fix: Restore all files lost during destructive rebase

A previous `git pull --rebase origin main` dropped 177 local commits,
losing 3400+ files across admin-v2, backend, studio-v2, website,
klausur-service, and many other services. The partial restore attempt
(660295e2) only recovered some files.

This commit restores all missing files from pre-rebase ref 98933f5e
while preserving post-rebase additions (night-scheduler, night-mode UI,
NightModeWidget dashboard integration).

Restored features include:
- AI Module Sidebar (FAB), OCR Labeling, OCR Compare
- GPU Dashboard, RAG Pipeline, Magic Help
- Klausur-Korrektur (8 files), Abitur-Archiv (5+ files)
- Companion, Zeugnisse-Crawler, Screen Flow
- Full backend, studio-v2, website, klausur-service
- All compliance SDKs, agent-core, voice-service
- CI/CD configs, documentation, scripts

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backend/transcription_worker/worker.py

@@ -0,0 +1,129 @@
+"""
+BreakPilot Transcription Worker - Main Entry Point
+
+Runs as an RQ worker, processing transcription jobs from the queue.
+"""
+
+import os
+import sys
+import signal
+import structlog
+from redis import Redis
+from rq import Worker, Queue, Connection
+
+# Configure logging
+structlog.configure(
+    processors=[
+        structlog.stdlib.filter_by_level,
+        structlog.stdlib.add_logger_name,
+        structlog.stdlib.add_log_level,
+        structlog.stdlib.PositionalArgumentsFormatter(),
+        structlog.processors.TimeStamper(fmt="iso"),
+        structlog.processors.StackInfoRenderer(),
+        structlog.processors.format_exc_info,
+        structlog.processors.UnicodeDecoder(),
+        structlog.processors.JSONRenderer()
+    ],
+    wrapper_class=structlog.stdlib.BoundLogger,
+    context_class=dict,
+    logger_factory=structlog.stdlib.LoggerFactory(),
+    cache_logger_on_first_use=True,
+)
+
+log = structlog.get_logger(__name__)
+
+# Configuration
+REDIS_URL = os.getenv("REDIS_URL", "redis://localhost:6379/1")
+QUEUE_NAME = os.getenv("QUEUE_NAME", "transcription")
+WORKER_NAME = os.getenv("WORKER_NAME", f"transcription-worker-{os.getpid()}")
+
+
+def setup_signal_handlers(worker: Worker):
+    """Setup graceful shutdown handlers."""
+
+    def shutdown_handler(signum, frame):
+        log.info("shutdown_signal_received", signal=signum)
+        worker.request_stop(signum, frame)
+
+    signal.signal(signal.SIGINT, shutdown_handler)
+    signal.signal(signal.SIGTERM, shutdown_handler)
+
+
+def preload_models():
+    """Preload ML models to reduce first-job latency."""
+    log.info("preloading_models")
+
+    try:
+        from .transcriber import WhisperTranscriber
+        from .diarizer import SpeakerDiarizer
+
+        # Initialize transcriber (downloads model if needed)
+        whisper_model = os.getenv("WHISPER_MODEL", "large-v3")
+        device = os.getenv("WHISPER_DEVICE", "cpu")
+        compute_type = os.getenv("WHISPER_COMPUTE_TYPE", "int8")
+
+        transcriber = WhisperTranscriber(
+            model_name=whisper_model,
+            device=device,
+            compute_type=compute_type
+        )
+        log.info("whisper_model_loaded", model=whisper_model, device=device)
+
+        # Initialize diarizer (downloads model if needed)
+        pyannote_token = os.getenv("PYANNOTE_AUTH_TOKEN")
+        if pyannote_token:
+            diarizer = SpeakerDiarizer(auth_token=pyannote_token)
+            log.info("pyannote_model_loaded")
+        else:
+            log.warning("pyannote_token_missing", message="Speaker diarization disabled")
+
+    except Exception as e:
+        log.error("model_preload_failed", error=str(e))
+        # Don't fail startup, models will be loaded on first job
+
+
+def main():
+    """Main entry point for the worker."""
+    log.info(
+        "worker_starting",
+        redis_url=REDIS_URL,
+        queue=QUEUE_NAME,
+        worker_name=WORKER_NAME
+    )
+
+    # Connect to Redis
+    redis_conn = Redis.from_url(REDIS_URL)
+
+    # Test connection
+    try:
+        redis_conn.ping()
+        log.info("redis_connected")
+    except Exception as e:
+        log.error("redis_connection_failed", error=str(e))
+        sys.exit(1)
+
+    # Preload models
+    preload_models()
+
+    # Create queue
+    queue = Queue(QUEUE_NAME, connection=redis_conn)
+
+    # Create worker
+    worker = Worker(
+        queues=[queue],
+        connection=redis_conn,
+        name=WORKER_NAME
+    )
+
+    # Setup signal handlers
+    setup_signal_handlers(worker)
+
+    log.info("worker_ready", queues=[QUEUE_NAME])
+
+    # Start processing
+    with Connection(redis_conn):
+        worker.work(with_scheduler=True)
+
+
+if __name__ == "__main__":
+    main()