import os
import gradio as gr
import pinecone
from gpt_index import GPTIndexMemory, GPTPineconeIndex
import streamlit as st

from streamlit_chat import message as st_message
from langchain.agents import Tool
from langchain.chains.conversation.memory import ConversationBufferMemory
from langchain import OpenAI
from langchain.agents import initialize_agent

OPENAI_API_KEY=os.environ.get("OPENAI_API_KEY")
PINECONE_API_KEY=os.environ.get("PINECONE_API_KEY")
PINECONE_ENV=os.environ.get("PINECONE_ENV")

pointing_pinecone_index=pinecone.Index("sethgodin")
main_index = GPTPineconeIndex([],pinecone_index=pointing_pinecone_index)
tools = [
    Tool(
        name = "GPT Index",
        func=lambda q: str(main_index.query(q)),
        description="useful for when you want to answer questions about the author. The input to this tool should be a complete english sentence.",
        return_direct=True
    ),
]

memory = GPTIndexMemory(index=main_index, memory_key="chat_history", query_kwargs={"response_mode": "compact"})
llm=OpenAI(temperature=0)
agent_chain = initialize_agent([], llm, agent="conversational-react-description", memory=memory)

if "history" not in st.session_state:
    st.session_state.history = []

def generate_answer():
    user_message=st.session_state.input_text
    message_bot = agent_chain.run(input=user_message)
    st.session_state.history.append({"message": user_message, "is_user": True})
    st.session_state.history.append({"message": message_bot, "is_user": False})
    
st.text_input("Response", key="input_text", on_change=generate_answer)

for chat in st.session_state.history:
    st_message(**chat)
st.text_input("Response", key="input_text", on_change=generate_answer)

for chat in st.session_state.history:
    st_message(**chat)