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chore: import upstream snapshot with attribution
2026-07-13 12:38:16 +08:00

550 lines
18 KiB
Python

import atexit
import json
import multiprocessing
import time
import warnings
from typing import Dict, List, Optional, Union
import aiohttp
import requests
from sglang.global_config import global_config
from sglang.lang.backend.base_backend import BaseBackend
from sglang.lang.chat_template import get_chat_template, get_chat_template_by_model_path
from sglang.lang.choices import ChoicesDecision, ChoicesSamplingMethod
from sglang.lang.interpreter import StreamExecutor
from sglang.lang.ir import (
REGEX_BOOL,
REGEX_FLOAT,
REGEX_INT,
REGEX_STR,
SglSamplingParams,
)
from sglang.utils import http_request
class RuntimeEndpoint(BaseBackend):
def __init__(
self,
base_url: str,
api_key: Optional[str] = None,
verify: Optional[str] = None,
chat_template_name: Optional[str] = None,
):
super().__init__()
self.support_concate_and_append = True
self.base_url = base_url
self.api_key = api_key
self.verify = verify
res = http_request(
self.base_url + "/get_model_info",
api_key=self.api_key,
verify=self.verify,
)
self._assert_success(res)
self.model_info = res.json()
if chat_template_name:
self.chat_template = get_chat_template(chat_template_name)
else:
self.chat_template = get_chat_template_by_model_path(
self.model_info["model_path"]
)
def get_model_name(self):
return self.model_info["model_path"]
def flush_cache(self):
res = http_request(
self.base_url + "/flush_cache",
api_key=self.api_key,
verify=self.verify,
method="POST",
)
self._assert_success(res)
def get_server_info(self):
res = http_request(
self.base_url + "/server_info",
api_key=self.api_key,
verify=self.verify,
)
self._assert_success(res)
return res.json()
def get_chat_template(self):
return self.chat_template
def cache_prefix(self, prefix_str: str):
res = http_request(
self.base_url + "/generate",
json={"text": prefix_str, "sampling_params": {"max_new_tokens": 0}},
api_key=self.api_key,
verify=self.verify,
)
self._assert_success(res)
def start_profile(self):
res = http_request(
self.base_url + "/start_profile",
api_key=self.api_key,
verify=self.verify,
)
self._assert_success(res)
def stop_profile(self):
res = http_request(
self.base_url + "/stop_profile",
api_key=self.api_key,
verify=self.verify,
)
self._assert_success(res)
def commit_lazy_operations(self, s: StreamExecutor):
data = {"text": s.text_, "sampling_params": {"max_new_tokens": 0}}
self._add_images(s, data)
res = http_request(
self.base_url + "/generate",
json=data,
api_key=self.api_key,
verify=self.verify,
)
self._assert_success(res)
def fill_image(self, s: StreamExecutor):
data = {"text": s.text_, "sampling_params": {"max_new_tokens": 0}}
self._add_images(s, data)
res = http_request(
self.base_url + "/generate",
json=data,
api_key=self.api_key,
verify=self.verify,
)
self._assert_success(res)
def _handle_dtype_to_regex(self, sampling_params: SglSamplingParams):
if sampling_params.dtype is None:
return
if sampling_params.stop == ():
sampling_params.stop = []
dtype_regex = None
if sampling_params.dtype in ["int", int]:
dtype_regex = REGEX_INT
sampling_params.stop.extend([" ", "\n"])
elif sampling_params.dtype in ["float", float]:
dtype_regex = REGEX_FLOAT
sampling_params.stop.extend([" ", "\n"])
elif sampling_params.dtype in ["str", str]:
dtype_regex = REGEX_STR
elif sampling_params.dtype in ["bool", bool]:
dtype_regex = REGEX_BOOL
else:
raise RuntimeError(f"Invalid dtype: {sampling_params.dtype}")
if dtype_regex is not None and sampling_params.regex is not None:
warnings.warn(
f"Both dtype and regex are set. Only dtype will be used. dtype: {sampling_params.dtype}, regex: {sampling_params.regex}"
)
sampling_params.regex = dtype_regex
def generate(
self,
s: StreamExecutor,
sampling_params: SglSamplingParams,
):
self._handle_dtype_to_regex(sampling_params)
data = {
"text": s.text_,
"sampling_params": {
"skip_special_tokens": global_config.skip_special_tokens_in_output,
"spaces_between_special_tokens": global_config.spaces_between_special_tokens_in_out,
**sampling_params.to_srt_kwargs(),
},
}
for item in [
"return_logprob",
"logprob_start_len",
"top_logprobs_num",
"return_text_in_logprobs",
]:
value = getattr(sampling_params, item, None)
if value is not None:
data[item] = value
self._add_images(s, data)
res = http_request(
self.base_url + "/generate",
json=data,
api_key=self.api_key,
verify=self.verify,
)
self._assert_success(res)
