Update app.py

app.py

@@ -1,7 +1,7 @@
 from langchain.document_loaders import HuggingFaceDatasetLoader
 from langchain_community.document_loaders.csv_loader import CSVLoader
 from langchain.text_splitter import RecursiveCharacterTextSplitter, CharacterTextSplitter
-from langchain.embeddings import HuggingFaceEmbeddings
+from langchain_community.embeddings import HuggingFaceEmbeddings
 from transformers import AutoTokenizer, AutoModelForQuestionAnswering
 from transformers import AutoTokenizer, pipeline
 from langchain import HuggingFacePipeline
@@ -19,9 +19,6 @@ import difflib
 modelPath = "MSEAJYTHTH/NFPC"
 # db_files = ["MSEAJYTHTH/NFPC/index.faiss", "MSEAJYTHTH/NFPC/index.pkl"]
 
-index = FAISS.read_index('MSEAJYTHTH/NFPC/index.faiss')
-
-
 model_kwargs = {'device':'cpu'}
 
 encode_kwargs = {'normalize_embeddings': False}
@@ -34,7 +31,7 @@ embeddings = HuggingFaceEmbeddings(
 
 
 # 두 파일을 업로드한 후에는 다음과 같이 코드를 수정할 수 있습니다.
-db = FAISS.load_local(index, embeddings, allow_dangerous_deserialization=True)
+db = FAISS.load_local("index.faiss", embeddings, allow_dangerous_deserialization=True)
 
 
 def find_best_page_content(question, keywords, db):