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# Q&A Chatbot | |
from langchain_openai import OpenAI | |
from langchain_google_genai import GoogleGenerativeAI | |
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 = GoogleGenerativeAI(model="models/text-bison-001", google_api_key=os.environ["GOOGLE_API_KEY"]) | |
#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) | |