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app (1).py

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+import gradio as gr
+import PyPDF2
+import os
+import openai
+import re
+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':
+          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            : [Mention Reason and keys from job_description and resume get this matched percentage.].
+                  Skills To Improve : [Mention the skills How to improve and get 100 percentage job description matching].
+                  Keywords          : [matched key words from {job_description} and {resume}].
+                  """,
+          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:30px;'><center>
+            <img class="leftimage" align="left" src="https://companieslogo.com/img/orig/RAND.AS_BIG-0f1935a4.png?t=1651813778" alt="Image" width="210" height="210">
+            <h1 class ="center" style="color:#fff">ADOPLE AI</h1></center>
+            <br><center><h1 style="color:#fff">Resume Analyser</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()

requirements.txt

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+openai
+gradio
+PyPDF2==2.12.1
+plotly
+plotly-express

style.css

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+#col-container {
+  max-width: 600px;
+  margin-left: auto;
+  margin-right: auto;
+}
+
+#row-flex {
+  display: flex;
+  align-items: center;
+  justify-content: center;
+}
+.leftimage .rightimage{
+  float:left;
+  filter: drop-shadow(20px 20px 10px white);
+}
+.leftimage{
+  padding-top:0px;
+  margin-left:210px;
+}
+.rightimage{
+  padding-top:40px;
+  margin-right:220px;
+}
+a,
+a:hover,
+a:visited {
+  text-decoration-line: underline;
+  font-weight: 600;
+  color: #1f2937 !important;
+}
+
+.dark a,
+.dark a:hover,
+.dark a:visited {
+  color: #f3f4f6 !important;
+}