app.py

import gradio as gr
import os
import openai
import re
import PyPDF2
import plotly.graph_objects as go

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':
          text = ""
          try:
            with open(file_path, "rb") as pdf_file:
                pdf_reader = PyPDF2.PdfReader(pdf_file)
                num_pages = len(pdf_reader.pages)
                
                for page_num in range(num_pages):
                    page = pdf_reader.pages[page_num]
                    text += page.extract_text()
                    
            return text
          except Exception as e:
            return str(e)

        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,job_description, resume):



      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:**
          Introduction to say we've assessment the resume
                  the result should be in this format:
                  Matched Percentage: Precisely [get matching percentage between job description and resume]%.
                  Qualification Matching Percentage: [matching percentage between job description and resume qualifications].
                  Skills Matching Percentage: [matching percentage between job description and resume skills].
                  Experience Matching Percentage: [matching percentage between job description and resume experience].
                  Reason            : [Reasons for why this resume matched and not matched.].
                  Skills To Improve : [Mention the skills to improve for the candidate according to the given job description. If there are no matches, simply say N/A.].
                  Keywords          : [Return the matched keywords from resume and job_description. If there are no matches, simply say N/A.]
                  Company : [Extracted company name from job description].
                  Irrevelant: [mention the Irrevelant skills and expericence]
                  Recommend Course:  [mention specific course to recommend the candidate for job description needs].
                  Experience: [mention specific experience to recommend the candidate for job description needs].
                  Tailor Your Application: [Emphasize relevant areas].
                  Certifications: [Pursue certifications in mention area].
                  Feel free to contact us for further clarification.
                  Best wishes,
          Your job is to write a proper E-Mail to the candidate from the organization with the job role, the candidate's name, organization name, and the body of this E-Mail should be in the above format.
""",
          temperature=0,
          max_tokens=1000,
          stop=None,
      )
      generated_text = response.choices[0].text.strip()
      # result += generated_text + "\n-------------------------------------------------------------------------------------\n"
      return generated_text

    def clear(self,jobDescription,resume,result_email):
      jobDescription = None
      resume = None
      result_email = None
      return jobDescription, resume, result_email

    def main(self,job_description_path, resume_list_path):

      tot_result = ""
      print(tot_result)
      job_description = self.extract_text_from_file(job_description_path.name)
      for resume_path in resume_list_path:
          resume = self.extract_text_from_file(resume_path.name)
          result = self.responce_from_ai(job_description,resume)
          tot_result = tot_result + result + "\n-------------------------------------------------------------------------------------\n"
      
      # lines = tot_result.split('\n')
      # for line in lines:
      #     matched_percentage = re.search(r"Matched Percentage: Precisely (\d+)%\.", result)
      #     if matched_percentage:
      #         matched_percentage = int(matched_percentage.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)])
      return tot_result

    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">Candidate Assessment and Communication</h1></center>""")
            with gr.Row(elem_id="col-container"):
              with gr.Column(scale=0.55, min_width=150, ):
                jobDescription = gr.File(label="Job Description", file_types = [".pdf",".txt"])
              with gr.Column(scale=0.55, min_width=150):
                resume = gr.File(label="Resume", file_types = [".pdf",".txt"] , file_count="multiple")
            with gr.Row(elem_id="col-container"):
              with gr.Column(scale=0.80, min_width=150):
                analyse = gr.Button("Analyse")
              with gr.Column(scale=0.20, min_width=150):
                clear_btn = gr.ClearButton()
            with gr.Row(elem_id="col-container"):
              with gr.Column(scale=1.0, min_width=150):
                result_email = gr.Textbox(label="E-mail", lines=10)
            # with gr.Row(elem_id="col-container"):
            #   with gr.Column(scale=0.50, min_width=150):
            #     pychart = gr.Plot(label="Matching Percentage Chart")
            analyse.click(self.main, [jobDescription, resume], [result_email])
            clear_btn.click(self.clear,[jobDescription,resume,result_email],[jobDescription,resume,result_email] )

      app.launch(debug = True)

if __name__ == "__main__":
    resume = ResumeAnalyser()
    answer = resume.gradio_interface()