Update app.py

app.py

@@ -1,4 +1,5 @@
 import streamlit as st
+from streamlit_chat import message
 from langchain.document_loaders.csv_loader import CSVLoader
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain.embeddings import HuggingFaceEmbeddings
@@ -8,6 +9,9 @@ from langchain.memory import ConversationBufferMemory
 from langchain.chains import ConversationalRetrievalChain
 import sys
 
+st.title("Chat with csv using Open Source Inference point")
+
+
 DB_FAISS_PATH = "vectorstore/db_faiss"
 loader = CSVLoader(file_path="data/2019.csv", encoding="utf-8", csv_args={'delimiter': ','})
 data = loader.load()
@@ -40,6 +44,14 @@ pipe = pipeline("text-generation",model="mistralai/Mistral-7B-v0.1",model_type="
 
 qa = ConversationalRetrievalChain.from_llm(llm, retriever=docsearch.as_retriever())
 
+# Insert a chat message container.
+>>> with st.chat_message("user"):
+>>>    st.write("Hello 👋")
+>>>    st.line_chart(np.random.randn(30, 3))
+
+# Display a chat input widget.
+>>> st.chat_input("Say something")
+
 while True:
     chat_history = []
     #query = "What is the value of  GDP per capita of Finland provided in the data?"