from langchain.llms import OpenAI
import os
import streamlit as st
from langchain.chat_models import ChatOpenAI
from langchain.prompts.chat import ChatPromptTemplate
from langchain.schema import BaseOutputParser


chat_llm = ChatOpenAI(temperature=0.5, model='gpt-3.5-turbo')

class CommaseperatedOutput(BaseOutputParser):
    def parse(self, text:str):
        return text
    

# function to call openai api and get response
def get_response(question):
    template = "You are a naughty assistant who is great at flirting. You have to make a cheesy pickup line by using words given by user."
    human_template = "{text}"
    chatprompt = ChatPromptTemplate.from_messages([
                ('system', template),
                ('human', human_template)])

    chain = chatprompt|chat_llm|CommaseperatedOutput()

    try:
        response = chain.invoke({"text":question})
    except:
        response = "I am running out of money right now. Come back after a decade. I am hoping to be a rich by then."
    
    return response
# create streamlit app

st.set_page_config(page_title="Langchain Application")

st.header("Your Flirting Guardian")

input = st.text_input("You give me words and I will give you a pickup line: ", key="input")
response = get_response(input)


submit = st.button("Get a pickup line")
if submit:
    st.subheader("Here is your pickup line")
    st.write(response)