Initial implementation of pgvector and Oracle 26ai vector search demo

Three FastAPI backends comparing PostgreSQL/pgvector and Oracle 26ai for
semantic image search using CLIP embeddings: Python-side embedding for both
databases, plus Oracle in-database embedding via VECTOR_EMBEDDING(CLIP_TXT).

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

pgvector-demo/backend/embedder.py

@@ -0,0 +1,17 @@
+from sentence_transformers import SentenceTransformer
+from PIL import Image
+
+_model = None
+
+def _get_model():
+    global _model
+    if _model is None:
+        _model = SentenceTransformer("clip-ViT-B-32")
+    return _model
+
+def embed_image(path: str) -> list[float]:
+    img = Image.open(path).convert("RGB")
+    return _get_model().encode(img).tolist()
+
+def embed_text(text: str) -> list[float]:
+    return _get_model().encode(text).tolist()