Merge branch 'main' into main

core/handle/audioHandle.py

@@ -35,11 +35,13 @@ async def handleAudioMessage(conn, audio):
         conn.asr_audio.clear()
         conn.reset_vad_states()
 
+
 async def startToChat(conn, text):
     # 异步发送 stt 信息
-    asyncio.create_task(
+    stt_task = asyncio.create_task(
         schedule_with_interrupt(0, send_stt_message(conn, text))
     )
+    conn.scheduled_tasks.append(stt_task)
     conn.executor.submit(conn.chat, text)
 
 
@@ -52,7 +54,10 @@ async def sendAudioMessage(conn, audios, duration, text):
         conn.tts_start_speak_time = time.time()
 
     # 发送 sentence_start（每个音频文件之前发送一次）
-    await send_tts_message(conn, "sentence_start", text)
+    sentence_task = asyncio.create_task(
+        schedule_with_interrupt(base_delay, send_tts_message(conn, "sentence_start", text))
+    )
+    conn.scheduled_tasks.append(sentence_task)
 
     conn.tts_duration += duration
 
@@ -60,10 +65,6 @@ async def sendAudioMessage(conn, audios, duration, text):
     for idx, opus_packet in enumerate(audios):
         await conn.websocket.send(opus_packet)
 
-        # 每个音频文件发送结束时，发送 sentence_end
-        if idx == len(audios) - 1:
-            await send_tts_message(conn, "sentence_end", text)
-
     if conn.llm_finish_task and text == conn.tts_last_text:
         stop_duration = conn.tts_duration - (time.time() - conn.tts_start_speak_time)
         stop_task = asyncio.create_task(
@@ -71,6 +72,7 @@ async def sendAudioMessage(conn, audios, duration, text):
         )
         conn.scheduled_tasks.append(stop_task)
 
+
 async def send_tts_message(conn, state, text=None):
     """发送 TTS 状态消息"""
     message = {
@@ -85,6 +87,7 @@ async def send_tts_message(conn, state, text=None):
     if state == "stop":
         conn.clearSpeakStatus()
 
+
 async def send_stt_message(conn, text):
     """发送 STT 状态消息"""
     stt_text = get_string_no_punctuation_or_emoji(text)

core/providers/llm/base.py

@@ -0,0 +1,8 @@
+from abc import ABC, abstractmethod
+
+
+class LLMProviderBase(ABC):
+    @abstractmethod
+    def response(self, session_id, dialogue):
+        """LLM response generator"""
+        pass

core/providers/llm/dify/dify.py

@@ -0,0 +1,39 @@
+import json
+import logging
+import requests
+from core.providers.llm.base import LLMProviderBase
+
+logger = logging.getLogger(__name__)
+
+
+class LLMProvider(LLMProviderBase):
+    def __init__(self, config):
+        self.api_key = config["api_key"]
+        self.base_url = config.get("base_url", "https://api.dify.ai/v1").rstrip('/')
+
+    def response(self, session_id, dialogue):
+        try:
+            # 取最后一条用户消息
+            last_msg = next(m for m in reversed(dialogue) if m["role"] == "user")
+
+            # 发起流式请求
+            with requests.post(
+                    f"{self.base_url}/chat-messages",
+                    headers={"Authorization": f"Bearer {self.api_key}"},
+                    json={
+                        "query": last_msg["content"],
+                        "response_mode": "streaming",
+                        "user": session_id,
+                        "inputs": {}
+                    },
+                    stream=True
+            ) as r:
+                for line in r.iter_lines():
+                    if line.startswith(b'data: '):
+                        event = json.loads(line[6:])
+                        if event.get('answer'):
+                            yield event['answer']
+
+        except Exception as e:
+            logger.error(f"Error in response generation: {e}")
+            yield "【服务响应异常】"

