update:优化配置及文档

This commit is contained in:
hrz
2025-04-30 15:05:42 +08:00
parent 9e9af2a031
commit d2f8f05acb
18 changed files with 167 additions and 137 deletions
+19 -26
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@@ -81,7 +81,7 @@ xiaozhi-server
下载完后,回到本教程继续往下。
##### 1.2.3.2 下载 config.yaml
##### 1.2.3.2 创建 config.yaml
用浏览器打开[这个链接](../main/xiaozhi-server/config.yaml)。
@@ -224,43 +224,36 @@ python app.py
## 配置项目
如果你的`xiaozhi-server`目录没有`data`,你需要创建`data`目录。
如果你的`data`下面没有`.config.yaml`文件,你可以把`xiaozhi-server`目录下的`config.yaml`文件复制到`data`,并重命名为`.config.yaml`
如果你的`data`下面没有`.config.yaml`文件,有两个方式,任选一种:
修改`xiaozhi-server``data`目录下的`.config.yaml`文件,配置本项目必须的一个配置。
第一个方式:你可以把`xiaozhi-server`目录下的`config.yaml`文件复制到`data`,并重命名为`.config.yaml`。在此文件上修改
第二个方式:你也可以创建在`data`目录下手动创建`.config.yaml`空文件,然后在这个文件中增加必要的配置信息,系统会优先读取`.config.yaml`文件的配置,如果`.config.yaml`没有配置的,系统会自动去加载`xiaozhi-server`目录下的`config.yaml`的配置。推荐使用这种方式,这种方式是最简洁的方式。
- 默认的LLM使用的是`ChatGLMLLM`,你需要配置密钥,因为他们的模型,虽然有免费的,但是仍要去[官网](https://bigmodel.cn/usercenter/proj-mgmt/apikeys)注册密钥,才能启动。
配置说明:这里是各个功能使用的默认组件,例如LLM默认使用`ChatGLMLLM`模型。如果需要切换模型,就是改对应的名称。
本项目的默认配置仅是成本最低配置(`glm-4-flash``EdgeTTS`都是免费的),如果需要更优的更快的搭配,需要自己结合部署环境切换各组件的使用。
以下是一个能正常跑起来的,最简单的`.config.yaml`配置示例
```
server:
websocket: ws://你的ip或者域名:端口号/xiaozhi/v1/
prompt: |
我是一个叫小智/小志的台湾女孩,说话机车,声音好听,习惯简短表达,爱用网络梗。
我的男朋友是一个程序员,梦想是开发出一个机器人,能够帮助人们解决生活中的各种问题。
我是一个喜欢哈哈大笑的女孩,爱东说西说吹牛,不合逻辑的也照吹,就要逗别人开心。
请你像一个人一样说话,请勿返回配置xml及其他特殊字符。
selected_module:
VAD: SileroVAD
ASR: FunASR
LLM: ChatGLMLLM
TTS: EdgeTTS
# 默认不开启记忆,如需开启请看配置文件里的描述
Memory: nomem
# 默认不开启意图识别,如需开启请看配置文件里的描述
Intent: nointent
```
LLM: DoubaoLLM
比如修改`LLM`使用的组件,就看本项目支持哪些`LLM` API接口,当前支持的是`openai``dify`。欢迎验证和支持更多LLM平台的接口。
使用时,在`selected_module`修改成对应的如下LLM配置的名称:
```
LLM:
DeepSeekLLM:
type: openai
...
ChatGLMLLM:
type: openai
...
DifyLLM:
type: dify
...
