pip install 정리

main.py

@@ -4,7 +4,6 @@ import os
 import streamlit as st
 from dotenv import load_dotenv
 from kiwipiepy import Kiwi
-from langchain.chat_models import ChatOpenAI
 from langchain.retrievers import ContextualCompressionRetriever, EnsembleRetriever
 from langchain.retrievers.document_compressors import CrossEncoderReranker
 from langchain_community.cross_encoders import HuggingFaceCrossEncoder
@@ -21,6 +20,7 @@ from langchain_community.vectorstores import FAISS
 from langchain_core.messages import ChatMessage
 from langchain_experimental.text_splitter import SemanticChunker
 from langchain_huggingface import HuggingFaceEmbeddings
+from langchain_openai import ChatOpenAI
 
 csv.field_size_limit(10000000)
 load_dotenv()
@@ -87,7 +87,8 @@ def save_faiss_index(faiss_index, path="faiss_index"):
     print("-------------------------------------------")
     print("save_faiss_index")
     print("-------------------------------------------")
-    
+
+
 def load_faiss_index(path="faiss_index"):
     embeddings = embedding()
     print("-------------------------------------------")
@@ -174,11 +175,10 @@ if user_input := st.chat_input():
 
     with st.spinner("문서 검색 및 답변 생성 중..."):
         docs = reranker.invoke(user_input)
-        print(docs)
 
         context_texts = "\n\n".join(
             [
-                f"- {doc[0].metadata['source']} (유사도: {doc[1]}): {doc[0].page_content}" 
+                f"- {doc[0].metadata['source']} (유사도: {doc[1]}): {doc[0].page_content}"
                 for doc in docs
             ]
         )