backtrader/llm_manager.py

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from typing import Optional
import requests
from config_manager import get_config_manager
from logger_manager import get_logger
config_manager = get_config_manager()
logger = get_logger()
class LLMManager:
"""LLM管理器负责加载API配置并提供与LLM交互的功能"""
_instance = None # 单例实例
def __init__(self):
self._api_key = None
self._api_base = None
self._model = None
self._temperature = None
def __new__(cls):
"""实现单例模式"""
if cls._instance is None:
cls._instance = super(LLMManager, cls).__new__(cls)
cls._instance._config = None
cls._instance._api_key = None
cls._instance._api_base = None
cls._instance._model = None
cls._instance._provider = None
return cls._instance
def initialize(self):
"""初始化LLM配置"""
llm_config = config_manager.get('llm', {})
# 加载LLM配置
self._api_key = llm_config.get('api_key', '')
self._api_base = llm_config.get('api_base', 'https://api.openai.com/v1')
self._model = llm_config.get('model', 'gpt-3.5-turbo')
self._temperature = llm_config.get('temperature', 0.7)
if not self._api_key:
logger.warning("警告: LLM API密钥未配置请在config.yaml中设置。")
def chat(self, content: str, prompt: Optional[str] = None) -> str:
"""
与LLM进行对话
Args:
content: 用户输入内容
prompt: 可选的系统提示词
Returns:
LLM的回复内容
"""
if self._config is None:
self.initialize()
headers = {
"Authorization": f"Bearer {self._api_key}",
"Content-Type": "application/json"
}
messages = []
# 添加系统提示(如果有)
if prompt:
messages.append({"role": "system", "content": prompt})
# 添加用户消息
messages.append({"role": "user", "content": content})
payload = {
"model": self._model,
"messages": messages,
"temperature": self._temperature,
}
logger.debug(f"请求数据: {payload}")
response = requests.post(
f"{self._api_base}/chat/completions",
headers=headers,
json=payload
)
if response.status_code != 200:
logger.info(f"请求失败: {response.status_code}, {response.text}")
return "请求失败,请稍后再试。"
return response.json()["choices"][0]["message"]["content"]
# 提供简单的访问函数
def get_llm_manager() -> LLMManager:
"""获取LLM管理器实例"""
return LLMManager()