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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_jobdescription,pdf_data_cv): | |
| try: | |
| container_name = "jobdescriptions" | |
| json_blob_name = f"{pdf_name}_jsondata.json" | |
| pdf_blob_name_jobdescription = f"{pdf_name}.pdf" | |
| pdf_blob_name_cv = f"{pdf_name}_resume.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_jobdescription) | |
| pdf_blob_client.upload_blob(pdf_data_jobdescription, overwrite=True) | |
| pdf_blob_client = container_client.get_blob_client(pdf_blob_name_cv) | |
| pdf_blob_client.upload_blob(pdf_data_cv, overwrite=True) | |
| link = "https://tensora.ai/workgenius/cv-evaluation2/?job="+pdf_name | |
| st.success('Data and PDF files have been successfully uploaded. The link to the chatbot for the potential candidate is the following: ') | |
| st.write(link) | |
| return True | |
| except Exception as e: | |
| print(f"Fehler beim Hochladen der Daten: {str(e)}") | |
| return False | |
| def test(text_val): | |
| print(text_val) | |
| 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 and resume as PDF and enter the job title for the position. To receive the evaluation of the potential candidate, please provide your email address.") | |
| upload_success = True | |
| with st.form("job_inputs",clear_on_submit=True): | |
| uploaded_file_jobdescription = st.file_uploader("Upload the job description:", type=["pdf"]) | |
| uploaded_file_cv = st.file_uploader("Upload the resume:", 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_jobdescription and uploaded_file_cv: | |
| 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_jobdescription = uploaded_file_jobdescription.read() | |
| pdf_data_cv = uploaded_file_cv.read() | |
| upload_success = upload_blob(pdf_name, json_data, pdf_data_jobdescription,pdf_data_cv) | |
| 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() |