mirror of
https://github.com/xinnan-tech/xiaozhi-esp32-server.git
synced 2026-07-22 15:13:55 +08:00
488 lines
19 KiB
Python
488 lines
19 KiB
Python
import json
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import socket
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import subprocess
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import re
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import requests
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from typing import Dict, Any
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from core.utils import tts, llm, intent, memory, vad, asr
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TAG = __name__
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emoji_map = {
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'neutral': '😶',
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'happy': '🙂',
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'laughing': '😆',
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'funny': '😂',
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'sad': '😔',
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'angry': '😠',
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'crying': '😭',
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'loving': '😍',
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'embarrassed': '😳',
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'surprised': '😲',
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'shocked': '😱',
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'thinking': '🤔',
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'winking': '😉',
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'cool': '😎',
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'relaxed': '😌',
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'delicious': '🤤',
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'kissy': '😘',
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'confident': '😏',
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'sleepy': '😴',
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'silly': '😜',
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'confused': '🙄'
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}
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def get_local_ip():
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try:
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s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
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# Connect to Google's DNS servers
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s.connect(("8.8.8.8", 80))
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local_ip = s.getsockname()[0]
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s.close()
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return local_ip
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except Exception as e:
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return "127.0.0.1"
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def is_private_ip(ip_addr):
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"""
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Check if an IP address is a private IP address (compatible with IPv4 and IPv6).
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@param {string} ip_addr - The IP address to check.
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@return {bool} True if the IP address is private, False otherwise.
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"""
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try:
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# Validate IPv4 or IPv6 address format
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if not re.match(
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r"^(\d{1,3}\.){3}\d{1,3}$|^([0-9a-fA-F]{1,4}:){7}[0-9a-fA-F]{1,4}$", ip_addr
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):
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return False # Invalid IP address format
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# IPv4 private address ranges
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if "." in ip_addr: # IPv4 address
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ip_parts = list(map(int, ip_addr.split(".")))
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if ip_parts[0] == 10:
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return True # 10.0.0.0/8 range
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elif ip_parts[0] == 172 and 16 <= ip_parts[1] <= 31:
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return True # 172.16.0.0/12 range
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elif ip_parts[0] == 192 and ip_parts[1] == 168:
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return True # 192.168.0.0/16 range
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elif ip_addr == "127.0.0.1":
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return True # Loopback address
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elif ip_parts[0] == 169 and ip_parts[1] == 254:
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return True # Link-local address 169.254.0.0/16
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else:
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return False # Not a private IPv4 address
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else: # IPv6 address
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ip_addr = ip_addr.lower()
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if ip_addr.startswith("fc00:") or ip_addr.startswith("fd00:"):
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return True # Unique Local Addresses (FC00::/7)
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elif ip_addr == "::1":
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return True # Loopback address
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elif ip_addr.startswith("fe80:"):
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return True # Link-local unicast addresses (FE80::/10)
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else:
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return False # Not a private IPv6 address
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except (ValueError, IndexError):
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return False # IP address format error or insufficient segments
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def get_ip_info(ip_addr, logger):
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try:
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if is_private_ip(ip_addr):
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ip_addr = ""
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url = f"https://whois.pconline.com.cn/ipJson.jsp?json=true&ip={ip_addr}"
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resp = requests.get(url).json()
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ip_info = {"city": resp.get("city")}
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return ip_info
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except Exception as e:
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logger.bind(tag=TAG).error(f"Error getting client ip info: {e}")
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return {}
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def write_json_file(file_path, data):
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"""将数据写入 JSON 文件"""
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with open(file_path, "w", encoding="utf-8") as file:
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json.dump(data, file, ensure_ascii=False, indent=4)
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def is_punctuation_or_emoji(char):
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"""检查字符是否为空格、指定标点或表情符号"""
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# 定义需要去除的中英文标点（包括全角/半角）
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punctuation_set = {
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"，",
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",", # 中文逗号 + 英文逗号
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"-",
