## Conversational AI Chatbot
from langchain_openai import OpenAI
from dotenv import load_dotenv
import streamlit as st
import os
#from langchain.schema import HumanMessage,SystemMessage,AIMessage
from langchain_openai import ChatOpenAI
from langchain.chains import ConversationChain
from langchain.chains.conversation.memory import ConversationEntityMemory
from langchain.chains.conversation.prompt import ENTITY_MEMORY_CONVERSATION_TEMPLATE

## Initialising Session State
# Set Streamlit page configuration
st.set_page_config(page_title='Conversational Chatbot', layout='wide')
st.header("Hey there! Ask me anything.")
# Initialize session states
if "generated" not in st.session_state:
    st.session_state["generated"] = [] # Output
if "past" not in st.session_state:
    st.session_state["past"] = [] #Previous states
if "input" not in st.session_state:
    st.session_state["input"] = "" 
if "stored_session" not in st.session_state:
    st.session_state["stored_session"] = []

#User input 
def get_text():
     ## Getting input from user
    input=st.text_input("Input:",key='input')
    #response = get_response(input)
    submit = st.button("Ask the question")
    return input

# Define function to start a new chat
def new_chat():
    """
    Clears session state and starts a new chat.
    """
    save = []
    for i in range(len(st.session_state['generated'])-1, -1, -1):
        save.append("User:" + st.session_state["past"][i])
        save.append("Bot:" + st.session_state["generated"][i])        
    st.session_state["stored_session"].append(save)
    st.session_state["generated"] = []
    st.session_state["past"] = []
    st.session_state["input"] = ""
    st.session_state.entity_memory.entity_store = {}
    st.session_state.entity_memory.buffer.clear()


chat = ChatOpenAI(openai_api_key=os.environ["OPENAI_API_KEY"],
                  temperature=0.5,model='gpt-3.5-turbo',verbose=False)

# Create a ConversationEntityMemory object if not already created
if 'entity_memory' not in st.session_state:
        st.session_state.entity_memory = ConversationEntityMemory(llm=chat)
        
# Create the ConversationChain object with the specified configuration
Conversation = ConversationChain(
        llm=chat, 
        prompt=ENTITY_MEMORY_CONVERSATION_TEMPLATE,
        memory=st.session_state.entity_memory
        )


# Get the user input
user_input = get_text()
if user_input:
    output = Conversation.run(input=user_input)  
    st.session_state.past.append(user_input)
    st.session_state.generated.append(output)

# Allow to download as well
download_str = []
with st.expander("Conversation", expanded=True):
    for i in range(len(st.session_state['generated'])-1, -1, -1):
        st.info(st.session_state["past"][i])
        st.success(st.session_state["generated"][i])
        download_str.append(st.session_state["past"][i])
        download_str.append(st.session_state["generated"][i])
    
    # Can throw error - requires fix
    download_str = '\n'.join(download_str)
    if download_str:
        st.download_button('Download',download_str)

# Display stored conversation sessions in the sidebar
for i, sublist in enumerate(st.session_state.stored_session):
        with st.sidebar.expander(label= f"Conversation-Session:{i}"):
            st.write(sublist)

# Allow the user to clear all stored conversation sessions
if st.session_state.stored_session:   
    if st.sidebar.checkbox("Clear-all"):
        del st.session_state.stored_session