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| import streamlit as st | |
| import google.generativeai as genai | |
| import os | |
| import PyPDF2 as pdf | |
| from dotenv import load_dotenv | |
| import json | |
| import re | |
| import time | |
| load_dotenv() | |
| genai.configure(api_key=os.getenv('GOOGLE_API_KEY')) | |
| def get_gemeni_response(input_text): | |
| model = genai.GenerativeModel('gemini-pro') | |
| response = model.generate_content(input_text) | |
| return response.text | |
| def input_pdf_text(upload_file): | |
| reader = pdf.PdfReader(upload_file) | |
| text = "" | |
| for page in range(len(reader.pages)): | |
| page_text = reader.pages[page].extract_text() | |
| text += str(page_text) | |
| return text | |
| def parse_response(response): | |
| """Validate and parse JSON response string.""" | |
| # Ensure response is JSON-like with regex before parsing | |
| if re.match(r'^\{.*\}$', response.strip(), re.DOTALL): | |
| try: | |
| return json.loads(response) | |
| except json.JSONDecodeError: | |
| return None | |
| return None | |
| # Enhanced Prompt Engineering | |
| input_prompt = """ | |
| Act as a highly skilled ATS (Applicant Tracking System) expert with strong knowledge of software engineering, data science, analytics, and big data engineering. | |
| Your goal is to analyze the resume content and compare it to the provided job description. Provide the following: | |
| 1. An overall Job Description (JD) Match percentage. | |
| 2. Top missing keywords or phrases relevant to the job description. | |
| 3. A summary of the profile, highlighting strengths and areas for improvement. | |
| Structure the output as a JSON with the following keys: | |
| - "JD Match": percentage match as a string with "%" sign. | |
| - "MissingKeywords": a list of missing but important keywords. | |
| - "ProfileSummary": a summary as a single string. | |
| Example format: | |
| {{"JD Match":"85%", "MissingKeywords":["data analysis", "team leadership"], "ProfileSummary":"Highly skilled engineer with 10 years of experience in data engineering."}} | |
| resume: {text} | |
| description: {jd} | |
| """ | |
| # Streamlit app setup | |
| st.title('Smart ATS') | |
| st.write( | |
| "Welcome! This tool helps you improve your resume's alignment with the job description, ensuring it is optimized for ATS.") | |
| # Job Description input | |
| jd = st.text_area("Paste the Job Description:", help="Paste the job description you want your resume to match.") | |
| # Resume upload | |
| uploaded_file = st.file_uploader("Upload your Resume (PDF format only):", type="pdf", | |
| help="Ensure your resume is in PDF format for analysis.") | |
| # Display submit button with progress | |
| submit = st.button("Analyze Resume") | |
| if submit: | |
| if uploaded_file is not None and jd: | |
| # Show loading spinner while processing | |
| with st.spinner("Analyzing your resume, please wait..."): | |
| text = input_pdf_text(uploaded_file) | |
| response = get_gemeni_response(input_prompt.format(text=text, jd=jd)) | |
| # Retry parsing up to 2 times | |
| response_dict = None | |
| for _ in range(2): | |
| response_dict = parse_response(response) | |
| if response_dict: | |
| break | |
| time.sleep(1) # Slight delay before retrying | |
| if response_dict: | |
| # Display Job Description Match | |
| st.subheader("Job Description Match") | |
| st.metric(label="Matching Score", value=response_dict.get("JD Match", "N/A")) | |
| # Display Missing Keywords | |
| st.subheader("Top Missing Keywords") | |
| missing_keywords = response_dict.get("MissingKeywords", []) | |
| if missing_keywords: | |
| st.write(", ".join(missing_keywords)) | |
| else: | |
| st.write("All key terms are covered!") | |
| # Display Profile Summary | |
| st.subheader("Profile Summary") | |
| st.text(response_dict.get("ProfileSummary", "No summary available.")) | |
| # Generate downloadable report | |
| st.download_button( | |
| label="Download ATS Report", | |
| data=json.dumps(response_dict, indent=4), | |
| file_name="ATS_Analysis_Report.json", | |
| mime="application/json" | |
| ) | |
| else: | |
| st.error("Error parsing response. Please try again.") | |
| st.write(response) # Display raw response for debugging | |
| elif not jd: | |
| st.warning("Please paste a job description.") | |
| else: | |
| st.warning("Please upload your resume in PDF format.") | |