app.py import streamlit as st from langchain.prompts import PromptTemplate from langchain.llms import CTransformers ## Function To get response from LLAma 2 model def getLLamaresponse(input_text,no_words,blog_style): ### LLama2 model llm=CTransformers(model='models/llama-2-7b-chat.ggmlv3.q8_0.bin', model_type='llama', config={'max_new_tokens':256, 'temperature':0.01}) ## Prompt Template template=""" Write a blog for {blog_style} job profile for a topic {input_text} within {no_words} words. """ prompt=PromptTemplate(input_variables=["blog_style","input_text",'no_words'], template=template) ## Generate the ressponse from the LLama 2 model 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 Blog Topic") ## creating to more columns for additonal 2 fields 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") ## Final response if submit: st.write(getLLamaresponse(input_text,no_words,blog_style)) requirements.txt sentence-transformers uvicorn ctransformers langchain python-box streamlit