app.py

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

import os
from dotenv import load_dotenv
load_dotenv()


## Langsmith Tracking
os.environ['LANGCHAIN_API_KEY'] = os.getenv('LANGCHAIN_API_KEY')
os.environ['LANGCHAIN_TRACING_V2'] = 'true'
os.environ['LANGCHAIN_PROJECT'] = "Simple Q&A Chatbot With OpenAI"
os.environ['GROQ_API_KEY'] = os.getenv('GROQ_API_KEY')

## Prompt Template
propmt = ChatPromptTemplate(
    [
        ("system", "You are an helpful AI assistant. Please answer to the questions to the best of your ability."),
        ("human","question:{question}"),
    ]
)


def get_response(question, model):
    model = ChatGroq(model=model)
    output_parser = StrOutputParser()
    chain = propmt|model|output_parser
    response = chain.invoke({"question": question})
    return response


st.title("Simple Q&A Chatbot With GROQ")

model = st.selectbox("Select a model", ["llama-3.1-8b-instant","gemma2-9b-it","llama-3.1-70b-Versatile"])
st.write("This is a simple Q&A chatbot that uses GROQ to answer questions. Ask any question and the chatbot will try to answer it.")
input_question = st.text_input("Ask a question")

if input_question:
    response = get_response(input_question, model)
    st.write(response)
else:
    st.write("Please ask a question")