
quality: str = "medium"
|
||
tv_station: str = "FOLX SLOVENIJA" # za Nextcloud target mapo
|
||
|
||
|
||
class StartJobIn(BaseModel):
|
||
job_id: str
|
||
mode: str = "track"
|
||
lang: Optional[str] = None # None/auto = Whisper auto-detect
|
||
auto_chorus: bool = True
|
||
include_prebuild: bool = False # vključi pre-chorus build-up
|
||
start: Optional[float] = None
|
||
duration: Optional[float] = 30
|
||
max_duration: Optional[float] = 45
|
||
min_duration: Optional[float] = 20
|
||
no_subs: bool = False
|
||
subtitle_style: str = "reels"
|
||
whisper_model: str = "large-v3"
|
||
quality: str = "medium"
|
||
# LLM za semantično analizo + popravke
|
||
llm_provider: str = "claude" # claude / gemini / auto
|
||
llm_model: Optional[str] = None # specifičen model (privzeto najboljši za provider)
|
||
# STT provider (Scribe je 18x hitreje + boljša multilingual accuracy)
|
||
whisper_provider: str = "auto" # auto / elevenlabs / local
|
||
# Batch tracking za multi-upload (Telegram summary)
|
||
batch_id: Optional[str] = None
|
||
# TV postaja — določa Nextcloud target mapo
|
||
tv_station: str = "FOLX SLOVENIJA"
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────
|
||
# Dedup check
|
||
# ────────────────────────────────────────────────────────────────
|
||
class DedupCheckRequest(BaseModel):
|
||
filenames: list[str]
|
||
tv_station: str = "FOLX SLOVENIJA"
|
||
|
||
|
||
@app.post("/api/dedup/check")
|
||
async def dedup_check_endpoint(payload: DedupCheckRequest, user: str = Depends(check_auth)):
|
||
"""Preveri katere filename so že obdelane (na isti TV postaji).
|
||
|
||
Vrne dict { filename: {match} | null }
|
||
"""
|
||
result = {}
|
||
for fn in payload.filenames:
|
||
match = dedup_check(fn, payload.tv_station)
|
||
result[fn] = match
|
||
return {"results": result, "tv_station": payload.tv_station}
|
||
|
||
|
||
@app.post("/api/dedup/remove")
|
||
async def dedup_remove_endpoint(payload: DedupCheckRequest, user: str = Depends(check_auth)):
|
||
"""Izbriši dedup zapise — uporabnik želi re-narediti komad."""
|
||
for fn in payload.filenames:
|
||
dedup_remove(fn, payload.tv_station)
|
||
return {"ok": True, "removed": payload.filenames}
|
||
|
||
|
||
@app.get("/api/dedup/list")
|
||
async def dedup_list(tv_station: Optional[str] = None, user: str = Depends(check_auth)):
|
||
"""Seznam vseh obdelanih komadov (opcijsko filtrirano po TV postaji)."""
|
||
import sqlite3
|
||
_dedup_init()
|
||
conn = sqlite3.connect(str(DEDUP_DB))
|
||
conn.row_factory = sqlite3.Row
|
||
if tv_station:
|
||
rows = conn.execute(
|
||
"SELECT * FROM processed_videos WHERE tv_station = ? ORDER BY uploaded_at DESC",
|
||
(tv_station,)
|
||
).fetchall()
|
||
else:
|
||
rows = conn.execute(
|
||
"SELECT * FROM processed_videos ORDER BY uploaded_at DESC"
|
||
).fetchall()
|
||
conn.close()
|
||
return {"count": len(rows), "items": [dict(r) for r in rows]}
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────
|
||
# Upload (file)
|
||
# ────────────────────────────────────────────────────────────────
|
||
@app.post("/api/upload")
|
||
async def upload_video(
|
||
file: UploadFile = File(...),
|
||
artist: Optional[str] = Form(None),
|
||
title: Optional[str] = Form(None),
|
||
batch_id: Optional[str] = Form(None),
|
||
user: str = Depends(check_auth),
|
||
):
|
||
if not file.filename:
|
||
raise HTTPException(400, "Brez imena")
|
||
|
||
job_id = uuid.uuid4().hex[:12]
|
||
ext = Path(file.filename).suffix or ".mp4"
|
||
input_path = UPLOAD_DIR / f"{job_id}{ext}"
|
||
|
||
size = 0
|
||
with input_path.open("wb") as f:
|
||
while chunk := await file.read(1024 * 1024):
|
||
size += len(chunk)
|
||
if size > MAX_UPLOAD_MB * 1024 * 1024:
|
||
f.close()
|
||
input_path.unlink(missing_ok=True)
|
||
raise HTTPException(413, f"Prevelika datoteka (limit {MAX_UPLOAD_MB} MB)")
|
||
f.write(chunk)
|
||
|
||
job = {
|
||
"id": job_id,
|
||
"source_type": "upload",
|
||
"filename": file.filename,
|
||
"input_path": str(input_path),
|
||
"size_mb": round(size / 1024 / 1024, 2),
|
||
"status": "uploaded",
|
||
"current_step": "Naloženo, čaka na obdelavo",
|
||
"created_at": time.time(),
|
||
"updated_at": time.time(),
|
||
}
|
||
|
||
if batch_id:
|
||
job["batch_id"] = batch_id
|
||
|
||
# Artist + title — najprej user-provided, potem Qnet match, potem parse iz filename
|
||
# Qnet match poskusimo VEDNO (audit + tv_station auto-fill), ne glede na to
|
||
# ali je client že poslal artist+title (jih je morda dobil iz Qnet match-a sam)
|
||
qm = qnet_match.match_filename(file.filename)
|
||
if qm["matched"] and qm["confidence"] >= 0.85:
|
||
job["qnet_match"] = {
|
||
"method": qm["method"],
|
||
"confidence": qm["confidence"],
|
||
"matched_file": qm["file"],
|
||
"matched_station": qm["station"],
|
||
}
|
||
# Auto-set tv_station, če še ni — uporabnik ga lahko ročno spremeni v UI
|
||
if not job.get("tv_station"):
|
||
job["tv_station"] = qm["station"]
|
||
|
||
if artist and title:
|
||
# User je vpisal ali potrdil (lahko prihaja iz client-side Qnet match-a)
|
||
job["parsed_artist"] = artist.strip()
|
||
job["parsed_title"] = title.strip()
|
||
job["has_clean_name"] = True
|
||
else:
|
||
# Fallback: Qnet match (server-side) → parse_artist_title regex
|
||
if qm["matched"] and qm["confidence"] >= 0.85:
|
||
job["parsed_artist"] = qm["artist"]
|
||
job["parsed_title"] = qm["title"]
|
||
job["has_clean_name"] = True
|
||
print(f"🎯 Qnet match [{qm['method']}, {qm['confidence']}]: "
|
||
f"{qm['station']} — {qm['artist']} — {qm['title']}", flush=True)
|
||
else:
|
||
# Fallback: regex parser
|
||
a, t = parse_artist_title(file.filename)
|
||
if a:
|
||
job["parsed_artist"] = a
|
||
if t:
|
||
job["parsed_title"] = t
|
||
job["has_clean_name"] = bool(a and t)
|
||
|
||
save_job(job)
|
||
# S3 mirror — direct upload datoteka
|
||
_persist_to_s3(input_path, "upload")
|
||
return job
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────
|
||
# YouTube submit
|
||
# ────────────────────────────────────────────────────────────────
|
||
class YouTubePlaylistPreviewIn(BaseModel):
|
||
url: str
|
||
|
||
|
||
@app.post("/api/youtube/playlist-preview")
|
||
async def youtube_playlist_preview(payload: YouTubePlaylistPreviewIn, user: str = Depends(check_auth)):
|
||
"""Resolve YouTube URL — vrne listo videov če je playlist, ali en item.
