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


def get_llm_response(input_text, no_words, blog_style):
    llm=CTransformers(model="llama-2-7b-chat.ggmlv3.q8_0.bin", model_type="llama",
                        config={"max_new_tokens": 256, "temperature": 0.5})
    template="""
        Write a blog for {blog_style} job profile for a topic {input_text}
        with max {no_words} words.
    """

    prompt=PromptTemplate(input_variables=["blog_style", "input_text", "no_words"],
                            template=template)

    response=llm(prompt.format(blog_style=blog_style, input_text=input_text, no_words=no_words))
    print(response)
    return response

st.set_page_config(page_title="Generate Blogs", page_icon="", layout="centered", initial_sidebar_state="collapsed")
st.header("Generate Blogs")

input_text=st.text_input("Enter the 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("Create")

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