RAG/VektorDataBase/embedder.py

# embedder.py

from sentence_transformers import SentenceTransformer

# multilingual-e5-large modelini yükle
model = SentenceTransformer("intfloat/multilingual-e5-large")

def get_embedding(text: str) -> list[float]:
    try:
        formatted = f"passage: {text.strip()}"
        return model.encode(formatted, convert_to_numpy=True).tolist()
    except Exception as e:
        print(f"Embed hatası: {e}")
        return None