|
||
|
||
Frontend uporabi to za preview pred submit-om: če je playlist, user vidi
|
||
koliko komadov je in lahko potrdi.
|
||
"""
|
||
import sys as _sys
|
||
_sys.path.insert(0, str(SCRIPTS_DIR))
|
||
try:
|
||
from yt_download import get_playlist
|
||
except ImportError:
|
||
raise HTTPException(500, "yt_download modul ne dostopen")
|
||
|
||
try:
|
||
info = get_playlist(payload.url)
|
||
except subprocess.TimeoutExpired:
|
||
raise HTTPException(504, "yt-dlp timeout (>120s) — preveri URL")
|
||
except Exception as e:
|
||
raise HTTPException(500, f"yt-dlp napaka: {e}")
|
||
|
||
if info.get("error"):
|
||
raise HTTPException(400, f"yt-dlp: {info['error']}")
|
||
if not info.get("items"):
|
||
raise HTTPException(400, "Ni najdenih videov na tem URL-u")
|
||
|
||
return info
|
||
|
||
|
||
@app.post("/api/youtube")
|
||
async def submit_youtube(
|
||
payload: YouTubeJobIn,
|
||
background: BackgroundTasks,
|
||
user: str = Depends(check_auth),
|
||
):
|
||
"""Submit YouTube URL — single video ali cela playlist.
|
||
|
||
Če URL vsebuje 'list=' parameter, resolve-amo playlist in kreiramo
|
||
batch jobs (en job za vsak video). Single video kreira en job.
|
||
"""
|
||
url = payload.url.strip()
|
||
is_playlist_url = "list=" in url and "watch?" not in url.split("list=")[0].split("&")[0]
|
||
# Bolj robustno: če ima list= ampak tudi v= potem je morda single video iz playliste
|
||
# → tretiraj kot single (default)
|
||
has_list = "list=" in url
|
||
has_v = "v=" in url or "/watch?" in url or "youtu.be/" in url
|
||
treat_as_playlist = has_list and not has_v # samo "playlist?list=..." URLs
|
||
# Pa tudi če je explicit "/playlist?" v URL-u
|
||
if "/playlist?" in url:
|
||
treat_as_playlist = True
|
||
|
||
if treat_as_playlist:
|
||
# Resolve playlist
|
||
import sys as _sys
|
||
_sys.path.insert(0, str(SCRIPTS_DIR))
|
||
try:
|
||
from yt_download import get_playlist
|
||
except ImportError:
|
||
raise HTTPException(500, "yt_download modul ne dostopen")
|
||
|
||
try:
|
||
info = get_playlist(url)
|
||
except Exception as e:
|
||
raise HTTPException(500, f"Playlist resolve napaka: {e}")
|
||
|
||
items = info.get("items", [])
|
||
if not items:
|
||
raise HTTPException(400, "Playlist je prazen ali ni dostopen")
|
||
|
||
# Batch ID za grupiranje
|
||
batch_id = "yt-batch-" + uuid.uuid4().hex[:8]
|
||
playlist_title = info.get("playlist_title", "YouTube Playlist")
|
||
created_jobs = []
|
||
|
||
for item in items:
|
||
job_id = uuid.uuid4().hex[:12]
|
||
# Probaj match proti Qnet bazi (parsa Artist - Title iz YouTube naslova)
|
||
yt_title = item.get("title", "")
|
||
qm = qnet_match.match_filename(yt_title)
|
||
|
||
job = {
|
||
"id": job_id,
|
||
"source_type": "youtube",
|
||
"youtube_url": item["url"],
|
||
"youtube_title": yt_title,
|
||
"youtube_id": item.get("id"),
|
||
"youtube_uploader": item.get("uploader", ""),
|
||
"playlist_url": url,
|
||
"playlist_title": playlist_title,
|
||
"batch_id": batch_id,
|
||
"status": "queued",
|
||
"current_step": "V vrsti za YouTube prenos",
|
||
"created_at": time.time(),
|
||
"updated_at": time.time(),
|
||
"mode": payload.mode,
|
||
"lang": payload.lang,
|
||
"auto_chorus": payload.auto_chorus,
|
||
"start": payload.start,
|
||
"duration": payload.duration,
|
||
"no_subs": payload.no_subs,
|
||
"subtitle_style": payload.subtitle_style,
|
||
"whisper_model": payload.whisper_model,
|
||
"quality": payload.quality,
|
||
"tv_station": payload.tv_station,
|
||
}
|
||
|
||
# Qnet match — auto-fill clean Artist/Title in tv_station če je matched
|
||
if qm["matched"] and qm["confidence"] >= 0.85:
|
||
job["parsed_artist"] = qm["artist"]
|
||
job["parsed_title"] = qm["title"]
|
||
job["has_clean_name"] = True
|
||
job["qnet_match"] = {
|
||
"method": qm["method"],
|
||
"confidence": qm["confidence"],
|
||
"matched_file": qm["file"],
|
||
"matched_station": qm["station"],
|
||
}
|
||
# Auto-set tv_station iz Qnet match-a (override default)
|
||
job["tv_station"] = qm["station"]
|
||
else:
|
||
# Fallback: regex parser na YT naslovu
|
||
a, t = parse_artist_title(yt_title)
|
||
if a: job["parsed_artist"] = a
|
||
if t: job["parsed_title"] = t
|
||
job["has_clean_name"] = bool(a and t)
|
||
|
||
save_job(job)
|
||
created_jobs.append(job)
|
||
|
||
print(f"📋 YouTube playlist '{playlist_title}': {len(created_jobs)} jobov v batch {batch_id}", flush=True)
|
||
return {
|
||
"is_playlist": True,
|
||
"batch_id": batch_id,
|
||
"playlist_title": playlist_title,
|
||
"count": len(created_jobs),
|
||
"jobs": created_jobs,
|
||
}
|
||
|
||
# ─── Single video ───
|
||
job_id = uuid.uuid4().hex[:12]
