Update app.py

app.py

@@ -19,9 +19,11 @@ from langchain_core.runnables.history import RunnableWithMessageHistory
 from langchain_core.chat_history import BaseChatMessageHistory
 from langchain_community.chat_message_histories import ChatMessageHistory
 from multiprocessing import Process
+from zipfile import ZipFile
 
-if not os.path.isdir('database'):
-    os.system("unzip database.zip")
+with ZipFile("database.zip") as f:
+    f.extractall()
+    
 retriever = None
 conversational_rag_chain = None
 loader = DirectoryLoader('./database', glob="./*.txt", loader_cls=TextLoader)
@@ -31,13 +33,6 @@ documents = loader.load()
 text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
 splits = text_splitter.split_documents(documents)
 
-print()
-print("-------")
-print("TextSplitter, DirectoryLoader")
-print("-------")
-
-persist_directory = 'db'
-
 model_name = "BAAI/bge-small-en-v1.5"
 model_kwargs = {'device': 'cpu'}
 encode_kwargs = {'normalize_embeddings': True}
@@ -56,7 +51,7 @@ def format_docs(docs):
 retriever = vectorstore.as_retriever()
 
 prompt = hub.pull("rlm/rag-prompt")
-llm = HuggingFaceEndpoint(repo_id="mistralai/Mistral-7B-Instruct-v0.3")
+llm = HuggingFaceEndpoint(repo_id="google/gemma-2-2b-it")
 rag_chain = (
     {"context": retriever | format_docs, "question": RunnablePassthrough()}
     | prompt
@@ -65,9 +60,9 @@ rag_chain = (
 )
 
 ### Contextualize question ###
-contextualize_q_system_prompt = """Given a chat history and the latest user question \
-which might reference context in the chat history, formulate a standalone question \
-which can be understood without the chat history. Do NOT answer the question, \
+contextualize_q_system_prompt = """Given a chat history and the latest user question
+which might reference context in the chat history, formulate a standalone question
+which can be understood without the chat history. Do NOT answer the question,
 just reformulate it if needed and otherwise return it as is."""
 contextualize_q_prompt = ChatPromptTemplate.from_messages(
     [
@@ -82,12 +77,13 @@ history_aware_retriever = create_history_aware_retriever(
 
 
 ### Answer question ###
-qa_system_prompt = """You are an assistant for question-answering tasks. \
-Use the following pieces of retrieved context to answer the question. \
-If you don't know the answer, just say that you don't know. \
-Use three sentences maximum and keep the answer concise.\
+qa_system_prompt = """You are an assistant for question-answering tasks.
+Use the following pieces of retrieved context to answer the question.
+If you don't know the answer, just say that you don't know.
+Use three sentences maximum and keep the answer concise. Do not repeat 'Assistant: ' or 'AI: '.
 
-{context}"""
+{context}
+{}"""
 qa_prompt = ChatPromptTemplate.from_messages(
     [
         ("system", qa_system_prompt),