Create app.py

app.py

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+import gradio as gr
+from transformers import Pix2StructProcessor, Pix2StructForConditionalGeneration
+from PIL import Image
+import torch
+
+# Load model & processor
+processor = Pix2StructProcessor.from_pretrained("google/deplot")
+model = Pix2StructForConditionalGeneration.from_pretrained("google/deplot")
+
+# Move model to GPU if available
+device = "cuda" if torch.cuda.is_available() else "cpu"
+model.to(device)
+
+def extract_chart_data(img: Image.Image):
+    inputs = processor(images=img, return_tensors="pt").to(device)
+    outputs = model.generate(**inputs)
+    result = processor.decode(outputs[0], skip_special_tokens=True)
+    return result
+
+# Gradio interface
+iface = gr.Interface(
+    fn=extract_chart_data,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="DePlot Chart Data Extractor",
+    description="Upload a chart image and get its extracted data/description."
+)
+
+iface.launch()