重新划分目录 (#214)

* 🦄 refactor(web): 修改zhikongtaiweb到web

* 🦄 refactor: 重写前端

路由守护尚未写完

* 🦄 refactor: 标准化路由

* update:前端重写,保留后端

* update:添加前端代码

* update:pip转成poetry启动

* update:增加mem0ai包依赖

* update:文档增加mem0ai的描述

* feat: play online mp3 (#181)

Co-authored-by: 欣南科技 <huangrongzhuang@xin-nan.com>

* 修改前端代码

* update:调整项目目录

* update:优化

* update:配置文件去除8002端口

* update:增加开发说明

* update:更新开发协议

---------

Co-authored-by: kalicyh <34980061+kaliCYH@users.noreply.github.com>
Co-authored-by: hrz <1710360675@qq.com>
Co-authored-by: freshlife001 <talent@mises.site>
Co-authored-by: CGD <3030332422@qq.com>
This commit is contained in:
欣南科技
2025-03-05 23:13:24 +08:00
committed by GitHub
co-authored by kalicyh hrz freshlife001 CGD
parent 8b151d07c2
commit 0e43748fdc
289 changed files with 18127 additions and 85418 deletions
+24
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import importlib
import logging
import os
import sys
import time
import wave
import uuid
from abc import ABC, abstractmethod
from typing import Optional, Tuple, List
from core.providers.asr.base import ASRProviderBase
from config.logger import setup_logging
TAG = __name__
logger = setup_logging()
def create_instance(class_name: str, *args, **kwargs) -> ASRProviderBase:
"""工厂方法创建ASR实例"""
if os.path.exists(os.path.join('core', 'providers', 'asr', f'{class_name}.py')):
lib_name = f'core.providers.asr.{class_name}'
if lib_name not in sys.modules:
sys.modules[lib_name] = importlib.import_module(f'{lib_name}')
return sys.modules[lib_name].ASRProvider(*args, **kwargs)
raise ValueError(f"不支持的ASR类型: {class_name},请检查该配置的type是否设置正确")
@@ -0,0 +1,97 @@
import random
import threading
import time
from typing import Set
class AuthCodeGenerator:
_instance = None
_instance_lock = threading.Lock()
def __new__(cls):
if not cls._instance:
with cls._instance_lock:
if not cls._instance:
cls._instance = super(AuthCodeGenerator, cls).__new__(cls)
# 初始化随机种子
random.seed(time.time())
return cls._instance
def __init__(self):
# 确保 __init__ 只被调用一次
if not hasattr(self, '_initialized'):
self._used_codes: Set[str] = set()
self._code_timestamps = {}
self._lock = threading.Lock()
self._code_timeout = 3 * 24 * 60 * 60
self._initialized = True
@classmethod
def get_instance(cls):
"""获取AuthCodeGenerator的单例实例"""
return cls()
def generate_code(self) -> str:
"""
生成6位数字认证码,确保不重复
返回: 6位数字字符串
"""
with self._lock:
self._clean_expired_codes() # 清理过期code
while True:
# 使用时间戳和已用码数量作为种子,确保每次生成不同的随机数
seed = int(time.time() * 1000) + len(self._used_codes)
random.seed(seed)
# 生成6位随机数字
code = ''.join(str(random.randint(0, 9)) for _ in range(6))
# 检查是否已存在
if code not in self._used_codes:
self._used_codes.add(code)
self._code_timestamps[code] = time.time()
return code
def remove_code(self, code: str) -> bool:
"""
删除已使用的认证码
参数:
code: 要删除的认证码
返回:
bool: 删除成功返回True,码不存在返回False
"""
print('remove_code', code)
with self._lock:
if code in self._used_codes:
self._used_codes.remove(code)
if code in self._code_timestamps:
del self._code_timestamps[code]
return True
return False
def is_code_used(self, code: str) -> bool:
"""
检查认证码是否已被使用
参数:
code: 要检查的认证码
返回:
bool: 如果码存在返回True,否则返回False
"""
with self._lock:
return code in self._used_codes
def clear_codes(self):
"""清空所有已使用的认证码"""
with self._lock:
self._used_codes.clear()
self._code_timestamps.clear()
def _clean_expired_codes(self):
"""清理过期的认证码"""
current_time = time.time()
expired_codes = [
code for code, timestamp in self._code_timestamps.items()
if (current_time - timestamp) > self._code_timeout
]
for code in expired_codes:
self._used_codes.remove(code)
del self._code_timestamps[code]
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import uuid
from typing import List, Dict
from datetime import datetime
class Message:
def __init__(self, role: str, content: str = None, uniq_id: str = None):
self.uniq_id = uniq_id if uniq_id is not None else str(uuid.uuid4())
self.role = role
self.content = content
class Dialogue:
def __init__(self):
self.dialogue: List[Message] = []
# 获取当前时间
self.current_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
def put(self, message: Message):
self.dialogue.append(message)
def get_llm_dialogue(self) -> List[Dict[str, str]]:
dialogue = []
for m in self.dialogue:
dialogue.append({"role": m.role, "content": m.content})
return dialogue
