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| import streamlit as st | |
| import os | |
| from dotenv import load_dotenv | |
| from langchain_community.llms import OpenAI | |
| from langchain_google_genai import ChatGoogleGenerativeAI | |
| from fpdf import FPDF | |
| import fitz | |
| # Load environment variables | |
| load_dotenv() | |
| def generate_resume(details): | |
| prompt = f""" | |
| Create an ATS-optimized resume based on the following details: | |
| Name: {details['name']} | |
| Contact Information: {details['contact']} | |
| LinkedIn Profile: {details['linkedin']} | |
| Professional Summary: {details['summary']} | |
| Work Experience: {details['experience']} | |
| Education: {details['education']} | |
| Skills: {details['skills']} | |
| Certifications: {details['certifications']} | |
| Projects: {details['projects']} | |
| Provide the resume in a well-structured format. | |
| """ | |
| llm = OpenAI(temperature=0.7, openai_api_key=st.secrets["OPENAI_API_KEY"],max_tokens=1500) | |
| resume = llm(prompt) | |
| return resume | |
| def create_pdf(resume_text, filename): | |
| pdf = FPDF() | |
| pdf.add_page() | |
| pdf.set_auto_page_break(auto=True, margin=15) | |
| pdf.set_font("Arial", size=12) | |
| for line in resume_text.split('\n'): | |
| pdf.multi_cell(0, 10, line.encode('latin-1', 'replace').decode('latin-1')) | |
| pdf.output(filename) | |
| def extract_text_from_pdf(pdf_file): | |
| doc = fitz.open(stream=pdf_file.read(), filetype="pdf") | |
| text = "" | |
| for page in doc: | |
| text += page.get_text() | |
| return text | |
| def parse_extracted_text(text): | |
| details = { | |
| 'name': "", | |
| 'contact': "", | |
| 'linkedin': "", | |
| 'summary': "", | |
| 'experience': "", | |
| 'education': "", | |
| 'skills': "", | |
| 'certifications': "", | |
| 'projects': "" | |
| } | |
| # Here, you would implement parsing logic to extract details from the text. | |
| # For simplicity, this example assumes the text is well-structured and uses basic keyword extraction. | |
| # In a real-world scenario, you would use more sophisticated text parsing techniques. | |
| lines = text.split('\n') | |
| for i, line in enumerate(lines): | |
| if "Name:" in line: | |
| details['name'] = line.split("Name:")[1].strip() | |
| elif "Contact Information:" in line: | |
| details['contact'] = line.split("Contact Information:")[1].strip() | |
| elif "LinkedIn Profile:" in line: | |
| details['linkedin'] = line.split("LinkedIn Profile:")[1].strip() | |
| elif "Professional Summary:" in line: | |
| details['summary'] = line.split("Professional Summary:")[1].strip() | |
| elif "Work Experience:" in line: | |
| details['experience'] = " ".join(lines[i+1:i+5]).strip() | |
| elif "Education:" in line: | |
| details['education'] = " ".join(lines[i+1:i+3]).strip() | |
| elif "Skills:" in line: | |
| details['skills'] = line.split("Skills:")[1].strip() | |
| elif "Certifications:" in line: | |
| details['certifications'] = line.split("Certifications:")[1].strip() | |
| elif "Projects:" in line: | |
| details['projects'] = " ".join(lines[i+1:i+3]).strip() | |
| return details | |
| def app(): | |
| st.title("Resume Creation") | |
| uploaded_file = st.file_uploader("Upload a resume to pre-fill details", type=["pdf"]) | |
| if uploaded_file: | |
| if st.button("Submit"): | |
| extracted_text = extract_text_from_pdf(uploaded_file) | |
| details = parse_extracted_text(extracted_text) | |
| st.write("Extracted Text:", extracted_text) # Debug: Show the extracted text | |
| st.write("Parsed Details:", details) # Debug: Show the parsed details | |
| else: | |
| details = { | |
| 'name': "", | |
| 'contact': "", | |
| 'linkedin': "", | |
| 'summary': "", | |
| 'experience': "", | |
| 'education': "", | |
| 'skills': "", | |
| 'certifications': "", | |
| 'projects': "" | |
| } | |
| else: | |
| details = { | |
| 'name': "", | |
| 'contact': "", | |
| 'linkedin': "", | |
| 'summary': "", | |
| 'experience': "", | |
| 'education': "", | |
| 'skills': "", | |
| 'certifications': "", | |
| 'projects': "" | |
| } | |
| with st.form("resume_form"): | |
| st.header("Enter your details to generate an ATS-optimized resume") | |
| name = st.text_input("Name", value=details['name']) | |
