114 lines
3.6 KiB
Python
114 lines
3.6 KiB
Python
"""
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Gemini LLM实现
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使用Gemini 2.5-pro中转API进行文本生成
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"""
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import os
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import sys
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from typing import Optional, Dict, Any
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from openai import OpenAI
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from .base import BaseLLM
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# 添加utils目录到Python路径并导入重试模块
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try:
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current_dir = os.path.dirname(os.path.abspath(__file__))
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root_dir = os.path.dirname(os.path.dirname(current_dir))
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utils_dir = os.path.join(root_dir, 'utils')
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if utils_dir not in sys.path:
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sys.path.append(utils_dir)
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from retry_helper import with_retry, with_graceful_retry, LLM_RETRY_CONFIG
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except ImportError:
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# 如果无法导入重试模块，使用空装饰器避免报错
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def with_retry(config):
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def decorator(func):
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return func
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return decorator
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LLM_RETRY_CONFIG = None
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class GeminiLLM(BaseLLM):
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"""Gemini LLM实现类"""
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def __init__(self, api_key: Optional[str] = None, model_name: Optional[str] = None):
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"""
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初始化Gemini客户端
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Args:
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api_key: Gemini API密钥，如果不提供则从环境变量读取
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model_name: 模型名称，默认使用gemini-2.5-pro
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"""
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if api_key is None:
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api_key = os.getenv("GEMINI_API_KEY")
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if not api_key:
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raise ValueError("Gemini API Key未找到！请设置GEMINI_API_KEY环境变量或在初始化时提供")
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super().__init__(api_key, model_name)
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# 初始化OpenAI客户端，使用Gemini的中转endpoint
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self.client = OpenAI(
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api_key=self.api_key,
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base_url="https://www.chataiapi.com/v1"
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)
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self.default_model = model_name or self.get_default_model()
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def get_default_model(self) -> str:
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"""获取默认模型名称"""
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return "gemini-2.5-pro"
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@with_retry(LLM_RETRY_CONFIG)
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def invoke(self, system_prompt: str, user_prompt: str, **kwargs) -> str:
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"""
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调用Gemini API生成回复
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Args:
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system_prompt: 系统提示词
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user_prompt: 用户输入
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**kwargs: 其他参数，如temperature、max_tokens等
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Returns:
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Gemini生成的回复文本
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"""
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try:
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# 构建消息
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messages = [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": user_prompt}
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]
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# 设置默认参数
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params = {
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"model": self.default_model,
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"messages": messages,
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"temperature": kwargs.get("temperature", 0.7),
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"max_tokens": kwargs.get("max_tokens", 30000), # 提高到30000以支持一万字报告
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"stream": False
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}
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# 调用API
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response = self.client.chat.completions.create(**params)
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# 提取回复内容
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if response.choices and response.choices[0].message:
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content = response.choices[0].message.content
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return self.validate_response(content)
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else:
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return ""
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except Exception as e:
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print(f"Gemini API调用错误: {str(e)}")
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raise e
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def get_model_info(self) -> Dict[str, Any]:
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"""
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获取当前模型信息
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Returns:
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模型信息字典
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"""
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return {
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"provider": "Gemini",
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"model": self.default_model,
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"api_base": "https://www.chataiapi.com/v1"
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}
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