mirror of
https://github.com/xinnan-tech/xiaozhi-esp32-server.git
synced 2026-07-22 23:23:55 +08:00
199 lines
8.7 KiB
Python
199 lines
8.7 KiB
Python
import asyncio
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import time
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import aiohttp
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import requests
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from urllib.parse import urlparse, parse_qs
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from typing import Optional, Dict
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from config.logger import setup_logging
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from core.utils.cache.manager import cache_manager
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from core.utils.cache.config import CacheType
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TAG = __name__
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logger = setup_logging()
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class VoiceprintProvider:
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"""声纹识别服务提供者"""
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def __init__(self, config: dict):
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self.original_url = config.get("url", "")
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self.speakers = config.get("speakers", [])
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self.speaker_map = self._parse_speakers()
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# 声纹识别相似度阈值，默认0.4
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self.similarity_threshold = float(config.get("similarity_threshold", 0.4))
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# 解析API地址和密钥
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self.api_url = None
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self.api_key = None
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self.speaker_ids = []
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if not self.original_url:
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logger.bind(tag=TAG).warning("声纹识别URL未配置，声纹识别将被禁用")
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self.enabled = False
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else:
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# 解析URL和key
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parsed_url = urlparse(self.original_url)
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base_url = f"{parsed_url.scheme}://{parsed_url.netloc}"
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# 从查询参数中提取key
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query_params = parse_qs(parsed_url.query)
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self.api_key = query_params.get('key', [''])[0]
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if not self.api_key:
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logger.bind(tag=TAG).error("URL中未找到key参数，声纹识别将被禁用")
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self.enabled = False
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else:
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# 构造identify接口地址
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self.api_url = f"{base_url}/voiceprint/identify"
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# 提取speaker_ids
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for speaker_str in self.speakers:
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try:
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parts = speaker_str.split(",", 2)
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if len(parts) >= 1:
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speaker_id = parts[0].strip()
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self.speaker_ids.append(speaker_id)
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except Exception:
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continue
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# 检查是否有有效的说话人配置
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if not self.speaker_ids:
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logger.bind(tag=TAG).warning("未配置有效的说话人，声纹识别将被禁用")
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self.enabled = False
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else:
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# 进行健康检查，验证服务器是否可用
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if self._check_server_health():
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self.enabled = True
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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}")
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else:
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self.enabled = False
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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}")
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def _parse_speakers(self) -> Dict[str, Dict[str, str]]:
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"""解析说话人配置"""
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speaker_map = {}
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for speaker_str in self.speakers:
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try:
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parts = speaker_str.split(",", 2)
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if len(parts) >= 3:
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speaker_id, name, description = parts[0].strip(), parts[1].strip(), parts[2].strip()
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speaker_map[speaker_id] = {
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"name": name,
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"description": description
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}
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except Exception as e:
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logger.bind(tag=TAG).warning(f"解析说话人配置失败: {speaker_str}, 错误: {e}")
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return speaker_map
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def _check_server_health(self) -> bool:
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"""检查声纹识别服务器健康状态"""
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if not self.api_url or not self.api_key:
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return False
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cache_key = f"{self.api_url}:{self.api_key}"
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# 检查缓存
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cached_result = cache_manager.get(CacheType.VOICEPRINT_HEALTH, cache_key)
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if cached_result is not None:
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logger.bind(tag=TAG).debug(f"使用缓存的健康状态: {cached_result}")
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return cached_result
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# 缓存过期或不存在
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logger.bind(tag=TAG).info("执行声纹服务器健康检查")
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try:
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# 健康检查URL
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parsed_url = urlparse(self.api_url)
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health_url = f"{parsed_url.scheme}://{parsed_url.netloc}/voiceprint/health?key={self.api_key}"
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# 发送健康检查请求
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response = requests.get(health_url, timeout=3)
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if response.status_code == 200:
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result = response.json()
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if result.get("status") == "healthy":
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logger.bind(tag=TAG).info("声纹识别服务器健康检查通过")
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is_healthy = True
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else:
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logger.bind(tag=TAG).warning(f"声纹识别服务器状态异常: {result}")
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is_healthy = False
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else:
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logger.bind(tag=TAG).warning(f"声纹识别服务器健康检查失败: HTTP {response.status_code}")
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is_healthy = False
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except requests.exceptions.ConnectTimeout:
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logger.bind(tag=TAG).warning("声纹识别服务器连接超时")
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is_healthy = False
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except requests.exceptions.ConnectionError:
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logger.bind(tag=TAG).warning("声纹识别服务器连接被拒绝")
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is_healthy = False
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except Exception as e:
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logger.bind(tag=TAG).warning(f"声纹识别服务器健康检查异常: {e}")
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is_healthy = False
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# 使用全局缓存管理器缓存结果
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cache_manager.set(CacheType.VOICEPRINT_HEALTH, cache_key, is_healthy)
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logger.bind(tag=TAG).info(f"健康检查结果已缓存: {is_healthy}")
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return is_healthy
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async def identify_speaker(self, audio_data: bytes, session_id: str) -> Optional[str]:
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"""识别说话人"""
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if not self.enabled or not self.api_url or not self.api_key:
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logger.bind(tag=TAG).debug("声纹识别功能已禁用或未配置，跳过识别")
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return None
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try:
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api_start_time = time.monotonic()
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# 准备请求头
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headers = {
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'Authorization': f'Bearer {self.api_key}',
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'Accept': 'application/json'
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}
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# 准备multipart/form-data数据
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data = aiohttp.FormData()
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data.add_field('speaker_ids', ','.join(self.speaker_ids))
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data.add_field('file', audio_data, filename='audio.wav', content_type='audio/wav')
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timeout = aiohttp.ClientTimeout(total=10)
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# 网络请求
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async with aiohttp.ClientSession(timeout=timeout) as session:
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async with session.post(self.api_url, headers=headers, data=data) as response:
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if response.status == 200:
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result = await response.json()
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speaker_id = result.get("speaker_id")
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score = result.get("score", 0)
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total_elapsed_time = time.monotonic() - api_start_time
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logger.bind(tag=TAG).info(f"声纹识别耗时: {total_elapsed_time:.3f}s")
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# 相似度阈值检查
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if score < self.similarity_threshold:
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logger.bind(tag=TAG).warning(f"声纹识别相似度{score:.3f}低于阈值{self.similarity_threshold}")
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return "未知说话人"
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if speaker_id and speaker_id in self.speaker_map:
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result_name = self.speaker_map[speaker_id]["name"]
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logger.bind(tag=TAG).info(f"声纹识别成功: {result_name} (相似度: {score:.3f})")
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return result_name
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else:
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logger.bind(tag=TAG).warning(f"未识别的说话人ID: {speaker_id}")
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return "未知说话人"
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else:
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logger.bind(tag=TAG).error(f"声纹识别API错误: HTTP {response.status}")
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return None
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except asyncio.TimeoutError:
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elapsed = time.monotonic() - api_start_time
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logger.bind(tag=TAG).error(f"声纹识别超时: {elapsed:.3f}s")
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return None
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except Exception as e:
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elapsed = time.monotonic() - api_start_time
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logger.bind(tag=TAG).error(f"声纹识别失败: {e}")
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return None
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