Upload app.py

app.py

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+import gradio as gr
+import fitz
+import os
+import zipfile
+
+def process(input_pdf):
+    # Conversion of PDF to JPG images
+    pdf = fitz.open(input_pdf)
+    first_page = pdf[0]
+    pix = first_page.get_pixmap()
+    image_bytes = pix.tobytes("jpg")
+    pdf.close()
+
+    temp_dir = "images"
+    basename = os.path.basename(input_pdf).split('.')[0]
+    image_name = basename + "jpg"
+    os.makedirs(temp_dir, exist_ok=True)
+    with open(os.path.join(temp_dir, image_name), "wb") as f:
+        f.write(image_bytes)
+    
+    image_path = os.path.join(temp_dir, image_name)
+    output = model.inference(image=image_path, prompt=task_prompt)["predictions"][0]
+
+    return output
+
+task_name = "SGSInvoice"
+task_prompt = f"<s_{task_name}>"
+model = DonutModel.from_pretrained("uartimcs/donut-invoice-extract")
+model.eval()
+demo = gr.Interface(fn=process,inputs=gr.File(file_types=['.pdf']),outputs="json", title=f"Donut 🍩 demonstration for `{task_name}` task",)
+demo.launch()
+
+