154 lines
4.7 KiB
Python
154 lines
4.7 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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#
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# A very basic example of sglang worker handling pre-processed requests.
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#
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# Dynamo does the HTTP handling, prompt templating and tokenization, then forwards the
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# request via NATS to this python script, which runs sglang.
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#
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# The key differences between this and `server_sglang_tok.py` are:
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# - The `register_llm` function registers us a `Chat` and `Completions` model that accepts `Tokens` input
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# - The `generate` function receives a pre-tokenized request and must return token_ids in the response.
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#
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# Setup a virtualenv with dynamo.llm, dynamo.runtime and sglang[all] installed
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# in lib/bindings/python `maturin develop` and `pip install -e .` should do it
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# Start nats and etcd:
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# - nats-server -js
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#
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# Window 1: `python server_sglang.py`. Wait for log "Starting endpoint".
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# Window 2: `dynamo-run out=dyn
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import argparse
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import asyncio
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import sys
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import sglang
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import uvloop
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from sglang.srt.server_args import ServerArgs
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from dynamo.llm import ModelInput, ModelType, register_llm
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from dynamo.runtime import DistributedRuntime, dynamo_worker
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DEFAULT_ENDPOINT = "dyn://dynamo.backend.generate"
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DEFAULT_MODEL = "Qwen/Qwen3-0.6B"
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DEFAULT_TEMPERATURE = 0.7
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class Config:
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"""Command line parameters or defaults"""
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namespace: str
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component: str
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endpoint: str
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model: str
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class RequestHandler:
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"""
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Request handler for the generate endpoint
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"""
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def __init__(self, engine):
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self.engine_client = engine
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async def generate(self, request):
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# print(f"Received request: {request}")
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sampling_params = {
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"temperature": request["sampling_options"]["temperature"]
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or DEFAULT_TEMPERATURE,
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# sglang defaults this to 128
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"max_new_tokens": request["stop_conditions"]["max_tokens"],
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}
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num_output_tokens_so_far = 0
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gen = await self.engine_client.async_generate(
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input_ids=request["token_ids"], sampling_params=sampling_params, stream=True
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)
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async for res in gen:
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# res is a dict
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finish_reason = res["meta_info"]["finish_reason"]
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if finish_reason:
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# Don't forward the stop token
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out = {"token_ids": [], "finish_reason": finish_reason["type"]}
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else:
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next_total_toks = len(res["output_ids"])
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out = {"token_ids": res["output_ids"][num_output_tokens_so_far:]}
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yield out
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num_output_tokens_so_far = next_total_toks
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@dynamo_worker(static=False)
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async def worker(runtime: DistributedRuntime):
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await init(runtime, cmd_line_args())
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async def init(runtime: DistributedRuntime, config: Config):
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"""
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Instantiate and serve
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"""
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component = runtime.namespace(config.namespace).component(config.component)
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await component.create_service()
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endpoint = component.endpoint(config.endpoint)
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await register_llm(
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ModelInput.Tokens,
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ModelType.Chat | ModelType.Completions,
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endpoint,
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config.model,
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)
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engine_args = ServerArgs(
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model_path=config.model,
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skip_tokenizer_init=True,
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)
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engine_client = sglang.Engine(server_args=engine_args)
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# the server will gracefully shutdown (i.e., keep opened TCP streams finishes)
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# after the lease is revoked
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await endpoint.serve_endpoint(RequestHandler(engine_client).generate)
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def cmd_line_args():
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parser = argparse.ArgumentParser(
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description="SGLang server integrated with Dynamo runtime."
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)
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parser.add_argument(
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"--endpoint",
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type=str,
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default=DEFAULT_ENDPOINT,
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help=f"Dynamo endpoint string in 'dyn://namespace.component.endpoint' format. Default: {DEFAULT_ENDPOINT}",
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)
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parser.add_argument(
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"--model",
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type=str,
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default=DEFAULT_MODEL,
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help=f"Path to disk model or HuggingFace model identifier to load. Default: {DEFAULT_MODEL}",
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)
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args = parser.parse_args()
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config = Config()
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config.model = args.model
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endpoint_str = args.endpoint.replace("dyn://", "", 1)
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endpoint_parts = endpoint_str.split(".")
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if len(endpoint_parts) != 3:
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print(
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f"Invalid endpoint format: '{args.endpoint}'. Expected 'dyn://namespace.component.endpoint' or 'namespace.component.endpoint'."
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)
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sys.exit(1)
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parsed_namespace, parsed_component_name, parsed_endpoint_name = endpoint_parts
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config.namespace = parsed_namespace
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config.component = parsed_component_name
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config.endpoint = parsed_endpoint_name
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return config
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if __name__ == "__main__":
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uvloop.install()
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asyncio.run(worker())
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