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- #!/usr/bin/env python3
- # -*- coding: utf-8 -*-
- """
- 音频识别脚本
- 主要功能:将音频转文字(ASR),参考视频识别模块的结构实现
- 支持从 formatted_content 中提取音频 URL,下载后上传至 Gemini 进行转写。
- """
- import os
- import json
- import time
- import sys
- import uuid
- import requests
- from typing import Dict, Any, List, Optional
- from dotenv import load_dotenv
- # 导入自定义模块
- sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
- from utils.logging_config import get_logger
- # 创建 logger
- logger = get_logger('AudioIdentifier')
- # 导入Google Generative AI
- import google.generativeai as genai
- from google.generativeai.types import HarmCategory, HarmBlockThreshold
- # 缓存目录配置
- CACHE_DIR = os.path.join(os.path.dirname(__file__), 'cache')
- # 缓存文件最大保留时间(秒)
- CACHE_MAX_AGE = 3600 # 1小时
- class AudioIdentifier:
- def __init__(self):
- # 加载环境变量
- load_dotenv()
- # 延迟配置Gemini,在真正使用时再设置
- self._configured = False
- self.model = None
- self.api_key = None
- # 初始化缓存清理时间
- self.last_cache_cleanup = time.time()
- # 系统提示词:仅做语音转文字
- self.system_prompt = (
- "你是一个专业的音频转写助手。请严格将音频中的语音内容转换为文字,不要添加任何分析、解释或评论。"
- )
- def _ensure_configured(self):
- """确保Gemini已配置"""
- if not self._configured:
- # 与图片模块保持一致读取 GEMINI_API_KEY_1,若无则回退 GEMINI_API_KEY
- self.api_key = os.getenv('GEMINI_API_KEY_1') or os.getenv('GEMINI_API_KEY')
- if not self.api_key:
- raise ValueError('请在环境变量中设置 GEMINI_API_KEY_1 或 GEMINI_API_KEY')
- genai.configure(api_key=self.api_key)
- # 使用通用多模态模型进行音频理解
- self.model = genai.GenerativeModel(
- model_name='gemini-2.5-flash',
- generation_config=genai.GenerationConfig(
- response_mime_type='text/plain',
- temperature=0.2,
- max_output_tokens=40960
- ),
- safety_settings={
- HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
- HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_NONE,
- }
- )
- self._configured = True
- def cleanup_cache(self):
- """清理过期的缓存文件"""
- try:
- current_time = time.time()
- if current_time - self.last_cache_cleanup < 3600:
- return
- if not os.path.exists(CACHE_DIR):
- return
- cleaned_count = 0
- for filename in os.listdir(CACHE_DIR):
- file_path = os.path.join(CACHE_DIR, filename)
- if os.path.isfile(file_path):
- file_age = current_time - os.path.getmtime(file_path)
- if file_age > CACHE_MAX_AGE:
- try:
- os.remove(file_path)
- cleaned_count += 1
- except Exception as e:
- logger.warning(f'清理缓存文件失败: {file_path}, 错误: {e}')
- if cleaned_count > 0:
- logger.info(f'已清理 {cleaned_count} 个过期缓存文件')
- self.last_cache_cleanup = current_time
- except Exception as e:
- logger.error(f'清理缓存失败: {e}')
- def download_audio(self, audio_url: str) -> Optional[str]:
- """下载音频到本地缓存并返回路径"""
- # 猜测常见音频类型,后续统一按 mp3 保存
- file_path = os.path.join(CACHE_DIR, f'{str(uuid.uuid4())}.mp3')
- try:
- os.makedirs(CACHE_DIR, exist_ok=True)
- except Exception as e:
- logger.error(f'创建缓存目录失败: {e}')
- return None
- try:
- for attempt in range(3):
- try:
- response = requests.get(url=audio_url, timeout=60)
- if response.status_code == 200:
- try:
- with open(file_path, 'wb') as f:
- f.write(response.content)
- return file_path
- except Exception as e:
- logger.error(f'音频保存失败: {e}')
- if os.path.exists(file_path):
- try:
- os.remove(file_path)
- except Exception:
- pass
- return None
- else:
- logger.warning(f'音频下载失败,状态码: {response.status_code}')
- if attempt == 2:
- return None
- except Exception as e:
- logger.warning(f'下载尝试 {attempt + 1} 失败: {e}')
- if attempt < 2:
- time.sleep(1)
- continue
- return None
- except Exception as e:
- logger.error(f'下载过程异常: {e}')
- return None
- return None
- def upload_audio_to_gemini(self, audio_path: str) -> Optional[Any]:
- """上传音频至 Gemini,返回文件对象"""
- self._ensure_configured()
- max_retries = 3
- retry_delay = 5
- for attempt in range(max_retries):
- try:
- if not os.path.exists(audio_path):
- logger.error('错误: 文件不存在')
- return None
- file_size = os.path.getsize(audio_path)
- if file_size == 0:
- logger.error('错误: 文件大小为0')
- return None
- try:
- with open(audio_path, 'rb') as f:
- f.read(1024)
- except Exception as e:
- logger.error(f'错误: 文件无法读取 - {e}')
- return None
- try:
- # 使用常见音频 MIME 类型。若后续需要可根据扩展名判断
- audio_file = genai.upload_file(path=audio_path, mime_type='audio/mpeg')
- except Exception as e:
- msg = str(e)
- logger.error(f'错误: 文件上传请求失败 - {msg}')
- if any(k in msg.lower() for k in ['broken pipe', 'connection', 'timeout', 'network']):
- if attempt < max_retries - 1:
- time.sleep(retry_delay)