core/providers/llm/openai/openai.py

@@ -0,0 +1,35 @@
+import logging
+import openai
+from core.providers.llm.base import LLMProviderBase
+
+logger = logging.getLogger(__name__)
+
+
+class LLMProvider(LLMProviderBase):
+    def __init__(self, config):
+        self.model_name = config.get("model_name")
+        self.api_key = config.get("api_key")
+        if 'base_url' in config:
+            self.base_url = config.get("base_url")
+        else:
+            self.base_url = config.get("url")
+        if "你" in self.api_key:
+            logger.error("你还没配置LLM的密钥，请在配置文件中配置密钥，否则无法正常工作")
+        self.client = openai.OpenAI(api_key=self.api_key, base_url=self.base_url)
+
+    def response(self, session_id, dialogue):
+        try:
+            responses = self.client.chat.completions.create(
+                model=self.model_name,
+                messages=dialogue,
+                stream=True
+            )
+            for chunk in responses:
+                # 检查是否存在有效的choice且content不为空
+                if chunk.choices and len(chunk.choices) > 0:
+                    delta = chunk.choices[0].delta
+                    content = getattr(delta, 'content', '')
+                    if content:  # 仅在content非空时生成
+                        yield content
+        except Exception as e:
+            logger.error(f"Error in response generation: {e}")

core/providers/tts/base.py

@@ -0,0 +1,83 @@
+import asyncio
+import logging
+import os
+import numpy as np
+import opuslib
+from pydub import AudioSegment
+from abc import ABC, abstractmethod
+
+logger = logging.getLogger(__name__)
+
+
+class TTSProviderBase(ABC):
+    def __init__(self, config, delete_audio_file):
+        self.delete_audio_file = delete_audio_file
+        self.output_file = config.get("output_file")
+
+    @abstractmethod
+    def generate_filename(self):
+        pass
+
+    def to_tts(self, text):
+        tmp_file = self.generate_filename()
+        try:
+            max_repeat_time = 5
+            while not os.path.exists(tmp_file) and max_repeat_time > 0:
+                asyncio.run(self.text_to_speak(text, tmp_file))
+                if not os.path.exists(tmp_file):
+                    max_repeat_time = max_repeat_time - 1
+                    logger.error(f"语音生成失败: {text}:{tmp_file}，再试{max_repeat_time}次")
+
+            if max_repeat_time > 0:
+                logger.info(f"语音生成成功: {text}:{tmp_file}，重试{5 - max_repeat_time}次")
+
+            return tmp_file
+        except Exception as e:
+            logger.info(f"Failed to generate TTS file: {e}")
+            return None
+
+    @abstractmethod
+    async def text_to_speak(self, text, output_file):
+        pass
+
+    def wav_to_opus_data(self, wav_file_path):
+        # 使用pydub加载PCM文件
+        # 获取文件后缀名
+        file_type = os.path.splitext(wav_file_path)[1]
+        if file_type:
+            file_type = file_type.lstrip('.')
+        audio = AudioSegment.from_file(wav_file_path, format=file_type)
+
+        duration = len(audio) / 1000.0
+
+        # 转换为单声道和16kHz采样率（确保与编码器匹配）
+        audio = audio.set_channels(1).set_frame_rate(16000)
+
+        # 获取原始PCM数据（16位小端）
+        raw_data = audio.raw_data
+
+        # 初始化Opus编码器
+        encoder = opuslib.Encoder(16000, 1, opuslib.APPLICATION_AUDIO)
+
+        # 编码参数
+        frame_duration = 60  # 60ms per frame
+        frame_size = int(16000 * frame_duration / 1000)  # 960 samples/frame
+
+        opus_datas = []
+        # 按帧处理所有音频数据（包括最后一帧可能补零）
+        for i in range(0, len(raw_data), frame_size * 2):  # 16bit=2bytes/sample
+            # 获取当前帧的二进制数据
+            chunk = raw_data[i:i + frame_size * 2]
+
+            # 如果最后一帧不足，补零
+            if len(chunk) < frame_size * 2:
+                chunk += b'\x00' * (frame_size * 2 - len(chunk))
+
+            # 转换为numpy数组处理
+            np_frame = np.frombuffer(chunk, dtype=np.int16)
+
+            # 编码Opus数据
+            opus_data = encoder.encode(np_frame.tobytes(), frame_size)
+            opus_datas.append(opus_data)
+
+        return opus_datas, duration