def get_llm_dialogue_with_memory(self, memory_str: str = None) -> List[Dict[str, str]]:
# 构建带记忆的对话
dialogue = []
# 添加系统提示和记忆
system_message = next(
(msg for msg in self.dialogue if msg.role == "system"), None
)
if system_message:
enhanced_system_prompt = (
f"{system_message.content}\n\n"
f"相关记忆:\n{memory_str}"
)
dialogue.append({"role": "system", "content": enhanced_system_prompt})
# 添加用户和助手的对话
for msg in self.dialogue:
if msg.role != "system": # 跳过原始的系统消息
dialogue.append({"role": msg.role, "content": msg.content})
return dialogue
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import os
import sys
# 添加项目根目录到Python路径
current_dir = os.path.dirname(os.path.abspath(__file__))
project_root = os.path.abspath(os.path.join(current_dir, "..", ".."))
sys.path.insert(0, project_root)
from config.logger import setup_logging
import importlib
logger = setup_logging()
def create_instance(class_name, *args, **kwargs):
# 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)
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")
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import asyncio
from typing import Dict
from config.logger import setup_logging
TAG = __name__
logger = setup_logging()
class FileLockManager:
_instance = None
_locks: Dict[str, asyncio.Lock] = {}
def __new__(cls):
if cls._instance is None:
cls._instance = super(FileLockManager, cls).__new__(cls)
return cls._instance
@classmethod
def get_lock(cls, file_path: str) -> asyncio.Lock:
"""获取指定文件的锁"""
if file_path not in cls._locks:
cls._locks[file_path] = asyncio.Lock()
return cls._locks[file_path]
@classmethod
async def acquire_lock(cls, file_path: str):
"""获取锁"""
lock = cls.get_lock(file_path)
await lock.acquire()
logger.bind(tag=TAG).debug(f"Acquired lock for {file_path}")
@classmethod
def release_lock(cls, file_path: str):
"""释放锁"""
if file_path in cls._locks:
try:
cls._locks[file_path].release()
logger.bind(tag=TAG).debug(f"Released lock for {file_path}")
except RuntimeError as e:
logger.bind(tag=TAG).warning(f"Failed to release lock for {file_path}: {e}")
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import os
import sys
import importlib
from config.logger import setup_logging
from core.utils.util import read_config, get_project_dir
logger = setup_logging()
def create_instance(class_name, *args, **kwargs):
if os.path.exists(os.path.join('core', 'providers', 'memory', class_name, f'{class_name}.py')):
lib_name = f'core.providers.memory.{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].MemoryProvider(*args, **kwargs)
raise ValueError(f"不支持的记忆服务类型: {class_name}")
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import struct
def decode_opus_from_file(input_file):
"""
从p3文件中解码 Opus 数据,并返回一个 Opus 数据包的列表以及总时长。
"""
opus_datas = []
total_frames = 0
sample_rate = 16000 # 文件采样率
frame_duration_ms = 60 # 帧时长
frame_size = int(sample_rate * frame_duration_ms / 1000)
with open(input_file, 'rb') as f:
while True:
# 读取头部(4字节):[1字节类型,1字节保留,2字节长度]
header = f.read(4)
if not header:
break
# 解包头部信息
_, _, data_len = struct.unpack('>BBH', header)
# 根据头部指定的长度读取 Opus 数据
opus_data = f.read(data_len)
if len(opus_data) != data_len:
raise ValueError(f"Data length({len(opus_data)}) mismatch({data_len}) in the file.")
opus_datas.append(opus_data)
total_frames += 1
# 计算总时长
total_duration = (total_frames * frame_duration_ms) / 1000.0
return opus_datas, total_duration
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import os
import sys
from config.logger import setup_logging
import importlib
logger = setup_logging()
def create_instance(class_name, *args, **kwargs):
# 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)
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")
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import os
import re
import json
import yaml
import socket
import subprocess
def get_project_dir():
"""获取项目根目录"""
return os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) + '/'
def get_local_ip():
try:
s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
# Connect to Google's DNS servers
s.connect(("8.8.8.8", 80))
local_ip = s.getsockname()[0]
s.close()
return local_ip
except Exception as e:
return "127.0.0.1"
def read_config(config_path):
with open(config_path, "r", encoding="utf-8") as file:
config = yaml.safe_load(file)
return config
def write_json_file(file_path, data):
"""将数据写入 JSON 文件"""
