Update app.py

app.py

@@ -0,0 +1,30 @@
+import gradio as gr
+from transformers import AutoProcessor, AutoModelForVision2Seq
+from PIL import Image
+import torch
+
+# Load the model and processor
+model_name = "ds4sd/SmolDocling-256M-preview"
+processor = AutoProcessor.from_pretrained(model_name)
+model = AutoModelForVision2Seq.from_pretrained(
+    model_name, torch_dtype=torch.bfloat16
+).to("cuda" if torch.cuda.is_available() else "cpu")
+
+# Define the inference function
+def process_image(image):
+    inputs = processor(images=image, return_tensors="pt").to(model.device)
+    outputs = model.generate(**inputs, max_new_tokens=1024)
+    result = processor.batch_decode(outputs, skip_special_tokens=True)[0]
+    return result
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=process_image,
+    inputs=gr.inputs.Image(type="pil"),
+    outputs="text",
+    title="SmolDocling Document Conversion",
+    description="Upload an image of a document page to convert it to structured text."
+)
+
+if __name__ == "__main__":
+    iface.launch()