obj = res.json()
comp = obj["text"]
return comp, obj["meta_info"]
def generate_stream(
self,
s: StreamExecutor,
sampling_params: SglSamplingParams,
):
self._handle_dtype_to_regex(sampling_params)
data = {
"text": s.text_,
"sampling_params": {
"skip_special_tokens": global_config.skip_special_tokens_in_output,
"spaces_between_special_tokens": global_config.spaces_between_special_tokens_in_out,
**sampling_params.to_srt_kwargs(),
},
}
for item in [
"return_logprob",
"logprob_start_len",
"top_logprobs_num",
"return_text_in_logprobs",
]:
value = getattr(sampling_params, item, None)
if value is not None:
data[item] = value
data["stream"] = True
self._add_images(s, data)
res = http_request(
self.base_url + "/generate",
json=data,
stream=True,
api_key=self.api_key,
verify=self.verify,
)
self._assert_success(res)
pos = 0
for chunk in res.iter_lines(decode_unicode=False):
chunk = chunk.decode("utf-8")
if chunk and chunk.startswith("data:"):
if chunk == "data: [DONE]":
break
data = json.loads(chunk[5:].strip("\n"))
chunk_text = data["text"][pos:]
meta_info = data["meta_info"]
pos += len(chunk_text)
yield chunk_text, meta_info
def select(
self,
s: StreamExecutor,
choices: List[str],
temperature: float,
choices_method: ChoicesSamplingMethod,
) -> ChoicesDecision:
assert temperature <= 1e-5
# Cache common prefix
data = {"text": s.text_, "sampling_params": {"max_new_tokens": 0}}
obj = self._generate_http_request(s, data)
prompt_len = obj["meta_info"]["prompt_tokens"]
logprob_start_len = max(prompt_len - 2, 0) # For token healing
# Compute logprob
data = {
"text": [s.text_ + c for c in choices],
"sampling_params": {
"max_new_tokens": 0,
"temperature": 0,
},
"return_logprob": True,
"return_text_in_logprobs": True,
"logprob_start_len": logprob_start_len,
}
obj = self._generate_http_request(s, data)
input_token_logprobs = [r["meta_info"]["input_token_logprobs"] for r in obj]
output_token_logprobs = [r["meta_info"]["output_token_logprobs"] for r in obj]
normalized_prompt_logprobs = [
compute_normalized_prompt_logprobs(r["meta_info"]["input_token_logprobs"])
for r in obj
]
# Remove extra token if no token healing occurred
for i in range(len(input_token_logprobs)):
healed_token_str = input_token_logprobs[i][0][-1]
if s.text_.endswith(healed_token_str):
healed_token_logprob = input_token_logprobs[i][0][0]
normalized_prompt_logprobs[i] = (
normalized_prompt_logprobs[i] * len(input_token_logprobs[i])
- healed_token_logprob
) / (len(input_token_logprobs[i]) - 1)
input_token_logprobs[i] = input_token_logprobs[i][1:]
# Compute unconditional logprobs if required
if choices_method.requires_unconditional_logprobs:
input_ids = [[el[1] for el in subl] for subl in input_token_logprobs]
data = {
"input_ids": input_ids,
"sampling_params": {"max_new_tokens": 0},
"return_logprob": True,
}
obj = self._generate_http_request(s, data)
unconditional_token_logprobs = [
r["meta_info"]["input_token_logprobs"] for r in obj
]
else:
unconditional_token_logprobs = None
return choices_method(
choices=choices,
normalized_prompt_logprobs=normalized_prompt_logprobs,
input_token_logprobs=input_token_logprobs,
output_token_logprobs=output_token_logprobs,
unconditional_token_logprobs=unconditional_token_logprobs,
)
def concatenate_and_append(self, src_rids: List[str], dst_rid: str):
res = http_request(
self.base_url + "/concate_and_append_request",
json={"src_rids": src_rids, "dst_rid": dst_rid},
api_key=self.api_key,
verify=self.verify,
)
self._assert_success(res)
def _generate_http_request(self, s: StreamExecutor, data):
self._add_images(s, data)
res = http_request(
self.base_url + "/generate",
json=data,
api_key=self.api_key,
verify=self.verify,
)
self._assert_success(res)
return res.json()
def _add_images(self, s: StreamExecutor, data):
if s.images_:
assert len(s.images_) == 1, "Only support one image."
data["image_data"] = s.images_[0][1]
def _assert_success(self, res):
if res.status_code != 200:
try:
content = res.json()
except json.JSONDecodeError:
content = res.text
raise RuntimeError(content)
def compute_normalized_prompt_logprobs(input_logprobs):
values = [x[0] for x in input_logprobs if x[0]]
return sum(values) / len(values)
class Runtime:
"""
A wrapper for the HTTP server.
This is used for launching the server in a python program without
using the command line interface.
It is mainly used for the frontend language.
You should use the Engine class if you want to do normal offline processing without the frontend language.
