52 lines
1.7 KiB
Python
52 lines
1.7 KiB
Python
import argparse
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from vllm import EngineArgs, LLMEngine, SamplingParams
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def main(args: argparse.Namespace):
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# Parse the CLI argument and initialize the engine.
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engine_args = EngineArgs.from_cli_args(args)
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engine = LLMEngine.from_engine_args(engine_args)
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# Test the following prompts.
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test_prompts = [
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("A robot may not injure a human being",
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SamplingParams(temperature=0.0, logprobs=1, prompt_logprobs=1)),
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("To be or not to be,",
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SamplingParams(temperature=0.8, top_k=5, presence_penalty=0.2)),
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("What is the meaning of life?",
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SamplingParams(n=2,
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best_of=5,
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temperature=0.8,
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top_p=0.95,
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frequency_penalty=0.1)),
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("It is only with the heart that one can see rightly",
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SamplingParams(n=3, best_of=3, use_beam_search=True,
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temperature=0.0)),
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]
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# Run the engine by calling `engine.step()` manually.
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request_id = 0
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while True:
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# To test continuous batching, we add one request at each step.
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if test_prompts:
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prompt, sampling_params = test_prompts.pop(0)
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engine.add_request(str(request_id), prompt, sampling_params)
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request_id += 1
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request_outputs = engine.step()
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for request_output in request_outputs:
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if request_output.finished:
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print(request_output)
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if not (engine.has_unfinished_requests() or test_prompts):
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break
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(
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description='Demo on using the LLMEngine class directly')
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parser = EngineArgs.add_cli_args(parser)
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args = parser.parse_args()
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main(args)
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