api_key: xxxxxxxxxxxxxxx.xxxxxx
```
建议先将最简单的配置运行起来,然后再去`xiaozhi/config.yaml`阅读配置的使用说明。
比如你要换更换模型,修改`selected_module`下的配置就行。
## 模型文件
本项目语音识别模型,默认使用`SenseVoiceSmall`模型,进行语音转文字。因为模型较大,需要独立下载,下载后把`model.pt`
@@ -10,9 +10,6 @@ import lombok.Data;
@Data
@Schema(description = "获取智能体模型配置DTO")
public class AgentModelsDTO {
@NotBlank(message = "密钥不能为空")
@Schema(description = "密钥")
private String secret;
@NotBlank(message = "设备MAC地址不能为空")
@Schema(description = "设备MAC地址")
@@ -2,8 +2,6 @@ package xiaozhi.modules.security.secret;
import java.io.IOException;
import lombok.RequiredArgsConstructor;
import lombok.extern.slf4j.Slf4j;
import org.apache.commons.lang3.StringUtils;
import org.apache.shiro.web.filter.authc.AuthenticatingFilter;
import org.springframework.web.bind.annotation.RequestMethod;
@@ -12,6 +10,8 @@ import jakarta.servlet.ServletRequest;
import jakarta.servlet.ServletResponse;
import jakarta.servlet.http.HttpServletRequest;
import jakarta.servlet.http.HttpServletResponse;
import lombok.RequiredArgsConstructor;
import lombok.extern.slf4j.Slf4j;
import xiaozhi.common.constant.Constant;
import xiaozhi.common.exception.ErrorCode;
import xiaozhi.common.utils.HttpContextUtils;
@@ -55,7 +55,7 @@ public class ServerSecretFilter extends AuthenticatingFilter {
String token = getRequestToken((HttpServletRequest) servletRequest);
if (StringUtils.isBlank(token)) {
// token为空,返回401
this.sendUnauthorizedResponse((HttpServletResponse) servletResponse, "Authorization token不能为空");
this.sendUnauthorizedResponse((HttpServletResponse) servletResponse, "服务器密钥不能为空");
return false;
}
@@ -63,7 +63,7 @@ public class ServerSecretFilter extends AuthenticatingFilter {
String serverSecret = getServerSecret();
if (StringUtils.isBlank(serverSecret) || !serverSecret.equals(token)) {
// token无效,返回401
this.sendUnauthorizedResponse((HttpServletResponse) servletResponse, "无效的Authorization token");
this.sendUnauthorizedResponse((HttpServletResponse) servletResponse, "无效的服务器密钥");
return false;
}
@@ -77,7 +77,7 @@ public class ServerSecretFilter extends AuthenticatingFilter {
response.setContentType("application/json;charset=utf-8");
response.setHeader("Access-Control-Allow-Credentials", "true");
response.setHeader("Access-Control-Allow-Origin", HttpContextUtils.getOrigin());
try {
String json = JsonUtils.toJsonString(new Result<Void>().error(ErrorCode.UNAUTHORIZED, message));
response.getWriter().print(json);
@@ -102,4 +102,4 @@ public class ServerSecretFilter extends AuthenticatingFilter {
private String getServerSecret() {
return sysParamsService.getValue(Constant.SERVER_SECRET, true);
}
}
}
@@ -25,7 +25,7 @@ INSERT INTO `ai_model_provider` (`id`, `model_type`, `provider_code`, `name`, `f
-- TTS模型供应器
('SYSTEM_TTS_edge', 'TTS', 'edge', 'Edge TTS', '[{"key":"voice","label":"音色","type":"string"},{"key":"output_dir","label":"输出目录","type":"string"}]', 1, 1, NOW(), 1, NOW()),
('SYSTEM_TTS_doubao', 'TTS', 'doubao', '火山引擎TTS', '[{"key": "api_url","label": "API地址","type": "string"},{"key": "voice","label": "音色","type": "string"},{"key": "output_dir","label": "输出目录","type": "string"},{"key": "authorization","label": "授权","type": "string"},{"key": "appid","label": "应用ID","type": "string"},{"key": "access_token","label": "访问令牌","type": "string"},{"key": "cluster","label": "集群","type": "string"},{"key": "speed_ratio","label": "语速","type": "number"},{"key": "volume_ratio","label": "音量","type": "number"},{"key": "pitch_ratio","label": "音高","type": "number"}]', 2, 1, NOW(), 1, NOW()),
('SYSTEM_TTS_doubao', 'TTS', 'doubao', '火山引擎TTS', '[{"key":"api_url","label":"API地址","type":"string"},{"key":"voice","label":"音色","type":"string"},{"key":"output_dir","label":"输出目录","type":"string"},{"key":"authorization","label":"授权","type":"string"},{"key":"appid","label":"应用ID","type":"string"},{"key":"access_token","label":"访问令牌","type":"string"},{"key":"cluster","label":"集群","type":"string"}]', 2, 1, NOW(), 1, NOW()),
