Merge branch 'xinnan-tech:main' into fix/manager-api-voice-print

This commit is contained in:
醒心online
2025-07-28 12:01:41 +08:00
committed by GitHub
21 changed files with 676 additions and 76 deletions
+1 -2
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@@ -235,7 +235,7 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
---
## 功能清单 ✨
### 已实现 ✅
![请参考-全模块安装架构图](docs/images/deploy2.png)
| 功能模块 | 描述 |
|:---:|:---|
| 核心架构 | 基于WebSocket和HTTP服务器,提供完整的控制台管理和认证系统 |
@@ -271,7 +271,6 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
---
## 本项目支持的平台/组件列表 📋
### LLM 语言模型
| 使用方式 | 支持平台 | 免费平台 |
+1 -2
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@@ -233,7 +233,7 @@ This project provides the following testing tools to help you verify the system
---
## Feature List ✨
### Implemented ✅
![请参考-全模块安装架构图](docs/images/deploy2.png)
| Feature Module | Description |
|:---:|:---|
| Core Architecture | Based on WebSocket and HTTP servers, provides complete console management and authentication system |
@@ -269,7 +269,6 @@ Xiaozhi is an ecosystem. When using this product, you can also check out other e
---
## Supported Platforms/Components List 📋
### LLM Language Models
| Usage Method | Supported Platforms | Free Platforms |
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@@ -237,7 +237,7 @@ public interface Constant {
/**
* 版本号
*/
public static final String VERSION = "0.7.2";
public static final String VERSION = "0.7.3";
/**
* 无效固件URL
@@ -41,6 +41,7 @@ import xiaozhi.modules.agent.service.AgentTemplateService;
import xiaozhi.modules.agent.vo.AgentInfoVO;
import xiaozhi.modules.device.service.DeviceService;
import xiaozhi.modules.model.dto.ModelProviderDTO;
import xiaozhi.modules.model.entity.ModelConfigEntity;
import xiaozhi.modules.model.service.ModelConfigService;
import xiaozhi.modules.model.service.ModelProviderService;
import xiaozhi.modules.security.user.SecurityUser;
@@ -324,9 +325,32 @@ public class AgentServiceImpl extends BaseServiceImpl<AgentDao, AgentEntity> imp
// 删除音频数据
agentChatHistoryService.deleteByAgentId(existingEntity.getId(), true, false);
}
boolean b = validateLLMIntentParams(dto.getLlmModelId(), dto.getIntentModelId());
if (!b) {
throw new RenException("LLM大模型和Intent意图识别,选择参数不匹配");
}
this.updateById(existingEntity);
}
/**
* 验证大语言模型和意图识别的参数是否符合匹配
*
* @param llmModelId 大语言模型id
* @param intentModelId 意图识别id
* @return T 匹配 : F 不匹配
*/
private boolean validateLLMIntentParams(String llmModelId, String intentModelId) {
ModelConfigEntity llmModelData = modelConfigService.selectById(llmModelId);
String type = llmModelData.getConfigJson().get("type").toString();
// 如果查询大语言模型是openai或者ollama,意图识别选参数都可以
if ("openai".equals(type) || "ollama".equals(type)) {
return true;
}
// 除了openai和ollama的类型,不可以选择id为Intent_function_call(函数调用)的意图识别
return !"Intent_function_call".equals(intentModelId);
}
@Override
@Transactional(rollbackFor = Exception.class)
public String createAgent(AgentCreateDTO dto) {
@@ -21,11 +21,7 @@ import xiaozhi.common.utils.ConvertUtils;
import xiaozhi.common.utils.Result;
import xiaozhi.modules.agent.service.AgentTemplateService;
import xiaozhi.modules.config.service.ConfigService;
import xiaozhi.modules.model.dto.ModelBasicInfoDTO;
import xiaozhi.modules.model.dto.ModelConfigBodyDTO;
import xiaozhi.modules.model.dto.ModelConfigDTO;
import xiaozhi.modules.model.dto.ModelProviderDTO;
import xiaozhi.modules.model.dto.VoiceDTO;
import xiaozhi.modules.model.dto.*;
import xiaozhi.modules.model.entity.ModelConfigEntity;
import xiaozhi.modules.model.service.ModelConfigService;
import xiaozhi.modules.model.service.ModelProviderService;
@@ -52,6 +48,14 @@ public class ModelController {
return new Result<List<ModelBasicInfoDTO>>().ok(modelList);
}
@GetMapping("/llm/names")
@Operation(summary = "获取LLM模型信息")
@RequiresPermissions("sys:role:normal")
