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import streamlit as st | |
from dotenv import load_dotenv, find_dotenv | |
_ = load_dotenv(find_dotenv()) | |
from components.ui.sidebar import sidebar_section | |
from components.ui.personal_data import personal_data_section | |
from components.ui.education import education_section | |
from components.ui.experience import experience_section | |
from components.ui.skills import skills_section | |
# This job_title variable will show up in the page title and will be used by LLM to determine relevant skills: | |
job_title= "Data Scientist" | |
# App configuration | |
st.set_page_config(page_title=f"Applying to {job_title} Vacancy", layout="wide") | |
st.title(f"Applying to {job_title} Vacancy", anchor="center") | |
st.write("### *This is a demo for resume parsing with Large Language Models.*") | |
st.write("Upload your resume on the left sidebar to automatically parse your data.") | |
st.write("*Warning: the contents of the file you upload will be sent to Groq-API for inference*") | |
# Sidebar | |
sidebar_section(job_title= job_title) | |
# Personal Data Section | |
personal_data_section() | |
# Education Section | |
education_section() | |
# Experience Section | |
experience_section() | |
# Skills Section | |
skills_section() | |
st.write("* Clicking the submit button below will only show you the final data dictionary after parsing the resume and performing manual edits on it.*") | |
submit = st.button('Submit', key="sumbit") | |
if submit: | |
st.divider() | |
st.write("### Final Candidate Data:") | |
st.write(st.session_state.candidate_data) | |