Create app.py

app.py

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+!pip install transformers torch gradio pillow --quiet
+
+
+from transformers import pipeline
+
+pipe = pipeline("image-text-to-text", model="google/medgemma-4b-it")
+
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
+            {"type": "text", "text": "What animal is on the candy?"}
+        ]
+    },
+]
+
+result = pipe(text=messages)
+print(result[0]["generated_text"])
+
+# 建立 Gradio UI
+iface = gr.Interface(
+    fn=predict,
+    inputs=["text", "text"],  # image_url, question
+    outputs="text",
+    title="MedGemma Demo",
+    description="Input an image URL and a question to get MedGemma's answer."
+)
+
+iface.launch()