# ========= Copyright 2023-2024 @ CAMEL-AI.org. 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.
# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
import logging
import threading
import time
from typing import Any, Dict, List, Optional, Union
from openai import OpenAI, Stream
from camel.configs import SGLANG_API_PARAMS, SGLangConfig
from camel.messages import OpenAIMessage
from camel.models import BaseModelBackend
from camel.types import (
ChatCompletion,
ChatCompletionChunk,
ModelType,
)
from camel.utils import BaseTokenCounter, OpenAITokenCounter
[docs]
class SGLangModel(BaseModelBackend):
r"""SGLang service interface.
Args:
model_type (Union[ModelType, str]): Model for which a backend is
created.
model_config_dict (Optional[Dict[str, Any]], optional): A dictionary
that will be fed into:obj:`openai.ChatCompletion.create()`. If
:obj:`None`, :obj:`SGLangConfig().as_dict()` will be used.
(default: :obj:`None`)
api_key (Optional[str], optional): The API key for authenticating with
the model service. SGLang doesn't need API key, it would be ignored
if set. (default: :obj:`None`)
url (Optional[str], optional): The url to the model service. If not
provided, :obj:`"http://127.0.0.1:30000/v1"` will be used.
(default: :obj:`None`)
token_counter (Optional[BaseTokenCounter], optional): Token counter to
use for the model. If not provided, :obj:`OpenAITokenCounter(
ModelType.GPT_4O_MINI)` will be used.
(default: :obj:`None`)
Reference: https://sgl-project.github.io/backend/openai_api_completions.html
"""
def __init__(
self,
model_type: Union[ModelType, str],
model_config_dict: Optional[Dict[str, Any]] = None,
api_key: Optional[str] = None,
url: Optional[str] = None,
token_counter: Optional[BaseTokenCounter] = None,
) -> None:
if model_config_dict is None:
model_config_dict = SGLangConfig().as_dict()
self.server_process = None
self.last_run_time: Optional[float] = (
None # Will be set when the server starts
)
self._lock = threading.Lock()
self._inactivity_thread: Optional[threading.Thread] = None
super().__init__(
model_type, model_config_dict, api_key, url, token_counter
)
self._client = None
if self._url:
# Initialize the client if an existing URL is provided
self._client = OpenAI(
timeout=180,
max_retries=3,
api_key="Set-but-ignored", # required but ignored
base_url=self._url,
)
def _start_server(self) -> None:
from sglang.utils import ( # type: ignore[import-untyped]
execute_shell_command,
wait_for_server,
)
try:
if not self._url:
cmd = (
f"python -m sglang.launch_server "
f"--model-path {self.model_type} "
f"--port 30000 "
f"--host 0.0.0.0"
)
server_process = execute_shell_command(cmd)
wait_for_server("http://localhost:30000")
self._url = "http://127.0.0.1:30000/v1"
self.server_process = server_process
# Start the inactivity monitor in a background thread
self._inactivity_thread = threading.Thread(
target=self._monitor_inactivity, daemon=True
)
self._inactivity_thread.start()
self.last_run_time = time.time()
# Initialize the client after the server starts
self._client = OpenAI(
timeout=180,
max_retries=3,
api_key="Set-but-ignored", # required but ignored
base_url=self._url,
)
except Exception as e:
raise RuntimeError(f"Failed to start SGLang server: {e}") from e
def _ensure_server_running(self) -> None:
r"""Ensures that the server is running. If not, starts the server."""
with self._lock:
if self.server_process is None:
self._start_server()
def _monitor_inactivity(self):
r"""Monitor whether the server process has been inactive for over 10
minutes.
"""
from sglang.utils import terminate_process
while True:
# Check every 10 seconds
time.sleep(10)
# Over 10 minutes
with self._lock:
# Over 10 minutes
if self.last_run_time and (
time.time() - self.last_run_time > 600
):
if self.server_process:
terminate_process(self.server_process)
self.server_process = None
self._client = None # Invalidate the client
logging.info(
"Server process terminated due to inactivity."
)
break
@property
def token_counter(self) -> BaseTokenCounter:
r"""Initialize the token counter for the model backend.
Returns:
BaseTokenCounter: The token counter following the model's
tokenization style.
"""
if not self._token_counter:
self._token_counter = OpenAITokenCounter(ModelType.GPT_4O_MINI)
return self._token_counter
[docs]
def check_model_config(self):
r"""Check whether the model configuration contains any
unexpected arguments to SGLang API.
Raises:
ValueError: If the model configuration dictionary contains any
unexpected arguments to OpenAI API.
"""
for param in self.model_config_dict:
if param not in SGLANG_API_PARAMS:
raise ValueError(
f"Unexpected argument `{param}` is "
"input into SGLang model backend."
)
[docs]
def run(
self,
messages: List[OpenAIMessage],
) -> Union[ChatCompletion, Stream[ChatCompletionChunk]]:
r"""Runs inference of OpenAI chat completion.
Args:
messages (List[OpenAIMessage]): Message list with the chat history
in OpenAI API format.
Returns:
Union[ChatCompletion, Stream[ChatCompletionChunk]]:
`ChatCompletion` in the non-stream mode, or
`Stream[ChatCompletionChunk]` in the stream mode.
"""
# Ensure server is running
self._ensure_server_running()
with self._lock:
# Update last run time
self.last_run_time = time.time()
if self._client is None:
raise RuntimeError(
"Client is not initialized. Ensure the server is running."
)
response = self._client.chat.completions.create(
messages=messages,
model=self.model_type,
**self.model_config_dict,
)
return response
@property
def stream(self) -> bool:
r"""Returns whether the model is in stream mode, which sends partial
results each time.
Returns:
bool: Whether the model is in stream mode.
"""
return self.model_config_dict.get('stream', False)