core/providers/tts/doubao.py

@@ -0,0 +1,56 @@
+import os
+import uuid
+import json
+import base64
+import requests
+from datetime import datetime
+from core.providers.tts.base import TTSProviderBase
+
+
+class TTSProvider(TTSProviderBase):
+    def __init__(self, config, delete_audio_file):
+        super().__init__(config, delete_audio_file)
+        self.appid = config.get("appid")
+        self.access_token = config.get("access_token")
+        self.cluster = config.get("cluster")
+        self.voice = config.get("voice")
+
+        self.host = "openspeech.bytedance.com"
+        self.api_url = f"https://{self.host}/api/v1/tts"
+        self.header = {"Authorization": f"Bearer;{self.access_token}"}
+
+    def generate_filename(self, extension=".wav"):
+        return os.path.join(self.output_file, f"tts-{datetime.now().date()}@{uuid.uuid4().hex}{extension}")
+
+    async def text_to_speak(self, text, output_file):
+        request_json = {
+            "app": {
+                "appid": self.appid,
+                "token": "access_token",
+                "cluster": self.cluster
+            },
+            "user": {
+                "uid": "1"
+            },
+            "audio": {
+                "voice_type": self.voice,
+                "encoding": "wav",
+                "speed_ratio": 1.0,
+                "volume_ratio": 1.0,
+                "pitch_ratio": 1.0,
+            },
+            "request": {
+                "reqid": str(uuid.uuid4()),
+                "text": text,
+                "text_type": "plain",
+                "operation": "query",
+                "with_frontend": 1,
+                "frontend_type": "unitTson"
+            }
+        }
+
+        resp = requests.post(self.api_url, json.dumps(request_json), headers=self.header)
+        if "data" in resp.json():
+            data = resp.json()["data"]
+            file_to_save = open(output_file, "wb")
+            file_to_save.write(base64.b64decode(data))

core/providers/tts/edge.py

@@ -0,0 +1,18 @@
+import os
+import uuid
+import edge_tts
+from datetime import datetime
+from core.providers.tts.base import TTSProviderBase
+
+
+class TTSProvider(TTSProviderBase):
+    def __init__(self, config, delete_audio_file):
+        super().__init__(config, delete_audio_file)
+        self.voice = config.get("voice")
+
+    def generate_filename(self, extension=".mp3"):
+        return os.path.join(self.output_file, f"tts-{datetime.now().date()}@{uuid.uuid4().hex}{extension}")
+
+    async def text_to_speak(self, text, output_file):
+        communicate = edge_tts.Communicate(text, voice=self.voice)  # Use your preferred voice
+        await communicate.save(output_file)

core/server.py

@@ -25,11 +25,17 @@ class WebSocketServer:
                 self.config["delete_audio"]
             ),
             llm.create_instance(
-                self.config["selected_module"]["LLM"],
+                self.config["selected_module"]["LLM"]
+                if not 'type' in self.config["LLM"][self.config["selected_module"]["LLM"]]
+                else
+                self.config["LLM"][self.config["selected_module"]["LLM"]]['type'],
                 self.config["LLM"][self.config["selected_module"]["LLM"]],
             ),
             tts.create_instance(
-                self.config["selected_module"]["TTS"],
+                self.config["selected_module"]["TTS"]
+                if not 'type' in self.config["TTS"][self.config["selected_module"]["TTS"]]
+                else
+                self.config["TTS"][self.config["selected_module"]["TTS"]]["type"],
                 self.config["TTS"][self.config["selected_module"]["TTS"]],
                 self.config["delete_audio"]
             )

core/utils/llm.py

@@ -1,7 +1,10 @@
+import os
+import sys
 import json
 import logging
 import openai
 import requests
+import importlib
 from datetime import datetime
 from core.utils.util import is_segment
 from core.utils.util import get_string_no_punctuation_or_emoji
@@ -11,132 +14,15 @@ from abc import ABC, abstractmethod
 logger = logging.getLogger(__name__)
 
