update

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 from langchain_community.embeddings import HuggingFaceEmbeddings
 from langchain_community.vectorstores import FAISS
 from openai import OpenAI
+from translate import translate_ko_to_en
 
 YOUR_OPENAI_API_KEY = "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"
 # 임베딩 모델 로드
@@ -20,7 +21,14 @@ retriever = vectorstore.as_retriever(search_kwargs={"k": 3})
 
 
 def chatbot(input_question):
+    eng = translate_ko_to_en(input_question)
+    print(f"translated eng: {eng}")
     basic_docs = retriever.invoke(input_question)
+    eng_docs = retriever.invoke(eng)
+    basic_docs = list(set().union(eng_docs,basic_docs))
+    
+    print(f"basic docs: {basic_docs}")
+
     context = "\n".join([doc.page_content for doc in basic_docs])  
 
     client = OpenAI(

requirements.txt

@@ -4,3 +4,5 @@ openai==1.58.1
 gradio
 sentence-transformers
 faiss-cpu
+transformers
+sentencepiece