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email_app / app.py

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Update app.py

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

	#Function to get the response back
	def getLLMResponse(form_input,email_sender,email_recipient,email_style):
	#llm = OpenAI(temperature=.9, model="text-davinci-003")

	# Wrapper for Llama-2-7B-Chat, Running Llama 2 on CPU

	#Quantization is reducing model precision by converting weights from 16-bit floats to 8-bit integers,
	#enabling efficient deployment on resource-limited devices, reducing model size, and maintaining performance.

	#C Transformers offers support for various open-source models,
	#among them popular ones like Llama, GPT4All-J, MPT, and Falcon.


	#C Transformers is the Python library that provides bindings for transformer models implemented in C/C++ using the GGML library

	llm = CTransformers(model='BashitAli/llama-2-7b-chat.ggmlv3.q5_K_M', #https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/blob/main/llama-2-7b-chat.ggmlv3.q8_0.bin
	model_type='llama',
	config={'max_new_tokens': 256,
	'temperature': 0.01})


	#Template for building the PROMPT
	template = """
	Write a email with {style} style and includes topic :{email_topic}.\n\nSender: {sender}\nRecipient: {recipient}
	\n\nEmail Text:

	"""

	#Creating the final PROMPT
	prompt = PromptTemplate(
	input_variables=["style","email_topic","sender","recipient"],
	template=template,)


	#Generating the response using LLM
	response=llm(prompt.format(email_topic=form_input,sender=email_sender,recipient=email_recipient,style=email_style))
	print(response)

	return response


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

	form_input = st.text_area('Enter the email topic', height=275)

	#Creating columns for the UI - To receive inputs from user
	col1, col2, col3 = st.columns([10, 10, 5])
	with col1:
	email_sender = st.text_input('Sender Name')
	with col2:
	email_recipient = st.text_input('Recipient Name')
	with col3:
	email_style = st.selectbox('Writing Style',
	('Formal', 'Appreciating', 'Not Satisfied', 'Neutral'),
	index=0)


	submit = st.button("Generate")

	#When 'Generate' button is clicked, execute the below code
	if submit:
	st.write(getLLMResponse(form_input,email_sender,email_recipient,email_style))