('SYSTEM_TTS_siliconflow', 'TTS', 'siliconflow', '硅基流动TTS', '[{"key":"model","label":"模型","type":"string"},{"key":"voice","label":"音色","type":"string"},{"key":"output_dir","label":"输出目录","type":"string"},{"key":"access_token","label":"访问令牌","type":"string"},{"key":"response_format","label":"响应格式","type":"string"}]', 3, 1, NOW(), 1, NOW()),
('SYSTEM_TTS_cozecn', 'TTS', 'cozecn', 'COZECN TTS', '[{"key":"voice","label":"音色","type":"string"},{"key":"output_dir","label":"输出目录","type":"string"},{"key":"access_token","label":"访问令牌","type":"string"},{"key":"response_format","label":"响应格式","type":"string"}]', 4, 1, NOW(), 1, NOW()),
('SYSTEM_TTS_fishspeech', 'TTS', 'fishspeech', 'FishSpeech TTS', '[{"key":"output_dir","label":"输出目录","type":"string"},{"key":"response_format","label":"响应格式","type":"string"},{"key":"reference_id","label":"参考ID","type":"string"},{"key":"reference_audio","label":"参考音频","type":"dict","dict_name":"reference_audio"},{"key":"reference_text","label":"参考文本","type":"dict","dict_name":"reference_text"},{"key":"normalize","label":"是否标准化","type":"boolean"},{"key":"max_new_tokens","label":"最大新令牌数","type":"number"},{"key":"chunk_length","label":"块长度","type":"number"},{"key":"top_p","label":"top_p值","type":"number"},{"key":"repetition_penalty","label":"重复惩罚","type":"number"},{"key":"temperature","label":"温度","type":"number"},{"key":"streaming","label":"是否流式","type":"boolean"},{"key":"use_memory_cache","label":"是否使用内存缓存","type":"string"},{"key":"seed","label":"种子","type":"number"},{"key":"channels","label":"通道数","type":"number"},{"key":"rate","label":"采样率","type":"number"},{"key":"api_key","label":"API密钥","type":"string"},{"key":"api_url","label":"API地址","type":"string"}]', 5, 1, NOW(), 1, NOW()),
@@ -0,0 +1,3 @@
update `ai_model_provider` set `fields` =
'[{"key": "api_url","label": "API地址","type": "string"},{"key": "voice","label": "音色","type": "string"},{"key": "output_dir","label": "输出目录","type": "string"},{"key": "authorization","label": "授权","type": "string"},{"key": "appid","label": "应用ID","type": "string"},{"key": "access_token","label": "访问令牌","type": "string"},{"key": "cluster","label": "集群","type": "string"},{"key": "speed_ratio","label": "语速","type": "number"},{"key": "volume_ratio","label": "音量","type": "number"},{"key": "pitch_ratio","label": "音高","type": "number"}]'
where `id` = 'SYSTEM_TTS_doubao';
@@ -85,4 +85,11 @@ databaseChangeLog:
changes:
- sqlFile:
encoding: utf8
path: classpath:db/changelog/202504291043.sql
path: classpath:db/changelog/202504291043.sql
- changeSet:
id: 202504301339
author: Goody
changes:
- sqlFile:
encoding: utf8
path: classpath:db/changelog/202504301339.sql
+1 -2
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@@ -1,7 +1,7 @@
import asyncio
import sys
import signal
from config.settings import load_config, check_config_file
from config.settings import load_config
from core.websocket_server import WebSocketServer
from core.ota_server import SimpleOtaServer
from core.utils.util import check_ffmpeg_installed
@@ -31,7 +31,6 @@ async def wait_for_exit():
async def main():
check_config_file()
check_ffmpeg_installed()
config = load_config()
+5 -5
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@@ -1,7 +1,7 @@
# 如果您是一名开发者,建议阅读以下内容。如果不是开发者,可以忽略这部分内容。
# 在开发中,在项目根目录创建data目录,将【config.yaml】复制一份,改成【.config.yaml】,放进data目录中
# 系统会优先读取【data/.config.yaml】文件的配置。
# 这样做,可以避免在提交代码的时候,错误地提交密钥信息,保护您的密钥安全。
# 在开发中,请在项目根目录创建data目录,然后在data目录创建名称为【.config.yaml】的空文件
# 然后你想修改覆盖修改什么配置,就修改【.config.yaml】文件,而不是修改【config.yaml】文件
# 系统会优先读取【data/.config.yaml】文件的配置,如果【.config.yaml】文件里的配置不存在,系统会自动去读取【config.yaml】文件的配置
# 这样做,可以最简化配置,保护您的密钥安全。
# #####################################################################################
# #############################以下是服务器基本运行配置####################################
@@ -158,7 +158,7 @@ selected_module:
