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import streamlit as st | |
import google.generativeai as genai | |
import os | |
import PyPDF2 as pdf | |
import json | |
import re | |
import ast | |
genai.configure(api_key=os.getenv("GOOGLE_API_KEY")) | |
def get_gemini_repsonse(input): | |
model=genai.GenerativeModel('gemini-pro') | |
response=model.generate_content(input) | |
return response.text | |
def input_pdf_text(uploaded_file): | |
reader=pdf.PdfReader(uploaded_file) | |
text="" | |
for page in range(len(reader.pages)): | |
page=reader.pages[page] | |
text+=str(page.extract_text()) | |
return text | |
#Prompt Template | |
input_prompt=""" | |
Hey Act Like a skilled or very experience ATS(Application Tracking System) | |
with a deep understanding of tech field,software engineering,data science ,data analyst | |
and big data engineer. Your task is to evaluate the resume based on the given job description. | |
You must consider the job market is very competitive and you should provide | |
best assistance for improving thr resumes. Assign the percentage Matching based | |
on Jd and | |
the missing keywords with high accuracy | |
resume:{text} | |
description:{jd} | |
I want the response in one single string having the structure | |
{{"JD Match":"%","MissingKeywords:[]","Profile Summary":""}} | |
""" | |
## streamlit app | |
st.title("Applicant Tracking System (ATS)") | |
st.text("Improve Your Resume ATS") | |
jd=st.text_area("Paste the Job Description") | |
uploaded_file=st.file_uploader("Upload Your Resume",type="pdf",help="Please uplaod the pdf") | |
submit = st.button("Submit") | |
if submit: | |
if uploaded_file is not None: | |
text=input_pdf_text(uploaded_file) | |
response_string=get_gemini_repsonse(input_prompt) | |
# Extract JD match percentage | |
jd_match = int(re.search(r'"JD Match":"(\d+)%?"', response_string).group(1)) | |
# Extract missing keywords | |
missing_keywords = re.search(r'"MissingKeywords":(.*?)]', response_string).group(1) + ']' | |
missing_keywords = eval(missing_keywords) # Convert string representation of list to actual list | |
# Extract profile summary | |
profile_summary = re.search(r'"Profile Summary":"(.*?)"', response_string).group(1) | |
# Streamlit app | |
st.title("Resume Evaluation Result") | |
st.write("JD Match:", f"{str(jd_match)}%") | |
st.write("Missing Keywords:", missing_keywords) | |
st.write("Profile Summary:", profile_summary) | |
# If JD match percentage is more than 80%, display balloons | |
if jd_match >= 80: | |
st.balloons() | |