""" Run one test prompt. Usage: python3 -m sglang.test.send_one python3 -m sglang.test.send_one --profile --profile-steps 5 python3 -m sglang.test.send_one --profile --profile-by-stage """ import argparse import dataclasses import json from typing import Optional import requests import tabulate from sglang.profiler import run_profile @dataclasses.dataclass class BenchArgs: host: str = "localhost" port: int = 30000 batch_size: int = 1 different_prompts: bool = False seed: Optional[int] = None temperature: float = 0.0 max_new_tokens: int = 512 frequency_penalty: float = 0.0 presence_penalty: float = 0.0 json: bool = False return_logprob: bool = False prompt: str = ( "Human: Give me a fully functional FastAPI server. Show the python code.\n\nAssistant:" ) image: bool = False many_images: bool = False stream: bool = False profile: bool = False profile_steps: int = 3 profile_by_stage: bool = False profile_prefix: Optional[str] = None @staticmethod def add_cli_args(parser: argparse.ArgumentParser): parser.add_argument("--host", type=str, default=BenchArgs.host) parser.add_argument("--port", type=int, default=BenchArgs.port) parser.add_argument("--batch-size", type=int, default=BenchArgs.batch_size) parser.add_argument( "--different-prompts", action="store_true", default=BenchArgs.different_prompts, ) parser.add_argument("--seed", type=int, default=BenchArgs.seed) parser.add_argument("--temperature", type=float, default=BenchArgs.temperature) parser.add_argument( "--max-new-tokens", type=int, default=BenchArgs.max_new_tokens ) parser.add_argument( "--frequency-penalty", type=float, default=BenchArgs.frequency_penalty ) parser.add_argument( "--presence-penalty", type=float, default=BenchArgs.presence_penalty ) parser.add_argument("--json", action="store_true") parser.add_argument("--return-logprob", action="store_true") parser.add_argument("--prompt", type=str, default=BenchArgs.prompt) parser.add_argument("--image", action="store_true") parser.add_argument("--many-images", action="store_true") parser.add_argument("--stream", action="store_true") parser.add_argument("--profile", action="store_true") parser.add_argument( "--profile-steps", type=int, default=BenchArgs.profile_steps ) parser.add_argument("--profile-by-stage", action="store_true") parser.add_argument( "--profile-prefix", type=str, default=BenchArgs.profile_prefix ) @classmethod def from_cli_args(cls, args: argparse.Namespace): attrs = [attr.name for attr in dataclasses.fields(cls)] return cls(**{attr: getattr(args, attr) for attr in attrs}) def send_one_prompt(args: BenchArgs): base_url = f"http://{args.host}:{args.port}" # Construct the input if args.image: args.prompt = ( "Human: Describe this image in a very short sentence.\n\nAssistant:" ) image_data = "https://raw.githubusercontent.com/sgl-project/sglang/main/examples/assets/example_image.png" elif args.many_images: args.prompt = ( "Human: I have one reference image and many images." "Describe their relationship in a very short sentence.\n\nAssistant:" ) image_data = [ "https://raw.githubusercontent.com/sgl-project/sglang/main/examples/assets/example_image.png", "https://raw.githubusercontent.com/sgl-project/sglang/main/examples/assets/example_image.png", "https://raw.githubusercontent.com/sgl-project/sglang/main/examples/assets/example_image.png", "https://raw.githubusercontent.com/sgl-project/sglang/main/examples/assets/example_image.png", ] else: image_data = None prompt = args.prompt if args.json: prompt = ( "Human: What is the capital of France and how is that city like. " "Give me 3 trivial information about that city. " "Write in a format of json.\nAssistant:" ) json_schema = "$$ANY$$" else: json_schema = None if args.batch_size > 1: if not args.different_prompts: prompt = [prompt] * args.batch_size else: prompt = [f"Test case {i+1}: " + prompt for i in range(args.batch_size)] json_data = { "text": prompt, "image_data": image_data, "sampling_params": { "sampling_seed": args.seed, "temperature": args.temperature, "max_new_tokens": args.max_new_tokens, "frequency_penalty": args.frequency_penalty, "presence_penalty": args.presence_penalty, "json_schema": json_schema, "stop": ["Question", "Assistant:", "<|separator|>", "<|eos|>"], }, "return_logprob": args.return_logprob, "stream": args.stream, } # Run profiler if requested if args.profile: print(f"Running profiler with {args.profile_steps} steps...") run_profile( url=base_url, num_steps=args.profile_steps, activities=["CPU", "GPU"], profile_by_stage=args.profile_by_stage, profile_prefix=args.profile_prefix, ) # Send the request response = requests.post( f"{base_url}/generate", json=json_data, stream=args.stream, ) if args.stream: last_len = 0 for chunk in response.iter_lines(decode_unicode=False): chunk = chunk.decode("utf-8") if chunk and chunk.startswith("data:"): if chunk == "data: [DONE]": break ret = json.loads(chunk[5:].strip("\n")) chunk_str = ret["text"][last_len:] last_len = len(ret["text"]) print(chunk_str, end="", flush=True) else: ret = response.json() if args.batch_size > 1: ret = ret[0] if response.status_code != 200: print(ret) return 0, 0 # Print results if "spec_verify_ct" in ret["meta_info"] and ret["meta_info"]["spec_verify_ct"] > 0: acc_length = ( ret["meta_info"]["completion_tokens"] / ret["meta_info"]["spec_verify_ct"] ) else: acc_length = 1.0 latency = ret["meta_info"]["e2e_latency"] speed = ret["meta_info"]["completion_tokens"] / latency tokens = ret["meta_info"]["completion_tokens"] if not args.stream: print(ret["text"]) print() headers = ["Latency (s)", "Tokens", "Acc Length", "Speed (token/s)"] rows = [[f"{latency:.3f}", f"{tokens}", f"{acc_length:.3f}", f"{speed:.2f}"]] msg = tabulate.tabulate(rows, headers=headers, tablefmt="pretty") print(msg) return acc_length, speed if __name__ == "__main__": parser = argparse.ArgumentParser() BenchArgs.add_cli_args(parser) args = BenchArgs.from_cli_args(parser.parse_args()) send_one_prompt(args)