# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import argparse import logging import sys import time from nemo.deploy.nlp import NemoQueryLLMPyTorch LOGGER = logging.getLogger("NeMo") def get_args(argv): parser = argparse.ArgumentParser( formatter_class=argparse.ArgumentDefaultsHelpFormatter, description=f"Queries Triton server running an in-framework Nemo model", ) parser.add_argument("-u", "--url", default="0.0.0.0", type=str, help="url for the triton server") parser.add_argument("-mn", "--model_name", required=True, type=str, help="Name of the triton model") prompt_group = parser.add_mutually_exclusive_group(required=True) prompt_group.add_argument("-p", "--prompt", required=False, type=str, help="Prompt") prompt_group.add_argument("-pf", "--prompt_file", required=False, type=str, help="File to read the prompt from") parser.add_argument("-mol", "--max_output_len", default=128, type=int, help="Max output token length") parser.add_argument("-tk", "--top_k", default=1, type=int, help="top_k") parser.add_argument("-tpp", "--top_p", default=0.0, type=float, help="top_p") parser.add_argument("-t", "--temperature", default=1.0, type=float, help="temperature") parser.add_argument("-it", "--init_timeout", default=60.0, type=float, help="init timeout for the triton server") parser.add_argument("-clp", "--compute_logprob", default=None, action='store_true', help="Returns log_probs") args = parser.parse_args(argv) return args def query_llm( url, model_name, prompts, max_output_len=128, top_k=1, top_p=0.0, temperature=1.0, compute_logprob=None, init_timeout=60.0, ): start_time = time.time() nemo_query = NemoQueryLLMPyTorch(url, model_name) result = nemo_query.query_llm( prompts=prompts, max_length=max_output_len, top_k=top_k, top_p=top_p, temperature=temperature, compute_logprob=compute_logprob, init_timeout=init_timeout, ) end_time = time.time() LOGGER.info(f"Query execution time: {end_time - start_time:.2f} seconds") return result def query(argv): args = get_args(argv) if args.prompt_file is not None: with open(args.prompt_file, "r") as f: args.prompt = f.read() outputs = query_llm( url=args.url, model_name=args.model_name, prompts=[args.prompt], max_output_len=args.max_output_len, top_k=args.top_k, top_p=args.top_p, temperature=args.temperature, compute_logprob=args.compute_logprob, init_timeout=args.init_timeout, ) print(outputs) if __name__ == '__main__': query(sys.argv[1:])