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19 lines
605 B
Python
19 lines
605 B
Python
from __future__ import annotations
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from typing import List
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from functools import lru_cache
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from .config import get_settings
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@lru_cache
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def _load_model():
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from sentence_transformers import SentenceTransformer
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settings = get_settings()
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model = SentenceTransformer(settings.MODEL_NAME, device="cpu")
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return model
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def embed_texts(texts: List[str]) -> list[list[float]]:
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model = _load_model()
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texts = [t if isinstance(t, str) else str(t) for t in texts]
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vecs = model.encode(texts, normalize_embeddings=True, convert_to_numpy=False)
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return [list(map(float, v)) for v in vecs]
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