| |
| import os |
|
|
| from openai import OpenAI |
|
|
| os.environ['CUDA_VISIBLE_DEVICES'] = '0' |
|
|
|
|
| def infer(client, model: str, messages): |
| resp = client.chat.completions.create(model=model, messages=messages) |
| scores = resp.choices[0].message.content |
| print(f'messages: {messages}') |
| print(f'scores: {scores}') |
| return scores |
|
|
|
|
| def run_client(host: str = '127.0.0.1', port: int = 8000): |
| client = OpenAI( |
| api_key='EMPTY', |
| base_url=f'http://{host}:{port}/v1', |
| ) |
| model = client.models.list().data[0].id |
| print(f'model: {model}') |
|
|
| messages = [{ |
| 'role': 'user', |
| 'content': 'what is the capital of China?', |
| }, { |
| 'role': 'assistant', |
| 'content': 'Beijing.', |
| }] |
| infer(client, model, messages) |
|
|
|
|
| if __name__ == '__main__': |
| from swift.llm import run_deploy, DeployArguments |
| with run_deploy( |
| DeployArguments( |
| model='Qwen/Qwen3-Reranker-0.6B', |
| task_type='generative_reranker', |
| infer_backend='vllm', |
| gpu_memory_utilization=0.7, |
| verbose=False, |
| log_interval=-1)) as port: |
| run_client(port=port) |
|
|