|
||
job = {
|
||
"id": job_id,
|
||
"source_type": "youtube",
|
||
"youtube_url": url,
|
||
"status": "queued",
|
||
"current_step": "V vrsti za YouTube prenos",
|
||
"created_at": time.time(),
|
||
"updated_at": time.time(),
|
||
"mode": payload.mode,
|
||
"lang": payload.lang,
|
||
"auto_chorus": payload.auto_chorus,
|
||
"start": payload.start,
|
||
"duration": payload.duration,
|
||
"no_subs": payload.no_subs,
|
||
"subtitle_style": payload.subtitle_style,
|
||
"whisper_model": payload.whisper_model,
|
||
"quality": payload.quality,
|
||
"tv_station": payload.tv_station,
|
||
}
|
||
|
||
# Fetch YT metadata že ob submit (preko yt.biba.live API ali lokalni yt-dlp).
|
||
# Uporabljamo isti yt_download modul, da konsistentno dobimo vse pomembne polja.
|
||
# Če fetch ne uspe, gre job naprej brez metadat — worker bo še enkrat probal.
|
||
try:
|
||
import sys as _sys
|
||
_sys.path.insert(0, str(SCRIPTS_DIR))
|
||
from yt_download import get_info as yt_get_info
|
||
info = yt_get_info(url)
|
||
if info:
|
||
yt_title = info.get("title", "") or ""
|
||
job["youtube_title"] = yt_title
|
||
job["youtube_id"] = info.get("id") or ""
|
||
job["youtube_uploader"] = info.get("uploader") or info.get("channel") or ""
|
||
job["youtube_duration"] = info.get("duration")
|
||
job["youtube_thumbnail"] = info.get("thumbnail") or ""
|
||
job["youtube_description"] = (info.get("description") or "")[:2000] # cap na 2KB
|
||
job["youtube_upload_date"] = info.get("upload_date") or ""
|
||
job["youtube_webpage_url"] = info.get("webpage_url") or url
|
||
|
||
# Qnet match na YT naslovu (kot pri playlist)
|
||
if yt_title:
|
||
qm = qnet_match.match_filename(yt_title)
|
||
if qm["matched"] and qm["confidence"] >= 0.85:
|
||
job["parsed_artist"] = qm["artist"]
|
||
job["parsed_title"] = qm["title"]
|
||
job["has_clean_name"] = True
|
||
job["qnet_match"] = {
|
||
"method": qm["method"],
|
||
"confidence": qm["confidence"],
|
||
"matched_file": qm["file"],
|
||
"matched_station": qm["station"],
|
||
}
|
||
# Auto-set tv_station iz Qnet match-a (override default)
|
||
job["tv_station"] = qm["station"]
|
||
else:
|
||
# Fallback: regex parser na YT naslovu
|
||
a, t = parse_artist_title(yt_title)
|
||
if a: job["parsed_artist"] = a
|
||
if t: job["parsed_title"] = t
|
||
job["has_clean_name"] = bool(a and t)
|
||
except Exception as e:
|
||
print(f"⚠️ Cannot fetch YT metadata at submit: {e}", flush=True)
|
||
|
||
save_job(job)
|
||
return job
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────
|
||
# Start processing for uploaded job
|
||
# ────────────────────────────────────────────────────────────────
|
||
@app.post("/api/process")
|
||
async def start_processing(
|
||
payload: StartJobIn,
|
||
background: BackgroundTasks,
|
||
user: str = Depends(check_auth),
|
||
):
|
||
job = load_job(payload.job_id)
|
||
if not job:
|
||
raise HTTPException(404, "Job ne obstaja")
|
||
|
||
update_job(
|
||
payload.job_id,
|
||
status="queued",
|
||
mode=payload.mode,
|
||
lang=payload.lang,
|
||
auto_chorus=payload.auto_chorus,
|
||
include_prebuild=payload.include_prebuild,
|
||
start=payload.start,
|
||
duration=payload.duration,
|
||
max_duration=payload.max_duration,
|
||
min_duration=payload.min_duration,
|
||
no_subs=payload.no_subs,
|
||
subtitle_style=payload.subtitle_style,
|
||
whisper_model=payload.whisper_model,
|
||
quality=payload.quality,
|
||
llm_provider=payload.llm_provider,
|
||
llm_model=payload.llm_model,
|
||
whisper_provider=payload.whisper_provider,
|
||
batch_id=payload.batch_id,
|
||
tv_station=payload.tv_station,
|
||
current_step="V vrsti za obdelavo",
|
||
# Počisti pretekle napake (retry-friendly)
|
||
chorus_error=None,
|
||
interrupted_at=None,
|
||
)
|
||
# Queue worker (background thread) bo pograbil ta job — ne zaganjamo neposredno.
|
||
# To pomeni, da se ob več upload-ih obdelujejo zaporedno (1 hkrati = stabilno).
|
||
return load_job(payload.job_id)
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────
|
||
# Job queries
|
||
# ────────────────────────────────────────────────────────────────
|
||
@app.get("/api/jobs")
|
||
async def get_jobs(user: str = Depends(check_auth)):
|
||
return {"jobs": list_jobs()}
|
||
|
||
|
||
@app.get("/api/jobs/{job_id}")
|
||
async def get_job(job_id: str, user: str = Depends(check_auth)):
|
||
job = load_job(job_id)
|
||
if not job:
|
||
raise HTTPException(404, "Ne obstaja")
|
||
return _clean_job_titles(job)
|
||
|
||
|
||
@app.get("/api/stream/{job_id}")
|
||
async def stream_job(job_id: str, user: str = Depends(check_auth)):
|
||
"""Server-Sent Events za real-time status."""
