ACRCloud auto-recognition: never block uploads, fall back to fingerprinting

Changes:

1. UI: removed blocking prompt() that asked for artist+title on filename
   that didn't match 'Artist - Title' pattern. Upload always proceeds.
   Instead shows yellow warning saying 'server will try to recognize'.

2. Backend: added scripts/acr_recognize.py — extracts 20s audio sample
   from video (at 15s and 60s offsets for robustness), computes ACRCloud
   fingerprint via native binary (3KB payload), sends to identify API.

3. Pipeline: process_job() now runs ACR recognition step before analysis
   IF parsed_artist or parsed_title is missing. Result is saved to job
   metadata and used for download filename + Scribe/Claude filename hint.

4. Credentials: ACR_HOST + ACR_ACCESS_KEY + ACR_SECRET_KEY env vars
   added to Coolify (using existing keys from openclaw fb-agent metka).

5. requirements.txt: added pyacrcloud==1.0.11 for native fingerprinting.

This unblocks future automation/cron upload pipelines — files don't need
to be perfectly named, ACRCloud will identify them automatically.

Fallback chain:
1. Filename parsing (Artist - Title.mp4)
2. ACRCloud audio fingerprint (works even for '12345.mp4', 'IMG_001.mp4')
3. If both fail: download filename uses 'reel_<id>.mp4' (still works)

app/main.py

@@ -338,6 +338,35 @@ def process_job(job_id):
         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) ──────────────────────────
         if job.get("auto_chorus"):
             update_job(job_id, current_step="Analiza pesmi (transkript + energija)")