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import gradio as gr | |
import PyPDF2 | |
import os | |
import openai | |
import re | |
import plotly.graph_objects as go | |
from typing import Iterable | |
import gradio as gr | |
from gradio.themes.base import Base | |
import time | |
class ResumeAnalyser: | |
def __init__(self): | |
pass | |
def extract_text_from_file(self,file_path): | |
# Get the file extension | |
file_extension = os.path.splitext(file_path)[1] | |
if file_extension == '.pdf': | |
with open(file_path, 'rb') as file: | |
# Create a PDF file reader object | |
reader = PyPDF2.PdfFileReader(file) | |
# Create an empty string to hold the extracted text | |
extracted_text = "" | |
# Loop through each page in the PDF and extract the text | |
for page_number in range(reader.getNumPages()): | |
page = reader.getPage(page_number) | |
extracted_text += page.extractText() | |
return extracted_text | |
elif file_extension == '.txt': | |
with open(file_path, 'r') as file: | |
# Just read the entire contents of the text file | |
return file.read() | |
else: | |
return "Unsupported file type" | |
def responce_from_ai(self,textjd, textcv): | |
resume = self.extract_text_from_file(textjd) | |
job_description = self.extract_text_from_file(textcv) | |
response = openai.Completion.create( | |
engine="text-davinci-003", | |
prompt=f""" | |
Given the job description and the resume, assess the matching percentage to 100 and if 100 percentage not matched mention the remaining percentage with reason. **Job Description:**{job_description}**Resume:**{resume} | |
**Detailed Analysis:** | |
the result should be in this format: | |
Matched Percentage: [matching percentage]. | |
Reason : [Tell me only the one line reason why the resume matched. If there is no matches simply say N/A.]. | |
Skills To Improve : [Mention the skills to improve for the candidate to given job description.If there is no matches simply say N/A.]. | |
Keywords : [Return the matched keywords from {resume} and {job_description}.If there is no matches simply say N/A.] | |
""", | |
temperature=0, | |
max_tokens=100, | |
n=1, | |
stop=None, | |
) | |
generated_text = response.choices[0].text.strip() | |
print(generated_text) | |
return generated_text | |
def matching_percentage(self,job_description_path, resume_path): | |
job_description_path = job_description_path.name | |
resume_path = resume_path.name | |
generated_text = self.responce_from_ai(job_description_path, resume_path) | |
result = generated_text | |
lines = result.split('\n') | |
matched_percentage = None | |
matched_percentage_txt = None | |
reason = None | |
skills_to_improve = None | |
keywords = None | |
for line in lines: | |
if line.startswith('Matched Percentage:'): | |
match = re.search(r"Matched Percentage: (\d+)%", line) | |
if match: | |
matched_percentage = int(match.group(1)) | |
matched_percentage_txt = (f"Matched Percentage: {matched_percentage}%") | |
elif line.startswith('Reason'): | |
reason = line.split(':')[1].strip() | |
elif line.startswith('Skills To Improve'): | |
skills_to_improve = line.split(':')[1].strip() | |
elif line.startswith('Keywords'): | |
keywords = line.split(':')[1].strip() | |
# Extract the matched percentage using regular expression | |
# match1 = re.search(r"Matched Percentage: (\d+)%", matched_percentage) | |
# matched_Percentage = int(match1.group(1)) | |
# Creating a pie chart with plotly | |
labels = ['Matched', 'Remaining'] | |
values = [matched_percentage, 100 - matched_percentage] | |
fig = go.Figure(data=[go.Pie(labels=labels, values=values)]) | |
# fig.update_layout(title='Matched Percentage') | |
return matched_percentage_txt,reason, skills_to_improve, keywords,fig | |
def gradio_interface(self): | |
with gr.Blocks(css="style.css",theme='karthikeyan-adople/hudsonhayes-gray') as app: | |
gr.HTML("""<center class="darkblue" style='background-color:rgb(0,1,36); text-align:center;padding:25px;'><center><h1 class ="center"> | |
<img src="file=logo.png" height="110px" width="280px"></h1></center> | |
<br><h1 style="color:#fff">AI Resume Analyzer</h1></center>""") | |
with gr.Row(): | |
with gr.Column(scale=0.45, min_width=150, ): | |
jobDescription = gr.File(label="Job Description") | |
with gr.Column(scale=0.45, min_width=150): | |
resume = gr.File(label="Resume") | |
with gr.Column(scale=0.10, min_width=150): | |
analyse = gr.Button("Analyse") | |
with gr.Row(): | |
with gr.Column(scale=1.0, min_width=150): | |
perncentage = gr.Textbox(label="Matching Percentage",lines=8) | |
with gr.Column(scale=1.0, min_width=150): | |
reason = gr.Textbox(label="Matching Reason",lines=8) | |
with gr.Column(scale=1.0, min_width=150): | |
skills = gr.Textbox(label="Skills To Improve",lines=8) | |
with gr.Column(scale=1.0, min_width=150): | |
keywords = gr.Textbox(label="Matched Keywords",lines=8) | |
with gr.Row(): | |
with gr.Column(scale=1.0, min_width=150): | |
pychart = gr.Plot(label="Matching Percentage Chart") | |
analyse.click(self.matching_percentage, [jobDescription, resume], [perncentage,reason,skills,keywords,pychart]) | |
app.launch() | |
resume=ResumeAnalyser() | |
resume.gradio_interface() |