main.py

import os
import streamlit as st
from langchain.llms import HuggingFaceHub
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate

from models import llms

class UserInterface():

    def __init__(self, ):
        st.warning("Warning: Some models may not work and some models may require GPU to run")
        st.text("An Open Source Chat Application")
        st.header("Open LLMs")

        self.API_KEY = st.sidebar.text_input(
            'API Key',
            type='password',
            help="Type in your HuggingFace API key to use this app"
        )

        models_name = (
            "HuggingFaceH4/zephyr-7b-beta",
            "Open-Orca/Mistral-7B-OpenOrca",
        )
        self.models = st.sidebar.selectbox(
            label="Choose your models",
            options=models_name,
            help="Choose your model",
        )

        self.temperature = st.sidebar.slider(
            label='Temperature',
            min_value=0.1,
            max_value=1.0,
            step=0.1,
            value=0.5,
            help="Set the temperature to get accurate or random result"
        )

        self.max_token_length = st.sidebar.slider(
            label="Token Length",
            min_value=32,
            max_value=2048,
            step=16,
            value=64,
            help="Set max tokens to generate maximum amount of text output"
        )


        self.model_kwargs = {
            "temperature": self.temperature,
            "max_length": self.max_token_length
        }

        os.environ['HUGGINGFACEHUB_API_TOKEN'] = self.API_KEY

    
    def form_data(self):

        try:
            if not self.API_KEY.startswith('hf_'):
                st.warning('Please enter your API key!', icon='⚠')
                text_input_visibility = True
            
            
            st.subheader("Context")
            context = st.chat_input(disabled=text_input_visibility)
            st.subheader("Question")
            question = st.chat_input(disabled=text_input_visibility)


            template = """
            Answer the question based on the context, if you don't know then output "Out of Context"
            Context: {context}
            Question: {question}

            Answer: 
            """
            prompt = PromptTemplate(
                template=template,
                input_variables=[
                    'question',
                    'context'
                ]
            )
            llm = HuggingFaceHub(
                repo_id = self.model_name,
                model_kwargs = self.model_kwargs
            )

            llm_chain = LLMChain(
                prompt=prompt,
                llm=llm,
            )

            result = llm_chain.run({
                "question": question,
                "context": context
            })

            st.markdown(result)
        except Exception as e:
            st.error(e, icon="🚨")

model = UserInterface()
model.form_data()