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vector-search-demo/oravector-demo/backend/embedder.py
T
dierk 66f7db40b0 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>
2026-05-19 11:33:16 +02:00

18 lines
443 B
Python

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()