new file: app.py

new file: requirements.txt

app.py

@@ -0,0 +1,28 @@
+from transformers import AutoProcessor, PaliGemmaForConditionalGeneration
+from PIL import Image
+import torch
+import gradio as gr
+
+# Load model and processor
+processor = AutoProcessor.from_pretrained("google/paligemma-3b")
+model = PaliGemmaForConditionalGeneration.from_pretrained(
+    "google/paligemma-3b", 
+    torch_dtype=torch.float16, 
+    device_map="auto"
+)
+
+def ecommerce_assistant(image, question):
+    prompt = f"Question: {question}\nAnswer:"
+    inputs = processor(text=prompt, images=image, return_tensors="pt").to("cuda", torch.float16)
+    outputs = model.generate(**inputs, max_new_tokens=50)
+    return processor.batch_decode(outputs, skip_special_tokens=True)[0]
+
+demo = gr.Interface(
+    fn=ecommerce_assistant,
+    inputs=["image", "text"],
+    outputs="text",
+    title="🛍️ E-commerce Visual Assistant",
+    description="Upload a product photo and ask questions like 'What brand is this?' or 'Can I buy it online?'"
+)
+
+demo.launch()

requirements.txt

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+transformers
+torch
+gradio
+Pillow