Update app.py

app.py

@@ -1,12 +1,15 @@
 import os
 from cerebras.cloud.sdk import Cerebras
-from markdown import markdown
+from markitdown import MarkItDown
 from weasyprint import HTML
 import gradio as gr
 
 # Ensure you get the API key from environment variables
 api_key = os.environ.get("CEREBRAS_API_KEY")
 
+# Initialize MarkItDown instance
+md_converter = MarkItDown()
+
 # Functions for resume optimization
 def create_prompt(resume_string: str, jd_string: str) -> str:
     """
@@ -88,26 +91,30 @@ def get_resume_response(prompt: str, api_key: str, model: str = "llama-3.3-70b",
 
     return response_string
 
-def process_resume(resume, jd_string):
+def process_resume(resume_file, jd_string):
     """
     Process a resume file against a job description to create an optimized version.
     """
-    # Read the resume
-    with open(resume, "r", encoding="utf-8") as file:
-        resume_string = file.read()
+    try:
+        # Convert the uploaded file to Markdown
+        result = md_converter.convert(resume_file.name)
+        resume_string = result.text_content
+
+        # Create prompt for optimization
+        prompt = create_prompt(resume_string, jd_string)
+
+        # Generate the optimized resume using Cerebras' Llama 3.3 70B model
+        response_string = get_resume_response(prompt, api_key)
+        response_list = response_string.split("## Additional Suggestions")
 
-    # Create prompt for optimization
-    prompt = create_prompt(resume_string, jd_string)
+        # Extract new resume and suggestions for improvement
+        new_resume = response_list[0]
+        suggestions = "## Additional Suggestions \n\n" + response_list[1]
 
-    # Generate the optimized resume using Cerebras' Llama 3.3 70B model
-    response_string = get_resume_response(prompt, api_key)
-    response_list = response_string.split("## Additional Suggestions")
-    
-    # Extract new resume and suggestions for improvement
-    new_resume = response_list[0]
-    suggestions = "## Additional Suggestions \n\n" + response_list[1]
+        return new_resume, new_resume, suggestions
 
-    return new_resume, new_resume, suggestions
+    except Exception as e:
+        return f"Error processing file: {str(e)}", "", ""
 
 def export_resume(new_resume):
     """
@@ -116,10 +123,10 @@ def export_resume(new_resume):
     try:
         # Save as PDF
         output_pdf_file = "resumes/resume_new.pdf"
-        
+
         # Convert Markdown to HTML
-        html_content = markdown(new_resume)
-        
+        html_content = new_resume
+
         # Convert HTML to PDF and save
         HTML(string=html_content).write_pdf(output_pdf_file, stylesheets=['resumes/style.css'])
 
@@ -135,7 +142,7 @@ with gr.Blocks() as app:
 
     # Gather inputs
     with gr.Row():
-        resume_input = gr.File(label="Upload Your Resume (.md)")    
+        resume_input = gr.File(label="Upload Your Resume (Supported Files)")    
         jd_input = gr.Textbox(label="Paste the Job Description Here", lines=9, interactive=True, placeholder="Paste job description...")
 
     run_button = gr.Button("Optimize Resume 🤖")
@@ -148,7 +155,7 @@ with gr.Blocks() as app:
     output_resume = gr.Textbox(label="Edit resume and export!", interactive=True)
     export_button = gr.Button("Export Resume as PDF 🚀")
     export_result = gr.Markdown(label="Export Result")
-    
+
     # Event binding
     run_button.click(process_resume, inputs=[resume_input, jd_input], outputs=[output_resume_md, output_resume, output_suggestions])
     export_button.click(export_resume, inputs=[output_resume], outputs=[export_result])