|
||
|
||
async def gen():
|
||
last_status = None
|
||
last_step = None
|
||
for _ in range(600): # max 10 min stream
|
||
job = load_job(job_id)
|
||
if not job:
|
||
yield f"data: {json.dumps({'error': 'not found'})}\n\n"
|
||
return
|
||
if job["status"] != last_status or job.get("current_step") != last_step:
|
||
yield f"data: {json.dumps(job, ensure_ascii=False)}\n\n"
|
||
last_status = job["status"]
|
||
last_step = job.get("current_step")
|
||
if job["status"] in ("done", "failed"):
|
||
return
|
||
await asyncio.sleep(1)
|
||
|
||
return StreamingResponse(gen(), media_type="text/event-stream")
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────
|
||
# Download / preview
|
||
# ────────────────────────────────────────────────────────────────
|
||
@app.get("/api/download/{job_id}")
|
||
async def download(job_id: str, user: str = Depends(check_auth)):
|
||
job = load_job(job_id)
|
||
if not job or job.get("status") != "done":
|
||
raise HTTPException(404, "Ne pripravljen")
|
||
out = Path(job["output_path"])
|
||
_ensure_local(out, "output")
|
||
if not out.exists():
|
||
raise HTTPException(404, "Output ne obstaja")
|
||
|
||
# Pametno ime: "Izvajalec - Naslov - REEL.mp4"
|
||
download_name = build_download_filename(job)
|
||
|
||
return FileResponse(
|
||
out,
|
||
media_type="video/mp4",
|
||
filename=download_name,
|
||
)
|
||
|
||
|
||
@app.get("/api/preview/{job_id}")
|
||
async def preview(job_id: str, request: Request, user: str = Depends(check_auth)):
|
||
"""Video preview z Range request podporo (potrebno za HTML5 video player)."""
|
||
job = load_job(job_id)
|
||
if not job or job.get("status") != "done":
|
||
raise HTTPException(404, "Ne pripravljen")
|
||
out = Path(job["output_path"])
|
||
_ensure_local(out, "output")
|
||
if not out.exists():
|
||
raise HTTPException(404, "Output ne obstaja")
|
||
|
||
file_size = out.stat().st_size
|
||
range_header = request.headers.get("range") or request.headers.get("Range")
|
||
|
||
if range_header:
|
||
# Parse "bytes=START-END"
|
||
try:
|
||
range_str = range_header.replace("bytes=", "").strip()
|
||
start_s, end_s = range_str.split("-")
|
||
start = int(start_s) if start_s else 0
|
||
end = int(end_s) if end_s else file_size - 1
|
||
end = min(end, file_size - 1)
|
||
if start > end or start >= file_size:
|
||
return Response(status_code=416) # Range Not Satisfiable
|
||
chunk_size = end - start + 1
|
||
|
||
def iter_file():
|
||
with open(out, "rb") as f:
|
||
f.seek(start)
|
||
remaining = chunk_size
|
||
while remaining > 0:
|
||
read_size = min(64 * 1024, remaining)
|
||
data = f.read(read_size)
|
||
if not data:
|
||
break
|
||
remaining -= len(data)
|
||
yield data
|
||
|
||
headers = {
|
||
"Content-Range": f"bytes {start}-{end}/{file_size}",
|
||
"Accept-Ranges": "bytes",
|
||
"Content-Length": str(chunk_size),
|
||
"Content-Type": "video/mp4",
|
||
"Cache-Control": "no-cache, must-revalidate", # browser ne sme cachat starega output-a
|
||
}
|
||
return StreamingResponse(iter_file(), status_code=206, headers=headers,
|
||
media_type="video/mp4")
|
||
except (ValueError, IndexError):
|
||
pass
|
||
|
||
# Brez Range — vrni cel file
|
||
return FileResponse(
|
||
out,
|
||
media_type="video/mp4",
|
||
headers={
|
||
"Accept-Ranges": "bytes",
|
||
"Content-Length": str(file_size),
|
||
"Cache-Control": "no-cache, must-revalidate", # browser ne sme cachat starega output-a
|
||
},
|
||
)
|
||
|
||
|
||
@app.delete("/api/jobs/{job_id}")
|
||
async def delete_job(job_id: str, user: str = Depends(check_auth)):
|
||
job = load_job(job_id)
|
||
if not job:
|
||
raise HTTPException(404, "Ne obstaja")
|
||
# Glavni input + output (po job records)
|
||
for key, kind in (("input_path", "upload"), ("output_path", "output")):
|
||
p = job.get(key)
|
||
if p:
|
||
local_p = Path(p)
|
||
local_p.unlink(missing_ok=True)
|
||
_delete_from_s3(local_p.name, kind)
|
||
# Pomožne datoteke v outputs/ (analysis, subtitles, low-q, waveform)
|
||
for fname in (
|
||
f"{job_id}.mp4",
|
||
f"{job_id}.analysis.json",
|
||
f"{job_id}.subtitles.srt",
|
||
f"{job_id}.subtitles.ass",
|
||
f"{job_id}_source_low.mp4",
|
||
):
|
||
f = OUTPUT_DIR / fname
|
||
f.unlink(missing_ok=True)
|
||
_delete_from_s3(fname, "output")
|
||
# Waveform PNG-ji (več velikosti) — listanje ker imena niso fiksna
|
||
try:
|
||
for wf in OUTPUT_DIR.glob(f"{job_id}_waveform_*.png"):
|
||
wf_name = wf.name
|
||
wf.unlink(missing_ok=True)
|
||
_delete_from_s3(wf_name, "output")
|
||
except Exception:
|
||
pass
|
||
# YT info.json
|
||
info_json = UPLOAD_DIR / f"{job_id}_yt.info.json"
|
||
if info_json.exists():
|
||
info_json.unlink(missing_ok=True)
|
||
_delete_from_s3(f"{job_id}_yt.info.json", "upload")
|
||
# Job metadata
|
||
jp = job_path(job_id)
|
||
jp.unlink(missing_ok=True)
|
||
_delete_from_s3(f"{job_id}.json", "job_meta")
|
||
return {"deleted": job_id}
|
||
|
||
|
||
# ─── EDIT FEATURE ────────────────────────────────────────────────
|
||
@app.get("/api/source-video/{job_id}")
|
||
async def source_video(job_id: str, quality: str = "high", user: str = Depends(check_auth)):
|
||
"""Vrne 16:9 original video za predogled v editorju.
|
||
|
||
quality='high' (default): originalni file
|
||
quality='low': 480p re-encoded version (cached) — za hitro scrubbanje v editorju
|
||
"""
|
||
job = load_job(job_id)
|
||
if not job:
|
||
raise HTTPException(404, "Ne obstaja")
|
||
src = job.get("input_path")
|
||
if not src:
|
||
raise HTTPException(404, "Original video ne obstaja")
|
||
_ensure_local(src, "upload")
|
||
if not Path(src).exists():
|
||
raise HTTPException(404, "Original video ne obstaja")
|
||
|
||
if quality == "low":
|
||
# 480p cached za hitro scrubbanje
|
||
cache_path = OUTPUT_DIR / f"{job_id}_source_low.mp4"
|
||
# Najprej probaj fetch iz S3 (po cleanupu lahko manjka lokalno)
|
||
_ensure_local(cache_path, "output")
|
||
cache_valid = cache_path.exists() and cache_path.stat().st_size > 1024
|
||
|
||
if not cache_valid:
|
||
if cache_path.exists():
|
||
cache_path.unlink()
|
||
cmd = [
|
||
"ffmpeg", "-y",
|
||
"-i", str(src),
|
||
"-vf", "scale=854:480:force_original_aspect_ratio=decrease,scale=trunc(iw/2)*2:trunc(ih/2)*2",
|
||
"-c:v", "libx264",
|
||
"-preset", "veryfast", # malo boljša kvaliteta od ultrafast
|
||
"-crf", "28",
|
||
"-c:a", "aac",
|
||
"-b:a", "96k",
|
||
"-movflags", "+faststart",
|
||
"-loglevel", "error",
|
||
str(cache_path),
|
||
]
|
||
try:
|
||
proc = subprocess.run(cmd, capture_output=True, text=True, timeout=120)
|
||
if proc.returncode != 0 or not cache_path.exists() or cache_path.stat().st_size < 1024:
|
||
if cache_path.exists():
|
||
cache_path.unlink()
|
||
raise HTTPException(500, f"FFmpeg failed: {(proc.stderr or 'unknown')[-300:]}")
|
||
# Mirror v S3 po regeneraciji
|
||
_persist_to_s3(cache_path, "output")
|
||
except subprocess.TimeoutExpired:
|
||
if cache_path.exists():
|
||
cache_path.unlink()
|
||
raise HTTPException(500, "Low-q source render timeout (>120s)")
|
||
|
||
return FileResponse(
|
||
path=cache_path,
|
||
media_type="video/mp4",
|
||
filename=f"source_low_{job_id}.mp4",
|
||
headers={"Accept-Ranges": "bytes", "Cache-Control": "max-age=3600"},
|
||
)
|
||
|
||
return FileResponse(
|
||
path=src,
|
||
media_type="video/mp4",
|
||
filename=f"source_{job_id}.mp4",
|
||
headers={"Accept-Ranges": "bytes"},
|
||
)
|
||
|
||
|
||
@app.get("/api/waveform/{job_id}")
|
||
async def waveform(job_id: str, width: int = 1200, height: int = 80, user: str = Depends(check_auth)):
|
||
"""Vrne PNG waveform celotne pesmi za visualizacijo v Edit modalu.
|
||
|
||
Cache enkrat per pesem, file size ~10-50 KB.
|
||
"""
|
||
job = load_job(job_id)
|
||
if not job:
|
||
raise HTTPException(404, "Ne obstaja")
|
||
src = job.get("input_path")
|
||
if not src:
|
||
raise HTTPException(404, "Original video ne obstaja")
|
||
_ensure_local(src, "upload")
|
||
if not Path(src).exists():
|
||
raise HTTPException(404, "Original video ne obstaja")
|
||
|
||
width = max(400, min(width, 3000))
|
||
height = max(40, min(height, 200))
|
||
|
||
cache_path = OUTPUT_DIR / f"{job_id}_waveform_{width}x{height}.png"
|
||
_ensure_local(cache_path, "output")
|
||
cache_valid = cache_path.exists() and cache_path.stat().st_size > 100
|
||
|
||
if not cache_valid:
|
||
if cache_path.exists():
|
||
cache_path.unlink()
|
||
# ffmpeg showwavespic filter — generira en sam PNG s celotnim waveformom
|
||
# colors: rdeč #ff6b6b kot accent
|
||
cmd = [
|
||
"ffmpeg", "-y",
|
||
"-i", str(src),
|
||
"-filter_complex",
|
||
f"[0:a]aformat=channel_layouts=mono,showwavespic=s={width}x{height}:colors=#ff6b6b:scale=lin:draw=full[wave]",
|
||
"-map", "[wave]",
|
||
"-frames:v", "1",
|
||
"-loglevel", "error",
|
||
str(cache_path),
|
||
]
|
||
try:
|
||
proc = subprocess.run(cmd, capture_output=True, text=True, timeout=30)
|
||
if proc.returncode != 0 or not cache_path.exists() or cache_path.stat().st_size < 100:
|
||
if cache_path.exists():
|
||
cache_path.unlink()
|
||
raise HTTPException(500, f"Waveform render failed: {(proc.stderr or 'unknown')[-300:]}")
|
||
# Mirror v S3 po regeneraciji
|
||
_persist_to_s3(cache_path, "output")
|
||
except subprocess.TimeoutExpired:
|
||
if cache_path.exists():
|
||
cache_path.unlink()
|
||
raise HTTPException(500, "Waveform render timeout (>30s)")
|
||
|
||
return FileResponse(
|
||
path=cache_path,
|
||
media_type="image/png",
|
||
headers={"Cache-Control": "max-age=3600"},
|
||
)
|
||
|
||
|
||
@app.api_route("/api/preview-clip/{job_id}", methods=["GET", "HEAD"])
|
||
async def preview_clip(
|
||
job_id: str,
|
||
start: float,
|
||
end: float,
|
||
user: str = Depends(check_auth),
|
||
):
|
||
"""Live preview odseka + 10s konteksta pred/po — low-quality 480p clip.
|
||
|
||
Vrne odsek od (start-10s) do (end+10s), 480p quality.
|
||
Frontend lahko free-scruba v tem range-u + drag-a handle.
|
||
BREZ reframe (16:9 ostane), BREZ napisov, BREZ face tracking.
|
||
|
||
Cache po start+end timestampih.