 
-class LLM(ABC):
-    @abstractmethod
-    def response(self, session_id, dialogue):
-        """LLM response generator"""
-        pass
-
-
-class DeepSeekLLM(LLM):
-    def __init__(self, config):
-        self.model_name = config.get("model_name")
-        self.api_key = config.get("api_key")
-        self.base_url = config.get("url")
-        self.client = openai.OpenAI(api_key=self.api_key, base_url=self.base_url)
-
-    def response(self, session_id, dialogue):
-        logger.info(f"Generating response using {dialogue}")
-        try:
-            responses = self.client.chat.completions.create(
-                model=self.model_name,
-                messages=dialogue,
-                stream=True
-            )
-            for chunk in responses:
-                # 检查是否存在有效的choice且content不为空
-                if chunk.choices and len(chunk.choices) > 0:
-                    delta = chunk.choices[0].delta
-                    content = getattr(delta, 'content', '')
-                    if content:  # 仅在content非空时生成
-                        yield content
-        except Exception as e:
-            logger.error(f"Error in response generation: {e}")
-
-
-class ChatGLMLLM(LLM):
-    def __init__(self, config):
-        self.model_name = config.get("model_name")
-        self.api_key = config.get("api_key")
-        self.base_url = config.get("url")
-        self.client = openai.OpenAI(api_key=self.api_key, base_url=self.base_url)
-
-    def response(self, session_id, dialogue):
-        try:
-            responses = self.client.chat.completions.create(
-                model=self.model_name,
-                messages=dialogue,
-                stream=True
-            )
-            for chunk in responses:
-                # 检查是否存在有效的choice且content不为空
-                if chunk.choices and len(chunk.choices) > 0:
-                    delta = chunk.choices[0].delta
-                    content = getattr(delta, 'content', '')
-                    if content:  # 仅在content非空时生成
-                        yield content
-        except Exception as e:
-            logger.error(f"Error in response generation: {e}")
-
-class AliLLM(LLM):
-    def __init__(self, config):
-        self.model_name = config.get("model_name")
-        self.api_key = config.get("api_key")
-        self.base_url = config.get("base_url")
-        self.client = openai.OpenAI(api_key=self.api_key, base_url=self.base_url)
-
-    def response(self, session_id, dialogue):
-        try:
-            responses = self.client.chat.completions.create(
-                model=self.model_name,
-                messages=dialogue,
-                stream=True
-            )
-            for chunk in responses:
-                # 检查是否存在有效的choice且content不为空
-                if chunk.choices and len(chunk.choices) > 0:
-                    delta = chunk.choices[0].delta
-                    content = getattr(delta, 'content', '')
-                    if content:  # 仅在content非空时生成
-                        yield content
-        except Exception as e:
-            logger.error(f"Error in response generation: {e}")
-
-class DifyLLM(LLM):
-    def __init__(self, config):
-        self.api_key = config["api_key"]
-        self.base_url = config.get("base_url", "https://api.dify.ai/v1").rstrip('/')
-
-    def response(self, session_id, dialogue):
-        try:
-            # 取最后一条用户消息
-            last_msg = next(m for m in reversed(dialogue) if m["role"] == "user")
-
-            # 发起流式请求
-            with requests.post(
-                    f"{self.base_url}/chat-messages",
-                    headers={"Authorization": f"Bearer {self.api_key}"},
-                    json={
-                        "query": last_msg["content"],
-                        "response_mode": "streaming",
-                        "user": session_id,
-                        "inputs": {}
-                    },
-                    stream=True
-            ) as r:
-                for line in r.iter_lines():
-                    if line.startswith(b'data: '):
-                        event = json.loads(line[6:])
-                        if event.get('answer'):
-                            yield event['answer']
-
-        except Exception:
-            yield "【服务响应异常】"
-
-
 def create_instance(class_name, *args, **kwargs):
-    # 获取类对象
-    cls_map = {
-        "DeepSeekLLM": DeepSeekLLM,
-        "ChatGLMLLM": ChatGLMLLM,
-        "DifyLLM": DifyLLM,
-        "AliLLM": AliLLM,
-        # 可扩展其他LLM实现
-    }
+    # 创建LLM实例
+    if os.path.exists(os.path.join('core', 'providers', 'llm', class_name, f'{class_name}.py')):
+        lib_name = f'core.providers.llm.{class_name}.{class_name}'
+        if lib_name not in sys.modules:
+            sys.modules[lib_name] = importlib.import_module(f'{lib_name}')
+            return sys.modules[lib_name].LLMProvider(*args, **kwargs)
 