with open(file_path, 'w', encoding='utf-8') as file:
json.dump(data, file, ensure_ascii=False, indent=4)
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)
punctuation_set = {
'', ',', # 中文逗号 + 英文逗号
'', '.', # 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
}
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)
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)
# 处理开头的字符
start = 0
while start < len(chars) and is_punctuation_or_emoji(chars[start]):
start += 1
# 处理结尾的字符
end = len(chars) - 1
while end >= start and is_punctuation_or_emoji(chars[end]):
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
full_width_punctuations = '!"#$%&'()*+,-。/:;<=>?@[\]^_`{|}~'
half_width_punctuations = '!"#$%&\'()*+,-./:;<=>?@[\]^_`{|}~'
space = ' ' # 半角空格
full_width_space = ' ' # 全角空格
# 去除全角和半角符号以及空格
result = ''.join([char for char in text if
char not in full_width_punctuations and char not in half_width_punctuations and char not in space and char not in full_width_space])
if result == "Yeah":
return 0, ""
return len(result), result
def check_password(password):
"""
检查密码是否满足以下条件:
1. 密码长度大于八位。
2. 密码包含英文和数字。
3. 密码不能包含“xiaozhi”字符。
:param password: 要检查的密码
:return: 如果密码满足条件,则返回True;否则返回False。
"""
# 检查密码长度
if len(password) < 8:
return False
# 检查是否包含英文字符和数字
if not re.search(r'[A-Za-z]', password) or not re.search(r'[0-9]', password):
return False
# 检查是否包含“xiaozhi”字符
if "xiaozhi" in password:
return False
if "1234" in password:
return False
# 如果满足所有条件,则返回True
return True
def check_ffmpeg_installed():
ffmpeg_installed = False
try:
# 执行ffmpeg -version命令,并捕获输出
result = subprocess.run(
['ffmpeg', '-version'],
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
text=True,
check=True # 如果返回码非零则抛出异常
)
# 检查输出中是否包含版本信息(可选)
output = result.stdout + result.stderr
if 'ffmpeg version' in output.lower():
ffmpeg_installed = True
return False
except (subprocess.CalledProcessError, FileNotFoundError):
# 命令执行失败或未找到
ffmpeg_installed = False
if not ffmpeg_installed:
error_msg = "您的电脑还没正确安装ffmpeg\n"
error_msg += "\n建议您:\n"
error_msg += "1、按照项目的安装文档,正确进入conda环境\n"
error_msg += "2、查阅安装文档,如何在conda环境中安装ffmpeg\n"
raise ValueError(error_msg)
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from abc import ABC, abstractmethod
from config.logger import setup_logging
import opuslib_next
import time
import numpy as np
import torch
TAG = __name__
logger = setup_logging()
class VAD(ABC):
@abstractmethod
def is_vad(self, conn, data):
"""检测音频数据中的语音活动"""
pass
class SileroVAD(VAD):
def __init__(self, config):
logger.bind(tag=TAG).info("SileroVAD", config)
self.model, self.utils = torch.hub.load(repo_or_dir=config["model_dir"],
source='local',
model='silero_vad',
force_reload=False)
(get_speech_timestamps, _, _, _, _) = self.utils
self.decoder = opuslib_next.Decoder(16000, 1)
self.vad_threshold = config.get("threshold")
self.silence_threshold_ms = config.get("min_silence_duration_ms")
def is_vad(self, conn, opus_packet):
try:
pcm_frame = self.decoder.decode(opus_packet, 960)
conn.client_audio_buffer += pcm_frame # 将新数据加入缓冲区
# 处理缓冲区中的完整帧(每次处理512采样点)
client_have_voice = False
while len(conn.client_audio_buffer) >= 512 * 2:
# 提取前512个采样点(1024字节)
chunk = conn.client_audio_buffer[:512 * 2]
conn.client_audio_buffer = conn.client_audio_buffer[512 * 2:]
# 转换为模型需要的张量格式
audio_int16 = np.frombuffer(chunk, dtype=np.int16)
audio_float32 = audio_int16.astype(np.float32) / 32768.0
audio_tensor = torch.from_numpy(audio_float32)
# 检测语音活动
speech_prob = self.model(audio_tensor, 16000).item()
client_have_voice = speech_prob >= self.vad_threshold
# 如果之前有声音,但本次没有声音,且与上次有声音的时间查已经超过了静默阈值,则认为已经说完一句话
if conn.client_have_voice and not client_have_voice:
stop_duration = time.time() * 1000 - conn.client_have_voice_last_time
if stop_duration >= self.silence_threshold_ms:
conn.client_voice_stop = True
if client_have_voice:
conn.client_have_voice = True
conn.client_have_voice_last_time = time.time() * 1000
return client_have_voice
except opuslib_next.OpusError as e:
logger.bind(tag=TAG).info(f"解码错误: {e}")
except Exception as e:
logger.bind(tag=TAG).error(f"Error processing audio packet: {e}")
def create_instance(class_name, *args, **kwargs) -> VAD:
# 获取类对象
cls_map = {
"SileroVAD": SileroVAD,
# 可扩展其他SileroVAD实现
}
if cls := cls_map.get(class_name):
return cls(*args, **kwargs)
raise ValueError(f"不支持的SileroVAD类型: {class_name}")