public Result<List<LlmModelBasicInfoDTO>> getLlmModelCodeList(@RequestParam(required = false) String modelName) {
List<LlmModelBasicInfoDTO> llmModelCodeList = modelConfigService.getLlmModelCodeList(modelName);
return new Result<List<LlmModelBasicInfoDTO>>().ok(llmModelCodeList);
}
@GetMapping("/{modelType}/provideTypes")
@Operation(summary = "获取模型供应器列表")
@RequiresPermissions("sys:role:superAdmin")
@@ -0,0 +1,13 @@
package xiaozhi.modules.model.dto;
import lombok.Data;
import lombok.EqualsAndHashCode;
/**
* LLM的模型的基础展示数据
*/
@EqualsAndHashCode(callSuper = true)
@Data
public class LlmModelBasicInfoDTO extends ModelBasicInfoDTO{
private String type;
}
@@ -4,6 +4,7 @@ import java.util.List;
import xiaozhi.common.page.PageData;
import xiaozhi.common.service.BaseService;
import xiaozhi.modules.model.dto.LlmModelBasicInfoDTO;
import xiaozhi.modules.model.dto.ModelBasicInfoDTO;
import xiaozhi.modules.model.dto.ModelConfigBodyDTO;
import xiaozhi.modules.model.dto.ModelConfigDTO;
@@ -13,6 +14,8 @@ public interface ModelConfigService extends BaseService<ModelConfigEntity> {
List<ModelBasicInfoDTO> getModelCodeList(String modelType, String modelName);
List<LlmModelBasicInfoDTO> getLlmModelCodeList(String modelName);
PageData<ModelConfigDTO> getPageList(String modelType, String modelName, String page, String limit);
ModelConfigDTO add(String modelType, String provideCode, ModelConfigBodyDTO modelConfigBodyDTO);
@@ -8,6 +8,7 @@ import java.util.stream.Collectors;
import org.apache.commons.lang3.StringUtils;
import org.springframework.stereotype.Service;
import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
import com.baomidou.mybatisplus.core.metadata.IPage;
@@ -23,6 +24,7 @@ import xiaozhi.common.utils.ConvertUtils;
import xiaozhi.modules.agent.dao.AgentDao;
import xiaozhi.modules.agent.entity.AgentEntity;
import xiaozhi.modules.model.dao.ModelConfigDao;
import xiaozhi.modules.model.dto.LlmModelBasicInfoDTO;
import xiaozhi.modules.model.dto.ModelBasicInfoDTO;
import xiaozhi.modules.model.dto.ModelConfigBodyDTO;
import xiaozhi.modules.model.dto.ModelConfigDTO;
@@ -52,6 +54,25 @@ public class ModelConfigServiceImpl extends BaseServiceImpl<ModelConfigDao, Mode
return ConvertUtils.sourceToTarget(entities, ModelBasicInfoDTO.class);
}
@Override
public List<LlmModelBasicInfoDTO> getLlmModelCodeList(String modelName) {
List<ModelConfigEntity> entities = modelConfigDao.selectList(
new QueryWrapper<ModelConfigEntity>()
.eq("model_type", "llm")
.eq("is_enabled", 1)
.like(StringUtils.isNotBlank(modelName), "model_name", "%" + modelName + "%")
.select("id", "model_name", "config_json"));
// 处理获取到的内容
return entities.stream().map(item -> {
LlmModelBasicInfoDTO dto = new LlmModelBasicInfoDTO();
dto.setId(item.getId());
dto.setModelName(item.getModelName());
String type = item.getConfigJson().get("type").toString();
dto.setType(type);
return dto;
}).toList();
}
@Override
public PageData<ModelConfigDTO> getPageList(String modelType, String modelName, String page, String limit) {
Map<String, Object> params = new HashMap<String, Object>();
@@ -94,6 +115,21 @@ public class ModelConfigServiceImpl extends BaseServiceImpl<ModelConfigDao, Mode
if (CollectionUtil.isEmpty(providerList)) {
throw new RenException("供应器不存在");
}
if (modelConfigBodyDTO.getConfigJson().containsKey("llm")) {
String llm = modelConfigBodyDTO.getConfigJson().get("llm").toString();
ModelConfigEntity modelConfigEntity = modelConfigDao.selectOne(new LambdaQueryWrapper<ModelConfigEntity>()
.eq(ModelConfigEntity::getId, llm));
String selectModelType = (modelConfigEntity == null || modelConfigEntity.getModelType() == null) ? null
: modelConfigEntity.getModelType().toUpperCase();
if (modelConfigEntity == null || !"LLM".equals(selectModelType)) {
throw new RenException("设置的LLM不存在");
}
String type = modelConfigEntity.getConfigJson().get("type").toString();
