源代码 examples/online_serving/openai_cross_encoder_score.py.
OpenAI 交叉编码器评分#
# SPDX-License-Identifier: Apache-2.0
"""
Example online usage of Score API.
Run `vllm serve <model> --task score` to start up the server in vLLM.
"""
import argparse
import pprint
import requests
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
if __name__ == "__main__":
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="BAAI/bge-reranker-v2-m3")
args = parser.parse_args()
api_url = f"http://{args.host}:{args.port}/score"
model_name = args.model
text_1 = "What is the capital of Brazil?"
text_2 = "The capital of Brazil is Brasilia."
prompt = {"model": model_name, "text_1": text_1, "text_2": text_2}
score_response = post_http_request(prompt=prompt, api_url=api_url)
print("Prompt when text_1 and text_2 are both strings:")
pprint.pprint(prompt)
print("Score Response:")
pprint.pprint(score_response.json())
text_1 = "What is the capital of France?"
text_2 = [
"The capital of Brazil is Brasilia.", "The capital of France is Paris."
]
prompt = {"model": model_name, "text_1": text_1, "text_2": text_2}
score_response = post_http_request(prompt=prompt, api_url=api_url)
print("Prompt when text_1 is string and text_2 is a list:")
pprint.pprint(prompt)
print("Score Response:")
pprint.pprint(score_response.json())
text_1 = [
"What is the capital of Brazil?", "What is the capital of France?"
]
text_2 = [
"The capital of Brazil is Brasilia.", "The capital of France is Paris."
]
prompt = {"model": model_name, "text_1": text_1, "text_2": text_2}
score_response = post_http_request(prompt=prompt, api_url=api_url)
print("Prompt when text_1 and text_2 are both lists:")
pprint.pprint(prompt)
print("Score Response:")
pprint.pprint(score_response.json())