app.py

'''
    This is the main file of the app. This file contains the code for the streamlit app.
'''

import time
import datetime
import base64
import streamlit as st
from streamlit_chat import message

from job_description_generator import predict_job_description, get_job_description_conversation
from job_description_fixer import fix_job_description, get_job_description_fixer_conversation
from interview_questions_generator import (predict_interview_question,
                                           get_interview_questions_conversation)
from cover_letter_generator import get_cover_letter
from top_accomplishment_generator import get_accomplishments
from constants import PROMPT_VERSION

conversation = get_job_description_conversation()
if 'generator_conversation' not in st.session_state:
    with open("./conversation.txt", "a", encoding='utf-8') as f:
        #add a horizontal line
        f.write("--------------------------------------------------\n")
        #add the date
        f.write(f"Conversation on {datetime.datetime.now()}, prompt_{PROMPT_VERSION}: \n\n")
    st.session_state['generator_conversation'] = conversation

fixer_conversation = get_job_description_fixer_conversation()
if 'fixer_conversation' not in st.session_state:
    st.session_state['fixer_conversation'] = fixer_conversation

st.session_state['response'] = {'history': [], 'prediction': ''}

interview_questions_conversation = get_interview_questions_conversation()
if 'interview_questions_conversation' not in st.session_state:
    st.session_state['interview_questions_conversation'] = interview_questions_conversation

def get_downloadable_conversation(input_text, response):
    '''
        Downloads the conversation to a text file.
    '''
    conversation_to_save = f"Conversation with JobGPT on {datetime.datetime.now()}, prompt_{PROMPT_VERSION}: \n\n"
    for historical_message in response['history']:
        conversation_to_save = conversation_to_save + historical_message + "\n"
    conversation_to_save = conversation_to_save + f"Human: {input_text} \n"
    conversation_to_save = conversation_to_save + f"JobGPT: {response['prediction']} \n"
    conversation_to_save = conversation_to_save + "----------------------------------------\n"
    return conversation_to_save

def message_writer(input_text, response):
    '''
        Writes the messages to the chat window.
    '''
    messages = []
    current_message = ""
    current_is_user = True

    for historical_message in response['history']:
        if "human" in historical_message.lower():
            messages.append([current_message, current_is_user])
            current_message = historical_message.replace("Human:", "")
            current_is_user = True
        elif "JobGPT" in historical_message:
            messages.append([current_message, current_is_user])
            current_message = historical_message.replace("JobGPT:", "")
            current_is_user = False
        else:
            current_message = current_message + "\n" + historical_message
    messages.append([current_message, current_is_user])
    for message_to_send, is_user in messages:
        if message_to_send.strip() != "":
            message(message_to_send, is_user=is_user)
    message(input_text, is_user=True)
    message(response['prediction'], is_user=False)
    return 0


def setup():
    """
    Streamlit related setup. This has to be run for each page.
    """
    hide_streamlit_style = """
    
    <style>
    #MainMenu {visibility: hidden;}
    footer {visibility: hidden;}
    </style>
    """
    st.markdown(hide_streamlit_style, unsafe_allow_html=True)

def main():
    '''
     Main function of the app.
    '''
    setup()

    #create a sidebar where you can select your page
    st.sidebar.title("JobGPT")
    st.sidebar.markdown("---")
    #selector
    page = st.sidebar.selectbox(
        "Select a page", ["Home",
                          "Job Description Generator",
                          "Job Description Fixer",
                          "Cover Letter Generator",
                          "Interview questions generator",
                          "Accomplishments Generator"])
    if page == "Home":
        st.title("JobGPT")
        st.write("Select a page in the sidebar to get started.")
        st.write("### Available options:")
        st.write("1. Job Description Generator")
        st.write("2. Job Description Fixer")
        st.write("3. Cover Letter Generator")
        st.write("4. Interview Questions Generator")
        st.write("5. Accomplishments Generator")
        st.markdown("---")