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"－", # 英文连字符 + 中文全角横线
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"、", # 中文顿号
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"“",
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"”",
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"\"", # 中文双引号 + 英文引号
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"：",
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":", # 中文冒号 + 英文冒号
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}
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if char.isspace() or char in punctuation_set:
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return True
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# 检查表情符号（保留原有逻辑）
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code_point = ord(char)
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emoji_ranges = [
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(0x1F600, 0x1F64F),
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(0x1F300, 0x1F5FF),
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(0x1F680, 0x1F6FF),
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(0x1F900, 0x1F9FF),
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(0x1FA70, 0x1FAFF),
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(0x2600, 0x26FF),
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(0x2700, 0x27BF),
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]
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return any(start <= code_point <= end for start, end in emoji_ranges)
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def get_string_no_punctuation_or_emoji(s):
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"""去除字符串首尾的空格、标点符号和表情符号"""
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chars = list(s)
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# 处理开头的字符
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start = 0
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while start < len(chars) and is_punctuation_or_emoji(chars[start]):
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start += 1
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# 处理结尾的字符
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end = len(chars) - 1
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while end >= start and is_punctuation_or_emoji(chars[end]):
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end -= 1
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return "".join(chars[start : end + 1])
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def remove_punctuation_and_length(text):
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# 全角符号和半角符号的Unicode范围
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full_width_punctuations = (
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"！＂＃＄％＆＇（）＊＋，－。／：；＜＝＞？＠［＼］＾＿｀｛｜｝～"
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)
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half_width_punctuations = r'!"#$%&\'()*+,-./:;<=>?@[\]^_`{|}~'
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space = " " # 半角空格
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full_width_space = " " # 全角空格
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# 去除全角和半角符号以及空格
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result = "".join(
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[
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char
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for char in text
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if char not in full_width_punctuations
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and char not in half_width_punctuations
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and char not in space
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and char not in full_width_space
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]
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)
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if result == "Yeah":
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return 0, ""
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return len(result), result
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def check_model_key(modelType, modelKey):
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if "你" in modelKey:
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raise ValueError(
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"你还没配置" + modelType + "的密钥，请检查一下所使用的LLM是否配置了密钥"
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)
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return True
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def parse_string_to_list(value, separator=";"):
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"""
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将输入值转换为列表
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Args:
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value: 输入值，可以是 None、字符串或列表
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separator: 分隔符，默认为分号
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Returns:
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list: 处理后的列表
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"""
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if value is None or value == "":
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return []
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elif isinstance(value, str):
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return [item.strip() for item in value.split(separator) if item.strip()]
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elif isinstance(value, list):
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return value
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return []
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def check_ffmpeg_installed():
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ffmpeg_installed = False
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try:
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# 执行ffmpeg -version命令，并捕获输出
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result = subprocess.run(
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["ffmpeg", "-version"],
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE,
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text=True,
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check=True, # 如果返回码非零则抛出异常
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)
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# 检查输出中是否包含版本信息（可选）
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output = result.stdout + result.stderr
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if "ffmpeg version" in output.lower():
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ffmpeg_installed = True
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return False
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except (subprocess.CalledProcessError, FileNotFoundError):
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# 命令执行失败或未找到
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ffmpeg_installed = False
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if not ffmpeg_installed:
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error_msg = "您的电脑还没正确安装ffmpeg\n"
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error_msg += "\n建议您：\n"
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error_msg += "1、按照项目的安装文档，正确进入conda环境\n"
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error_msg += "2、查阅安装文档，如何在conda环境中安装ffmpeg\n"
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raise ValueError(error_msg)
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def extract_json_from_string(input_string):
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"""提取字符串中的 JSON 部分"""
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pattern = r"(\{.*\})"
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match = re.search(pattern, input_string, re.DOTALL) # 添加 re.DOTALL
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if match:
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return match.group(1) # 返回提取的 JSON 字符串