|
||
"""
|
||
job = load_job(job_id)
|
||
if not job:
|
||
raise HTTPException(404, "Ne obstaja")
|
||
src = job.get("input_path")
|
||
if not src:
|
||
raise HTTPException(404, "Original video ne obstaja")
|
||
_ensure_local(src, "upload")
|
||
if not Path(src).exists():
|
||
raise HTTPException(404, "Original video ne obstaja")
|
||
|
||
if end <= start:
|
||
raise HTTPException(400, "end mora biti večji od start")
|
||
duration = end - start
|
||
if duration < 1:
|
||
raise HTTPException(400, "Trajanje vsaj 1s")
|
||
if duration > 90:
|
||
raise HTTPException(400, "Trajanje največ 90s")
|
||
|
||
# Razširi z 10s pred in po (kontekst za fine-tune)
|
||
CONTEXT_BEFORE = 10.0
|
||
CONTEXT_AFTER = 10.0
|
||
extract_start = max(0, start - CONTEXT_BEFORE)
|
||
extract_end = end + CONTEXT_AFTER
|
||
extract_duration = extract_end - extract_start
|
||
|
||
# Cache key — razširjen preview se shrani po orig start+end
|
||
cache_key = f"{job_id}_preview_ctx_{start:.1f}_{end:.1f}.mp4"
|
||
cache_path = OUTPUT_DIR / cache_key
|
||
|
||
# Validate cache: datoteka mora obstajati IN biti vsaj 1KB
|
||
cache_valid = cache_path.exists() and cache_path.stat().st_size > 1024
|
||
|
||
if not cache_valid:
|
||
if cache_path.exists():
|
||
cache_path.unlink()
|
||
cmd = [
|
||
"ffmpeg", "-y",
|
||
"-ss", f"{max(0, extract_start - 0.5):.2f}",
|
||
"-i", str(src),
|
||
"-ss", f"{min(0.5, extract_start):.2f}",
|
||
"-t", f"{extract_duration:.2f}",
|
||
"-vf", "scale=854:480:force_original_aspect_ratio=decrease,scale=trunc(iw/2)*2:trunc(ih/2)*2",
|
||
"-c:v", "libx264",
|
||
"-preset", "ultrafast",
|
||
"-crf", "30",
|
||
"-c:a", "aac",
|
||
"-b:a", "96k",
|
||
"-movflags", "+faststart",
|
||
"-loglevel", "error",
|
||
str(cache_path),
|
||
]
|
||
try:
|
||
proc = subprocess.run(cmd, capture_output=True, text=True, timeout=20)
|
||
if proc.returncode != 0 or not cache_path.exists() or cache_path.stat().st_size < 1024:
|
||
if cache_path.exists():
|
||
cache_path.unlink()
|
||
raise HTTPException(500, f"FFmpeg failed: {(proc.stderr or 'unknown')[-300:]}")
|
||
except subprocess.TimeoutExpired:
|
||
if cache_path.exists():
|
||
cache_path.unlink()
|
||
raise HTTPException(500, "Preview render timeout (>20s)")
|
||
|
||
return FileResponse(
|
||
path=cache_path,
|
||
media_type="video/mp4",
|
||
headers={
|
||
"Accept-Ranges": "bytes",
|
||
"Cache-Control": "max-age=300",
|
||
# Vrnem original start kot custom header da frontend ve mapiranje
|
||
"X-Preview-Original-Start": f"{extract_start:.2f}",
|
||
"X-Preview-Original-End": f"{extract_end:.2f}",
|
||
},
|
||
)
|
||
|
||
|
||
@app.get("/api/transcript/{job_id}")
|
||
async def get_transcript(job_id: str, user: str = Depends(check_auth)):
|
||
"""Vrne transkript (segmente + words) za editor."""
|
||
job = load_job(job_id)
|
||
if not job:
|
||
raise HTTPException(404, "Ne obstaja")
|
||
analysis_path = OUTPUT_DIR / f"{job_id}.analysis.json"
|
||
_ensure_local(analysis_path, "output")
|
||
if not analysis_path.exists():
|
||
raise HTTPException(404, "Analysis ne obstaja")
|
||
try:
|
||
analysis = json.loads(analysis_path.read_text())
|
||
transcript = analysis.get("transcript", {})
|
||
clip_range = analysis.get("clip_range", {})
|
||
# video_duration: probaj iz analysis, sicer iz zadnjega segmenta, sicer 0
|
||
video_dur = analysis.get("video_duration") or job.get("video_duration") or 0
|
||
if not video_dur and transcript.get("segments"):
|
||
video_dur = max((s.get("end", 0) for s in transcript["segments"]), default=0)
|
||
return {
|
||
"segments": transcript.get("segments", []),
|
||
"language": transcript.get("language", "?"),
|
||
"clip_range": clip_range,
|
||
"video_duration": video_dur,
|
||
}
|
||
except Exception as e:
|
||
raise HTTPException(500, f"Napaka pri branju: {e}")
|
||
|
||
|
||
# ─── Qnet song match (MB player baza) ────────────────────────────
|
||
@app.get("/api/qnet/stats")
|
||
async def qnet_stats(user: str = Depends(check_auth)):
|
||
"""Statistika Qnet baze (koliko songov, koliko star, po postajah)."""
|
||
return qnet_match.db_stats()
|
||
|
||
|
||
@app.get("/api/qnet/match")
|
||
async def qnet_match_filename(filename: str, user: str = Depends(check_auth)):
|
||
"""Test endpoint — vrne match result za poljuben filename."""
|
||
if not filename:
|
||
raise HTTPException(400, "filename query param required")
|
||
return qnet_match.match_filename(filename)
|
||
|
||
|
||
class QnetBatchMatchRequest(BaseModel):
|
||
filenames: list[str]
|
||
min_confidence: float = 0.85
|
||
|
||
|
||
@app.post("/api/qnet/match-batch")
|
||
async def qnet_match_batch(payload: QnetBatchMatchRequest, user: str = Depends(check_auth)):
|
||
"""Batch match — kliče client ob izbiri datotek za live preview v queue."""
|
||
results = {}
|
||
for fn in payload.filenames:
|
||
if not fn:
|
||
continue
|
||
r = qnet_match.match_filename(fn)
|
||
# Vrni samo zadetke nad minimum confidence; sicer null
|
||
if r["matched"] and r["confidence"] >= payload.min_confidence:
|
||
results[fn] = r
|
||
else:
|
||
results[fn] = None
|
||
return {"results": results}
|
||
|
||
|
||
@app.post("/api/qnet/sync")
|
||
async def qnet_sync(background: BackgroundTasks, user: str = Depends(check_auth)):
|
||
"""Sproži sync (fetch Songs.txt iz vseh playerjev). Async background task."""
