Update app.py

app.py

@@ -1,29 +1,31 @@
-
 from transformers import pipeline
+import gradio as gr
 
+# 建立 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?"}
-        ]
-    },
-]
+# 包裝成 API 函數
+def predict(image_url, question):
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "image", "url": image_url},
+                {"type": "text", "text": question}
+            ]
+        },
+    ]
+    result = pipe(text=messages)
+    return result[0]["generated_text"]
 
-result = pipe(text=messages)
-print(result[0]["generated_text"])
-
-import gradio as gr
-# 建立 Gradio UI
+# Gradio 介面（同時支援 UI 和 API）
 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."
+    title="MedGemma API + Demo",
+    description="呼叫 API 或用 UI 測試"
 )
 
-iface.launch()
+if __name__ == "__main__":
+    iface.launch()