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/sync_to_mongodb.py

@@ -0,0 +1,122 @@
+#!/opt/homebrew/bin/python3.11
+"""
+Sync chunks from PostgreSQL to MongoDB
+"""
+
+import psycopg2
+from pymongo import MongoClient
+
+
+VIDEO_UUID = "39567a0eb16f39fd"
+
+POSTGRES_CONFIG = {
+    "host": "localhost",
+    "port": 5432,
+    "user": "accusys",
+    "password": "Test3200",
+    "database": "momentry",
+}
+
+MONGO_URI = "mongodb://localhost:27017"
+MONGO_DB = "momentry"
+MONGO_COLLECTION = "chunks"
+
+
+def sync_to_mongodb():
+    """Sync chunks from PostgreSQL to MongoDB"""
+    # Connect to PostgreSQL
+    pg_conn = psycopg2.connect(**POSTGRES_CONFIG)
+    pg_cur = pg_conn.cursor()
+
+    # Get all chunks for the video
+    pg_cur.execute(
+        """
+        SELECT uuid, chunk_id, chunk_index, chunk_type, 
+               start_time, end_time, fps, start_frame, end_frame,
+               content, metadata, vector_id
+        FROM chunks 
+        WHERE uuid = %s AND chunk_type = 'sentence'
+        ORDER BY chunk_index
+    """,
+        (VIDEO_UUID,),
+    )
+
+    rows = pg_cur.fetchall()
+    print(f"Found {len(rows)} chunks in PostgreSQL")
+
+    # Connect to MongoDB
+    mongo_client = MongoClient(MONGO_URI)
+    mongo_db = mongo_client[MONGO_DB]
+    mongo_collection = mongo_db[MONGO_COLLECTION]
+
+    # Prepare documents
+    documents = []
+    for row in rows:
+        doc = {
+            "uuid": row[0],
+            "chunk_id": row[1],
+            "chunk_index": row[2],
+            "chunk_type": row[3],
+            "start_time": row[4],
+            "end_time": row[5],
+            "fps": row[6],
+            "start_frame": row[7],
+            "end_frame": row[8],
+            "content": row[9],
+            "metadata": row[10],
+            "vector_id": row[11],
+        }
+        documents.append(doc)
+
+    # Insert into MongoDB (upsert)
+    if documents:
+        # Delete existing chunks for this video
+        mongo_collection.delete_many({"uuid": VIDEO_UUID, "chunk_type": "sentence"})
+
+        # Insert new chunks
+        result = mongo_collection.insert_many(documents)
+        print(f"Inserted {len(result.inserted_ids)} chunks into MongoDB")
+
+    # Create text index for search
+    mongo_collection.create_index([("content", "text"), ("chunk_type", 1)])
+    print("Created text index")
+
+    pg_cur.close()
+    pg_conn.close()
+    mongo_client.close()
+
+    print("Done!")
+
+
+def test_mongodb_text_search():
+    """Test MongoDB text search"""
+    from pymongo import MongoClient
+    import time
+
+    mongo_client = MongoClient(MONGO_URI)
+    mongo_db = mongo_client[MONGO_DB]
+    mongo_collection = mongo_db[MONGO_COLLECTION]
+
+    test_queries = ["Paris", "Audrey Hepburn", "Cary Grant"]
+    results = {}
+
+    for query in test_queries:
+        start = time.time()
+        cursor = mongo_collection.find(
+            {"uuid": VIDEO_UUID, "chunk_type": "sentence", "$text": {"$search": query}}
+        ).limit(10)
+
+        rows = list(cursor)
+        elapsed = (time.time() - start) * 1000
+
+        results[query] = {"ms": round(elapsed, 2), "rows": len(rows)}
+        print(f"MongoDB text '{query}': {elapsed:.2f}ms, {len(rows)} rows")
+
+    mongo_client.close()
+    return results
+
+
+if __name__ == "__main__":
+    sync_to_mongodb()
+    print("\nTesting MongoDB text search:")
+    test_mongodb_text_search()