feat: Initial v0.9 release with API Key authentication

## v0.9.20260325_144654

### Features
- API Key Authentication System
- Job Worker System
- V2 Backup Versioning

### Bug Fixes
- get_processor_results_by_job column mapping

Co-authored-by: OpenCode

scripts/asrx_processor.py

@@ -0,0 +1,110 @@
+#!/opt/homebrew/bin/python3.11
+"""
+ASRX Processor - Speaker Diarization
+Uses whisperx for speaker diarization (local model)
+"""
+
+import sys
+import json
+import argparse
+import os
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+from redis_publisher import RedisPublisher
+
+
+def process_asrx(video_path: str, output_path: str, uuid: str = ""):
+    """Process video for speaker diarization using whisperx"""
+
+    publisher = RedisPublisher(uuid) if uuid else None
+    if publisher:
+        publisher.info("asrx", "ASRX_START")
+
+    try:
+        import whisperx
+    except ImportError:
+        if publisher:
+            publisher.error("asrx", "whisperx not installed")
+        result = {"language": None, "segments": []}
+        if publisher:
+            publisher.complete("asrx", "0 segments")
+        with open(output_path, "w") as f:
+            json.dump(result, f, indent=2)
+        return result
+
+    if publisher:
+        publisher.info("asrx", "ASRX_LOADING_MODEL")
+
+    try:
+        # Load model - using faster-whisper for better performance
+        # You can also use: "large-v3", "medium", "small", "base", "tiny"
+        model = whisperx.load_model("base", device="cpu", compute_type="int8")
+
+        if publisher:
+            publisher.info("asrx", "ASRX_TRANSCRIBING")
+
+        # Transcribe audio
+        result = model.transcribe(video_path, language="en")
+
+        # Align timestamps
+        model_a, metadata = whisperx.load_align_model(language_code=result["language"])
+        result = whisperx.align(
+            result["segments"], model_a, metadata, video_path, device="cpu"
+        )
+
+        # Diarization (speaker segmentation)
+        try:
+            import whisperx
+
+            diarize_model = whisperx.DiarizationPipeline(use_auth_token=None)
+            diarize_segments = diarize_model(video_path)
+
+            # Assign speaker labels
+            result = whisperx.assign_word_speakers(diarize_segments, result)
+        except Exception as e:
+            if publisher:
+                publisher.info("asrx", f"Diarization skipped: {e}")
+
+        # Build output
+        segments = []
+        for seg in result.get("segments", []):
+            text = seg.get("text", "").strip()
+            if text:
+                segments.append(
+                    {
+                        "start": seg.get("start", 0.0),
+                        "end": seg.get("end", 0.0),
+                        "text": text,
+                        "speaker_id": seg.get("speaker", None),
+                    }
+                )
+
+        output_result = {"language": result.get("language"), "segments": segments}
+
+        if publisher:
+            publisher.complete("asrx", f"{len(segments)} segments")
+
+        with open(output_path, "w") as f:
+            json.dump(output_result, f, indent=2)
+
+        return output_result
+
+    except Exception as e:
+        if publisher:
+            publisher.error("asrx", f"Error: {e}")
+        result = {"language": None, "segments": []}
+        if publisher:
+            publisher.complete("asrx", "0 segments")
+        with open(output_path, "w") as f:
+            json.dump(result, f, indent=2)
+        return result
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="ASRX Speaker Diarization")
+    parser.add_argument("video_path", help="Path to video file")
+    parser.add_argument("output_path", help="Output JSON path")
+    parser.add_argument("--uuid", "-u", help="UUID for Redis progress", default="")
+    args = parser.parse_args()
+
+    process_asrx(args.video_path, args.output_path, args.uuid)