app.py

import os
os.environ["GOOGLE_APPLICATION_CREDENTIALS"]="./gen-lang-client-0086983119-574504dba064.json"
from langchain.llms import GooglePalm
from langchain import PromptTemplate
from langchain import LLMChain
from dotenv import load_dotenv
load_dotenv()

import streamlit as st


## Function to load OpenAI model and get respones
def get_openai_response(question):
    llm = GooglePalm(google_api_key=os.environ["GOOGLE_API_KEY"], temperature=0.1)
    template ="""Your a Mashette Bot, act like a chatbot, user will ask you question give then Good Answers without Toxic answers. also if they greet you, greet them well.
    context:{question}
    answer:
    """

    prompt = PromptTemplate(template = template, input_variables= ["question"])
    story_llm = LLMChain(llm = llm, prompt = prompt, verbose = True)
    response = story_llm.predict(question = question)
    # print("Generated_text:",response)
    return response


# def get_openai_response(question):
#     llm = GooglePalm(google_api_key=os.environ["GOOGLE_API_KEY"], temperature=0.1)
#     response=llm(question)
#     return response

##initialize our streamlit app

st.set_page_config(page_title="Q&A Demo")

st.header("Mashette-Bot")

input=st.text_input("Input: ",key="input")
submit=st.button("Submit the question")
response=get_openai_response(input)

## If ask button is clicked

if submit:
    st.subheader("The Response is")
    st.write(response)