Update app.py

app.py

@@ -1,9 +1,10 @@
 from langchain_chroma import Chroma
 from langchain_huggingface import HuggingFaceEmbeddings
+from sentence_transformers import SentenceTransformer
+from sklearn.metrics.pairwise import cosine_similarity
 from openpyxl import load_workbook
 import pandas as pd
 import gradio as gr
-import math
 
 # Chroma DB 로드
 model_huggingface = HuggingFaceEmbeddings(model_name='BAAI/bge-m3')
@@ -43,6 +44,8 @@ def search_unit(unit_query):
 """
     return text
 
+downsample_model = SentenceTransformer('BAAI/bge-m3')
+
 def filter_semantically_similar_texts_by_embedding(df, embedding_field='embedding_input', similarity_threshold=0.8):
     texts = df[embedding_field].tolist()