import json import socket import subprocess import re import requests from typing import Dict, Any from core.utils import tts, llm, intent, memory, vad, asr TAG = __name__ emoji_map = { 'neutral': '😶', 'happy': '🙂', 'laughing': '😆', 'funny': '😂', 'sad': '😔', 'angry': '😠', 'crying': '😭', 'loving': '😍', 'embarrassed': '😳', 'surprised': '😲', 'shocked': '😱', 'thinking': '🤔', 'winking': '😉', 'cool': '😎', 'relaxed': '😌', 'delicious': '🤤', 'kissy': '😘', 'confident': '😏', 'sleepy': '😴', 'silly': '😜', 'confused': '🙄' } 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 is_private_ip(ip_addr): """ Check if an IP address is a private IP address (compatible with IPv4 and IPv6). @param {string} ip_addr - The IP address to check. @return {bool} True if the IP address is private, False otherwise. """ try: # Validate IPv4 or IPv6 address format if not re.match( r"^(\d{1,3}\.){3}\d{1,3}$|^([0-9a-fA-F]{1,4}:){7}[0-9a-fA-F]{1,4}$", ip_addr ): return False # Invalid IP address format # IPv4 private address ranges if "." in ip_addr: # IPv4 address ip_parts = list(map(int, ip_addr.split("."))) if ip_parts[0] == 10: return True # 10.0.0.0/8 range elif ip_parts[0] == 172 and 16 <= ip_parts[1] <= 31: return True # 172.16.0.0/12 range elif ip_parts[0] == 192 and ip_parts[1] == 168: return True # 192.168.0.0/16 range elif ip_addr == "127.0.0.1": return True # Loopback address elif ip_parts[0] == 169 and ip_parts[1] == 254: return True # Link-local address 169.254.0.0/16 else: return False # Not a private IPv4 address else: # IPv6 address ip_addr = ip_addr.lower() if ip_addr.startswith("fc00:") or ip_addr.startswith("fd00:"): return True # Unique Local Addresses (FC00::/7) elif ip_addr == "::1": return True # Loopback address elif ip_addr.startswith("fe80:"): return True # Link-local unicast addresses (FE80::/10) else: return False # Not a private IPv6 address except (ValueError, IndexError): return False # IP address format error or insufficient segments def get_ip_info(ip_addr, logger): try: if is_private_ip(ip_addr): ip_addr = "" url = f"https://whois.pconline.com.cn/ipJson.jsp?json=true&ip={ip_addr}" resp = requests.get(url).json() ip_info = {"city": resp.get("city")} return ip_info except Exception as e: logger.bind(tag=TAG).error(f"Error getting client ip info: {e}") return {} 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 "-", "-", # 英文连字符 + 中文全角横线 "、", # 中文顿号 "“", "”", "\"", # 中文双引号 + 英文引号 ":", ":", # 中文冒号 + 英文冒号 } 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 = r'!"#$%&\'()*+,-./:;<=>?@[\]^_`{|}~' 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_model_key(modelType, modelKey): if "你" in modelKey: raise ValueError( "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" ) return True def parse_string_to_list(value, separator=";"): """ 将输入值转换为列表 Args: value: 输入值,可以是 None、字符串或列表 separator: 分隔符,默认为分号 Returns: list: 处理后的列表 """ if value is None or value == "": return [] elif isinstance(value, str): return [item.strip() for item in value.split(separator) if item.strip()] elif isinstance(value, list): return value return [] 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) def extract_json_from_string(input_string): """提取字符串中的 JSON 部分""" pattern = r"(\{.*\})" match = re.search(pattern, input_string, re.DOTALL) # 添加 re.DOTALL if match: return match.group(1) # 返回提取的 JSON 字符串 return None def initialize_modules( logger, config: Dict[str, Any], init_vad=False, init_asr=False, init_llm=False, init_tts=False, init_memory=False, init_intent=False, ) -> Dict[str, Any]: """ 初始化所有模块组件 Args: config: 配置字典 Returns: Dict[str, Any]: 包含所有初始化后的模块的字典 """ modules = {} # 初始化TTS模块 if init_tts: select_tts_module = config["selected_module"]["TTS"] tts_type = ( select_tts_module if "type" not in config["TTS"][select_tts_module] else config["TTS"][select_tts_module]["type"] ) modules["tts"] = tts.create_instance( tts_type, config["TTS"][select_tts_module], str(config.get("delete_audio", True)).lower() in ("true", "1", "yes"), ) logger.bind(tag=TAG).info(f"初始化组件: tts成功 {select_tts_module}") # 初始化LLM模块 if init_llm: select_llm_module = config["selected_module"]["LLM"] llm_type = ( select_llm_module if "type" not in config["LLM"][select_llm_module] else config["LLM"][select_llm_module]["type"] ) modules["llm"] = llm.create_instance( llm_type, config["LLM"][select_llm_module], ) logger.bind(tag=TAG).info(f"初始化组件: llm成功 {select_llm_module}") # 初始化Intent模块 if init_intent: select_intent_module = config["selected_module"]["Intent"] intent_type = ( select_intent_module if "type" not in config["Intent"][select_intent_module] else config["Intent"][select_intent_module]["type"] ) modules["intent"] = intent.create_instance( intent_type, config["Intent"][select_intent_module], ) logger.bind(tag=TAG).info(f"初始化组件: intent成功 {select_intent_module}") # 初始化Memory模块 if init_memory: select_memory_module = config["selected_module"]["Memory"] memory_type = ( select_memory_module if "type" not in config["Memory"][select_memory_module] else config["Memory"][select_memory_module]["type"] ) modules["memory"] = memory.create_instance( memory_type, config["Memory"][select_memory_module], ) logger.bind(tag=TAG).info(f"初始化组件: memory成功 {select_memory_module}") # 初始化VAD模块 if init_vad: select_vad_module = config["selected_module"]["VAD"] vad_type = ( select_vad_module if "type" not in config["VAD"][select_vad_module] else config["VAD"][select_vad_module]["type"] ) modules["vad"] = vad.create_instance( vad_type, config["VAD"][select_vad_module], ) logger.bind(tag=TAG).info(f"初始化组件: vad成功 {select_vad_module}") # 初始化ASR模块 if init_asr: select_asr_module = config["selected_module"]["ASR"] asr_type = ( select_asr_module if "type" not in config["ASR"][select_asr_module] else config["ASR"][select_asr_module]["type"] ) modules["asr"] = asr.create_instance( asr_type, config["ASR"][select_asr_module], str(config.get("delete_audio", True)).lower() in ("true", "1", "yes"), ) logger.bind(tag=TAG).info(f"初始化组件: asr成功 {select_asr_module}") # 初始化自定义prompt if config.get("prompt", None) is not None: modules["prompt"] = config["prompt"] logger.bind(tag=TAG).info(f"初始化组件: prompt成功 {modules['prompt'][:50]}...") return modules def analyze_emotion(text): """ 分析文本情感并返回对应的emoji名称(支持中英文) """ if not text or not isinstance(text, str): return 'neutral' original_text = text text = text.lower().strip() # 检查是否包含现有emoji for emotion, emoji in emoji_map.items(): if emoji in original_text: return emotion # 标点符号分析 has_exclamation = '!' in original_text or '!' in original_text has_question = '?' in original_text or '?' in original_text has_ellipsis = '...' in original_text or '…' in original_text # 定义情感关键词映射(中英文扩展版) emotion_keywords = { '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', '好呀', '好的', 'happy', 'joy', 'great', 'good', 'nice', 'awesome', 'fantastic', 'wonderful'], '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', 'hahaha', 'hehe', 'rofl', 'funny', 'laugh'], 'funny': ['搞笑', '滑稽', '逗', '幽默', '笑点', '段子', '笑话', '太逗了', 'hilarious', 'joke', 'comedy'], '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', 'sad', 'upset', 'unhappy', 'depressed', 'sorrow', 'gloomy'], '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', 'angry', 'mad', 'annoyed', 'furious', 'pissed', 'hate'], 'crying': ['哭泣', '泪流', '大哭', '伤心欲绝', '泪目', '流泪', '哭死', '哭晕', '想哭', '泪崩', 'cry', 'crying', 'tears', 'sob', 'weep'], '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', 'love', 'like', 'adore', 'darling', 'sweetie', 'honey', 'miss you', 'heart'], 'embarrassed': ['尴尬', '不好意思', '害羞', '脸红', '难为情', '社死', '丢脸', '出丑', 'embarrassed', 'awkward', 'shy', 'blush'], 'surprised': ['惊讶', '吃惊', '天啊', '哇塞', '哇', '居然', '竟然', '没想到', '出乎意料', 'surprise', 'wow', 'omg', 'oh my god', 'amazing', 'unbelievable'], 'shocked': ['震惊', '吓到', '惊呆了', '不敢相信', '震撼', '吓死', '恐怖', '害怕', '吓人', 'shocked', 'shocking', 'scared', 'frightened', 'terrified', 'horror'], 'thinking': ['思考', '考虑', '想一下', '琢磨', '沉思', '冥想', '想', '思考中', '在想', 'think', 'thinking', 'consider', 'ponder', 'meditate'], 'winking': ['调皮', '眨眼', '你懂的', '坏笑', '邪恶', '奸笑', '使眼色', 'wink', 'teasing', 'naughty', 'mischievous'], 'cool': ['酷', '帅', '厉害', '棒极了', '真棒', '牛逼', '强', '优秀', '杰出', '出色', '完美', 'cool', 'awesome', 'amazing', 'great', 'impressive', 'perfect'], 'relaxed': ['放松', '舒服', '惬意', '悠闲', '轻松', '舒适', '安逸', '自在', 'relax', 'relaxed', 'comfortable', 'cozy', 'chill', 'peaceful'], 'delicious': ['好吃', '美味', '香', '馋', '可口', '香甜', '大餐', '大快朵颐', '流口水', '垂涎', 'delicious', 'yummy', 'tasty', 'yum', 'appetizing', 'mouthwatering'], 'kissy': ['亲亲', '么么', '吻', 'mua', 'muah', '亲一下', '飞吻', 'kiss', 'xoxo', 'hug', 'muah', 'smooch'], '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