app.py

import streamlit as st
from langchain.prompts import PromptTemplate
from langchain.llms import CTransformers

def get_blog_response(blog_context,blog_length,style):
    llm = CTransformers(model='models/llama-2-7b-chat.ggmlv3.q8_0.bin',
                        model_type='llama',
                        config={'max_new_tokens':256,
                                'temperature':0.01})
    template = """write a blog for {style} job profile for a topic {text} within {n_words} words."""
    prompt = PromptTemplate(input_variables=['style','text','n_words'],template=template)
    response = llm(prompt.format(style=style,text=blog_context,n_words=blog_length))
    return response



st.set_page_config(page_title="Generate blogs",
                   page_icon = "X", 
                   layout='centered', 
                   initial_sidebar_state = 'collapsed')

st.header("Generate blogs")
input_text = st.text_input("Enter the blog topic")
col1,col2 = st.columns([5,5])

with col1:
    no_words = st.text_input('No of words')
with col2:
    blog_style = st.selectbox('writing the blog for',('Researchers','Data Scientist','Common People'),index=0)
submit = st.button("Generate")

if submit:
    st.write(get_blog_response(input_text,no_words,blog_style))