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return None
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def initialize_modules(
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logger,
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config: Dict[str, Any],
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init_vad=False,
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init_asr=False,
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init_llm=False,
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init_tts=False,
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init_memory=False,
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init_intent=False,
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) -> Dict[str, Any]:
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"""
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初始化所有模块组件
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Args:
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config: 配置字典
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Returns:
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Dict[str, Any]: 包含所有初始化后的模块的字典
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"""
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modules = {}
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# 初始化TTS模块
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if init_tts:
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select_tts_module = config["selected_module"]["TTS"]
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tts_type = (
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select_tts_module
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if "type" not in config["TTS"][select_tts_module]
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else config["TTS"][select_tts_module]["type"]
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)
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modules["tts"] = tts.create_instance(
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tts_type,
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config["TTS"][select_tts_module],
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str(config.get("delete_audio", True)).lower() in ("true", "1", "yes"),
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)
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logger.bind(tag=TAG).info(f"初始化组件: tts成功 {select_tts_module}")
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# 初始化LLM模块
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if init_llm:
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select_llm_module = config["selected_module"]["LLM"]
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llm_type = (
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select_llm_module
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if "type" not in config["LLM"][select_llm_module]
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else config["LLM"][select_llm_module]["type"]
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)
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modules["llm"] = llm.create_instance(
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llm_type,
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config["LLM"][select_llm_module],
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)
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logger.bind(tag=TAG).info(f"初始化组件: llm成功 {select_llm_module}")
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# 初始化Intent模块
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if init_intent:
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select_intent_module = config["selected_module"]["Intent"]
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intent_type = (
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select_intent_module
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if "type" not in config["Intent"][select_intent_module]
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else config["Intent"][select_intent_module]["type"]
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)
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modules["intent"] = intent.create_instance(
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intent_type,
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config["Intent"][select_intent_module],
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)
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logger.bind(tag=TAG).info(f"初始化组件: intent成功 {select_intent_module}")
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# 初始化Memory模块
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if init_memory:
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select_memory_module = config["selected_module"]["Memory"]
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memory_type = (
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select_memory_module
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if "type" not in config["Memory"][select_memory_module]
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else config["Memory"][select_memory_module]["type"]
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)
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modules["memory"] = memory.create_instance(
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memory_type,
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config["Memory"][select_memory_module],
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)
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logger.bind(tag=TAG).info(f"初始化组件: memory成功 {select_memory_module}")
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# 初始化VAD模块
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if init_vad:
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select_vad_module = config["selected_module"]["VAD"]
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vad_type = (
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select_vad_module
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if "type" not in config["VAD"][select_vad_module]
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else config["VAD"][select_vad_module]["type"]
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)
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modules["vad"] = vad.create_instance(
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vad_type,
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config["VAD"][select_vad_module],
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)
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logger.bind(tag=TAG).info(f"初始化组件: vad成功 {select_vad_module}")
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# 初始化ASR模块
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if init_asr:
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select_asr_module = config["selected_module"]["ASR"]
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asr_type = (
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select_asr_module
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if "type" not in config["ASR"][select_asr_module]
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else config["ASR"][select_asr_module]["type"]
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)
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modules["asr"] = asr.create_instance(
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asr_type,
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config["ASR"][select_asr_module],
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str(config.get("delete_audio", True)).lower() in ("true", "1", "yes"),
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)
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logger.bind(tag=TAG).info(f"初始化组件: asr成功 {select_asr_module}")
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# 初始化自定义prompt
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if config.get("prompt", None) is not None:
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modules["prompt"] = config["prompt"]
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logger.bind(tag=TAG).info(f"初始化组件: prompt成功 {modules['prompt'][:50]}...")