// 如果查询大语言模型是openai或者ollama,意图识别选参数都可以
if (!"openai".equals(type) && !"ollama".equals(type)) {
throw new RenException("设置的LLM不是openai和ollama");
}
}
// 再更新供应器提供的模型
ModelConfigEntity modelConfigEntity = ConvertUtils.sourceToTarget(modelConfigBodyDTO, ModelConfigEntity.class);
@@ -137,6 +173,8 @@ public class ModelConfigServiceImpl extends BaseServiceImpl<ModelConfigDao, Mode
.or()
.eq("mem_model_id", modelId)
.or()
.eq("vllm_model_id", modelId)
.or()
.eq("intent_model_id", modelId));
if (!agents.isEmpty()) {
String agentNames = agents.stream()
+16
View File
@@ -106,6 +106,22 @@ export default {
});
}).send();
},
// 获取LLM模型名称列表
getLlmModelCodeList(modelName, callback) {
RequestService.sendRequest()
.url(`${getServiceUrl()}/models/llm/names`)
.method('GET')
.data({ modelName })
.success((res) => {
RequestService.clearRequestTime();
callback(res);
})
.networkFail(() => {
RequestService.reAjaxFun(() => {
this.getLlmModelCodeList(modelName, callback);
});
}).send();
},
// 获取模型音色列表
getModelVoices(modelId, voiceName, callback) {
const queryParams = new URLSearchParams({
+81 -13
View File
@@ -89,7 +89,7 @@
<div class="model-select-wrapper">
<el-select v-model="form.model[model.key]" filterable placeholder="请选择" class="form-select"
@change="handleModelChange(model.type, $event)">
<el-option v-for="(item, optionIndex) in modelOptions[model.type]"
<el-option v-for="(item, optionIndex) in modelOptions[model.type]" v-if="!item.isHidden"
:key="`option-${index}-${optionIndex}`" :label="item.label" :value="item.value" />
</el-select>
<div v-if="showFunctionIcons(model.type)" class="function-icons">
@@ -130,7 +130,6 @@
</div>
</div>
</div>
<function-dialog v-model="showFunctionDialog" :functions="currentFunctions" :all-functions="allFunctions"
:agent-id="$route.query.agentId" @update-functions="handleUpdateFunctions" @dialog-closed="handleDialogClosed" />
</div>
@@ -173,8 +172,9 @@ export default {
{ label: '视觉大模型(VLLM)', key: 'vllmModelId', type: 'VLLM' },
{ label: '意图识别(Intent)', key: 'intentModelId', type: 'Intent' },
{ label: '记忆(Memory)', key: 'memModelId', type: 'Memory' },
{ label: '语音合成(TTS)', key: 'ttsModelId', type: 'TTS' },
{ label: '语音合成(TTS)', key: 'ttsModelId', type: 'TTS' }
],
llmModeTypeMap: new Map(),
modelOptions: {},
templates: [],
loadingTemplate: false,
@@ -356,6 +356,9 @@ export default {
});
// 备份原始,以备取消时恢复
this.originalFunctions = JSON.parse(JSON.stringify(this.currentFunctions));
// 确保意图识别选项的可见性正确
this.updateIntentOptionsVisibility();
});
} else {
this.$message.error(data.msg || '获取配置失败');
@@ -364,16 +367,41 @@ export default {
},
fetchModelOptions() {
this.models.forEach(model => {
Api.model.getModelNames(model.type, '', ({ data }) => {
if (data.code === 0) {
this.$set(this.modelOptions, model.type, data.data.map(item => ({
value: item.id,
label: item.modelName
})));
} else {
this.$message.error(data.msg || '获取模型列表失败');
}
});
if (model.type != "LLM") {
Api.model.getModelNames(model.type, '', ({ data }) => {
if (data.code === 0) {
this.$set(this.modelOptions, model.type, data.data.map(item => ({
value: item.id,
label: item.modelName,
isHidden: false
})));
// 如果是意图识别选项,需要根据当前LLM类型更新可见性
if (model.type === 'Intent') {
this.updateIntentOptionsVisibility();
}
} else {
this.$message.error(data.msg || '获取模型列表失败');
}
});
} else {
Api.model.getLlmModelCodeList('', ({ data }) => {
if (data.code === 0) {
let LLMdata = []
data.data.forEach(item => {
LLMdata.push({
value: item.id,
label: item.modelName,
isHidden: false
})
this.llmModeTypeMap.set(item.id, item.type)
})
this.$set(this.modelOptions, model.type, LLMdata);
} else {
this.$message.error(data.msg || '获取LLM模型列表失败');
}
});
}
});
},
fetchVoiceOptions(modelId) {
@@ -410,6 +438,10 @@ export default {
if (type === 'Memory' && value !== 'Memory_nomem' && (this.form.chatHistoryConf === 0 || this.form.chatHistoryConf === null)) {
