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import streamlit as st
from streamlit_js_eval import streamlit_js_eval
from azure.storage.blob import BlobServiceClient
import json
import os
import uuid
connection_string = os.getenv("CONNECTION")
blob_service_client = BlobServiceClient.from_connection_string(connection_string)
def upload_blob(pdf_name, json_data, pdf_data):
try:
container_name = "jobdescriptions"
json_blob_name = f"{pdf_name}_jsondata.json"
pdf_blob_name = f"{pdf_name}.pdf"
container_client = blob_service_client.get_container_client(container_name)
json_blob_client = container_client.get_blob_client(json_blob_name)
json_blob_client.upload_blob(json_data.encode('utf-8'), overwrite=True)
pdf_blob_client = container_client.get_blob_client(pdf_blob_name)
pdf_blob_client.upload_blob(pdf_data, overwrite=True)
link = "https://tensora.ai/workgenius/cv-evaluation2/?job="+pdf_name
st.write('Data and PDF have been successfully uploaded. The link to the chatbot for the potential candidates is the following: '+link)
return True
except Exception as e:
print(f"Fehler beim Hochladen der Daten: {str(e)}")
return False
def main():
st.markdown(
"""
<style>
[data-testid=column]{
text-align: center;
display: flex;
align-items: center;
justify-content: center;
}
</style>
""",
unsafe_allow_html=True,
)
col1, col2 = st.columns([2, 1])
col1.title("Job description upload")
col2.image("https://www.workgenius.com/wp-content/uploads/2023/03/WorkGenius_navy-1.svg")
st.write("Please upload the job description as a PDF and enter the job title for the position. To receive the evaluation of the potential candidates, please enter your email address.")
upload_success = True
with st.form("job_inputs",clear_on_submit=True):
uploaded_file = st.file_uploader("Upload a PDF file:", type=["pdf"])
job_title = st.text_input("Enter the job title:")
email = st.text_input("Enter the email:")
submitted = st.form_submit_button("Submit")
if submitted:
if len(job_title) > 0 and len(email) > 0 and uploaded_file:
data = {
"title": job_title,
"email": email
}
json_data = json.dumps(data, ensure_ascii=False)
# Eine zufällige UUID generieren
random_uuid = uuid.uuid4()
# Die UUID als String darstellen
uuid_string = str(random_uuid)
pdf_name = uuid_string
pdf_data = uploaded_file.read()
upload_success = upload_blob(pdf_name, json_data, pdf_data)
else:
st.write("Please fill out both fields and upload a PDF file.")
if not upload_success:
st.error('An error has occurred. Please contact the administrator. Sorry for the inconvenience.', icon="🚨")
else:
col_empty, col_btn = st.columns([5, 1])
if col_btn.button("Clear" ,key="clear_btn",use_container_width=True):
streamlit_js_eval(js_expressions="parent.window.location.reload()")
if __name__ == "__main__":
main() |