modify getting AI model for cache

src/embedding.py

@@ -1,3 +1,4 @@
+import streamlit as st
 import numpy as np
 from sentence_transformers import SentenceTransformer
 
@@ -5,7 +6,11 @@ MODEL_NAME = "cl-nagoya/ruri-large"
 PREFIX_QUERY = "クエリ: "  # "query: "
 PASSAGE_QUERY = "文章: "  # "passage: "
 
-model = SentenceTransformer(MODEL_NAME)
+
+@st.cache_resource
+def get_sentence_model():
+    model = SentenceTransformer(MODEL_NAME)
+    return model
 
 
 def get_embeddings(texts: list[str], query=False, passage=False) -> np.ndarray:
@@ -14,6 +19,7 @@ def get_embeddings(texts: list[str], query=False, passage=False) -> np.ndarray:
     if passage:
         texts = [PASSAGE_QUERY + text for text in texts]
     # texts = [text[i : i + CHUNK_SIZE] for i in range(0, len(text), CHUNK_SIZE)]
+    model = get_sentence_model()
     embeddings = model.encode(texts)
     # print(embeddings.shape)
     # print(type(embeddings))