# 不想开通意图识别,就设置成:nointent
# 意图识别可使用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,这个意图识别暂时不支持控制音量大小等iot操作
# 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
# 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
# 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-1-5-pro-32k-250115
Intent: function_call
# 意图识别,是用于理解用户意图的模块,例如:播放音乐
+18 -30
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@@ -31,37 +31,19 @@ def load_config():
# 加载默认配置
default_config = read_config(default_config_path)
custom_config = read_config(custom_config_path)
# 加载用户自定义配置(如果存在)
if os.path.exists(custom_config_path):
custom_config = read_config(custom_config_path)
if custom_config.get("manager-api", {}).get("url"):
config = get_config_from_api(custom_config)
else:
# 合并配置
config = merge_configs(default_config, custom_config)
else:
config = default_config
if config.get("manager-api", {}).get("url"):
config = get_config_from_api(config)
# 初始化目录
ensure_directories(config)
_config_cache = config
return config
def get_config_file():
"""获取配置文件路径,优先使用私有配置文件(若存在)。
Returns:
str: 配置文件路径(相对路径或默认路径)
"""
default_config_file = "config.yaml"
config_file = default_config_file
if os.path.exists(get_project_dir() + "data/." + default_config_file):
config_file = "data/." + default_config_file
return config_file
def get_config_from_api(config):
"""从Java API获取配置"""
# 初始化API客户端
@@ -128,23 +110,29 @@ def ensure_directories(config):
def merge_configs(default_config, custom_config):
"""
递归合并配置,custom_config优先级更高
Args:
default_config: 默认配置
custom_config: 用户自定义配置
Returns:
合并后的配置
"""
if not isinstance(default_config, Mapping) or not isinstance(custom_config, Mapping):
if not isinstance(default_config, Mapping) or not isinstance(
custom_config, Mapping
):
return custom_config
merged = dict(default_config)
for key, value in custom_config.items():
if key in merged and isinstance(merged[key], Mapping) and isinstance(value, Mapping):
if (
key in merged
and isinstance(merged[key], Mapping)
and isinstance(value, Mapping)
):
merged[key] = merge_configs(merged[key], value)
else:
merged[key] = value
return merged
return merged
+2
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@@ -2,6 +2,7 @@ import os
import sys
from loguru import logger
from config.config_loader import load_config
from config.settings import check_config_file
SERVER_VERSION = "0.3.13"
@@ -32,6 +33,7 @@ def formatter(record):
def setup_logging():
check_config_file()
"""从配置文件中读取日志配置,并设置日志输出格式和级别"""
config = load_config()
log_config = config["log"]
+17 -37
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@@ -1,53 +1,33 @@
import os
from collections.abc import Mapping
from config import logger
from config.config_loader import read_config, get_project_dir, load_config
TAG = __name__
logger = logger.setup_logging()
default_config_file = "config.yaml"
def find_missing_keys(new_config, old_config, parent_key=""):
"""
递归查找缺失的配置项
返回格式:[缺失配置路径]
"""
missing_keys = []
if not isinstance(new_config, Mapping):
return missing_keys
for key, value in new_config.items():
# 构建当前配置路径
full_path = f"{parent_key}.{key}" if parent_key else key
# 检查键是否存在
if key not in old_config:
missing_keys.append(full_path)
continue
# 递归检查嵌套字典
if isinstance(value, Mapping):
sub_missing = find_missing_keys(
value, old_config[key], parent_key=full_path
)
missing_keys.extend(sub_missing)
return missing_keys
config_file_valid = False
def check_config_file():
global config_file_valid
if config_file_valid:
return
"""
简化的配置检查,仅提示用户配置文件的使用情况
"""
