File size: 2,187 Bytes
14a19cc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 | #!/usr/bin/env python3
"""Run PertMind with vLLM."""
from __future__ import annotations
import argparse
from vllm import LLM, SamplingParams
DEFAULT_SYSTEM_PROMPT = (
"You are PertMind, a biomedical assistant. For biomedical prediction, "
"screen-ranking, or gene-set interpretation tasks, answer first and then "
"provide a concise explanation. Use this style when applicable:\n"
"Final Answer: <answer>\nExplanation: <brief explanation>"
)
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--model", default=".", help="Path or Hugging Face model id.")
parser.add_argument("--prompt", required=True, help="User prompt.")
parser.add_argument("--system-prompt", default=DEFAULT_SYSTEM_PROMPT)
parser.add_argument("--max-tokens", type=int, default=768)
parser.add_argument("--temperature", type=float, default=0.0)
parser.add_argument("--top-p", type=float, default=0.95)
parser.add_argument("--max-model-len", type=int, default=12288)
parser.add_argument("--gpu-memory-utilization", type=float, default=0.85)
return parser.parse_args()
def main() -> int:
args = parse_args()
llm = LLM(
model=args.model,
trust_remote_code=True,
dtype="bfloat16",
max_model_len=args.max_model_len,
gpu_memory_utilization=args.gpu_memory_utilization,
)
tokenizer = llm.get_tokenizer()
messages = [
{"role": "system", "content": args.system_prompt},
{"role": "user", "content": args.prompt},
]
try:
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True,
enable_thinking=False,
)
except TypeError:
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
params = SamplingParams(
temperature=args.temperature,
top_p=args.top_p,
max_tokens=args.max_tokens,
)
output = llm.generate([text], params)[0].outputs[0].text.strip()
print(output)
return 0
if __name__ == "__main__":
raise SystemExit(main())
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