    elif page == "Job Description Generator":
        container_one = st.container()
        container_one.title("A Job Description Generating Chatbot")
        container_one.markdown(
            "JobGPT is a chatbot that generates job descriptions. \
                This is built just for demo purpose."
        )
        input_text = container_one.text_area(
            "Prompt",
            "Hi, can you please help me generate an unbiased job description?")
        button = container_one.button("Send")

        st.sidebar.markdown("---")
        st.sidebar.markdown("Click on `new chat` to start a new chat. \
                History will be cleared and you'll lose access to current chat."
                           )
        clear_session = st.sidebar.button("New Chat")

        if clear_session:
            with open("./conversation.txt", "a", encoding='utf-8') as f:
                #add a horizontal line
                f.write("--------------------------------------------------\n")
                #add the date
                f.write(f"Conversation on {datetime.datetime.now()}, prompt_{PROMPT_VERSION}: \n\n")
            st.session_state['generator_conversation'] = conversation
        container_one.markdown("---")

        initial_message = "Hello, how can I help you?"
        message(initial_message)
        #download_button = st.sidebar.button("Download Conversation")
        if button:
            response = predict_job_description(input_text,
                                               st.session_state['generator_conversation'])
            message_writer(input_text, response)
            st.session_state['response'] = response

            conversation_to_save = get_downloadable_conversation(
                input_text, st.session_state['response'])
            
            #write to conversation.txt
            with open("./conversation.txt", "a", encoding='utf-8') as f:
                f.write(f"HUMAN: {input_text}\n")
                f.write(f"BOT: {response['prediction']}\n")

            #download the conversation
            b64 = base64.b64encode(conversation_to_save.encode()).decode()
            href = f'<a href="data:file/txt;base64,{b64}" download="{datetime.datetime.now().strftime("%Y-%m-%d-%H-%M-%S")}-conversation.txt">Download conversation</a>'
            
            st.sidebar.markdown(href, unsafe_allow_html=True)
  
    elif page == "Job Description Fixer":
        container_two = st.container()
        container_two.title("A Job Description Fixing Chatbot")
        container_two.markdown(
            "JobGPT is a chatbot that fixes job descriptions. This is built just for demo purpose."
        )
        input_text = container_two.text_area(
            "Prompt",
            "Hi, can you please help me fix my job description? It's biased.")
        button = container_two.button("Send")

        st.sidebar.markdown("---")
        st.sidebar.markdown("Click on `new chat` to start a new chat. \
                History will be cleared and you'll lose access to current chat."
                           )
        clear_session = st.sidebar.button("New Chat")

        if clear_session:
            st.session_state['fixer_conversation'] = fixer_conversation
        container_two.markdown("---")

        initial_message = "Hello, how can I help you?"
        message(initial_message)

        if button:
            response = fix_job_description(
                input_text, st.session_state['fixer_conversation'])
            message_writer(input_text, response)
            st.session_state['response'] = response
            conversation_to_save = get_downloadable_conversation(
                input_text, st.session_state['response'])

            #download the conversation
            b64 = base64.b64encode(conversation_to_save.encode()).decode()
            href = f'<a href="data:file/txt;base64,{b64}" download="{datetime.datetime.now().strftime("%Y-%m-%d-%H-%M-%S")}-conversation.txt">Download conversation</a>'
            st.sidebar.markdown(href, unsafe_allow_html=True)

