vllm/examples/offline_inference/llm_engine_example.py

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# SPDX-License-Identifier: Apache-2.0
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import argparse
from typing import List, Tuple
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from vllm import EngineArgs, LLMEngine, RequestOutput, SamplingParams
from vllm.utils import FlexibleArgumentParser
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def create_test_prompts() -> List[Tuple[str, SamplingParams]]:
"""Create a list of test prompts with their sampling parameters."""
return [
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("A robot may not injure a human being",
SamplingParams(temperature=0.0, logprobs=1, prompt_logprobs=1)),
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("To be or not to be,",
SamplingParams(temperature=0.8, top_k=5, presence_penalty=0.2)),
("What is the meaning of life?",
SamplingParams(n=2,
best_of=5,
temperature=0.8,
top_p=0.95,
frequency_penalty=0.1)),
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]
def process_requests(engine: LLMEngine,
test_prompts: List[Tuple[str, SamplingParams]]):
"""Continuously process a list of prompts and handle the outputs."""
request_id = 0
while test_prompts or engine.has_unfinished_requests():
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if test_prompts:
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: List[RequestOutput] = engine.step()
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for request_output in request_outputs:
if request_output.finished:
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print(request_output)
def initialize_engine(args: argparse.Namespace) -> LLMEngine:
"""Initialize the LLMEngine from the command line arguments."""
engine_args = EngineArgs.from_cli_args(args)
return LLMEngine.from_engine_args(engine_args)
def main(args: argparse.Namespace):
"""Main function that sets up and runs the prompt processing."""
engine = initialize_engine(args)
test_prompts = create_test_prompts()
process_requests(engine, test_prompts)
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if __name__ == '__main__':
parser = FlexibleArgumentParser(
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description='Demo on using the LLMEngine class directly')
parser = EngineArgs.add_cli_args(parser)
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args = parser.parse_args()
main(args)