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app.py

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+import gradio as gr
+from transformers import pipeline
+from PIL import Image
+
+# โหลดโมเดลและ pipeline
+model, tokenizer = FastVisionModel.from_pretrained(
+    "unsloth/Llama-3.2-11B-Vision-Instruct",
+    load_in_4bit=True,
+    use_gradient_checkpointing="unsloth",
+    device_map="auto"
+)
+
+vision_pipeline = pipeline(
+    "image-to-text",
+    model=model,
+    tokenizer=tokenizer,
+    device=0
+)
+
+# ฟังก์ชันสำหรับ Gradio
+def analyze_image(image, instruction):
+    result = vision_pipeline(images=image, instruction=instruction, max_new_tokens=128)
+    return result[0]["generated_text"]
+
+# สร้าง UI ด้วย Gradio
+interface = gr.Interface(
+    fn=analyze_image,
+    inputs=[
+        gr.Image(type="pil"),
+        gr.Textbox(label="Instruction", value="You are an expert radiographer. Describe accurately what you see in this image.")
+    ],
+    outputs=gr.Textbox(label="Generated Text"),
+    title="Medical Image Analysis",
+    description="Analyze X-ray images and generate a diagnostic report."
+)
+
+# รันแอป
+if __name__ == "__main__":
+    interface.launch()