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/test_v2_with_text.py

@@ -0,0 +1,133 @@
+#!/opt/homebrew/bin/python3.11
+"""
+Vector Search Test with nomic-embed-text:v1.5 using prefixes - with text content
+"""
+
+import time
+import requests
+import psycopg2
+
+
+VIDEO_UUID = "39567a0eb16f39fd"
+
+POSTGRES_CONFIG = {
+    "host": "localhost",
+    "port": 5432,
+    "user": "accusys",
+    "password": "Test3200",
+    "database": "momentry",
+}
+
+MODEL = "nomic-embed-text:v1.5"
+QDRANT_COLLECTION = "chunks_v2"
+
+
+def get_embedding(text, prefix=""):
+    prompt = f"{prefix}{text}"
+    resp = requests.post(
+        "http://localhost:11434/api/embeddings", json={"model": MODEL, "prompt": prompt}
+    )
+    return resp.json()["embedding"]
+
+
+def get_text_from_chunk_id(chunk_id):
+    """Get text from PostgreSQL using chunk_id"""
+    conn = psycopg2.connect(**POSTGRES_CONFIG)
+    cur = conn.cursor()
+    cur.execute("SELECT content->>'text' FROM chunks WHERE chunk_id = %s", (chunk_id,))
+    result = cur.fetchone()
+    cur.close()
+    conn.close()
+    return result[0] if result else ""
+
+
+def test_queries(queries, use_prefix=True):
+    """Test queries against Qdrant"""
+    prefix = "search_query: " if use_prefix else ""
+
+    for query in queries:
+        embedding = get_embedding(query, prefix)
+
+        start = time.time()
+        resp = requests.post(
+            f"http://localhost:6333/collections/{QDRANT_COLLECTION}/points/search",
+            headers={"api-key": "Test3200Test3200Test3200"},
+            json={"vector": embedding, "limit": 3},
+        )
+        elapsed = (time.time() - start) * 1000
+
+        results = resp.json().get("result", [])
+
+        print(f"\nQuery: '{query}' ({elapsed:.1f}ms)")
+        print("-" * 60)
+        for i, r in enumerate(results):
+            score = r.get("score", 0)
+            # Try to get chunk_id from payload
+            payload = r.get("payload", {})
+            chunk_id = payload.get("chunk_id", "")
+            if not chunk_id:
+                # Try to get text from Qdrant payload
+                text = payload.get("text", "")[:50]
+            else:
+                # Get text from PostgreSQL
+                text = get_text_from_chunk_id(chunk_id)[:50]
+            print(f"  {i + 1}. [{score:.3f}] {text}...")
+
+
+# English queries
+ENGLISH_QUERIES = [
+    "a person talking",
+    "someone speaking on camera",
+    "outdoor scene",
+    "indoor setting",
+    "walking or moving",
+    "dialogue or conversation",
+    "looking at something",
+    "happy or joyful",
+    "serious or dramatic",
+    "comedy or funny",
+    "wearing a tie",
+    "holding an object",
+    "sitting on a chair",
+    "city or urban",
+    "building or room",
+    "open space",
+]
+
+# Chinese queries
+CHINESE_QUERIES = [
+    "有人在說話",
+    "戶外場景",
+    "室內場景",
+    "走路或移動",
+    "對話或交談",
+    "看著某樣東西",
+    "快樂或開心",
+    "嚴肅或戲劇性",
+    "喜劇或有趣",
+    "戴著領帶",
+    "拿著東西",
+    "坐在椅子上",
+    "城市或都市",
+    "建築物或房間",
+    "開放空間",
+]
+
+
+if __name__ == "__main__":
+    print("=" * 70)
+    print(f"Testing with {QDRANT_COLLECTION}")
+    print(f"Model: {MODEL}")
+    print("Prefix for chunks: search_document:")
+    print("Prefix for queries: search_query:")
+    print("=" * 70)
+
+    print("\n" + "=" * 70)
+    print("ENGLISH QUERIES")
+    print("=" * 70)
+    test_queries(ENGLISH_QUERIES)
+
+    print("\n" + "=" * 70)
+    print("CHINESE QUERIES")
+    print("=" * 70)
+    test_queries(CHINESE_QUERIES)