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  1. app.py +70 -0
  2. requirements.txt +7 -0
app.py ADDED
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+ import streamlit as st
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+ from langchain.prompts import PromptTemplate
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+ from langchain.llms import CTransformers
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+
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+ #Function to get the response back
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+ def getLLMResponse(form_input,email_sender,email_recipient,email_style):
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+ #llm = OpenAI(temperature=.9, model="text-davinci-003")
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+
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+ # Wrapper for Llama-2-7B-Chat, Running Llama 2 on CPU
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+
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+ #Quantization is reducing model precision by converting weights from 16-bit floats to 8-bit integers,
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+ #enabling efficient deployment on resource-limited devices, reducing model size, and maintaining performance.
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+
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+ #C Transformers offers support for various open-source models,
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+ #among them popular ones like Llama, GPT4All-J, MPT, and Falcon.
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+
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+
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+ #C Transformers is the Python library that provides bindings for transformer models implemented in C/C++ using the GGML library
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+
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+ llm = CTransformers(model='models/llama-2-7b-chat.ggmlv3.q8_0.bin', #https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/tree/main
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+ model_type='llama',
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+ config={'max_new_tokens': 256,
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+ 'temperature': 0.01})
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+
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+
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+ #Template for building the PROMPT
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+ template = """
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+ Write a email with {style} style and includes topic :{email_topic}.\n\nSender: {sender}\nRecipient: {recipient}
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+ \n\nEmail Text:
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+
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+ """
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+
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+ #Creating the final PROMPT
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+ prompt = PromptTemplate(
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+ input_variables=["style","email_topic","sender","recipient"],
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+ template=template,)
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+
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+
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+ #Generating the response using LLM
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+ response=llm(prompt.format(email_topic=form_input,sender=email_sender,recipient=email_recipient,style=email_style))
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+ print(response)
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+
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+ return response
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+
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+
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+ st.set_page_config(page_title="Generate Emails",
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+ page_icon='πŸ“§',
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+ layout='centered',
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+ initial_sidebar_state='collapsed')
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+ st.header("Generate Emails πŸ“§")
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+
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+ form_input = st.text_area('Enter the email topic', height=275)
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+
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+ #Creating columns for the UI - To receive inputs from user
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+ col1, col2, col3 = st.columns([10, 10, 5])
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+ with col1:
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+ email_sender = st.text_input('Sender Name')
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+ with col2:
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+ email_recipient = st.text_input('Recipient Name')
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+ with col3:
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+ email_style = st.selectbox('Writing Style',
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+ ('Formal', 'Appreciating', 'Not Satisfied', 'Neutral'),
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+ index=0)
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+
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+
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+ submit = st.button("Generate")
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+
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+ #When 'Generate' button is clicked, execute the below code
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+ if submit:
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+ st.write(getLLMResponse(form_input,email_sender,email_recipient,email_style))
requirements.txt ADDED
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+ sentence-transformers
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+ uvicorn
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+ ctransformers
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+ fastapi
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+ ipykernel
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+ langchain
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+ python-box