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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='TheBloke/OpenHermes-2.5-Mistral-7B-GGUF',
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)) |