code update

app.py

@@ -2,12 +2,13 @@ import io
 import streamlit as st
 from PyPDF2 import PdfReader
 from langchain.text_splitter import CharacterTextSplitter
-from langchain.embeddings.huggingface import HuggingFaceEmbeddings
-from langchain.vectorstores import FAISS
 from langchain.chains.question_answering import load_qa_chain
-from langchain.llms import HuggingFacePipeline
+from langchain_community.embeddings import HuggingFaceEmbeddings
+from langchain_community.vectorstores import FAISS
+from langchain_community.llms import HuggingFacePipeline
+
 from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
-from peft import PeftModel, PeftConfig
+
 
 # Global variables
 knowledge_base = None
@@ -38,11 +39,9 @@ def create_knowledge_base(chunks):
 def load_model():
     model_name = "halyn/gemma2-2b-it-finetuned-paperqa"
     tokenizer = AutoTokenizer.from_pretrained(model_name)
-    config = PeftConfig.from_pretrained(model_name)
-    model = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path)
-    model = PeftModel.from_pretrained(model, model_name)
-
+    model = AutoModelForCausalLM.from_pretrained(model_name)
     return pipeline("text-generation", model=model, tokenizer=tokenizer, max_new_tokens=150, temperature=0.1)
+
 # QA 체인 설정
 def setup_qa_chain():
     global qa_chain
@@ -99,7 +98,6 @@ def main_page():
                 st.error(f"Failed to process the PDF: {str(e)}")
 
 
-
 # 채팅 페이지 UI
 def chat_page():
     st.title(f"Ask anything about {st.session_state.paper_name}")