atsresumecheck / app.py
decodingdatascience's picture
Update app.py
cb022fa verified
import streamlit as st
import google.generativeai as genai
import os
import PyPDF2 as pdf
from dotenv import load_dotenv
import json
load_dotenv() ## load all our environment variables
os.getenv("GOOGLE_API_KEY")
genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
def get_gemini_response(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 Three blocks having the structure
JD Match:"%"
MissingKeywords:[]
Tips to Improve the Resume for Higher Match:""}}
"""
## streamlit app
st.title("DDS Smart ATS")
st.text("Improve Your Resume ATS Score Match")
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 = get_gemini_response(input_prompt.format(text=text, jd=jd))
st.subheader(response)