from langchain_core.prompts import ChatPromptTemplate
from langchain_openai import ChatOpenAI, OpenAIEmbeddings
from langchain_community.vectorstores import Chroma
from engine.tools import RAGTool, CareerRoadmapGenerator
from engine.langchain_agent import create_agent,run_agent
from bot.rag_indexing.indexing import retriever_from_docs
# Other imports if needed
import streamlit as st
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
import asyncio
from dotenv import load_dotenv
load_dotenv()
from bot.data_innput.input import user_input

st.set_page_config(page_title="Career Roadmap Generator")
st.header("Career Roadmap Generator")
st.write('Allows users to interact with the LLM')

if "memory" not in st.session_state:
    st.session_state["memory"] = [{"role": "system", "content": "You are a helpful assistant for generating career roadmaps."}]

if "agent" not in st.session_state:
    #model_name = "gpt-3.5-turbo"
    model_name = "gpt-4-turbo-preview"
    st.session_state['agent'] = create_agent(model_name)

# updading the chat page with messages
for message in st.session_state["memory"]:
    if message["role"] == "assistant":
        with st.chat_message(message["role"]):
            msg = message["content"]["output"]
            if "/bot/images/dall-e" in msg:
                address = msg.split("(")[1][:-1]
                print("address:",address)
                st.image(address)
            else:
                st.markdown(msg)
    elif message["role"] == "system":
        pass
    else:
        with st.chat_message(message["role"]):
            st.markdown(message["content"])


url = st.text_input("Please enter the job url:")
job_details = user_input(url)

# entering new message event handle
if prompt := st.chat_input("Your message ..."):
    st.session_state['memory'].append({"role":"user","content":prompt})
    with st.chat_message("user"):
        st.markdown(prompt)
    response = asyncio.run(run_agent(st.session_state["agent"],prompt))
    st.session_state['memory'].append({"role":"assistant","content":response})
    with st.chat_message("assistant"):
        if "/bot/images/dall-e" in response["output"]:
            address = response["output"].split("(")[1][:-1]
            st.image(address)
        else:
            st.markdown(response["output"])