Create app.py

app.py

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+import gradio as gr
+from PIL import Image
+
+# Define the prediction function for Gradio
+def predict(image, question):
+    inputs = processor(text=[question], images=[image], return_tensors="pt", padding=True).to(device)
+    outputs = model.generate(**inputs)
+    return processor.tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+# Create the Gradio interface
+interface = gr.Interface(
+    fn=predict,
+    inputs=["image", "text"],
+    outputs="text",
+    title="Florence 2 VQA - Engineering Drawings",
+    description="Upload an engineering drawing and ask a related question."
+)
+
+# Launch the Gradio interface
+interface.launch()