    elif page == "Cover Letter Generator":
        container_three = st.container()
        container_three.title("A Cover Letter Generating Chatbot")
        container_three.markdown( "JobGPT is a chatbot that generates cover letters. \
                                 This is built just for demo purpose.")
        container_three.markdown("---")
        uploaded_files = container_three.file_uploader("Upload your resume", type=["pdf", "txt", "docx"], accept_multiple_files=True)
        if uploaded_files is not None and uploaded_files != []:
            counter = 0
            for uploaded_file in uploaded_files:
                file_extension = uploaded_file.name.split(".")[-1]
                with open(f"./documents/resume_{counter}.{file_extension}", "wb") as file_io:
                    file_io.write(uploaded_file.getbuffer())
                counter += 1
            with st.spinner('Uploading...'):
                time.sleep(1)
            container_three.success('Uploaded!')
            container_three.markdown("---")
            form = container_three.form(key='my_form')
            title = form.text_input("Job Title (required)", placeholder="VP of Engineering")
            company = form.text_input("Company Name (required)", placeholder="Google")
            more_info = form.text_area("More Info",
                                       help="Add more info about you or the job in natural language",
                                       placeholder="I am a software engineer with 5 years of experience. The job focuses on building a new product in healthcare sector.")
            submit_button = form.form_submit_button(label='Submit')
            if submit_button:
                if title == "":
                    st.error("Please enter a job title")
                elif company == "":
                    st.error("Please enter a company name")
                else:
                    with st.spinner('Generating...'):
                        cover_letter = get_cover_letter(title, company, more_info, "./documents")
                        container_three.markdown("---")
                        container_three.markdown("### Cover Letter:")
                        container_three.write(cover_letter)
    elif page == "Accomplishments Generator":
        container_three = st.container()
        container_three.title("An Accomplishments Generating Chatbot")
        container_three.markdown( "JobGPT is a chatbot that generates Accomplishments from resume. \
                                 This is built just for demo purpose.")
        container_three.markdown("---")
        uploaded_file = container_three.file_uploader("Upload your resume", type=["pdf"])
        if uploaded_file is not None:
            with open("resume.pdf", "wb") as file_io:
                file_io.write(uploaded_file.getbuffer())

            with st.spinner('Uploading...'):
                time.sleep(1)
            container_three.success('Uploaded!')
            container_three.markdown("---")
            form = container_three.form(key='my_form')
            title = form.text_input("Job Title (required)", placeholder="VP of Engineering")
            company = form.text_input("Company Name (required)", placeholder="Google")
            job_description = form.text_area("Job Description",
                                       help="Paste the job description you are applying for",
                                       placeholder="We are looking for a software engineer with 5 years of experience. The job focuses on building a new product in healthcare sector")
            submit_button = form.form_submit_button(label='Submit')
            if submit_button:
                if title == "":
                    st.error("Please enter a job title")
                elif company == "":
                    st.error("Please enter a company name")
                elif job_description == "":
                    st.error("Please enter a job description")
                else:
                    with st.spinner('Generating...'):
                        accomplishments = get_accomplishments(title, company, job_description, "resume.pdf")
                        container_three.markdown("---")
                        container_three.markdown("### Top Accomplishments for the given job:")
                        container_three.write(accomplishments)
        
    elif page == "Interview questions generator":
        container_two = st.container()
        container_two.title("An Interview Questions Generating Chatbot")
        container_two.markdown(
            "JobGPT is a chatbot that generates interview questions.\
                This is built just for demo purpose."
        )
        input_text = container_two.text_area(
            "Prompt",
            "Hi, can you please help me generate interview questions?")
        button = container_two.button("Send")

        st.sidebar.markdown("---")
        st.sidebar.markdown("Click on `new chat` to start a new chat. \
                History will be cleared and you'll lose access to current chat."
                           )
        clear_session = st.sidebar.button("New Chat")

        if clear_session:
            st.session_state['interview_questions_conversation'] = interview_questions_conversation
        container_two.markdown("---")

        initial_message = "Hello, how can I help you?"
        message(initial_message)

        if button:
            response = predict_interview_question(
                input_text, st.session_state['interview_questions_conversation'])
            message_writer(input_text, response)
            st.session_state['response'] = response
    
            conversation_to_save = get_downloadable_conversation(
                input_text, st.session_state['response'])
            
            #download the conversation
            b64 = base64.b64encode(conversation_to_save.encode()).decode()
            href = f'<a href="data:file/txt;base64,{b64}" download="{datetime.datetime.now().strftime("%Y-%m-%d-%H-%M-%S")}-conversation.txt">Download conversation</a>'
            st.sidebar.markdown(href, unsafe_allow_html=True)

main()