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return modules
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def analyze_emotion(text):
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"""
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分析文本情感并返回对应的emoji名称（支持中英文）
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"""
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if not text or not isinstance(text, str):
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return 'neutral'
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original_text = text
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text = text.lower().strip()
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# 检查是否包含现有emoji
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for emotion, emoji in emoji_map.items():
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if emoji in original_text:
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return emotion
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# 标点符号分析
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has_exclamation = '!' in original_text or '！' in original_text
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has_question = '?' in original_text or '？' in original_text
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has_ellipsis = '...' in original_text or '…' in original_text
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# 定义情感关键词映射（中英文扩展版）
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emotion_keywords = {
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'happy': ['开心', '高兴', '快乐', '愉快', '幸福', '满意', '棒', '好', '不错', '完美', '棒极了', '太好了',
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'好呀', '好的', 'happy', 'joy', 'great', 'good', 'nice', 'awesome', 'fantastic', 'wonderful'],
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'laughing': ['哈哈', '哈哈哈', '呵呵', '嘿嘿', '嘻嘻', '笑死', '太好笑了', '笑死我了', 'lol', 'lmao', 'haha',
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'hahaha', 'hehe', 'rofl', 'funny', 'laugh'],
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'funny': ['搞笑', '滑稽', '逗', '幽默', '笑点', '段子', '笑话', '太逗了', 'hilarious', 'joke', 'comedy'],
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'sad': ['伤心', '难过', '悲哀', '悲伤', '忧郁', '郁闷', '沮丧', '失望', '想哭', '难受', '不开心', '唉', '呜呜',
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'sad', 'upset', 'unhappy', 'depressed', 'sorrow', 'gloomy'],
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'angry': ['生气', '愤怒', '气死', '讨厌', '烦人', '可恶', '烦死了', '恼火', '暴躁', '火大', '愤怒', '气炸了',
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'angry', 'mad', 'annoyed', 'furious', 'pissed', 'hate'],
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'crying': ['哭泣', '泪流', '大哭', '伤心欲绝', '泪目', '流泪', '哭死', '哭晕', '想哭', '泪崩',
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'cry', 'crying', 'tears', 'sob', 'weep'],
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'loving': ['爱你', '喜欢', '爱', '亲爱的', '宝贝', '么么哒', '抱抱', '想你', '思念', '最爱', '亲亲', '喜欢你',
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'love', 'like', 'adore', 'darling', 'sweetie', 'honey', 'miss you', 'heart'],
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'embarrassed': ['尴尬', '不好意思', '害羞', '脸红', '难为情', '社死', '丢脸', '出丑',
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'embarrassed', 'awkward', 'shy', 'blush'],
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'surprised': ['惊讶', '吃惊', '天啊', '哇塞', '哇', '居然', '竟然', '没想到', '出乎意料',
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'surprise', 'wow', 'omg', 'oh my god', 'amazing', 'unbelievable'],
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'shocked': ['震惊', '吓到', '惊呆了', '不敢相信', '震撼', '吓死', '恐怖', '害怕', '吓人',
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'shocked', 'shocking', 'scared', 'frightened', 'terrified', 'horror'],
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'thinking': ['思考', '考虑', '想一下', '琢磨', '沉思', '冥想', '想', '思考中', '在想',
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'think', 'thinking', 'consider', 'ponder', 'meditate'],