custom_config_file = get_project_dir() + "data/." + default_config_file
if not os.path.exists(custom_config_file):
logger.bind(tag=TAG).info("提示: 使用默认配置文件。如需自定义配置,请创建 data/.config.yaml 文件")
else:
logger.bind(tag=TAG).info(f"提示: 使用自定义配置文件 data/.config.yaml,配置将覆盖默认值")
raise FileNotFoundError(
"找不到data/.config.yaml文件,请按教程确认该配置文件是否存在"
)
# 检查是否从API读取配置
config = load_config()
if config.get("read_config_from_api", False):
logger.bind(tag=TAG).info("提示: 从API取配置")
print("从API取配置")
old_config_origin = read_config(custom_config_file)
if old_config_origin.get("selected_module") is not None:
error_msg = "您的配置文件好像既包含智控台的配置又包含本地配置:\n"
error_msg += "\n建议您:\n"
error_msg += "1、将根目录的config_from_api.yaml文件复制到data下,重命名为.config.yaml\n"
error_msg += "2、按教程配置好接口地址和密钥\n"
raise ValueError(error_msg)
config_file_valid = True
@@ -53,6 +53,8 @@ async def handleTextMessage(conn, message):
# 如果是唤醒词,且关闭了唤醒词回复,就不用回答
await send_stt_message(conn, text)
await send_tts_message(conn, "stop", None)
elif is_wakeup_words:
await startToChat(conn, "嘿,你好呀")
else:
# 否则需要LLM对文字内容进行答复
await startToChat(conn, text)
@@ -27,9 +27,14 @@ class TTSProvider(TTSProviderBase):
else:
self.voice = config.get("voice")
self.speed_ratio = float(config.get("speed_ratio", 0.1))
self.volume_ratio = float(config.get("volume_ratio", 0.1))
self.pitch_ratio = float(config.get("pitch_ratio", 0.1))
# 处理空字符串的情况
speed_ratio = config.get("speed_ratio", "1.0")
volume_ratio = config.get("volume_ratio", "1.0")
pitch_ratio = config.get("pitch_ratio", "1.0")
self.speed_ratio = float(speed_ratio) if speed_ratio else 1.0
self.volume_ratio = float(volume_ratio) if volume_ratio else 1.0
self.pitch_ratio = float(pitch_ratio) if pitch_ratio else 1.0
self.api_url = config.get("api_url")
self.authorization = config.get("authorization")
@@ -89,18 +89,35 @@ class TTSProvider(TTSProviderBase):
self.reference_audio = parse_string_to_list(config.get("reference_audio"))
self.reference_text = parse_string_to_list(config.get("reference_text"))
self.format = config.get("format", "wav")
self.channels = int(config.get("channels", 1))
self.rate = int(config.get("rate", 44100))
self.api_key = config.get("api_key", "YOUR_API_KEY")
have_key = check_model_key("FishSpeech TTS", self.api_key)
if not have_key:
return
self.normalize = config.get("normalize", True)
self.max_new_tokens = int(config.get("max_new_tokens", 1024))
self.chunk_length = int(config.get("chunk_length", 200))
self.top_p = float(config.get("top_p", 0.7))
self.repetition_penalty = float(config.get("repetition_penalty", 1.2))
self.temperature = float(config.get("temperature", 0.7))
# 处理空字符串的情况
channels = config.get("channels", "1")
rate = config.get("rate", "44100")
max_new_tokens = config.get("max_new_tokens", "1024")
chunk_length = config.get("chunk_length", "200")
self.channels = int(channels) if channels else 1
self.rate = int(rate) if rate else 44100
self.max_new_tokens = int(max_new_tokens) if max_new_tokens else 1024
self.chunk_length = int(chunk_length) if chunk_length else 200
# 处理空字符串的情况
top_p = config.get("top_p", "0.7")
temperature = config.get("temperature", "0.7")
repetition_penalty = config.get("repetition_penalty", "1.2")
self.top_p = float(top_p) if top_p else 0.7
self.temperature = float(temperature) if temperature else 0.7
self.repetition_penalty = (
float(repetition_penalty) if repetition_penalty else 1.2
)
self.streaming = str(config.get("streaming", False)).lower() in (
"true",
"1",
@@ -20,12 +20,29 @@ class TTSProvider(TTSProviderBase):
self.ref_audio_path = config.get("ref_audio_path")
self.prompt_text = config.get("prompt_text")
self.prompt_lang = config.get("prompt_lang", "zh")
self.top_k = int(config.get("top_k", 5))
self.top_p = float(config.get("top_p", 1))
self.temperature = float(config.get("temperature", 1))
