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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><img src="https://templates.images.credential.net/1612472097627370951721412474196.png" alt="Image" width="210" height="210"></center>
""")
with gr.Row():
with gr.Column(elem_id="col-container"):
gr.HTML(
"""<br style="color:white;">"""
)
gr.HTML(
"""<h2 style="text-align:center; color:"white">AI Resume Analyzer</h2> """
)
gr.HTML("<br>")
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="Keywords from Resume",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() |