Update app.py

app.py

@@ -2,14 +2,50 @@ import os
 from cerebras.cloud.sdk import Cerebras
 from markitdown import MarkItDown
 from weasyprint import HTML
+from docx import Document
+from pptx import Presentation
+from PyPDF2 import PdfReader
 import gradio as gr
+from PIL import Image
 
-# Ensure you get the API key from environment variables
 api_key = os.environ.get("CEREBRAS_API_KEY")
-
-# Initialize MarkItDown instance
 md_converter = MarkItDown()
 
+def extract_file_preview(file_path):
+    """
+    Extracts a preview of the file based on its format.
+    """
+    try:
+        file_ext = os.path.splitext(file_path)[-1].lower()
+
+        if file_ext in [".jpg", ".jpeg", ".png"]:
+            return Image.open(file_path)
+
+        elif file_ext == ".pdf":
+            reader = PdfReader(file_path)
+            return "\n".join([page.extract_text() for page in reader.pages[:2]])
+
+        elif file_ext in [".docx"]:
+            doc = Document(file_path)
+            return "\n".join([para.text for para in doc.paragraphs[:20]])
+
+        elif file_ext in [".pptx"]:
+            ppt = Presentation(file_path)
+            slides_text = []
+            for slide in ppt.slides[:5]:
+                slide_text = []
+                for shape in slide.shapes:
+                    if hasattr(shape, "text"):
+                        slide_text.append(shape.text)
+                slides_text.append("\n".join(slide_text))
+            return "\n---\n".join(slides_text)
+
+        else:
+            return "File preview not supported for this format."
+
+    except Exception as e:
+        return f"Error extracting file preview: {str(e)}"
+
 # Functions for resume optimization
 def create_prompt(resume_string: str, jd_string: str) -> str:
     """
@@ -91,74 +127,84 @@ def get_resume_response(prompt: str, api_key: str, model: str = "llama-3.3-70b",
 
     return response_string
 
-def process_resume(resume_file, jd_string):
-    """
-    Process a resume file against a job description to create an optimized version.
-    """
+def process_resume(file, jd_string):
     try:
-        # Convert the uploaded file to Markdown
-        result = md_converter.convert(resume_file.name)
-        resume_string = result.text_content
+        file_path = file.name
+        original_preview = extract_file_preview(file_path)
 
-        # 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")
+        result = md_converter.convert(file_path)
+        resume_string = result.text_content
 
-        # Extract new resume and suggestions for improvement
-        new_resume = response_list[0]
-        suggestions = "## Additional Suggestions \n\n" + response_list[1]
+        prompt = f"Optimize resume based on job description: {jd_string}"
+        optimized_resume = "Optimized resume placeholder"  # Simulate response for now.
 
-        return new_resume, new_resume, suggestions
+        # Save the files for download
+        original_file_path = file_path
+        optimized_file_path = "resumes/optimized_resume.md"
+        with open(optimized_file_path, "w", encoding="utf-8") as f:
+            f.write(optimized_resume)
 
+        return original_preview, resume_string, optimized_resume, original_file_path, optimized_file_path
     except Exception as e:
-        return f"Error processing file: {str(e)}", "", ""
+        return f"Error processing file: {str(e)}", "", "", "", ""
 
-def export_resume(new_resume):
-    """
-    Convert a markdown resume to PDF format and save it.
-    """
+def export_as_pdf(resume_md):
     try:
-        # Save as PDF
-        output_pdf_file = "resumes/resume_new.pdf"
-
-        # Convert Markdown to HTML
-        html_content = new_resume
-
-        # Convert HTML to PDF and save
-        HTML(string=html_content).write_pdf(output_pdf_file, stylesheets=['resumes/style.css'])
+        pdf_path = "resumes/optimized_resume.pdf"
+        HTML(string=resume_md).write_pdf(pdf_path)
+        return pdf_path
+    except Exception as e:
+        return f"Failed to export PDF: {str(e)}"
 
-        return f"Successfully exported resume to {output_pdf_file} 🎉"
+def export_as_word(resume_md):
+    try:
+        doc_path = "resumes/optimized_resume.docx"
+        doc = Document()
+        for line in resume_md.split("\n"):
+            doc.add_paragraph(line)
+        doc.save(doc_path)
+        return doc_path
     except Exception as e:
-        return f"Failed to export resume: {str(e)} 💔"
+        return f"Failed to export Word: {str(e)}"
 
-# Hugging Face Space UI
+# Gradio UI
 with gr.Blocks() as app:
-    # Create header and app description
     gr.Markdown("# Resume Optimizer 📄")
     gr.Markdown("Upload your resume, paste the job description, and get actionable insights!")
 
-    # Gather inputs
     with gr.Row():
-        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...")
+        resume_input = gr.File(label="Upload Your Resume")
+        jd_input = gr.Textbox(label="Paste Job Description", lines=5)
 
-    run_button = gr.Button("Optimize Resume 🤖")
-
-    # Display outputs
-    output_resume_md = gr.Markdown(label="New Resume")
-    output_suggestions = gr.Markdown(label="Suggestions")
-
-    # Editing results
-    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")
+    run_button = gr.Button("Optimize Resume")
+    
+    with gr.Row():
+        before_preview = gr.Markdown(label="Original File Preview")
+        before_md = gr.Markdown(label="Original (Markdown)")
+        after_md = gr.Markdown(label="Optimized (Markdown)")
 
-    # 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])
+    with gr.Row():
+        download_before = gr.File(label="Download Original")
+        #download_after_md = gr.File(label="Download Optimized (Markdown)")
+        download_after_pdf = gr.File(label="Download Optimized (PDF)")
+        download_after_word = gr.File(label="Download Optimized (Word)")
+
+    run_button.click(
+        process_resume,
+        inputs=[resume_input, jd_input],
+        outputs=[before_preview, before_md, after_md, download_before, download_after_md]
+    )
+    
+    gr.Button("Export as PDF").click(
+        export_as_pdf,
+        inputs=[after_md],
+        outputs=[download_after_pdf]
+    )
+    
+    gr.Button("Export as Word").click(
+        export_as_word,
+        inputs=[after_md],
+        outputs=[download_after_word]
+    )
 
-# Launch the app
-app.launch()
+app.launch()