Update app.py

app.py

@@ -1,10 +1,53 @@
 import gradio as gr
+from PyPDF2 import PdfReader
+from docx import Document
+import os
+
+def process_pdf(pdf_file, token):
+    try:
+        # Extract text from PDF
+        pdf_reader = PdfReader(pdf_file.name)
+        text = "\n".join([page.extract_text() for page in pdf_reader.pages])
+        
+        # Initialize LLM client
+        from huggingface_hub import InferenceClient
+        client = InferenceClient(token=token)
+        
+        # Generate rewritten text
+        response = client.text_generation(
+            prompt=f"Rewrite this text clearly and concisely while preserving all key information:\n\n{text}",
+            model="meta-llama/Llama-3.3-70B-Instruct",
+            max_new_tokens=2000
+        )
+        
+        # Create Word document
+        doc = Document()
+        doc.add_paragraph(response)
+        output_path = "rewritten.docx"
+        doc.save(output_path)
+        
+        return response, output_path
+    
+    except Exception as e:
+        return f"Error: {str(e)}", None
 
 with gr.Blocks(fill_height=True) as demo:
     with gr.Sidebar():
-        gr.Markdown("# Inference Provider")
-        gr.Markdown("This Space showcases the meta-llama/Llama-3.3-70B-Instruct model, served by the cerebras API. Sign in with your Hugging Face account to use this API.")
-        button = gr.LoginButton("Sign in")
-    gr.load("models/meta-llama/Llama-3.3-70B-Instruct", accept_token=button, provider="cerebras")
+        gr.Markdown("# PDF to Word Converter")
+        gr.Markdown("Upload a PDF to get rewritten text in Word format")
+        login_btn = gr.LoginButton("Sign in with HF")
     
-demo.launch()
+    with gr.Column():
+        file_input = gr.File(label="Upload PDF", type="file")
+        process_btn = gr.Button("Process PDF")
+        text_output = gr.Textbox(label="Rewritten Text", interactive=False)
+        file_output = gr.Download(label="Download Word File")
+    
+    process_btn.click(
+        fn=process_pdf,
+        inputs=[file_input, login_btn],
+        outputs=[text_output, file_output]
+    )
+
+if __name__ == "__main__":
+    demo.launch()