Gahow Wang
445e491123
third_party/vllm/ now tracked in git for direct patch management.
Based on vLLM v0.18.1 release with one patch applied:
vllm/v1/core/sched/scheduler.py:
Replace fatal assert with graceful skip when KV transfer callback
arrives for an already-aborted request during PD disaggregated serving.
Future vLLM modifications should be made directly in third_party/vllm/
and committed normally. The patches/ directory is kept as documentation
of what changed from upstream.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
71 lines
2.0 KiB
Python
71 lines
2.0 KiB
Python
# SPDX-License-Identifier: Apache-2.0
|
|
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
|
|
import os
|
|
from urllib.request import urlopen
|
|
|
|
from vllm import LLM, SamplingParams
|
|
|
|
os.environ["VLLM_ALLOW_LONG_MAX_MODEL_LEN"] = "1"
|
|
|
|
|
|
def load_prompt() -> str:
|
|
# Test cases with various lengths can be found at:
|
|
#
|
|
# https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2.5-1M/test-data/64k.txt
|
|
# https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2.5-1M/test-data/200k.txt
|
|
# https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2.5-1M/test-data/600k.txt
|
|
# https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2.5-1M/test-data/1m.txt
|
|
|
|
with urlopen(
|
|
"https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2.5-1M/test-data/600k.txt",
|
|
timeout=5,
|
|
) as response:
|
|
prompt = response.read().decode("utf-8")
|
|
return prompt
|
|
|
|
|
|
# Processing the prompt.
|
|
def process_requests(llm: LLM, prompts: list[str]) -> None:
|
|
# Create a sampling params object.
|
|
sampling_params = SamplingParams(
|
|
temperature=0.7,
|
|
top_p=0.8,
|
|
top_k=20,
|
|
repetition_penalty=1.05,
|
|
detokenize=True,
|
|
max_tokens=256,
|
|
)
|
|
# Generate texts from the prompts.
|
|
outputs = llm.generate(prompts, sampling_params)
|
|
# Print the outputs.
|
|
for output in outputs:
|
|
prompt_token_ids = output.prompt_token_ids
|
|
generated_text = output.outputs[0].text
|
|
print(
|
|
f"Prompt length: {len(prompt_token_ids)}, "
|
|
f"Generated text: {generated_text!r}"
|
|
)
|
|
|
|
|
|
# Create an LLM.
|
|
def initialize_engine() -> LLM:
|
|
llm = LLM(
|
|
model="Qwen/Qwen2.5-7B-Instruct-1M",
|
|
max_model_len=1048576,
|
|
tensor_parallel_size=4,
|
|
enforce_eager=True,
|
|
enable_chunked_prefill=True,
|
|
max_num_batched_tokens=131072,
|
|
)
|
|
return llm
|
|
|
|
|
|
def main():
|
|
llm = initialize_engine()
|
|
prompt = load_prompt()
|
|
process_requests(llm, [prompt])
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|