mirror of
https://github.com/xinnan-tech/xiaozhi-esp32-server.git
synced 2026-07-22 07:03:53 +08:00
Merge branch 'xinnan-tech:main' into fix/manager-api-voice-print
This commit is contained in:
@@ -235,7 +235,7 @@ Websocket接口地址: wss://2662r3426b.vicp.fun/xiaozhi/v1/
|
||||
---
|
||||
## 功能清单 ✨
|
||||
### 已实现 ✅
|
||||
|
||||

|
||||
| 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
@@ -233,7 +233,7 @@ This project provides the following testing tools to help you verify the system
|
||||
---
|
||||
## Feature List ✨
|
||||
### Implemented ✅
|
||||
|
||||

|
||||
| 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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|
Before Width: | Height: | Size: 644 KiB After Width: | Height: | Size: 256 KiB |
@@ -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
|
||||
|
||||
+24
@@ -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) {
|
||||
|
||||
+9
-5
@@ -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);
|
||||
|
||||
+38
@@ -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()
|
||||
|
||||
@@ -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({
|
||||
|
||||
@@ -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;
|
||||
|
||||
@@ -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/
|
||||
|
||||
@@ -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
|
||||
|
||||
|
||||
|
||||
@@ -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())
|
||||
@@ -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")
|
||||
|
||||
Reference in New Issue
Block a user