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app.py

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+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.chat_models import ChatOpenAI
+from langchain.chains import ConversationalRetrievalChain
+from langchain.document_loaders.csv_loader import CSVLoader
+from langchain.vectorstores import FAISS
+import tempfile 
+from streamlit_chat import message
+import streamlit as st
+
+import os 
+import sys
+import pandas as pd
+
+user_api_key = st.sidebar.text_input(
+    label="#### Your OpenAI API key 👇",
+    placeholder="Paste your openAI API key, sk-",
+    type="password")
+
+file_path='./personality_less.csv'
+
+
+loader = CSVLoader(file_path=file_path, encoding="utf-8", csv_args={
+                'delimiter': ','})
+
+data = loader.load()
+
+embeddings = OpenAIEmbeddings()
+vectorstore = FAISS.from_documents(data, embeddings)
+
+chain = ConversationalRetrievalChain.from_llm(
+llm = ChatOpenAI(temperature=0.0,model_name='gpt-3.5-turbo'),
+retriever=vectorstore.as_retriever())
+
+def conversational_chat(query):    
+    result = chain({"question": query, 
+    "chat_history": st.session_state['history']})
+    st.session_state['history'].append((query, result["answer"]))
+
+    return result["answer"]
+
+if 'history' not in st.session_state:
+    st.session_state['history'] = []
+
+    if 'generated' not in st.session_state:
+        st.session_state['generated'] = ["Hello ! Ask me anything about " + " 🤗"]
+
+    if 'past' not in st.session_state:
+        st.session_state['past'] = ["Hey ! 👋"]
+        
+    #container for the chat history
+    response_container = st.container()
+    #container for the user's text input
+    container = st.container()
+
+with container:
+    with st.form(key='my_form', clear_on_submit=True):
+        
+        user_input = st.text_input("Query:", placeholder="Talk about your csv data here (:", key='input')
+        submit_button = st.form_submit_button(label='Send')
+        
+    if submit_button and user_input:
+        output = conversational_chat(user_input)
+        
+        st.session_state['past'].append(user_input)
+        st.session_state['generated'].append(output)
+
+if st.session_state['generated']:
+        with response_container:
+            for i in range(len(st.session_state['generated'])):
+                message(st.session_state["past"][i], is_user=True, key=str(i) + '_user', avatar_style="big-smile")
+                message(st.session_state["generated"][i], key=str(i), avatar_style="thumbs")

requirements.txt

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+langchain 
+streamlit 
+openai 
+tiktoken 
+faiss-cpu 
+streamlit_chat