mirror of
https://github.com/xinnan-tech/xiaozhi-esp32-server.git
synced 2026-07-22 23:23:55 +08:00
82 lines
2.8 KiB
Python
82 lines
2.8 KiB
Python
from config.logger import setup_logging
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import google.generativeai as genai
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from core.providers.llm.base import LLMProviderBase
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TAG = __name__
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logger = setup_logging()
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class LLMProvider(LLMProviderBase):
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def __init__(self, config):
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"""初始化Gemini LLM Provider"""
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self.model_name = config.get("model_name", "gemini-1.5-pro")
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self.api_key = config.get("api_key")
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if not self.api_key or "你" in self.api_key:
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logger.bind(tag=TAG).error("你还没配置Gemini LLM的密钥，请在配置文件中配置密钥，否则无法正常工作")
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return
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try:
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# 初始化Gemini客户端
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genai.configure(api_key=self.api_key)
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self.model = genai.GenerativeModel(self.model_name)
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# 设置生成参数
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self.generation_config = {
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"temperature": 0.7,
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"top_p": 0.9,
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"top_k": 40,
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"max_output_tokens": 2048,
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}
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self.chat = None
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except Exception as e:
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logger.bind(tag=TAG).error(f"Gemini初始化失败: {e}")
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self.model = None
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def response(self, session_id, dialogue):
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"""生成Gemini对话响应"""
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if not self.model:
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yield "【Gemini服务未正确初始化】"
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return
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try:
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# 处理对话历史
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chat_history = []
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for msg in dialogue[:-1]: # 历史对话
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role = "model" if msg["role"] == "assistant" else "user"
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content = msg["content"].strip()
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if content:
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chat_history.append({
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"role": role,
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"parts": [content]
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})
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# 获取当前消息
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current_msg = dialogue[-1]["content"]
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# 创建新的聊天会话
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chat = self.model.start_chat(history=chat_history)
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# 发送消息并获取流式响应
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response = chat.send_message(
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current_msg,
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stream=True,
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generation_config=self.generation_config
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)
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# 处理流式响应
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for chunk in response:
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if hasattr(chunk, 'text') and chunk.text:
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yield chunk.text
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except Exception as e:
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error_msg = str(e)
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logger.bind(tag=TAG).error(f"Gemini响应生成错误: {error_msg}")
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# 针对不同错误返回友好提示
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if "Rate limit" in error_msg:
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yield "【Gemini服务请求太频繁,请稍后再试】"
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elif "Invalid API key" in error_msg:
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yield "【Gemini API key无效】"
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else:
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yield f"【Gemini服务响应异常: {error_msg}】"
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