mirror of
https://github.com/xinnan-tech/xiaozhi-esp32-server.git
synced 2026-07-22 07:03:53 +08:00
@@ -198,7 +198,9 @@ LLM:
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# token申请地址: https://aistudio.google.com/apikey
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# 若部署地无法访问接口,需要开启科学上网
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api_key: 你的gemini web key
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model_name: "gemini-1.5-pro" # gemini-1.5-pro 是免费的
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model_name: "gemini-2.0-flash"
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http_proxy: "" #"http://127.0.0.1:10808"
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https_proxy: "" #http://127.0.0.1:10808"
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CozeLLM:
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# 定义LLM API类型
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type: coze
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@@ -1,14 +1,19 @@
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import google.generativeai as genai
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from core.utils.util import check_model_key
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from core.providers.llm.base import LLMProviderBase
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from config.logger import setup_logging
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import requests
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import json
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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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self.http_proxy=config.get("http_proxy")
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self.https_proxy = config.get("https_proxy")
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have_key = check_model_key("LLM", self.api_key)
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if not have_key:
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@@ -16,6 +21,19 @@ class LLMProvider(LLMProviderBase):
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try:
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# 初始化Gemini客户端
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# 配置代理(如果提供了代理配置)
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self.proxies=None
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if self.http_proxy is not "" or self.https_proxy is not "":
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self.proxies = {
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"http": self.http_proxy,
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"https": self.https_proxy,
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}
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logger.bind(tag=TAG).info(f"Gemini set proxys:{self.proxies}")
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# 使用猴子补丁修改 google-generativeai 库的请求会话
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# 使用 session 对象配置 genai
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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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@@ -46,26 +64,55 @@ class LLMProvider(LLMProviderBase):
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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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"parts": [{"text":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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# 构建请求体
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request_body = {
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"contents": chat_history + [{"role": "user", "parts": [{"text":current_msg}]}],
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"generationConfig": self.generation_config
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}
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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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# 构建请求URL
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url = f"https://generativelanguage.googleapis.com/v1beta/models/{self.model_name}:generateContent?key={self.api_key}"
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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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# 构建请求头
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headers = {
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"Content-Type": "application/json",
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}
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# 发送POST请求,经测试手动 request 无法使用 stream 模式
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if self.proxies:
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logger.bind(tag=TAG).info(f"Gemini response mode ")
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response = requests.post(url, headers=headers, json=request_body, stream=False, proxies=self.proxies)
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try:
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data = response.json() # 直接解析JSON
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if 'candidates' in data and data['candidates']:
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yield data['candidates'][0]['content']['parts'][0]['text']
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else:
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yield "未找到候选回复。"
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except json.JSONDecodeError as e:
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yield f"JSON解码错误:{e}"
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except Exception as e:
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yield f"发生错误:{e}"
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else:
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logger.bind(tag=TAG).info(f"Gemini stream mode ")
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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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@@ -78,3 +125,13 @@ class LLMProvider(LLMProviderBase):
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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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except requests.exceptions.RequestException as e:
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yield f"请求失败:{e}"
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except json.JSONDecodeError as e:
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yield f"JSON解码错误:{e}"
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except Exception as e:
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yield f"发生错误:{e}"
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