updata inference demo

demo/demo_vllm_svg.py

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+import argparse
+
+from openai import OpenAI
+from transformers.utils.versions import require_version
+from PIL import Image
+from dots_ocr.utils import dict_promptmode_to_prompt
+from dots_ocr.model.inference import inference_with_vllm
+
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--ip", type=str, default="localhost")
+parser.add_argument("--port", type=str, default="8000")
+parser.add_argument("--model_name", type=str, default="rednote-hilab/dots.ocr")
+parser.add_argument("--prompt_mode", type=str, default="prompt_image_to_svg")
+
+args = parser.parse_args()
+
+require_version("openai>=1.5.0", "To fix: pip install openai>=1.5.0")
+
+
+def main():
+    addr = f"http://{args.ip}:{args.port}/v1"
+    image_path = "demo/demo_image2.png"
+    image = Image.open(image_path)
+    prompt = dict_promptmode_to_prompt[args.prompt_mode]
+
+    #prompt = Please generate the SVG code based on the image.viewBox="0 0 {img_width} {img_height}"
+    prompt = prompt.replace("{width}", str(image.width)).replace("{height}", str(image.height))
+
+    response = inference_with_vllm(
+        image,
+        prompt, 
+        ip=args.ip,
+        port=args.port,
+        temperature=0.9,           # SVG: low temperature often causes repetitive/looping output
+        top_p=1.0,
+        model_name=args.model_name,
+    )
+    print(f"response: {response}")
+
+
+if __name__ == "__main__":
+    main()