this.form.chatHistoryConf = 2;
}
if (type === 'LLM') {
// 当LLM类型改变时,更新意图识别选项的可见性
this.updateIntentOptionsVisibility();
}
},
fetchAllFunctions() {
return new Promise((resolve, reject) => {
@@ -450,6 +482,42 @@ export default {
}
this.showFunctionDialog = false;
},
updateIntentOptionsVisibility() {
// 根据当前选择的LLM类型更新意图识别选项的可见性
const currentLlmId = this.form.model.llmModelId;
if (!currentLlmId || !this.modelOptions['Intent']) return;
const llmType = this.llmModeTypeMap.get(currentLlmId);
if (!llmType) return;
this.modelOptions['Intent'].forEach(item => {
if (item.value === "Intent_function_call") {
// 如果llmType是openai或ollama,允许选择function_call
// 否则隐藏function_call选项
if (llmType === "openai" || llmType === "ollama") {
item.isHidden = false;
} else {
item.isHidden = true;
}
} else {
// 其他意图识别选项始终可见
item.isHidden = false;
}
});
// 如果当前选择的意图识别是function_call,但LLM类型不支持,则设置为可选的第一项
if (this.form.model.intentModelId === "Intent_function_call" &&
llmType !== "openai" && llmType !== "ollama") {
// 找到第一个可见的选项
const firstVisibleOption = this.modelOptions['Intent'].find(item => !item.isHidden);
if (firstVisibleOption) {
this.form.model.intentModelId = firstVisibleOption.value;
} else {
// 如果没有可见选项,设置为Intent_nointent
this.form.model.intentModelId = 'Intent_nointent';
}
}
},
updateChatHistoryConf() {
if (this.form.model.memModelId === 'Memory_nomem') {
this.form.chatHistoryConf = 0;
+20
View File
@@ -710,6 +710,26 @@ TTS:
# voice_id: female-shaonv
# weight: 1
# language_boost: auto
# MinimaxTTSHTTPStream和MinimaxTTSWebSocketStream还在测试,测试完再开放
#
# MinimaxTTSHTTPStream:
# # Minimax流式语音合成服务
# type: minimax_httpstream
# output_dir: tmp/
# group_id: 你的minimax平台groupID
# api_key: 你的minimax平台接口密钥
# model: "speech-01-turbo"
# voice_id: "female-shaonv"
#
# MinimaxTTSWebSocketStream:
# type: minimax_webSocket
# output_dir: tmp/
# group_id: 你的minimax平台groupID
# api_key: 你的minimax平台接口密钥
# model: "speech-01-turbo"
# voice_id: "female-shaonv"
AliyunTTS:
# 阿里云智能语音交互服务,需要先在阿里云平台开通服务,然后获取验证信息
# 平台地址:https://nls-portal.console.aliyun.com/
+1 -1
View File
@@ -5,7 +5,7 @@ from config.config_loader import load_config
from config.settings import check_config_file
from datetime import datetime
SERVER_VERSION = "0.7.2"
SERVER_VERSION = "0.7.3"
_logger_initialized = False
+20 -15
View File
@@ -132,6 +132,8 @@ class ConnectionHandler:
# tts相关变量
self.sentence_id = None
# 处理TTS响应没有文本返回
self.tts_MessageText = ""
# iot相关变量
self.iot_descriptors = {}
@@ -182,8 +184,13 @@ class ConnectionHandler:
await ws.send("端口正常,如需测试连接,请使用test_page.html")
await self.close(ws)
return
# 获取客户端ip地址
self.client_ip = ws.remote_address[0]
real_ip = self.headers.get("x-real-ip") or self.headers.get(
"x-forwarded-for"
)
if real_ip:
self.client_ip = real_ip.split(",")[0].strip()
else:
self.client_ip = ws.remote_address[0]
self.logger.bind(tag=TAG).info(
f"{self.client_ip} conn - Headers: {self.headers}"
)
@@ -335,7 +342,7 @@ class ConnectionHandler:
self.config.get("selected_module", {})
)
self.logger = create_connection_logger(self.selected_module_str)
"""初始化组件"""
if self.config.get("prompt") is not None:
user_prompt = self.config["prompt"]
@@ -351,10 +358,10 @@ class ConnectionHandler:
self.vad = self._vad
if self.asr is None:
self.asr = self._initialize_asr()
# 初始化声纹识别
self._initialize_voiceprint()
# 打开语音识别通道
asyncio.run_coroutine_threadsafe(
self.asr.open_audio_channels(self), self.loop
@@ -746,7 +753,7 @@ class ConnectionHandler:
content = response
# 在llm回复中获取情绪表情,一轮对话只在开头获取一次
if emotion_flag:
if emotion_flag and content is not None and content.strip():
asyncio.run_coroutine_threadsafe(
textUtils.get_emotion(self, content),
self.loop,
@@ -790,9 +797,9 @@ class ConnectionHandler:
if not bHasError:
# 如需要大模型先处理一轮,添加相关处理后的日志情况
if len(response_message) > 0:
self.dialogue.put(
Message(role="assistant", content="".join(response_message))
)
text_buff = "".join(response_message)
