from langchain_openai import ChatOpenAI
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.output_parsers import StrOutputParser
from langchain_community.llms import Ollama
import os

import streamlit as st

from dotenv import load_dotenv
load_dotenv()

#os.environ["OPENAI_API_KEY"]=os.getenv("OPENAI_API_KEY", "not found")
#langmith Tracking
os.environ["LANGCHAIN_TRACING_V2"]="true"   
os.environ["LANGCHAIN_API_KEY"]=os.getenv("LANGCHAIN_API_KEY", "not found")

#Prompt Template

prompt = ChatPromptTemplate.from_messages(
    [
        ("system", "You are a world class helpful assistant.Please respond to the user."),
        ("user","Question:{question}")
    ]
)

#streamlit framework

st.title('LLAMA3 using Langchain :sunglasses:') 
st.subheader("Designed by :blue[Kartavya.] How can i assist you:question:")
input_text = st.text_input("")

#OLLAMA LLAma3

llm = Ollama(model="llama3")
output_parser = StrOutputParser()
chain = prompt|llm|output_parser

if st.button("Enter"):
    st.write(chain.invoke({"question":input_text}))