"""
def __init__(
self,
log_level: str = "error",
launch_timeout: float = 300.0,
*args,
**kwargs,
):
"""See the arguments in server_args.py::ServerArgs
Args:
log_level: Log level for the server.
timeout: Timeout in seconds for waiting for the server to start.
*args: Additional arguments passed to ServerArgs.
**kwargs: Additional keyword arguments passed to ServerArgs.
"""
# We delay the import of any `sglang.srt` components in `sglang.lang`, so users can run
# client code without installing SRT server and its dependency if they want.
from sglang.srt.entrypoints.http_server import launch_server
from sglang.srt.server_args import ServerArgs
from sglang.srt.utils.network import is_port_available
self.server_args = ServerArgs(*args, log_level=log_level, **kwargs)
# Pre-allocate ports
for port in range(self.server_args.port, 40000):
if is_port_available(port):
break
self.server_args.override("runtime_endpoint.port_alloc", port=port)
self.url = self.server_args.url()
self.generate_url = self.url + "/generate"
# NOTE: We store pid instead of proc to fix some issues during __delete__
self.pid = None
ctx = multiprocessing.get_context("spawn")
proc = ctx.Process(
target=launch_server,
args=(self.server_args,),
)
proc.start()
self.pid = proc.pid
# Before python program terminates, call shutdown implicitly. Therefore, users don't have to explicitly call .shutdown()
atexit.register(self.shutdown)
# Wait for server to be ready by polling /health_generate
start_time = time.time()
with requests.Session() as session:
while time.time() - start_time < launch_timeout:
try:
response = session.get(f"{self.url}/health_generate")
if response.status_code == 200:
break
except requests.RequestException:
pass
if not proc.is_alive():
self.shutdown()
raise RuntimeError(
"Initialization failed. Please see the error messages above."
)
time.sleep(2)
else:
self.shutdown()
raise TimeoutError("Server failed to start within the timeout period.")
self.endpoint = RuntimeEndpoint(self.url)
def shutdown(self):
from sglang.srt.utils import kill_process_tree
if self.pid is not None:
kill_process_tree(self.pid)
self.pid = None
def start_profile(self):
self.endpoint.start_profile()
def stop_profile(self):
self.endpoint.stop_profile()
def cache_prefix(self, prefix: str):
self.endpoint.cache_prefix(prefix)
def get_tokenizer(self):
from sglang.srt.utils.hf_transformers_utils import get_tokenizer
return get_tokenizer(
self.server_args.tokenizer_path,
tokenizer_mode=self.server_args.tokenizer_mode,
trust_remote_code=self.server_args.trust_remote_code,
revision=self.server_args.revision,
)
async def async_generate(
self,
prompt: str,
sampling_params: Optional[Dict] = None,
session_id: Optional[str] = None,
):
if self.server_args.skip_tokenizer_init:
json_data = {
"input_ids": prompt,
"sampling_params": sampling_params,
"stream": True,
"session_id": session_id,
}
else:
json_data = {
"text": prompt,
"sampling_params": sampling_params,
"stream": True,
"session_id": session_id,
}
pos = 0
timeout = aiohttp.ClientTimeout(total=3 * 3600)
async with aiohttp.ClientSession(timeout=timeout, trust_env=True) as session:
async with session.post(self.generate_url, json=json_data) as response:
async for chunk, _ in response.content.iter_chunks():
chunk = chunk.decode("utf-8")
if chunk and chunk.startswith("data:"):
if chunk == "data: [DONE]\n\n":
break
data = json.loads(chunk[5:].strip("\n"))
if "text" in data:
cur = data["text"][pos:]
if cur:
yield cur
pos += len(cur)
else:
yield data
add_request = async_generate
def generate(
self,
prompt: Union[str, List[str]],
sampling_params: Optional[Dict] = None,
return_logprob: Optional[Union[List[bool], bool]] = False,
logprob_start_len: Optional[Union[List[int], int]] = None,
top_logprobs_num: Optional[Union[List[int], int]] = None,
lora_path: Optional[List[Optional[str]]] = None,
session_id: Optional[str] = None,
):
json_data = {
"text": prompt,
"sampling_params": sampling_params,
"return_logprob": return_logprob,
"logprob_start_len": logprob_start_len,
"top_logprobs_num": top_logprobs_num,
"lora_path": lora_path,
"session_id": session_id,
}
assert not isinstance(lora_path, list) or len(lora_path) == len(prompt)
response = requests.post(
self.url + "/generate",
json=json_data,
)
return json.dumps(response.json())
def encode(
self,
prompt: Union[str, List[str], List[Dict], List[List[Dict]]],
):
json_data = {"text": prompt}
response = requests.post(self.url + "/encode", json=json_data)
return json.dumps(response.json())
async def get_server_info(self):
async with aiohttp.ClientSession() as session:
async with session.get(f"{self.url}/server_info") as response:
if response.status == 200:
return await response.json()
else:
error_data = await response.json()
raise RuntimeError(
f"Failed to get server info. {error_data['error']['message']}"
)
def __del__(self):
self.shutdown()