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https://github.com/xinnan-tech/xiaozhi-esp32-server.git
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merge:main分支的manager-web和xiaozhi-server
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hrz
@@ -82,9 +82,10 @@ selected_module:
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TTS: EdgeTTS
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# 记忆模块，默认不开启记忆；如果想使用超长记忆，推荐使用mem0ai；如果注重隐私，请使用本地的mem_local_short
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Memory: nomem
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# 意图识别模块，默认使用function_call。开启后，可以播放音乐、控制音量、识别退出指令
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# 意图识别使用intent_llm，优点：通用性强，缺点：增加串行前置意图识别模块，会增加处理时间
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# 意图识别使用function_call，缺点：需要所选择的LLM支持function_call，优点：按需调用工具、速度快
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# 意图识别模块开启后，可以播放音乐、控制音量、识别退出指令。
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# 不想开通意图识别，就设置成：nointent
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# 意图识别可使用intent_llm，如果你的LLM是DifyLLM或CozeLLM，建议使用这个。优点：通用性强，缺点：增加串行前置意图识别模块，会增加处理时间，这个意图识别暂时不支持控制音量大小等iot操作
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# 意图识别可使用function_call，缺点：需要所选择的LLM支持function_call，优点：按需调用工具、速度快，理论上能全部操作所有iot指令
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# 默认免费的ChatGLMLLM就已经支持function_call，但是如果像追求稳定建议把LLM设置成：DoubaoLLM，使用的具体model_name是：doubao-pro-32k-functioncall-241028
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Intent: function_call
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@@ -97,9 +98,13 @@ Intent:
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intent_llm:
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# 不需要动type
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type: intent_llm
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# 配备意图识别独立的思考模型
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# 如果这里不填，则会默认使用selected_module.LLM的模型作为意图识别的思考模型
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# 如果你的selected_module.LLM选择了DifyLLM或CozeLLM，这里最好使用独立的LLM作为意图识别，例如使用免费的ChatGLMLLM
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llm: ChatGLMLLM
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function_call:
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# 不需要动type
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type: nointent
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type: function_call
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# plugins_func/functions下的模块，可以通过配置，选择加载哪个模块，加载后对话支持相应的function调用
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# 系统默认已经记载“handle_exit_intent(退出识别)”、“play_music(音乐播放)”插件，请勿重复加载
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# 下面是加载查天气、角色切换、加载查新闻的插件示例
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@@ -187,7 +192,7 @@ LLM:
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# 可在这里找到你的 api_key https://bailian.console.aliyun.com/?apiKey=1#/api-key
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base_url: https://dashscope.aliyuncs.com/compatible-mode/v1
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model_name: qwen-turbo
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api_key: 你的ali api key
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api_key: 你的deepseek web key
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temperature: 0.7 # 温度值
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max_tokens: 500 # 最大生成token数
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top_p: 1
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@@ -278,6 +283,18 @@ LLM:
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variables:
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k: "v"
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k2: "v2"
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XinferenceLLM:
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# 定义LLM API类型
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type: xinference
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# Xinference服务地址和模型名称
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model_name: qwen2.5:72b-AWQ # 使用的模型名称，需要预先在Xinference启动对应模型
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base_url: http://localhost:9997 # Xinference服务地址
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XinferenceSmallLLM:
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# 定义轻量级LLM API类型，用于意图识别
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type: xinference
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# Xinference服务地址和模型名称
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model_name: qwen2.5:3b-AWQ # 使用的小模型名称，用于意图识别
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base_url: http://localhost:9997 # Xinference服务地址
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TTS:
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# 当前支持的type为edge、doubao，可自行适配
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EdgeTTS:
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@@ -535,11 +552,3 @@ wakeup_words:
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- "喵喵同学"
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- "小滨小滨"
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- "小冰小冰"
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# 是否使用私有配置
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use_private_config: true
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# 远程配置
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# 数据格式：{"code": 0,"msg": "success","data": {"prompt": "我是小智","owner": "用户ID","ASR": {"FunASR": {}},"LLM": {"ChatGLMLLM": {}},"TTS": {"EdgeTTS": {}},"VAD": {"SileroVAD": {}},"Intent": {"function_call": {}},"Memory": {"nomem": {}},"selected_module": {"ASR": "FunASR","LLM": "ChatGLMLLM","TTS": "EdgeTTS","Intent": "function_call","Memory": "nomem","VAD": "SileroVAD"}}}
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remote_config:
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enabled: true
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url: http://192.168.5.11:8002/xiaozhi-esp32-api/api/v1/user/agent/loadAgentConfig/
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@@ -1,8 +1,6 @@
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import os
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import time
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import yaml
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import json
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import requests
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from config.logger import setup_logging
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from typing import Dict, Any, Optional
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from copy import deepcopy
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@@ -24,14 +22,6 @@ class PrivateConfig:
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async def load_or_create(self):
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try:
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# 优先通过远程获取配置
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fetch_config_ = {}
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remote_config = self.default_config['remote_config']
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self.logger.bind(tag=TAG).info(f"remote config: {remote_config}")
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if remote_config and remote_config['enabled']:
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fetch_config_ = await self.fetch_config(remote_config['url'])