self.tts_MessageText = text_buff
self.dialogue.put(Message(role="assistant", content=text_buff))
response_message.clear()
self.logger.bind(tag=TAG).debug(
f"function_name={function_name}, function_id={function_id}, function_arguments={function_arguments}"
@@ -814,9 +821,9 @@ class ConnectionHandler:
# 存储对话内容
if len(response_message) > 0:
self.dialogue.put(
Message(role="assistant", content="".join(response_message))
)
text_buff = "".join(response_message)
self.tts_MessageText = text_buff
self.dialogue.put(Message(role="assistant", content=text_buff))
if depth == 0:
self.tts.tts_text_queue.put(
TTSMessageDTO(
@@ -893,9 +900,7 @@ class ConnectionHandler:
if self.executor is None:
continue
# 提交任务到线程池
self.executor.submit(
self._process_report, *item
)
self.executor.submit(self._process_report, *item)
except Exception as e:
self.logger.bind(tag=TAG).error(f"聊天记录上报线程异常: {e}")
except queue.Empty:
@@ -12,7 +12,7 @@ async def sendAudioMessage(conn, sentenceType, audios, text):
conn.logger.bind(tag=TAG).info(f"发送音频消息: {sentenceType}, {text}")
pre_buffer = False
if conn.tts.tts_audio_first_sentence and text is not None:
if conn.tts.tts_audio_first_sentence:
conn.logger.bind(tag=TAG).info(f"发送第一段语音: {text}")
conn.tts.tts_audio_first_sentence = False
pre_buffer = True
@@ -73,7 +73,7 @@ async def send_tts_message(conn, state, text=None):
"""发送 TTS 状态消息"""
message = {"type": "tts", "state": state, "session_id": conn.session_id}
if text is not None:
message["text"] = text
message["text"] = textUtils.check_emoji(text)
# TTS播放结束
if state == "stop":
@@ -127,8 +127,6 @@ class TTSProvider(TTSProviderBase):
# 专属tts设置
self.message_id = ""
self.tts_text = ""
self.text_buffer = []
# 创建Opus编码器
self.opus_encoder = opus_encoder_utils.OpusEncoderUtils(
@@ -229,7 +227,6 @@ class TTSProvider(TTSProviderBase):
# aliyunStream独有的参数生成
self.message_id = str(uuid.uuid4().hex)
self.text_buffer = []
logger.bind(tag=TAG).info("开始启动TTS会话...")
future = asyncio.run_coroutine_threadsafe(
@@ -250,7 +247,6 @@ class TTSProvider(TTSProviderBase):
logger.bind(tag=TAG).debug(
f"开始发送TTS文本: {message.content_detail}"
)
self.text_buffer.append(message.content_detail)
future = asyncio.run_coroutine_threadsafe(
self.text_to_speak(message.content_detail, None),
loop=self.conn.loop,
@@ -275,9 +271,6 @@ class TTSProvider(TTSProviderBase):
if message.sentence_type == SentenceType.LAST:
try:
logger.bind(tag=TAG).info("开始结束TTS会话...")
self.tts_text = textUtils.get_string_no_punctuation_or_emoji(
"".join(self.text_buffer).replace("\n", "")
)
future = asyncio.run_coroutine_threadsafe(
self.finish_session(self.conn.sentence_id),
loop=self.conn.loop,
@@ -444,34 +437,35 @@ class TTSProvider(TTSProviderBase):
event_name = header.get("name")
if event_name == "SynthesisStarted":
logger.bind(tag=TAG).debug("TTS合成已启动")
elif event_name == "SentenceBegin":
logger.bind(tag=TAG).debug(
f"句子语音生成开始: {self.tts_text}"
)
opus_datas_cache = []
self.tts_audio_queue.put(
(SentenceType.FIRST, [], self.tts_text)
(SentenceType.FIRST, [], None)
)
elif event_name == "SentenceBegin":
opus_datas_cache = []
elif event_name == "SentenceEnd":
logger.bind(tag=TAG).info(
f"句子语音生成成功: {self.tts_text}"
)
if (
not is_first_sentence
or first_sentence_segment_count > 10
):
# 发送缓存的数据
self.tts_audio_queue.put(
(SentenceType.MIDDLE, opus_datas_cache, None)
)
if self.conn.tts_MessageText:
logger.bind(tag=TAG).info(
f"句子语音生成成功: {self.conn.tts_MessageText}"
)
self.tts_audio_queue.put(
(SentenceType.MIDDLE, opus_datas_cache, self.conn.tts_MessageText)
)
self.conn.tts_MessageText = None
else:
self.tts_audio_queue.put(
(SentenceType.MIDDLE, opus_datas_cache, None)
)
# 第一句话结束后,将标志设置为False
is_first_sentence = False
elif event_name == "SynthesisCompleted":
logger.bind(tag=TAG).debug(f"会话结束~~")
self._process_before_stop_play_files()
session_finished = True
self.reuse_judgment = time.time()