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'winking': ['调皮', '眨眼', '你懂的', '坏笑', '邪恶', '奸笑', '使眼色',
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'wink', 'teasing', 'naughty', 'mischievous'],
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'cool': ['酷', '帅', '厉害', '棒极了', '真棒', '牛逼', '强', '优秀', '杰出', '出色', '完美',
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'cool', 'awesome', 'amazing', 'great', 'impressive', 'perfect'],
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'relaxed': ['放松', '舒服', '惬意', '悠闲', '轻松', '舒适', '安逸', '自在',
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'relax', 'relaxed', 'comfortable', 'cozy', 'chill', 'peaceful'],
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'delicious': ['好吃', '美味', '香', '馋', '可口', '香甜', '大餐', '大快朵颐', '流口水', '垂涎',
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'delicious', 'yummy', 'tasty', 'yum', 'appetizing', 'mouthwatering'],
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'kissy': ['亲亲', '么么', '吻', 'mua', 'muah', '亲一下', '飞吻',
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'kiss', 'xoxo', 'hug', 'muah', 'smooch'],
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'confident': ['自信', '肯定', '确定', '毫无疑问', '当然', '必须的', '毫无疑问', '确信', '坚信',
|
||
'confident', 'sure', 'certain', 'definitely', 'positive'],
|
||
'sleepy': ['困', '睡觉', '晚安', '想睡', '好累', '疲惫', '疲倦', '困了', '想休息', '睡意',
|
||
'sleep', 'sleepy', 'tired', 'exhausted', 'bedtime', 'good night'],
|
||
'silly': ['傻', '笨', '呆', '憨', '蠢', '二', '憨憨', '傻乎乎', '呆萌',
|
||
'silly', 'stupid', 'dumb', 'foolish', 'goofy', 'ridiculous'],
|
||
'confused': ['疑惑', '不明白', '不懂', '困惑', '疑问', '为什么', '怎么回事', '啥意思', '不清楚',
|
||
'confused', 'puzzled', 'doubt', 'question', 'what', 'why', 'how']
|
||
}
|
||
|
||
# 特殊句型判断（中英文）
|
||
# 赞美他人
|
||
if any(phrase in text for phrase in
|
||
['你真', '你好', '您真', '你真棒', '你好厉害', '你太强了', '你真好', '你真聪明',
|
||
'you are', 'you\'re', 'you look', 'you seem', 'so smart', 'so kind']):
|
||
return 'loving'
|
||
# 自我赞美
|
||
if any(phrase in text for phrase in ['我真', '我最', '我太棒了', '我厉害', '我聪明', '我优秀',
|
||
'i am', 'i\'m', 'i feel', 'so good', 'so happy']):
|
||
return 'cool'
|
||
# 晚安/睡觉相关
|
||
if any(phrase in text for phrase in ['睡觉', '晚安', '睡了', '好梦', '休息了', '去睡了',
|
||
'sleep', 'good night', 'bedtime', 'go to bed']):
|
||
return 'sleepy'
|
||
# 疑问句
|
||
if has_question and not has_exclamation:
|
||
return 'thinking'
|
||
# 强烈情感（感叹号）
|
||
if has_exclamation and not has_question:
|
||
# 检查是否是积极内容
|
||
positive_words = emotion_keywords['happy'] + emotion_keywords['laughing'] + emotion_keywords['cool']
|
||
if any(word in text for word in positive_words):
|
||
return 'laughing'
|
||
# 检查是否是消极内容
|
||
negative_words = emotion_keywords['angry'] + emotion_keywords['sad'] + emotion_keywords['crying']
|
||
if any(word in text for word in negative_words):
|
||
return 'angry'
|
||
return 'surprised'
|
||
# 省略号（表示犹豫或思考）
|
||
if has_ellipsis:
|
||
return 'thinking'
|
||
|
||
# 关键词匹配（带权重）
|
||
emotion_scores = {emotion: 0 for emotion in emoji_map.keys()}
|
||
|
||
# 给匹配到的关键词加分
|
||
for emotion, keywords in emotion_keywords.items():
|
||
for keyword in keywords:
|
||
if keyword in text:
|
||
emotion_scores[emotion] += 1
|
||
|
||
# 给长文本中的重复关键词额外加分
|
||
if len(text) > 20: # 长文本
|
||
for emotion, keywords in emotion_keywords.items():
|
||
for keyword in keywords:
|
||
emotion_scores[emotion] += text.count(keyword) * 0.5
|
||
|
||
# 根据分数选择最可能的情感
|
||
max_score = max(emotion_scores.values())
|
||
if max_score == 0:
|
||
return 'happy' # 默认
|
||
|
||
# 可能有多个情感同分，根据上下文选择最合适的
|
||
top_emotions = [e for e, s in emotion_scores.items() if s == max_score]
|
||
|
||
# 如果多个情感同分，使用以下优先级
|
||
priority_order = [
|
||
'laughing', 'crying', 'angry', 'surprised', 'shocked', # 强烈情感优先
|
||
'loving', 'happy', 'funny', 'cool', # 积极情感
|
||
'sad', 'embarrassed', 'confused', # 消极情感
|
||
'thinking', 'winking', 'relaxed', # 中性情感
|
||
'delicious', 'kissy', 'confident', 'sleepy', 'silly' # 特殊场景
|
||
]
|
||
|
||
for emotion in priority_order:
|
||
if emotion in top_emotions:
|
||
return emotion
|
||
|
||
return top_emotions[0] # 如果都不在优先级列表里，返回第一个
|