|
||
sync_script = SCRIPTS_DIR / "sync_qnet.py"
|
||
if not sync_script.exists():
|
||
raise HTTPException(500, f"sync_qnet.py ne obstaja v {SCRIPTS_DIR}")
|
||
|
||
def run_sync():
|
||
try:
|
||
import subprocess
|
||
env = os.environ.copy()
|
||
env["QNET_DB_PATH"] = str(QNET_DIR / "songs.json")
|
||
env["QNET_LOOKUP_PATH"] = str(QNET_DIR / "songs_lookup.json")
|
||
proc = subprocess.run(
|
||
["python3", str(sync_script)],
|
||
env=env,
|
||
capture_output=True,
|
||
text=True,
|
||
timeout=300,
|
||
)
|
||
print(f"[qnet sync] exit={proc.returncode}", flush=True)
|
||
if proc.stdout:
|
||
print(f"[qnet sync] stdout:\n{proc.stdout}", flush=True)
|
||
if proc.stderr:
|
||
print(f"[qnet sync] stderr:\n{proc.stderr}", flush=True)
|
||
except Exception as e:
|
||
print(f"[qnet sync] error: {e}", flush=True)
|
||
|
||
background.add_task(run_sync)
|
||
return {"started": True, "lookup_path": str(QNET_DIR / "songs_lookup.json")}
|
||
|
||
|
||
class RecutRequest(BaseModel):
|
||
start: float
|
||
end: float
|
||
custom_segments: Optional[list] = None # [{start, end, text}] za override napisov
|
||
no_subs: Optional[bool] = None
|
||
auto_upload: bool = True # po končanem recut avto-naloži v Nextcloud (default: da, ker user je že pregledal)
|
||
|
||
|
||
# ─── Nextcloud upload ─────────────────────────────────────────────
|
||
NEXTCLOUD_URL = os.environ.get("NEXTCLOUD_URL", "").rstrip("/")
|
||
NEXTCLOUD_USER = os.environ.get("NEXTCLOUD_USER", "")
|
||
NEXTCLOUD_PASS = os.environ.get("NEXTCLOUD_PASS", "")
|
||
NEXTCLOUD_REELS_PATH = os.environ.get("NEXTCLOUD_REELS_PATH", "folxspeed/REELS")
|
||
|
||
# Mapping: Qnet baza station naziv → Nextcloud folder naziv.
|
||
# Qnet Songs.txt ima krajsa imena ("FOLX SLO", "ONE", "ZWEI"), Nextcloud
|
||
# pa daljse ("FOLX SLOVENIJA", "ONE DE", "ZWEI MUSIC"). Pri uploadu mapiramo.
|
||
STATION_TO_NEXTCLOUD_FOLDER = {
|
||
"FOLX SLO": "FOLX SLOVENIJA",
|
||
"FOLX SLOVENIJA": "FOLX SLOVENIJA",
|
||
"FOLX DE": "FOLX DE",
|
||
"ONE": "ONE DE",
|
||
"ONE DE": "ONE DE",
|
||
"ZWEI": "ZWEI MUSIC",
|
||
"ZWEI MUSIC": "ZWEI MUSIC",
|
||
"ADRIA": "ADRIA",
|
||
}
|
||
|
||
|
||
def _nextcloud_folder_for_station(tv_station: str) -> str:
|
||
"""Vrne pravi Nextcloud folder za dano tv_station (z mapping fallback)."""
|
||
if not tv_station:
|
||
return "FOLX SLOVENIJA"
|
||
return STATION_TO_NEXTCLOUD_FOLDER.get(tv_station.strip(), tv_station.strip())
|
||
|
||
|
||
def _nextcloud_configured():
|
||
return bool(NEXTCLOUD_URL and NEXTCLOUD_USER and NEXTCLOUD_PASS)
|
||
|
||
|
||
def _nextcloud_upload(local_path: str, remote_filename: str, target_subdir: str = None):
|
||
"""Naloži datoteko na Nextcloud preko WebDAV (stdlib urllib).
|
||
|
||
Vrne (success: bool, url: str | error_msg: str).
|
||
target_subdir = opcijsko podmapo (default: NEXTCLOUD_REELS_PATH)
|
||
"""
|
||
if not _nextcloud_configured():
|
||
return False, "Nextcloud ni konfiguriran (manjka NEXTCLOUD_URL/USER/PASS env)"
|
||
|
||
if not Path(local_path).exists():
|
||
return False, f"Datoteka ne obstaja: {local_path}"
|
||
|
||
import urllib.request, urllib.error, base64
|
||
from urllib.parse import quote
|
||
|
||
base_path = (target_subdir or NEXTCLOUD_REELS_PATH).strip("/")
|
||
safe_dir = "/".join(quote(p, safe="") for p in base_path.split("/"))
|
||
safe_file = quote(remote_filename, safe="")
|
||
url = f"{NEXTCLOUD_URL}/remote.php/dav/files/{NEXTCLOUD_USER}/{safe_dir}/{safe_file}"
|
||
|
||
auth = base64.b64encode(f"{NEXTCLOUD_USER}:{NEXTCLOUD_PASS}".encode()).decode()
|
||
|
||
try:
|
||
with open(local_path, "rb") as f:
|
||
data = f.read()
|
||
req = urllib.request.Request(
|
||
url,
|
||
data=data,
|
||
headers={
|
||
"Authorization": f"Basic {auth}",
|
||
"Content-Type": "video/mp4",
|
||
},
|
||
method="PUT",
|
||
)
|
||
with urllib.request.urlopen(req, timeout=120) as resp:
|
||
if resp.status in (200, 201, 204):
|
||
return True, url
|
||
return False, f"HTTP {resp.status}"
|
||
except urllib.error.HTTPError as e:
|
||
return False, f"HTTP {e.code}: {e.read().decode()[:200]}"
|
||
except Exception as e:
|
||
return False, f"Upload error: {e}"
|
||
|
||
|
||
@app.post("/api/jobs/{job_id}/upload-nextcloud")
|
||
async def upload_nextcloud(job_id: str, user: str = Depends(check_auth)):
|
||
"""Naloži dokončan reel na Nextcloud /folxspeed/REELS/{TV STATION}/."""
