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from dotenv import load_dotenv | |
load_dotenv() | |
import streamlit as st | |
import os | |
import io | |
import base64 | |
from PIL import Image | |
import pdf2image | |
from PyPDF2 import PdfReader | |
import google.generativeai as genai | |
from langchain.text_splitter import RecursiveCharacterTextSplitter | |
from langchain.vectorstores import FAISS, Chroma | |
from langchain.chains.question_answering import load_qa_chain | |
from langchain.embeddings.openai import OpenAIEmbeddings | |
from langchain.prompts import PromptTemplate | |
from openai import OpenAI | |
client = OpenAI() | |
#read pdf | |
def get_pdf_text(pdf_docs): | |
text="" | |
for pdf in pdf_docs: | |
pdf_reader= PdfReader(pdf) | |
for page in pdf_reader.pages: | |
text+= page.extract_text() | |
return text | |
#divide pdf text into overlapping chunks | |
def get_text_chunks(text): | |
text_splitter = RecursiveCharacterTextSplitter(chunk_size = 30, chunk_overlap=5) | |
chunks = text_splitter.split_text(text) | |
return chunks | |
#convert chunks to embeddings | |
def get_vector_store(text_chunks): | |
embeddings = OpenAIEmbeddings() | |
vector_store = FAISS.from_texts(text_chunks, embedding=embeddings) | |
#vector stores can be stored locally or even in a database | |
vector_store.save_local("faiss_index") | |
def get_openai_response(prompt): | |
completion = client.chat.completions.create( | |
model="gpt-3.5-turbo", # or other available engines | |
messages=[ | |
{"role": "user", "content": prompt} | |
] | |
) | |
return completion.choices[0].message.content | |
def main(): | |
st.set_page_config(page_title="Personal ATS") | |
st.header("ATS Keyword Matching") | |
input_text_title = st.text_area("Job Title: ", key="inpu_title") | |
input_text_jd = st.text_area("Job Description: ", key="input_jd") | |
pdf_docs = st.file_uploader("Upload Resume (pdf)", accept_multiple_files=True) | |
submit1 = st.button("Resume evaluation against job role") | |
submit2 = st.button("Percentage Match") | |
submit3 = st.button("Ideal Resume") | |
input_prompt1 = """ | |
You are an experienced Technical Human Resource Manager experienced in the field of {}, your task is to review the provided resume against the job description. | |
Please share your professional evaluation on whether the candidate's profile aligns with the role. | |
Highlight the strengths and weaknesses of the applicant in relation to the specified job requirements. | |
Resume: {} | |
Job Description: {} | |
""" | |
input_prompt2 = """ | |
You are an skilled ATS (Applicant Tracking System) scanner with a deep understanding in the field of {}, | |
your task is to evaluate the resume against the provided job description. You should output first the percentage of match between the resume and | |
the job description, followed by keywords matching, keywords missing, specific changes for resume to reach matching percentage | |
of above 85 and lastly your final thoughts. | |
Resume: {} | |
Job Description: {} | |
""" | |
input_prompt3_alternate = """ | |
You are an expert at making resumes for the job role of {}. Your task is to make an ideal resume for the job description I give you using ONLY the following three sections and then give me a keyword match percentage between the created resume and the job description at the end: | |
1. The skills section with comma separated technical tools and frameworks. | |
2. The work experience section with 3 job roles. | |
3. Projects section with six ADVANCED projects and you have to | |
make up your own projects from imagination that would use the same | |
tech stack specified in the job description with minimum overlap of tech stack between the projects. | |
Each project will have a project title followed by two bullet points. | |
First bullet point is the project description | |
and the second bullet point is the tech stack used to make the project. | |
You also have to give me exact value for keyword match percentage between the resume you created and the job description. | |
Job Description: {} | |
""" | |
input_prompt3 = """ | |
Write a resume based on the following job description for the {} position and include bullet point achievements that show impact and metrics. | |
It should include ONLY these section: | |
1. The skills section with comma separated technical tools and frameworks. | |
2. The work experience section with 3 job roles. | |
3. Projects section with six ADVANCED projects. Each project will have a project title followed by two bullet points. First bullet point is the project description and the second bullet point is the tech stack used to make the project. Use numbers that show impact and metrics | |
Job description: {} | |
""" | |
if submit1: | |
if pdf_docs is not None: | |
pdf_content = get_pdf_text(pdf_docs) | |
prompt = input_prompt1.format(input_text_title, pdf_content, input_text_jd) | |
response = get_openai_response(prompt) | |
st.subheader("Response: ") | |
st.write(response) | |
else: | |
st.write("Please upload resume") | |
elif submit2: | |
if pdf_docs is not None: | |
pdf_content = get_pdf_text(pdf_docs) | |
prompt = input_prompt2.format(input_text_title, pdf_content, input_text_jd) | |
response = get_openai_response(prompt) | |
st.subheader("Response: ") | |
st.write(response) | |
else: | |
st.write("Please upload resume") | |
elif submit3: | |
if input_text_jd is not None: | |
pdf_content = get_pdf_text(pdf_docs) | |
prompt = input_prompt3.format(input_text_title, input_text_jd) | |
response = get_openai_response(prompt) | |
st.subheader("Response: ") | |
st.write(response) | |
else: | |
st.write("Please upload resume") | |
if __name__ == "__main__": | |
main() |