-    if cls := cls_map.get(class_name):
-        return cls(*args, **kwargs)
-    raise ValueError(f"不支持的LLM类型: {class_name}")
+    raise ValueError(f"不支持的LLM类型: {class_name}，请检查该配置的type是否设置正确")
 
 
 if __name__ == "__main__":
@@ -145,7 +31,10 @@ if __name__ == "__main__":
     """
     config = read_config(get_project_dir() + "config.yaml")
     llm = create_instance(
-        config["selected_module"]["LLM"],
+        config["selected_module"]["LLM"]
+        if not "type" in config["LLM"][config["selected_module"]["LLM"]]
+        else
+        config["LLM"][config["selected_module"]["LLM"]]["type"],
         config["LLM"][config["selected_module"]["LLM"]]
     )
 

core/utils/tts.py

@@ -1,165 +1,22 @@
-import asyncio
-import logging
 import os
-import json
-import uuid
-import base64
+import sys
+import logging
+import importlib
 from datetime import datetime
-import edge_tts
-import numpy as np
-import opuslib
-import requests
 from core.utils.util import read_config, get_project_dir
-from pydub import AudioSegment
-from abc import ABC, abstractmethod
 
 logger = logging.getLogger(__name__)
 
 
-class TTS(ABC):
-    def __init__(self, config, delete_audio_file):
-        self.delete_audio_file = delete_audio_file
-        self.output_file = config.get("output_file")
-
-    @abstractmethod
-    def generate_filename(self):
-        pass
-
-    def to_tts(self, text):
-        tmp_file = self.generate_filename()
-        try:
-            max_repeat_time = 5
-            while not os.path.exists(tmp_file) and max_repeat_time > 0:
-                asyncio.run(self.text_to_speak(text, tmp_file))
-                if not os.path.exists(tmp_file):
-                    max_repeat_time = max_repeat_time - 1
-                    logger.error(f"语音生成失败: {text}:{tmp_file}，再试{max_repeat_time}次")
-
-            return tmp_file
-        except Exception as e:
-            logger.info(f"Failed to generate TTS file: {e}")
-            return None
-
-    @abstractmethod
-    async def text_to_speak(self, text, output_file):
-        pass
-
-    def wav_to_opus_data(self, wav_file_path):
-        # 使用pydub加载PCM文件
-        # 获取文件后缀名
-        file_type = os.path.splitext(wav_file_path)[1]
-        if file_type:
-            file_type = file_type.lstrip('.')
-        audio = AudioSegment.from_file(wav_file_path, format=file_type)
-
-        duration = len(audio) / 1000.0
-
-        # 转换为单声道和16kHz采样率（确保与编码器匹配）
-        audio = audio.set_channels(1).set_frame_rate(16000)
-
-        # 获取原始PCM数据（16位小端）
-        raw_data = audio.raw_data
-
-        # 初始化Opus编码器
-        encoder = opuslib.Encoder(16000, 1, opuslib.APPLICATION_AUDIO)
-
-        # 编码参数
-        frame_duration = 60  # 60ms per frame
-        frame_size = int(16000 * frame_duration / 1000)  # 960 samples/frame
-
-        opus_datas = []
-        # 按帧处理所有音频数据（包括最后一帧可能补零）
-        for i in range(0, len(raw_data), frame_size * 2):  # 16bit=2bytes/sample
-            # 获取当前帧的二进制数据
-            chunk = raw_data[i:i + frame_size * 2]
-
-            # 如果最后一帧不足，补零
-            if len(chunk) < frame_size * 2:
-                chunk += b'\x00' * (frame_size * 2 - len(chunk))
-
-            # 转换为numpy数组处理
-            np_frame = np.frombuffer(chunk, dtype=np.int16)
-
-            # 编码Opus数据
-            opus_data = encoder.encode(np_frame.tobytes(), frame_size)
-            opus_datas.append(opus_data)
-
-        return opus_datas, duration
-
-
-class EdgeTTS(TTS):
-    def __init__(self, config, delete_audio_file):
-        super().__init__(config, delete_audio_file)
-        self.voice = config.get("voice")
-
-    def generate_filename(self, extension=".mp3"):
-        return os.path.join(self.output_file, f"tts-{datetime.now().date()}@{uuid.uuid4().hex}{extension}")
-
-    async def text_to_speak(self, text, output_file):
-        communicate = edge_tts.Communicate(text, voice=self.voice)  # Use your preferred voice
-        await communicate.save(output_file)
-
-
-class DoubaoTTS(TTS):
-    def __init__(self, config, delete_audio_file):
-        super().__init__(config, delete_audio_file)
-        self.appid = config.get("appid")
-        self.access_token = config.get("access_token")
-        self.cluster = config.get("cluster")
-        self.voice = config.get("voice")
-
-        self.host = "openspeech.bytedance.com"
-        self.api_url = f"https://{self.host}/api/v1/tts"
-        self.header = {"Authorization": f"Bearer;{self.access_token}"}
-
-    def generate_filename(self, extension=".wav"):
-        return os.path.join(self.output_file, f"tts-{datetime.now().date()}@{uuid.uuid4().hex}{extension}")
-
-    async def text_to_speak(self, text, output_file):
-        request_json = {
-            "app": {
-                "appid": self.appid,
-                "token": "access_token",
-                "cluster": self.cluster
-            },
-            "user": {
-                "uid": "1"
-            },
-            "audio": {
-                "voice_type": self.voice,
-                "encoding": "wav",
-                "speed_ratio": 1.0,
-                "volume_ratio": 1.0,
-                "pitch_ratio": 1.0,
-            },
-            "request": {
-                "reqid": str(uuid.uuid4()),
-                "text": text,
-                "text_type": "plain",
-                "operation": "query",
-                "with_frontend": 1,
-                "frontend_type": "unitTson"
-            }
-        }
-
-        resp = requests.post(self.api_url, json.dumps(request_json), headers=self.header)
-        if "data" in resp.json():
-            data = resp.json()["data"]
-            file_to_save = open(output_file, "wb")
-            file_to_save.write(base64.b64decode(data))
-
-
 def create_instance(class_name, *args, **kwargs):
-    # 获取类对象
-    cls_map = {
-        "DoubaoTTS": DoubaoTTS,
-        "EdgeTTS": EdgeTTS,
-        # 可扩展其他TTS实现
-    }
+    # 创建TTS实例
+    if os.path.exists(os.path.join('core', 'providers', 'tts', f'{class_name}.py')):
+        lib_name = f'core.providers.tts.{class_name}'
+        if lib_name not in sys.modules:
+            sys.modules[lib_name] = importlib.import_module(f'{lib_name}')
+            return sys.modules[lib_name].TTSProvider(*args, **kwargs)
 