self.tts_text = ""
break
except json.JSONDecodeError:
logger.bind(tag=TAG).warning("收到无效的JSON消息")
@@ -232,7 +232,6 @@ class TTSProvider(TTSProviderBase):
loop=self.conn.loop,
)
future.result()
self.tts_audio_first_sentence = True
self.before_stop_play_files.clear()
logger.bind(tag=TAG).info("TTS会话启动成功")
except Exception as e:
@@ -52,7 +52,6 @@ class TTSProvider(TTSProviderBase):
self.processed_chars = 0
self.tts_text_buff = []
self.segment_count = 0
self.tts_audio_first_sentence = True
self.before_stop_play_files.clear()
elif ContentType.TEXT == message.content_type:
self.tts_text_buff.append(message.content_detail)
@@ -0,0 +1,230 @@
import os
import uuid
import json
import requests
from datetime import datetime
from typing import Iterator, Optional, Union
from core.providers.tts.base import TTSProviderBase
from core.utils.util import parse_string_to_list
class TTSProvider(TTSProviderBase):
def __init__(self, config, delete_audio_file):
super().__init__(config, delete_audio_file)
self.group_id = config.get("group_id")
self.api_key = config.get("api_key")
self.model = config.get("model")
if config.get("private_voice"):
self.voice = config.get("private_voice")
else:
self.voice = config.get("voice_id")
default_voice_setting = {
"voice_id": "female-shaonv",
"speed": 1,
"vol": 1,
"pitch": 0,
"emotion": "happy",
}
default_pronunciation_dict = {"tone": ["处理/(chu3)(li3)", "危险/dangerous"]}
defult_audio_setting = {
"sample_rate": 32000,
"bitrate": 128000,
"format": "mp3",
"channel": 1,
}
self.voice_setting = {
**default_voice_setting,
**config.get("voice_setting", {}),
}
self.pronunciation_dict = {
**default_pronunciation_dict,
**config.get("pronunciation_dict", {}),
}
self.audio_setting = {**defult_audio_setting, **config.get("audio_setting", {})}
self.timber_weights = parse_string_to_list(config.get("timber_weights"))
if self.voice:
self.voice_setting["voice_id"] = self.voice
self.host = "api.minimax.chat"
self.api_url = f"https://{self.host}/v1/t2a_v2?GroupId={self.group_id}"
self.header = {
"Content-Type": "application/json",
"Authorization": f"Bearer {self.api_key}",
}
self.audio_file_type = defult_audio_setting.get("format", "mp3")
def generate_filename(self, extension=".mp3"):
return os.path.join(
self.output_file,
f"tts-{__name__}{datetime.now().date()}@{uuid.uuid4().hex}{extension}",
)
async def text_to_speak(self, text, output_file):
"""非流式语音合成(保留原有实现)"""
request_json = {
"model": self.model,
"text": text,
"stream": False,
"voice_setting": self.voice_setting,
"pronunciation_dict": self.pronunciation_dict,
"audio_setting": self.audio_setting,
}
if type(self.timber_weights) is list and len(self.timber_weights) > 0:
request_json["timber_weights"] = self.timber_weights
request_json["voice_setting"]["voice_id"] = ""
try:
resp = requests.post(
self.api_url, json.dumps(request_json), headers=self.header
)
if resp.json()["base_resp"]["status_code"] == 0:
data = resp.json()["data"]["audio"]
audio_bytes = bytes.fromhex(data)
if output_file:
with open(output_file, "wb") as file_to_save:
file_to_save.write(audio_bytes)
else:
return audio_bytes
else:
raise Exception(
f"{__name__} status_code: {resp.status_code} response: {resp.content}"
)
except Exception as e:
raise Exception(f"{__name__} error: {e}")
def text_to_speak_stream(
self,
text: str,
chunk_callback: Optional[callable] = None
) -> Iterator[bytes]:
"""
流式语音合成方法
:param text: 要合成的文本
:param chunk_callback: 可选的回调函数,用于处理每个音频块
:return: 生成器,每次产生一个音频数据块(bytes)
"""
request_json = {
"model": self.model,
"text": text,
"stream": True,
"voice_setting": self.voice_setting,
"pronunciation_dict": self.pronunciation_dict,
"audio_setting": self.audio_setting,
}
if isinstance(self.timber_weights, list) and len(self.timber_weights) > 0:
request_json["timber_weights"] = self.timber_weights
request_json["voice_setting"]["voice_id"] = ""
try:
