Files
sglang/python/sglang/cli/utils.py
2025-11-06 14:45:50 +08:00

153 lines
5.1 KiB
Python

import hashlib
import json
import logging
import os
import tempfile
from typing import Optional
import filelock
from huggingface_hub import hf_hub_download
logger = logging.getLogger(__name__)
temp_dir = tempfile.gettempdir()
def _get_lock(model_name_or_path: str, cache_dir: Optional[str] = None):
lock_dir = cache_dir or temp_dir
os.makedirs(os.path.dirname(lock_dir), exist_ok=True)
model_name = model_name_or_path.replace("/", "-")
hash_name = hashlib.sha256(model_name.encode()).hexdigest()
lock_file_name = hash_name + model_name + ".lock"
lock = filelock.FileLock(os.path.join(lock_dir, lock_file_name), mode=0o666)
return lock
# Copied and adapted from hf_diffusers_utils.py
def _maybe_download_model(
model_name_or_path: str, local_dir: str | None = None, download: bool = True
) -> str:
"""
Resolve a model path. If it's a local directory, return it.
If it's a Hugging Face Hub ID, download only the config file
(`model_index.json` or `config.json`) and return its directory.
Args:
model_name_or_path: Local path or Hugging Face Hub model ID
local_dir: Local directory to save the downloaded file (if any)
download: Whether to download from Hugging Face Hub when needed
Returns:
Local directory path that contains the downloaded config file, or the original local directory.
"""
if os.path.exists(model_name_or_path):
logger.info("Model already exists locally")
return model_name_or_path
if not download:
return model_name_or_path
with _get_lock(model_name_or_path):
# Try `model_index.json` first (diffusers models)
try:
logger.info(
"Downloading model_index.json from HF Hub for %s...",
model_name_or_path,
)
file_path = hf_hub_download(
repo_id=model_name_or_path,
filename="model_index.json",
local_dir=local_dir,
)
logger.info("Downloaded to %s", file_path)
return os.path.dirname(file_path)
except Exception as e_index:
logger.debug("model_index.json not found or failed: %s", e_index)
# Fallback to `config.json`
try:
logger.info(
"Downloading config.json from HF Hub for %s...", model_name_or_path
)
file_path = hf_hub_download(
repo_id=model_name_or_path,
filename="config.json",
local_dir=local_dir,
)
logger.info("Downloaded to %s", file_path)
return os.path.dirname(file_path)
except Exception as e_config:
raise ValueError(
(
"Could not find model locally at %s and failed to download "
"model_index.json/config.json from HF Hub: %s"
)
% (model_name_or_path, e_config)
) from e_config
# Copied and adapted from hf_diffusers_utils.py
def is_diffusers_model_path(model_path: str) -> True:
"""
Verify if the model directory contains a valid diffusers configuration.
Args:
model_path: Path to the model directory
Returns:
The loaded model configuration as a dictionary if the model is a diffusers model
None if the model is not a diffusers model
"""
# Prefer model_index.json which indicates a diffusers pipeline
config_path = os.path.join(model_path, "model_index.json")
if not os.path.exists(config_path):
return False
# Load the config
with open(config_path) as f:
config = json.load(f)
# Verify diffusers version exists
if "_diffusers_version" not in config:
return False
return True
def get_is_diffusion_model(model_path: str):
model_path = _maybe_download_model(model_path)
is_diffusion_model = is_diffusers_model_path(model_path)
if is_diffusion_model:
logger.info("Diffusion model detected")
return is_diffusion_model
def get_model_path(extra_argv):
# Find the model_path argument
model_path = None
for i, arg in enumerate(extra_argv):
if arg == "--model-path":
if i + 1 < len(extra_argv):
model_path = extra_argv[i + 1]
break
elif arg.startswith("--model-path="):
model_path = arg.split("=", 1)[1]
break
if model_path is None:
# Fallback for --help or other cases where model-path is not provided
if any(h in extra_argv for h in ["-h", "--help"]):
raise Exception(
"Usage: sglang serve --model-path <model-name-or-path> [additional-arguments]\n\n"
"This command can launch either a standard language model server or a diffusion model server.\n"
"The server type is determined by the model path.\n"
"For specific arguments, please provide a model_path."
)
else:
raise Exception(
"Error: --model-path is required. "
"Please provide the path to the model."
)
return model_path