Initial commit: Momentry Core v0.1

- Rust-based digital asset management system
- Video analysis: ASR, OCR, YOLO, Face, Pose
- RAG capabilities with Qdrant vector database
- Multi-database support: PostgreSQL, Redis, MongoDB
- Monitoring system with launchd plists
- n8n workflow automation integration

scripts/asr_processor.py

@@ -0,0 +1,53 @@
+#!/opt/homebrew/bin/python3.11
+import sys
+import json
+import tempfile
+import os
+from faster_whisper import WhisperModel
+
+
+def run_asr(video_path, output_path):
+    print(f"ASR_START", file=sys.stderr)
+    print(f"Loading Whisper model...", file=sys.stderr)
+
+    model = WhisperModel("tiny", device="cpu", compute_type="int8")
+
+    print(f"Transcribing: {video_path}", file=sys.stderr)
+    segments, info = model.transcribe(video_path, beam_size=5)
+
+    print(f"ASR_LANGUAGE:{info.language}", file=sys.stderr)
+    print(
+        f"Detected language: {info.language} (probability: {info.language_probability:.2f})",
+        file=sys.stderr,
+    )
+
+    results = []
+    total_segments = 0
+
+    for segment in segments:
+        results.append(
+            {"start": segment.start, "end": segment.end, "text": segment.text.strip()}
+        )
+        total_segments += 1
+        if total_segments % 100 == 0:
+            print(f"ASR_PROGRESS:{total_segments}", file=sys.stderr)
+
+    output = {
+        "language": info.language,
+        "language_probability": info.language_probability,
+        "segments": results,
+    }
+
+    with open(output_path, "w") as f:
+        json.dump(output, f, indent=2)
+
+    print(f"ASR_COMPLETE:{total_segments}", file=sys.stderr)
+    print(f"ASR complete. {len(results)} segments.", file=sys.stderr)
+
+
+if __name__ == "__main__":
+    if len(sys.argv) != 3:
+        print("Usage: asr_processor.py <video_path> <output_json_path>")
+        sys.exit(1)
+
+    run_asr(sys.argv[1], sys.argv[2])