with requests.post(
self.api_url,
data=json.dumps(request_json),
headers=self.header,
stream=True
) as response:
# 检查HTTP状态码
if response.status_code != 200:
raise Exception(
f"HTTP error: {response.status_code}, response: {response.text}"
)
# 处理流式响应
for line in response.iter_lines():
if line: # 过滤空行
# 检查是否为数据行 (SSE格式)
if line.startswith(b'data:'):
try:
data = json.loads(line[5:].strip()) # 去掉"data:"前缀
# 检查API状态码
if data.get("base_resp", {}).get("status_code", -1) != 0:
raise Exception(
f"API error: {data.get('base_resp', {}).get('status_msg')}"
)
# 跳过非音频数据块
if "extra_info" in data:
continue
# 提取音频数据
audio_hex = data.get("data", {}).get("audio")
if audio_hex:
audio_chunk = bytes.fromhex(audio_hex)
if chunk_callback:
chunk_callback(audio_chunk)
yield audio_chunk
except json.JSONDecodeError:
# 忽略JSON解析错误(可能是心跳包等)
continue
except Exception as e:
raise e
except Exception as e:
raise Exception(f"{__name__} stream error: {e}")
def save_stream_to_file(
self,
text: str,
output_file: Optional[str] = None,
progress_callback: Optional[callable] = None
) -> str:
"""
流式合成并保存到文件
:param text: 要合成的文本
:param output_file: 输出文件路径,如果为None则自动生成
:param progress_callback: 可选的回调函数,接收已写入的字节数
:return: 保存的文件路径
"""
if not output_file:
output_file = self.generate_filename(extension=f".{self.audio_file_type}")
os.makedirs(os.path.dirname(output_file), exist_ok=True)
total_bytes = 0
try:
with open(output_file, "wb") as audio_file:
for audio_chunk in self.text_to_speak_stream(text):
audio_file.write(audio_chunk)
audio_file.flush()
total_bytes += len(audio_chunk)
if progress_callback:
progress_callback(total_bytes)
return output_file
except Exception as e:
# 清理可能创建的不完整文件
if os.path.exists(output_file):
os.remove(output_file)
raise e
def stream_to_audio_player(self, text: str, player_command: list = None):
"""
流式合成并直接播放音频
:param text: 要合成的文本
:param player_command: 音频播放器命令,默认使用mpv
"""
if player_command is None:
player_command = ["mpv", "--no-cache", "--no-terminal", "--", "fd://0"]
try:
import subprocess
player_process = subprocess.Popen(
player_command,
stdin=subprocess.PIPE,
stdout=subprocess.DEVNULL,
stderr=subprocess.DEVNULL,
)
for audio_chunk in self.text_to_speak_stream(text):
player_process.stdin.write(audio_chunk)
player_process.stdin.flush()
player_process.stdin.close()
player_process.wait()
except Exception as e:
raise Exception(f"Audio player error: {e}")
@@ -0,0 +1,180 @@
import os
import uuid
import json
import asyncio
import websockets
import ssl
from datetime import datetime
from core.providers.tts.base import TTSProviderBase
from core.utils.util import parse_string_to_list
class TTSProvider(TTSProviderBase):
def __init__(self, config, delete_audio_file):
super().__init__(config, delete_audio_file)
self.group_id = config.get("group_id")
self.api_key = config.get("api_key")
self.model = config.get("model")
# 初始化语音设置
default_voice_setting = {
"voice_id": "female-shaonv",
"speed": 1,
"vol": 1,
"pitch": 0,
"emotion": "happy",
}
default_pronunciation_dict = {"tone": ["处理/(chu3)(li3)", "危险/dangerous"]}
default_audio_setting = {
"sample_rate": 32000,
"bitrate": 128000,
"format": "mp3",
"channel": 1,
}
# 合并配置
self.voice_setting = {
**default_voice_setting,
**config.get("voice_setting", {}),
}
self.pronunciation_dict = {
**default_pronunciation_dict,
**config.get("pronunciation_dict", {}),
}
self.audio_setting = {
**default_audio_setting,
**config.get("audio_setting", {})
}
self.timber_weights = parse_string_to_list(config.get("timber_weights"))
# 设置语音ID
if config.get("private_voice"):
self.voice_setting["voice_id"] = config.get("private_voice")
elif config.get("voice_id"):
self.voice_setting["voice_id"] = config.get("voice_id")
# WebSocket配置
self.ws_url = "wss://api.minimaxi.com/ws/v1/t2a_v2"
self.headers = {
"Authorization": f"Bearer {self.api_key}",
"GroupId": self.group_id
}
self.audio_file_type = self.audio_setting.get("format", "mp3")