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self.logger.bind(tag=TAG).info(f"fetch_config: {fetch_config_}")
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await self.lock_manager.acquire_lock(self.config_path)
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try:
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if os.path.exists(self.config_path):
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@@ -40,9 +30,6 @@ class PrivateConfig:
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else:
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all_configs = {}
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if fetch_config_:
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all_configs[self.device_id] = fetch_config_
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if self.device_id not in all_configs:
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# Get selected module names
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selected_modules = self.default_config['selected_module']
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@@ -77,9 +64,9 @@ class PrivateConfig:
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all_configs[self.device_id] = device_config
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# Save updated configs
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with open(self.config_path, 'w', encoding='utf-8') as f:
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yaml.dump(all_configs, f, allow_unicode=True)
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# Save updated configs
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with open(self.config_path, 'w', encoding='utf-8') as f:
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yaml.dump(all_configs, f, allow_unicode=True)
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self.private_config = all_configs[self.device_id]
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@@ -251,60 +238,4 @@ class PrivateConfig:
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def get_owner(self) -> Optional[str]:
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"""获取设备当前所有者"""
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return self.private_config.get('owner')
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async def fetch_config(self, fetch_url: str) -> Dict[str, Any]:
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"""通过HTTP请求远程获取配置"""
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url = f"{fetch_url}{self.device_id}"
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headers = {
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'device_id': self.device_id
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}
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try:
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response = requests.get(url, headers=headers)
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response.raise_for_status() # 如果响应状态码不是200，会抛出异常
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# 检查响应内容类型是否为JSON
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if response.headers.get('Content-Type') != 'application/json':
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self.logger.bind(tag=TAG).error("Invalid content type: expected application/json")
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return {}
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# 解析JSON数据
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config_data = response.json()
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# 验证返回的数据结构
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if not isinstance(config_data, dict):
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self.logger.bind(tag=TAG).error("Invalid data format: expected a dictionary")
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return {}
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if config_data['code'] != 0:
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self.logger.bind(tag=TAG).error(f"Fetch config error: {config_data['msg']}")
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return {}
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config_data_ = config_data['data']
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if not isinstance(config_data_, dict):
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self.logger.bind(tag=TAG).error("Invalid config data format: expected a dictionary")
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return {}
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# 检查必要的字段是否存在
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required_fields = ['selected_module', 'prompt', 'LLM', 'TTS', 'ASR', 'VAD']
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for field in required_fields:
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if field not in config_data_:
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self.logger.bind(tag=TAG).error(f"Missing required field: {field}")
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return {}
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# 检查每个模块的配置是否正确
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for module in ['LLM', 'TTS', 'ASR', 'VAD']:
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if not isinstance(config_data_[module], dict):
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self.logger.bind(tag=TAG).error(f"Invalid data format for {module}: expected a dictionary")
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return {}
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selected_module = config_data_['selected_module'].get(module)
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if selected_module not in config_data_[module]:
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self.logger.bind(tag=TAG).error(f"Selected {module} not found in config: {selected_module}")
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return {}
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return config_data_
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except requests.exceptions.RequestException as e:
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self.logger.bind(tag=TAG).error(f"Error fetching config: {e}")
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return {}
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return self.private_config.get('owner')
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@@ -1,18 +0,0 @@
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'''
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自定义记忆，可以选择此模块
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'''
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from ..base import MemoryProviderBase, logger
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TAG = __name__
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class MemoryProvider(MemoryProviderBase):
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def __init__(self, config):
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super().__init__(config)
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async def save_memory(self, msgs):
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logger.bind(tag=TAG).debug("mem_custom mode: Custom memory saving is performed.")
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return None
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async def query_memory(self, query: str)-> str:
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logger.bind(tag=TAG).debug("mem_custom mode: Custom memory query is performed.")
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return ""
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