Create app.py

app.py

@@ -0,0 +1,23 @@
+import gradio as gr
+import torch
+from PIL import Image
+from transformers import ColPaliForRetrieval, ColPaliProcessor
+
+model_name = "vidore/colpali-v1.3-hf"
+model = ColPaliForRetrieval.from_pretrained(model_name, torch_dtype=torch.float32).eval()
+processor = ColPaliProcessor.from_pretrained(model_name)
+
+def process_image(image):
+    inputs = processor(images=image, return_tensors="pt")
+    with torch.no_grad():
+        outputs = model(**inputs)
+    return outputs.embeddings.squeeze().tolist()
+
+demo = gr.Interface(
+    fn=process_image,
+    inputs=gr.Image(type="pil"),
+    outputs="json",
+    examples=[["example1.jpg"], ["example2.jpg"]]
+)
+
+demo.launch()