import asyncio import time import aiohttp import requests from urllib.parse import urlparse, parse_qs from typing import Optional, Dict from config.logger import setup_logging from core.utils.cache.manager import cache_manager from core.utils.cache.config import CacheType TAG = __name__ logger = setup_logging() class VoiceprintProvider: """声纹识别服务提供者""" def __init__(self, config: dict): self.original_url = config.get("url", "") self.speakers = config.get("speakers", []) self.speaker_map = self._parse_speakers() # 声纹识别相似度阈值，默认0.4 self.similarity_threshold = float(config.get("similarity_threshold", 0.4)) # 解析API地址和密钥 self.api_url = None self.api_key = None self.speaker_ids = [] if not self.original_url: logger.bind(tag=TAG).warning("声纹识别URL未配置，声纹识别将被禁用") self.enabled = False else: # 解析URL和key parsed_url = urlparse(self.original_url) base_url = f"{parsed_url.scheme}://{parsed_url.netloc}" # 从查询参数中提取key query_params = parse_qs(parsed_url.query) self.api_key = query_params.get('key', [''])[0] if not self.api_key: logger.bind(tag=TAG).error("URL中未找到key参数，声纹识别将被禁用") self.enabled = False else: # 构造identify接口地址 self.api_url = f"{base_url}/voiceprint/identify" # 提取speaker_ids for speaker_str in self.speakers: try: parts = speaker_str.split(",", 2) if len(parts) >= 1: speaker_id = parts[0].strip() self.speaker_ids.append(speaker_id) except Exception: continue # 检查是否有有效的说话人配置 if not self.speaker_ids: logger.bind(tag=TAG).warning("未配置有效的说话人，声纹识别将被禁用") self.enabled = False else: # 进行健康检查，验证服务器是否可用 if self._check_server_health(): self.enabled = True logger.bind(tag=TAG).info(f"声纹识别已启用: API={self.api_url}, 说话人={len(self.speaker_ids)}个, 相似度阈值={self.similarity_threshold}") else: self.enabled = False logger.bind(tag=TAG).warning(f"声纹识别服务器不可用，声纹识别已禁用: {self.api_url}") def _parse_speakers(self) -> Dict[str, Dict[str, str]]: """解析说话人配置""" speaker_map = {} for speaker_str in self.speakers: try: parts = speaker_str.split(",", 2) if len(parts) >= 3: speaker_id, name, description = parts[0].strip(), parts[1].strip(), parts[2].strip() speaker_map[speaker_id] = { "name": name, "description": description } except Exception as e: logger.bind(tag=TAG).warning(f"解析说话人配置失败: {speaker_str}, 错误: {e}") return speaker_map def _check_server_health(self) -> bool: """检查声纹识别服务器健康状态""" if not self.api_url or not self.api_key: return False cache_key = f"{self.api_url}:{self.api_key}" # 检查缓存 cached_result = cache_manager.get(CacheType.VOICEPRINT_HEALTH, cache_key) if cached_result is not None: logger.bind(tag=TAG).debug(f"使用缓存的健康状态: {cached_result}") return cached_result # 缓存过期或不存在 logger.bind(tag=TAG).info("执行声纹服务器健康检查") try: # 健康检查URL parsed_url = urlparse(self.api_url) health_url = f"{parsed_url.scheme}://{parsed_url.netloc}/voiceprint/health?key={self.api_key}" # 发送健康检查请求 response = requests.get(health_url, timeout=3) if response.status_code == 200: result = response.json() if result.get("status") == "healthy": logger.bind(tag=TAG).info("声纹识别服务器健康检查通过") is_healthy = True else: logger.bind(tag=TAG).warning(f"声纹识别服务器状态异常: {result}") is_healthy = False else: logger.bind(tag=TAG).warning(f"声纹识别服务器健康检查失败: HTTP {response.status_code}") is_healthy = False except requests.exceptions.ConnectTimeout: logger.bind(tag=TAG).warning("声纹识别服务器连接超时") is_healthy = False except requests.exceptions.ConnectionError: logger.bind(tag=TAG).warning("声纹识别服务器连接被拒绝") is_healthy = False except Exception as e: logger.bind(tag=TAG).warning(f"声纹识别服务器健康检查异常: {e}") is_healthy = False # 使用全局缓存管理器缓存结果 cache_manager.set(CacheType.VOICEPRINT_HEALTH, cache_key, is_healthy) logger.bind(tag=TAG).info(f"健康检查结果已缓存: {is_healthy}") return is_healthy async def identify_speaker(self, audio_data: bytes, session_id: str) -> Optional[str]: """识别说话人""" if not self.enabled or not self.api_url or not self.api_key: logger.bind(tag=TAG).debug("声纹识别功能已禁用或未配置，跳过识别") return None try: api_start_time = time.monotonic() # 准备请求头 headers = { 'Authorization': f'Bearer {self.api_key}', 'Accept': 'application/json' } # 准备multipart/form-data数据 data = aiohttp.FormData() data.add_field('speaker_ids', ','.join(self.speaker_ids)) data.add_field('file', audio_data, filename='audio.wav', content_type='audio/wav') timeout = aiohttp.ClientTimeout(total=10) # 网络请求 async with aiohttp.ClientSession(timeout=timeout) as session: async with session.post(self.api_url, headers=headers, data=data) as response: if response.status == 200: result = await response.json() speaker_id = result.get("speaker_id") score = result.get("score", 0) total_elapsed_time = time.monotonic() - api_start_time logger.bind(tag=TAG).info(f"声纹识别耗时: {total_elapsed_time:.3f}s") # 相似度阈值检查 if score < self.similarity_threshold: logger.bind(tag=TAG).warning(f"声纹识别相似度{score:.3f}低于阈值{self.similarity_threshold}") return "未知说话人" if speaker_id and speaker_id in self.speaker_map: result_name = self.speaker_map[speaker_id]["name"] logger.bind(tag=TAG).info(f"声纹识别成功: {result_name} (相似度: {score:.3f})") return result_name else: logger.bind(tag=TAG).warning(f"未识别的说话人ID: {speaker_id}") return "未知说话人" else: logger.bind(tag=TAG).error(f"声纹识别API错误: HTTP {response.status}") return None except asyncio.TimeoutError: elapsed = time.monotonic() - api_start_time logger.bind(tag=TAG).error(f"声纹识别超时: {elapsed:.3f}s") return None except Exception as e: elapsed = time.monotonic() - api_start_time logger.bind(tag=TAG).error(f"声纹识别失败: {e}") return None