Update app.py

app.py

@@ -1,6 +1,6 @@
 import os
-from cerebras.cloud.sdk import Cerebras
 from markitdown import MarkItDown
+from cerebras.cloud.sdk import Cerebras
 from weasyprint import HTML
 import markdown
 import gradio as gr
@@ -88,55 +88,34 @@ def process_resume(resume, jd_string):
     """
     Process the uploaded resume and job description, optimize it, and return the result.
     """
-    try:
-        # Read file content from the resume path
-        with open(resume.name, "r", encoding="utf-8") as file:
-            resume_string = file.read()
-
-        # Create optimization prompt
-        prompt = create_prompt(resume_string, jd_string)
-
-        # Generate response using AI
-        response_string = get_resume_response(prompt, api_key)
-        response_list = response_string.split("## Additional Suggestions")
+    # Convert file to Markdown using MarkItDown
+    result = md_converter.convert(resume.name)
+    resume_string = result.text_content  # Get the converted Markdown content
 
-        # Extract new resume and suggestions for improvement
-        new_resume = response_list[0].strip() if len(response_list) > 0 else ""
-        suggestions = "## Additional Suggestions \n\n" + response_list[1].strip() if len(response_list) > 1 else ""
+    # Create optimization prompt
+    prompt = create_prompt(resume_string, jd_string)
 
-        # Save the optimized resume
-        optimized_file_path = "resumes/optimized_resume.md"
-        os.makedirs("resumes", exist_ok=True)  # Ensure the directory exists
-        with open(optimized_file_path, "w", encoding="utf-8") as f:
-            f.write(new_resume)
+    # Generate response from AI
+    response_string = get_resume_response(prompt, api_key)
 
-        # Prepare the download links
-        download_before = resume.name
-        download_after = optimized_file_path
+    # Split response into optimized resume and suggestions
+    response_list = response_string.split("## Additional Suggestions")
+    new_resume = response_list[0].strip()
+    suggestions = "## Additional Suggestions\n\n" + response_list[1].strip() if len(response_list) > 1 else ""
 
-        # Return the results (ensure five outputs)
-        return resume_string, new_resume, download_before, download_after, suggestions
-    except Exception as e:
-        return f"Error processing file: {str(e)}", "", "", "", ""
+    return resume_string, new_resume, suggestions
 
 def export_resume(new_resume):
     """
-    Convert a markdown resume to PDF format and save it.
-
-    Args:
-        new_resume (str): The resume content in markdown format
-
-    Returns:
-        str: A message indicating success or failure of the PDF export
+    Export the optimized resume (in Markdown format) as a PDF file.
     """
     try:
         # Convert Markdown to HTML
         html_content = markdown.markdown(new_resume)
-        
+
         # Convert HTML to PDF and save
         output_pdf_file = "resumes/optimized_resume.pdf"
-        os.makedirs("resumes", exist_ok=True)  # Ensure the directory exists
-        HTML(string=html_content).write_pdf(output_pdf_file, stylesheets=['resumes/style.css'])
+        HTML(string=html_content).write_pdf(output_pdf_file)
 
         return output_pdf_file  # Return the file path for download
     except Exception as e: