to 22

backend/src/application/services/embedding_service.py

@@ -0,0 +1,37 @@
+"""
+Сервис для вычисления эмбеддингов текстов
+"""
+from functools import lru_cache
+from typing import Iterable
+import numpy as np
+from sentence_transformers import SentenceTransformer
+
+
+class EmbeddingService:
+
+    def __init__(self, model_name: str | None = None):
+        self.model_name = model_name or "intfloat/multilingual-e5-base"
+        self._model = None
+
+    @property
+    def model(self) -> SentenceTransformer:
+        if self._model is None:
+            self._model = SentenceTransformer(self.model_name)
+        return self._model
+
+    def embed_texts(self, texts: Iterable[str]) -> list[list[float]]:
+        embeddings = self.model.encode(
+            list(texts),
+            batch_size=8,
+            show_progress_bar=False,
+            normalize_embeddings=True,
+        )
+        return [np.array(v, dtype=np.float32).tolist() for v in embeddings]
+
+    def embed_query(self, text: str) -> list[float]:
+        return self.embed_texts([text])[0]
+
+    @lru_cache(maxsize=1)
+    def model_version(self) -> str:
+        return self.model_name
+