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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)) |