# 处理空字符串的情况
top_k = config.get("top_k", "5")
top_p = config.get("top_p", "1")
temperature = config.get("temperature", "1")
batch_threshold = config.get("batch_threshold", "0.75")
batch_size = config.get("batch_size", "1")
speed_factor = config.get("speed_factor", "1.0")
seed = config.get("seed", "-1")
repetition_penalty = config.get("repetition_penalty", "1.35")
self.top_k = int(top_k) if top_k else 5
self.top_p = float(top_p) if top_p else 1
self.temperature = float(temperature) if temperature else 1
self.batch_threshold = float(batch_threshold) if batch_threshold else 0.75
self.batch_size = int(batch_size) if batch_size else 1
self.speed_factor = float(speed_factor) if speed_factor else 1.0
self.seed = int(seed) if seed else -1
self.repetition_penalty = (
float(repetition_penalty) if repetition_penalty else 1.35
)
self.text_split_method = config.get("text_split_method", "cut0")
self.batch_size = int(config.get("batch_size", 1))
self.batch_threshold = float(config.get("batch_threshold", 0.75))
self.split_bucket = str(config.get("split_bucket", True)).lower() in (
"true",
@@ -37,19 +54,19 @@ class TTSProvider(TTSProviderBase):
"1",
"yes",
)
self.speed_factor = float(config.get("speed_factor", 1.0))
self.streaming_mode = str(config.get("streaming_mode", False)).lower() in (
"true",
"1",
"yes",
)
self.seed = int(config.get("seed", -1))
self.parallel_infer = str(config.get("parallel_infer", True)).lower() in (
"true",
"1",
"yes",
)
self.repetition_penalty = float(config.get("repetition_penalty", 1.35))
self.aux_ref_audio_paths = parse_string_to_list(
config.get("aux_ref_audio_paths")
)
@@ -18,13 +18,22 @@ class TTSProvider(TTSProviderBase):
self.prompt_text = config.get("prompt_text")
self.prompt_language = config.get("prompt_language")
self.text_language = config.get("text_language", "audo")
self.top_k = int(config.get("top_k", 15))
self.top_p = float(config.get("top_p", 1.0))
self.temperature = float(config.get("temperature", 1.0))
# 处理空字符串的情况
top_k = config.get("top_k", "15")
top_p = config.get("top_p", "1.0")
temperature = config.get("temperature", "1.0")
sample_steps = config.get("sample_steps", "32")
speed = config.get("speed", "1.0")
self.top_k = int(top_k) if top_k else 15
self.top_p = float(top_p) if top_p else 1.0
self.temperature = float(temperature) if temperature else 1.0
self.sample_steps = int(sample_steps) if sample_steps else 32
self.speed = float(speed) if speed else 1.0
self.cut_punc = config.get("cut_punc", "")
self.speed = float(config.get("speed", 1.0))
self.inp_refs = parse_string_to_list(config.get("inp_refs"))
self.sample_steps = int(config.get("sample_steps", 32))
self.if_sr = str(config.get("if_sr", False)).lower() in ("true", "1", "yes")
def generate_filename(self, extension=".wav"):
@@ -21,7 +21,11 @@ class TTSProvider(TTSProviderBase):
else:
self.voice = config.get("voice", "alloy")
self.response_format = "wav"
self.speed = float(config.get("speed", 1.0))
# 处理空字符串的情况
speed = config.get("speed", "1.0")
self.speed = float(speed) if speed else 1.0
self.output_file = config.get("output_dir", "tmp/")
check_model_key("TTS", self.api_key)
@@ -21,8 +21,15 @@ class VADProvider(VADProviderBase):
(get_speech_timestamps, _, _, _, _) = self.utils
self.decoder = opuslib_next.Decoder(16000, 1)
self.vad_threshold = float(config.get("threshold", 0.5))
self.silence_threshold_ms = int(config.get("min_silence_duration_ms", 1000))
# 处理空字符串的情况
threshold = config.get("threshold", "0.5")
min_silence_duration_ms = config.get("min_silence_duration_ms", "1000")
self.vad_threshold = float(threshold) if threshold else 0.5
self.silence_threshold_ms = (
int(min_silence_duration_ms) if min_silence_duration_ms else 1000
)
def is_vad(self, conn, opus_packet):
try: