app.py

from langchain_groq import ChatGroq
from dotenv import load_dotenv
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.output_parsers import StrOutputParser
import os
import streamlit as st

load_dotenv()
st.title("Simple LangChain Chat-Bot")

prompt = ChatPromptTemplate.from_messages([
    ('system','You are a AI asisstant and your work is to answer the user question'),
    ('human',"question:{question}")
])


def simple_function(prompt,question,temperature,llm):
    llm = ChatGroq(model=llm,api_key=os.getenv("GROQ_API_KEY"))
    parser = StrOutputParser()
    chain = prompt|llm|parser
    response = chain.invoke({"question":question})  
    return response

question = st.text_area("Ask any question")

llm = st.sidebar.selectbox('Choose a Model',['llama-3.3-70b-versatile','llama-3.1-8b-instant','llama3-70b-8192'])

temperature = st.sidebar.slider("Set the temperature",min_value=0.0,max_value=1.0,value=0.7)

if st.button("Response the given question"):
    if st.spinner("Waiting..."):
        if question:
            st.write(simple_function(prompt,question,temperature,llm))