Update app.py

app.py

@@ -21,27 +21,20 @@ def reset_chat():
     st.session_state.messages = []
     st.session_state.context = None
 
-DB_PATH = './chroma_db'
+DB_PATH = './chroma_db_3'
 vectorstore = Chroma(persist_directory=DB_PATH, embedding_function=UpstageEmbeddings(model="solar-embedding-1-large"))
-
 chat = ChatUpstage(upstage_api_key = 'up_0NlJbP7KsNtBpQm2U0S7uCY3RMnFP')
 
 from langchain.retrievers.multi_query import MultiQueryRetriever
 retriever = MultiQueryRetriever.from_llm(
-    retriever=vectorstore.as_retriever(k=5), llm=chat)
+    retriever=vectorstore.as_retriever(), llm=chat)
 
-# 1) 챗봇에 '기억'을 입히기 위한 첫번째 단계
 
-# 이전 메시지들과 최신 사용자 질문을 분석해, 문맥에 대한 정보가 없이 혼자서만 봤을 때 이해할 수 있도록 질문을 다시 구성함.
-# 즉 새로 들어온 그 질문 자체에만 집중할 수 있도록 다시 재편성 (llm 예전 대화를 기억해서 대화를 재구성)
 from langchain.chains import create_history_aware_retriever
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
 
 contextualize_q_system_prompt = "When there are older conversations and more recent user questions, these questions may be related to previous conversations. In this case, change the question to a question that can be understood independently without needing to know the content of the conversation. You don't have to answer the question, just reformulate it if necessary or leave it as is."
 
-# MessagePlaceHolder: 'chat_history' 입력 키를 사용하여 이전 메세지 기록들을 프롬프트에 포함시킴. 
-# 즉, 프롬프트, 메세지 기록(문맥 정보), 사용자의 질문으로 프롬프트가 구성됨.
-
 contextualize_q_prompt = ChatPromptTemplate.from_messages(
     [
         ('system', contextualize_q_system_prompt),
@@ -50,17 +43,15 @@ contextualize_q_prompt = ChatPromptTemplate.from_messages(
     ]
 )
 
-# 이를 토대로 메세지 기록을 기억하는 retriever를 생성. 
 history_aware_retriever = create_history_aware_retriever(
     chat, retriever, contextualize_q_prompt
 )
 
-# 2) 체인을 사용하여 문서를 불러올 수 있는 retriever 체인 생성
 from langchain.chains import create_retrieval_chain
 from langchain.chains.combine_documents import create_stuff_documents_chain
 
 qa_system_prompt = """
-You are an intelligent assistant helping the members of the Korean National Assembly with questions related to law and policy. As you will respond to the Korean National Assembly, you must answer politely. Read the given questions carefully and give the answer in Korean ONLY using the following pieces of the context. WRITE YOUR ANSWER ONLY BASED ON THE CONTEXT.
+You are an intelligent assistant helping the members of the Korean National Assembly with questions related to law and policy. You must answer politely. Read the given questions carefully and give the answer in Korean ONLY using the following pieces of the context. AGAIN, WRITE YOUR ANSWER ONLY BASED ON THE CONTEXT FROM THE DATABASE AND DON'T SEARCH ON THE INTERNET.
 
 DO NOT TRY TO MAKE UP AN ANSWER:
  - If the answer to the question cannot be determined from the context alone, say "I cannot determine the answer to that.".
@@ -72,19 +63,17 @@ qa_prompt = ChatPromptTemplate.from_messages(
     [
         ('system', qa_system_prompt),
         MessagesPlaceholder('chat_history'),
-        ('human','{input}'+' 답변은 구체적으로 시간에 흐름에 따라 작성해줘. 그리고 답변할 때 metadata에 있는 source도 함께 제공해줘.'),
+        ('human','{input}'+' 답변은 구체적으로 최신 정보부터 시간의 흐름에 따라 작성해줘. 그리고 답변할 때 metadata에 있는 source를 함께 제공해줘.'),
     ]
 )
 
 question_answer_chain = create_stuff_documents_chain(chat, qa_prompt)
 
-# 결과값은 input, chat_history, context, answer 포함함.
 rag_chain = create_retrieval_chain(history_aware_retriever, question_answer_chain)
 
 
-
 # 웹사이트 제목
-st.title("국회 회의록 기반 챗봇 서비스 🚀")
+st.title("국회 회의록 기반 챗봇 서비스 :orange[NaraRAG] 📜⚖️")
 
 if 'messages' not in st.session_state:
         st.session_state['messages'] = [{'role': 'assistant',