+ ner online

Signed-off-by: wang.yuqi <noooop@126.com>

Author: noooop

examples/online_serving/ner.py

@@ -0,0 +1,69 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+"""
+Example online usage of Pooling API.
+
+Run `vllm serve <model> --runner pooling`
+to start up the server in vLLM. e.g.
+
+vllm serve boltuix/NeuroBERT-NER
+"""
+
+import argparse
+import pprint
+
+import requests
+import torch
+
+
+def post_http_request(prompt: dict, api_url: str) -> requests.Response:
+    headers = {"User-Agent": "Test Client"}
+    response = requests.post(api_url, headers=headers, json=prompt)
+    return response
+
+
+def parse_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--host", type=str, default="localhost")
+    parser.add_argument("--port", type=int, default=8000)
+    parser.add_argument("--model", type=str, default="boltuix/NeuroBERT-NER")
+
+    return parser.parse_args()
+
+
+def main(args):
+    from transformers import AutoTokenizer, AutoConfig
+    api_url = f"http://{args.host}:{args.port}/pooling"
+    model_name = args.model
+
+
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    config = AutoConfig.from_pretrained(model_name)
+    label_map = config.id2label
+
+    text = "Barack Obama visited Microsoft headquarters in Seattle on January 2025."
+
+    prompt = {"model": model_name, "input": text}
+    pooling_response = post_http_request(prompt=prompt, api_url=api_url)
+
+    outputs = pooling_response.json()["data"]
+
+    for output in outputs:
+        logits = torch.tensor(output['data'])
+        predictions = logits.argmax(dim=-1)
+
+        inputs = tokenizer(text, return_tensors="pt")
+
+        # Map predictions to labels
+        tokens = tokenizer.convert_ids_to_tokens(inputs["input_ids"][0])
+        labels = [label_map[p.item()] for p in predictions]
+
+        # Print results
+        for token, label in zip(tokens, labels):
+            if token not in tokenizer.all_special_tokens:
+                print(f"{token:15} → {label}")
+
+
+if __name__ == "__main__":
+    args = parse_args()
+    main(args)