def generate_filename(self, extension=".mp3"):
"""生成唯一的音频文件名"""
return os.path.join(
self.output_file,
f"tts-{__name__}{datetime.now().date()}@{uuid.uuid4().hex}{extension}",
)
async def _establish_connection(self):
"""建立WebSocket连接"""
ssl_context = ssl.create_default_context()
ssl_context.check_hostname = False
ssl_context.verify_mode = ssl.CERT_NONE
try:
ws = await websockets.connect(
self.ws_url,
additional_headers=self.headers,
ssl=ssl_context
)
connected = json.loads(await ws.recv())
if connected.get("event") == "connected_success":
print("连接成功")
return ws
return None
except Exception as e:
print(f"连接失败: {e}")
return None
async def _start_task(self, websocket):
"""发送任务开始请求"""
start_msg = {
"event": "task_start",
"model": self.model,
"voice_setting": self.voice_setting,
"pronunciation_dict": self.pronunciation_dict,
"audio_setting": self.audio_setting
}
if self.timber_weights and len(self.timber_weights) > 0:
start_msg["timber_weights"] = self.timber_weights
start_msg["voice_setting"]["voice_id"] = ""
await websocket.send(json.dumps(start_msg))
response = json.loads(await websocket.recv())
return response.get("event") == "task_started"
async def _continue_task(self, websocket, text):
"""发送继续请求并收集音频数据"""
await websocket.send(json.dumps({
"event": "task_continue",
"text": text
}))
audio_chunks = []
while True:
response = json.loads(await websocket.recv())
if "data" in response and "audio" in response["data"]:
audio_chunks.append(response["data"]["audio"])
if response.get("is_final"):
break
return "".join(audio_chunks)
async def _close_connection(self, websocket):
"""关闭连接"""
if websocket:
await websocket.send(json.dumps({"event": "task_finish"}))
await websocket.close()
print("连接已关闭")
async def text_to_speak(self, text, output_file=None):
"""主方法:文本转语音"""
ws = await self._establish_connection()
if not ws:
raise Exception("无法建立WebSocket连接")
try:
if not await self._start_task(ws):
raise Exception("任务启动失败")
hex_audio = await self._continue_task(ws, text)
audio_bytes = bytes.fromhex(hex_audio)
# 保存到文件或返回二进制数据
if output_file:
with open(output_file, "wb") as f:
f.write(audio_bytes)
print(f"音频已保存为{output_file}")
return output_file
else:
# 返回音频二进制数据(不播放)
return audio_bytes
finally:
await self._close_connection(ws)
async def main():
"""测试用主函数"""
# 示例配置
config = {
"group_id": "YOUR_GROUP_ID", # 替换为实际的group_id
"api_key": "YOUR_API_KEY", # 替换为实际的api_key
"model": "your-model", # 替换为实际的模型名称
"voice_id": "male-qn-qingse",
"voice_setting": {
"speed": 1.2,
"emotion": "happy"
}
}
tts = TTSProvider(config, delete_audio_file=True)
output_file = tts.generate_filename()
await tts.text_to_speak("这是一个测试文本,用于验证流式语音合成功能", output_file)
if __name__ == "__main__":
asyncio.run(main())
+21 -12
View File
@@ -24,6 +24,15 @@ EMOJI_MAP = {
"😘": "kissy",
"😏": "confident",
}
EMOJI_RANGES = [
(0x1F600, 0x1F64F),
(0x1F300, 0x1F5FF),
(0x1F680, 0x1F6FF),
(0x1F900, 0x1F9FF),
(0x1FA70, 0x1FAFF),
(0x2600, 0x26FF),
(0x2700, 0x27BF),
]
def get_string_no_punctuation_or_emoji(s):
@@ -65,18 +74,7 @@ def is_punctuation_or_emoji(char):
}
if char.isspace() or char in punctuation_set:
return True
# 检查表情符号(保留原有逻辑)
code_point = ord(char)
emoji_ranges = [
(0x1F600, 0x1F64F),
(0x1F300, 0x1F5FF),
(0x1F680, 0x1F6FF),
(0x1F900, 0x1F9FF),
(0x1FA70, 0x1FAFF),
(0x2600, 0x26FF),
(0x2700, 0x27BF),
]
return any(start <= code_point <= end for start, end in emoji_ranges)
return is_emoji(char)
async def get_emotion(conn, text):
@@ -102,3 +100,14 @@ async def get_emotion(conn, text):
except Exception as e:
conn.logger.bind(tag=TAG).warning(f"发送情绪表情失败,错误:{e}")
return
def is_emoji(char):
"""检查字符是否为emoji表情"""
code_point = ord(char)
return any(start <= code_point <= end for start, end in EMOJI_RANGES)
def check_emoji(text):
"""去除文本中的所有emoji表情"""
return ''.join(char for char in text if not is_emoji(char) and char != "\n")