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# Application that will help the Resume Screener will llms to find the best fits for the job
import streamlit as st
import uuid
from utils import *
# Creating session variables
if "unique_id" not in st.session_state:
st.session_state["unique_id"] = ''
def main():
st.set_page_config(page_title="Resume Screening Assistance")
st.title('HR Resume Screening Assistance')
st.subheader('I can help you in resume screening process')
job_description = st.text_area("Enter your job description", key="1")
document_count = st.text_area("No.of 'Resumes' to return", key="2")
# Upload the Resumes (pdf files)
pdf = st.file_uploader("Upload resumes here, only PDF files allowed", type=["pdf"], accept_multiple_files=True)
submit = st.button("Help me with the analysis")
if submit:
with st.spinner('Wait for it...'):
# Creating a unique id, so that we can use the query
# and get only the user uploaded documents from PINECONE vector store
st.session_state["unique_id"] = uuid.uuid4().hex
# Create a documents list out of all the user uploaded pdf files
docs = create_docs(pdf, st.session_state["unique_id"])
# Display the count of the docs that were uploaded
st.write(len(docs))
# Create embeddings instance
embeddings = create_embeddings_load_data()
# Push data to PINECONE
st.write(push_to_pinecone(
'63987f25-a66d-448f-8a91-d64a9dd71d9a',
"test", embeddings, docs)
)
st.success('Hope I was able to save your time <3')
if __name__ == '__main__':
main()
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