fix warning error

app.py

@@ -3,10 +3,9 @@ import streamlit as st
 from PyPDF2 import PdfReader
 from langchain.text_splitter import CharacterTextSplitter
 from langchain.chains.question_answering import load_qa_chain
-from langchain_community.embeddings import HuggingFaceEmbeddings
+from langchain_huggingface import HuggingFaceEmbeddings
 from langchain_community.vectorstores import FAISS
 from langchain_community.llms import HuggingFacePipeline
-
 from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 
 
@@ -32,13 +31,14 @@ def split_text(text):
 
 # FAISS 벡터 저장소 생성
 def create_knowledge_base(chunks):
-    embeddings = HuggingFaceEmbeddings()
+    model_name = "halyn/gemma2-2b-it-finetuned-paperqa"
+    embeddings = HuggingFaceEmbeddings(model_name=model_name)
     return FAISS.from_texts(chunks, embeddings)
 
 # Hugging Face 모델 로드
 def load_model():
     model_name = "halyn/gemma2-2b-it-finetuned-paperqa"
-    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    tokenizer = AutoTokenizer.from_pretrained(model_name, clean_up_tokenization_spaces=False)
     model = AutoModelForCausalLM.from_pretrained(model_name)
     return pipeline("text-generation", model=model, tokenizer=tokenizer, max_new_tokens=150, temperature=0.1)
 
@@ -49,7 +49,6 @@ def setup_qa_chain():
     llm = HuggingFacePipeline(pipeline=pipe)
     qa_chain = load_qa_chain(llm, chain_type="stuff")
     
-
 # 메인 페이지 UI
 def main_page():
     st.title("Welcome to GemmaPaperQA")

requirements.txt

@@ -11,3 +11,4 @@ requests==2.32.3
 huggingface-hub==0.25.1
 sentence-transformers==3.1.1
 peft==0.2.0
+langchain-huggingface