-    if cls := cls_map.get(class_name):
-        return cls(*args, **kwargs)
-    raise ValueError(f"不支持的TTS类型: {class_name}")
+    raise ValueError(f"不支持的TTS类型: {class_name}，请检查该配置的type是否设置正确")
 
 
 if __name__ == "__main__":
@@ -168,7 +25,10 @@ if __name__ == "__main__":
     """
     config = read_config(get_project_dir() + "config.yaml")
     tts = create_instance(
-        config["selected_module"]["TTS"],
+        config["selected_module"]["TTS"]
+        if not 'type' in config["TTS"][config["selected_module"]["TTS"]]
+        else
+        config["TTS"][config["selected_module"]["TTS"]]["type"],
         config["TTS"][config["selected_module"]["TTS"]],
         config["delete_audio"]
     )

core/utils/util.py

@@ -1,8 +1,7 @@
-import yaml
-import unicodedata
-import socket
 import os
 import json
+import yaml
+import socket
 
 
 def get_project_dir():
@@ -41,6 +40,7 @@ def is_segment(tokens):
     else:
         return False
 
+
 def is_punctuation_or_emoji(char):
     """检查字符是否为空格、指定标点或表情符号"""
     # 定义需要去除的中英文标点（包括全角/半角）
@@ -49,7 +49,7 @@ def is_punctuation_or_emoji(char):
         '。', '.',  # 中文句号 + 英文句号
         '！', '!',  # 中文感叹号 + 英文感叹号
         '-', '－',  # 英文连字符 + 中文全角横线
-        '、'         # 中文顿号
+        '、'  # 中文顿号
     }
     if char.isspace() or char in punctuation_set:
         return True
@@ -63,6 +63,7 @@ def is_punctuation_or_emoji(char):
     ]
     return any(start <= code_point <= end for start, end in emoji_ranges)
 
+
 def get_string_no_punctuation_or_emoji(s):
     """去除字符串首尾的空格、标点符号和表情符号"""
     chars = list(s)
@@ -74,7 +75,8 @@ def get_string_no_punctuation_or_emoji(s):
     end = len(chars) - 1
     while end >= start and is_punctuation_or_emoji(chars[end]):
         end -= 1
-    return ''.join(chars[start:end+1])
+    return ''.join(chars[start:end + 1])
+
 
 def remove_punctuation_and_length(text):
     # 全角符号和半角符号的Unicode范围