| contact = st.text_area("Contact Information (phone, email, address)", value=details['contact']) | |
| linkedin = st.text_input("LinkedIn Profile URL", value=details['linkedin']) | |
| summary = st.text_area("Professional Summary", value=details['summary']) | |
| experience = st.text_area("Work Experience (provide details of each job including company name, job title, duration, and responsibilities)", value=details['experience']) | |
| education = st.text_area("Education (provide details of degrees, institutions, and graduation dates)", value=details['education']) | |
| skills = st.text_area("Skills (list your skills)", value=details['skills']) | |
| certifications = st.text_area("Certifications (list any relevant certifications)", value=details['certifications']) | |
| projects = st.text_area("Projects (provide details of your projects)", value=details['projects']) | |
| submitted = st.form_submit_button("Generate Resume") | |
| if submitted: | |
| if name and contact and linkedin and summary and experience and education and skills and certifications and projects: | |
| details = { | |
| 'name': name, | |
| 'contact': contact, | |
| 'linkedin': linkedin, | |
| 'summary': summary, | |
| 'experience': experience, | |
| 'education': education, | |
| 'skills': skills, | |
| 'certifications': certifications, | |
| 'projects': projects | |
| } | |
| resume = generate_resume(details) | |
| st.header("Generated Resume") | |
| st.text(resume) | |
| # Save resume as PDF and provide download link | |
| pdf_filename = "resume.pdf" | |
| create_pdf(resume, pdf_filename) | |
| with open(pdf_filename, "rb") as pdf_file: | |
| st.download_button( | |
| label="Download Resume as PDF", | |
| data=pdf_file, | |
| file_name=pdf_filename, | |
| mime="application/pdf" | |
| ) | |
| else: | |
| st.error("Please fill in all the fields to generate the resume.") | |
| # st.title("Resume Creation") | |
| # uploaded_file = st.file_uploader("Upload a resume to pre-fill details", type=["pdf"]) | |
| # if uploaded_file: | |
| # extracted_text = extract_text_from_pdf(uploaded_file) | |
| # details = parse_extracted_text(extracted_text) | |
| # else: | |
| # details = { | |
| # 'name': "", | |
| # 'contact': "", | |
| # 'linkedin': "", | |
| # 'summary': "", | |
| # 'experience': "", | |
| # 'education': "", | |
| # 'skills': "", | |
| # 'certifications': "", | |
| # 'projects': "" | |
| # } | |
| # with st.form("profile_form"): | |
| # st.header("Enter your details to generate an ATS-optimized resume") | |
| # name = st.text_input("Name") | |
| # contact = st.text_area("Contact Information (phone, email, address)") | |
| # linkedin = st.text_input("LinkedIn Profile URL") | |
| # summary = st.text_area("Professional Summary") | |
| # experience = st.text_area("Work Experience (provide details of each job including company name, job title, duration, and responsibilities)") | |
| # education = st.text_area("Education (provide details of degrees, institutions, and graduation dates)") | |
| # skills = st.text_area("Skills (list your skills)") | |
| # certifications = st.text_area("Certifications (list any relevant certifications)") | |
| # projects = st.text_area("Projects (provide details of your projects)") | |
| # submitted = st.form_submit_button("Generate Resume") | |
| # if submitted: | |
| # if name and contact and linkedin and summary and experience and education and skills and certifications and projects: | |
| # details = { | |
| # 'name': name, | |
| # 'contact': contact, | |
| # 'linkedin': linkedin, | |
| # 'summary': summary, | |
| # 'experience': experience, | |
| # 'education': education, | |
| # 'skills': skills, | |
| # 'certifications': certifications, | |
| # 'projects': projects | |
| # } | |
| # resume = generate_resume(details) | |
| # st.header("Generated Resume") | |
| # st.text(resume) | |
| # # Save resume as PDF and provide download link | |
| # pdf_filename = "resume.pdf" | |
| # create_pdf(resume, pdf_filename) | |
| # with open(pdf_filename, "rb") as pdf_file: | |
| # st.download_button( | |
| # label="Download Resume as PDF", | |
| # data=pdf_file, | |
| # file_name=pdf_filename, | |
| # mime="application/pdf" | |
| # ) | |
| # else: | |
| # st.error("Please fill in all the fields to generate the resume.") | |