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