|
||
if not _nextcloud_configured():
|
||
raise HTTPException(500, "Nextcloud ni konfiguriran (manjka env vars)")
|
||
|
||
job = load_job(job_id)
|
||
if not job:
|
||
raise HTTPException(404, "Job ne obstaja")
|
||
|
||
if job.get("status") != "done":
|
||
raise HTTPException(400, f"Job ni done (status={job.get('status')})")
|
||
|
||
output_path = job.get("output_path")
|
||
if not output_path or not Path(output_path).exists():
|
||
raise HTTPException(404, "Output mp4 ne obstaja")
|
||
|
||
# Označim "uploading"
|
||
update_job(job_id, nextcloud_status="uploading", nextcloud_error=None)
|
||
|
||
# Lepo ime datoteke
|
||
download_name = build_download_filename(job)
|
||
|
||
# TV postaja določa target mapo (mapping Qnet -> Nextcloud folder)
|
||
tv_station = job.get("tv_station", "FOLX SLOVENIJA")
|
||
nc_folder = _nextcloud_folder_for_station(tv_station)
|
||
target_subdir = f"folxspeed/REELS/{nc_folder}"
|
||
|
||
print(f"☁️ Uploading {output_path} → Nextcloud /{target_subdir}/{download_name}", flush=True)
|
||
success, result = _nextcloud_upload(output_path, download_name, target_subdir=target_subdir)
|
||
|
||
if success:
|
||
update_job(
|
||
job_id,
|
||
nextcloud_status="uploaded",
|
||
nextcloud_url=result,
|
||
nextcloud_error=None,
|
||
hidden_after_upload=True, # skrij iz default UI prikaza (toggle za pokaz)
|
||
)
|
||
print(f"☁️ Upload OK: /{target_subdir}/{download_name}", flush=True)
|
||
# Zabeleži v dedup
|
||
try:
|
||
orig_filename = job.get("filename") or download_name
|
||
file_mb = job.get("output_size_mb") or job.get("size_mb")
|
||
dedup_record(orig_filename, tv_station, job_id, nextcloud_url=result, file_size_mb=file_mb)
|
||
except Exception as e:
|
||
print(f"⚠️ Dedup record failed: {e}", flush=True)
|
||
return {"ok": True, "url": result, "filename": download_name, "tv_station": tv_station}
|
||
else:
|
||
update_job(job_id, nextcloud_status="error", nextcloud_error=result)
|
||
raise HTTPException(500, f"Upload failed: {result}")
|
||
|
||
|
||
@app.post("/api/jobs/{job_id}/recut")
|
||
async def recut_job(job_id: str, payload: RecutRequest, user: str = Depends(check_auth)):
|
||
"""Re-rendar reel z user-defined timestampi (in opcijsko popravljenimi napisi).
|
||
|
||
Veliko hitrejše od full pipeline-a:
|
||
- Brez Soniox transkripta (re-uporabi shranjenega)
|
||
- Brez Claude analize (uporabnik je odločil)
|
||
- Samo: clip → reframe → subtitle → output
|
||
"""
|
||
job = load_job(job_id)
|
||
if not job:
|
||
raise HTTPException(404, "Ne obstaja")
|
||
|
||
src = job.get("input_path")
|
||
if not src:
|
||
raise HTTPException(400, "Original video manjka")
|
||
_ensure_local(src, "upload")
|
||
if not Path(src).exists():
|
||
raise HTTPException(400, "Original video manjka")
|
||
|
||
if payload.end <= payload.start:
|
||
raise HTTPException(400, "End mora biti večji od start")
|
||
if payload.end - payload.start < 5:
|
||
raise HTTPException(400, "Trajanje vsaj 5s")
|
||
if payload.end - payload.start > 60:
|
||
raise HTTPException(400, "Trajanje največ 60s")
|
||
|
||
duration = payload.end - payload.start
|
||
no_subs = payload.no_subs if payload.no_subs is not None else job.get("no_subs", False)
|
||
|
||
# Naloži obstoječi analysis
|
||
analysis_path = OUTPUT_DIR / f"{job_id}.analysis.json"
|
||
_ensure_local(analysis_path, "output")
|
||
if not analysis_path.exists():
|
||
raise HTTPException(500, "Analysis manjka — re-uplad pesmi")
|
||
|
||
analysis = json.loads(analysis_path.read_text())
|
||
|
||
# Posodobi clip range
|
||
analysis["clip_range"] = {
|
||
"start": payload.start,
|
||
"end": payload.end,
|
||
"duration": duration,
|
||
"reason": f"USER EDIT: ročno popravljen clip {payload.start:.1f}-{payload.end:.1f}s",
|
||
"source": "user_edit",
|
||
}
|
||
|
||
# Če uporabnik popravil napise, override segmenti
|
||
if payload.custom_segments:
|
||
# Ohrani originalni transcript ampak shrani custom segments za SRT
|
||
analysis["custom_subtitle_segments"] = payload.custom_segments
|
||
|
||
analysis_path.write_text(json.dumps(analysis, indent=2, ensure_ascii=False))
|
||
|
||
# Re-queue job v processing (worker ga bo obdelal)
|
||
# Reset upload flags da se reel pojavi v UI med renderiranjem,
|
||
# po končanem renderu pa avto-upload spet (in spet izgine).
|
||
update_job(
|
||
job_id,
|
||
status="queued",
|
||
no_subs=no_subs,
|
||
custom_clip=True, # flag da preskoči Soniox + Claude
|
||
auto_upload_to_nextcloud=payload.auto_upload, # avto-upload po končanem recut
|
||
hidden_after_upload=False, # vidno med renderiranjem
|
||
nextcloud_status="recutting", # signal: ima staro Nextcloud verzijo, čaka novo
|
||
current_step="V vrsti za recut",
|
||
error=None,
|
||
chorus_error=None,
|
||
)
|
||
|
||
# Briši stari output
|
||
out_mp4 = OUTPUT_DIR / f"{job_id}.mp4"
|
||
if out_mp4.exists():
|
||
out_mp4.unlink()
|
||
for ext in ("srt", "ass"):
|
||
p = OUTPUT_DIR / f"{job_id}.subtitles.{ext}"
|
||
if p.exists():
|
||
p.unlink()
|
||
|
||
return {
|
||
"status": "queued",
|
||
"job_id": job_id,
|
||
"start": payload.start,
|
||
"end": payload.end,
|
||
"duration": duration,
|
||
}
|
||
|
||
|
||
# ────────────────────────────────────────────────────────────────
|
||
# Nextcloud upload (folxspeed/REELS/)
|
||
# ────────────────────────────────────────────────────────────────
|
||
|
||
def _safe_filename_for_nextcloud(name: str) -> str:
|
||
"""Sanitize filename za Nextcloud — odstrani problematične znake."""
|
||
import re
|
||
# Zamenjaj problematične znake z '_'
|
||
name = re.sub(r'[\\/:*?"<>|]', '_', name)
|
||
# Strip control chars
|
||
name = ''.join(c for c in name if c.isprintable())
|
||
return name.strip()[:200] or "reel.mp4"
|