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# Q&A Chatbot
from langchain_openai import OpenAI
from dotenv import load_dotenv
load_dotenv() # take environment variables from .env.
import streamlit as st
import os
from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain
from langchain.chains import SequentialChain
## Function to load OpenAI model and get respones
def get_openai_response(country_name):
llm=OpenAI(openai_api_key=os.environ["OPEN_API_KEY"],temperature=0.5)
capital_template=PromptTemplate(input_variables=['country'],
template="Please tell me the capital of the {country}")
capital_chain=LLMChain(llm=llm,prompt=capital_template,output_key="capital")
famous_template=PromptTemplate(input_variables=['capital'],
template="Suggest me some amazing places to visit in {capital}")
famous_chain=LLMChain(llm=llm,prompt=famous_template,output_key="places")
eats_template=PromptTemplate(input_variables=['capital'],
template="Suggest the top 5 famous dishes to eat in {capital}")
eats_chain=LLMChain(llm=llm,prompt=eats_template,output_key="dishes")
chain=SequentialChain(chains=[capital_chain,famous_chain,eats_chain],
input_variables=['country'],
output_variables=['capital',"places","dishes"])
response=chain.invoke({'country':country_name})
return response
##initialize our streamlit app
st.set_page_config(page_title="Q&A Chatbot")
st.header("January Capital Guide")
input=st.text_input("Enter Country Name: ",key="input")
response=get_openai_response(input)
submit=st.button("Answer")
## If ask button is clicked
if submit:
st.subheader("The Answer is")
st.write(response)
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