OpenAI Pooling Client

OpenAI Pooling Client#

Source: examples/openai_pooling_client.py.

 1"""
 2Example online usage of Pooling API.
 3
 4Run `vllm serve <model> --task <embed|classify|reward|score>`
 5to start up the server in vLLM.
 6"""
 7import argparse
 8import pprint
 9
10import requests
11
12
13def post_http_request(prompt: dict, api_url: str) -> requests.Response:
14    headers = {"User-Agent": "Test Client"}
15    response = requests.post(api_url, headers=headers, json=prompt)
16    return response
17
18
19if __name__ == "__main__":
20    parser = argparse.ArgumentParser()
21    parser.add_argument("--host", type=str, default="localhost")
22    parser.add_argument("--port", type=int, default=8000)
23    parser.add_argument("--model",
24                        type=str,
25                        default="jason9693/Qwen2.5-1.5B-apeach")
26
27    args = parser.parse_args()
28    api_url = f"http://{args.host}:{args.port}/pooling"
29    model_name = args.model
30
31    # Input like Completions API
32    prompt = {"model": model_name, "input": "vLLM is great!"}
33    pooling_response = post_http_request(prompt=prompt, api_url=api_url)
34    print("Pooling Response:")
35    pprint.pprint(pooling_response.json())
36
37    # Input like Chat API
38    prompt = {
39        "model":
40        model_name,
41        "messages": [{
42            "role": "user",
43            "content": [{
44                "type": "text",
45                "text": "vLLM is great!"
46            }],
47        }]
48    }
49    pooling_response = post_http_request(prompt=prompt, api_url=api_url)
50    print("Pooling Response:")
51    pprint.pprint(pooling_response.json())