- retry_delay *= 2
- continue
- return None
- return None
- # 等待处理
- max_wait_time = 120
- waited = 0
- while getattr(audio_file, 'state', None) and getattr(audio_file.state, 'name', '') == 'PROCESSING' and waited < max_wait_time:
- time.sleep(2)
- waited += 2
- try:
- audio_file = genai.get_file(name=audio_file.name)
- if audio_file.state.name in ['FAILED', 'ERROR', 'INVALID']:
- if attempt < max_retries - 1:
- time.sleep(retry_delay)
- retry_delay *= 2
- break
- return None
- except Exception as e:
- logger.warning(f'获取文件状态失败: {e}')
- if waited <= 60:
- return None
- continue
- if getattr(audio_file, 'state', None) and audio_file.state.name == 'ACTIVE':
- logger.info(f'音频上传成功: {audio_file.name}')
- return audio_file
- else:
- if attempt < max_retries - 1:
- time.sleep(retry_delay)
- retry_delay *= 2
- continue
- return None
- except Exception as e:
- msg = str(e)
- if any(k in msg.lower() for k in ['broken pipe', 'connection', 'timeout', 'network']):
- if attempt < max_retries - 1:
- time.sleep(retry_delay)
- retry_delay *= 2
- continue
- return None
- logger.error(f'音频上传异常: {msg}')
- return None
- return None
- def extract_audio_urls(self, formatted_content: Dict[str, Any]) -> List[str]:
- """从 formatted_content 中提取音频 URL 列表
- 兼容以下结构:
- - audio_url_list: [{"audio_url": "..."}, ...]
- - voice_data: {"url": "..."} 或 [{"url": "..."}, ...]
- - bgm_data: {"url": "..."}
- """
- urls: List[str] = []
- # audio_url_list
- for item in (formatted_content.get('audio_url_list') or []):
- if isinstance(item, dict) and item.get('audio_url'):
- urls.append(item['audio_url'])
- elif isinstance(item, str):
- urls.append(item)
- # voice_data
- voice_data = formatted_content.get('voice_data')
- if isinstance(voice_data, dict) and voice_data.get('url'):
- urls.append(voice_data['url'])
- elif isinstance(voice_data, list):
- for v in voice_data:
- if isinstance(v, dict) and v.get('url'):
- urls.append(v['url'])
- elif isinstance(v, str):
- urls.append(v)
- # bgm_data
- bgm_data = formatted_content.get('bgm_data')
- if isinstance(bgm_data, dict) and bgm_data.get('url'):
- urls.append(bgm_data['url'])
- # 去重并保持顺序
- seen = set()
- deduped: List[str] = []
- for u in urls:
- if u and u not in seen:
- seen.add(u)
- deduped.append(u)
- return deduped
- def analyze_audios_with_gemini(self, audio_urls: List[str]) -> List[Dict[str, Any]]:
- """将音频上传到 Gemini 并进行转写,返回按输入顺序的结果列表"""
- if not audio_urls:
- return []
- results: List[Dict[str, Any]] = [{} for _ in range(len(audio_urls))]
- def process_one(idx_and_url) -> Dict[str, Any]:
- idx, url = idx_and_url
- audio_file = None
- local_path: Optional[str] = None
- try:
- self._ensure_configured()
- logger.info(f"配置Gemini: {self.api_key}")
- # 1. 下载
- local_path = self.download_audio(url)
- if not local_path:
- return {"url": url, "asr_content": "音频下载失败"}
- # 2. 上传
- audio_file = self.upload_audio_to_gemini(local_path)
- # 清理本地文件
- try:
- if local_path and os.path.exists(local_path):
- os.remove(local_path)
- except Exception:
- pass
- if not audio_file:
- return {"url": url, "asr_content": "音频上传失败"}
- # 3. 生成
- response = self.model.generate_content(
- contents=[self.system_prompt, audio_file],
- request_options={'timeout': 500}
- )
- # 尝试读取文本
- try:
- text_out = ''
- # 优先从 candidates 结构提取,避免某些情况下 .text 不可用
- candidates = getattr(response, 'candidates', None)
- if candidates and len(candidates) > 0:
- first = candidates[0]
- content = getattr(first, 'content', None)
- parts = getattr(content, 'parts', None) if content else None
- if parts and len(parts) > 0:
- part0 = parts[0]
- text_out = getattr(part0, 'text', None) if hasattr(part0, 'text') else part0.get('text') if isinstance(part0, dict) else ''
- if not text_out and hasattr(response, 'text') and isinstance(response.text, str):
- text_out = response.text
- text_out = (text_out or '').strip()
- if not text_out:
- return {"url": url, "asr_content": "ASR分析失败:无内容"}
- return {"url": url, "asr_content": text_out}
- except Exception as e:
- return {"url": url, "asr_content": f"ASR分析失败:{str(e)}"}
- except Exception as e:
- return {"url": url, "asr_content": f"处理失败: {str(e)}"}
- finally:
- # 4. 清理远端文件
- if audio_file and hasattr(audio_file, 'name'):
- try:
- genai.delete_file(name=audio_file.name)
- except Exception:
- pass
- # 顺序处理,保持简单稳妥
- for idx, url in enumerate(audio_urls):
- result = process_one((idx, url))
- results[idx] = result
- return results
- def process_audios(self, formatted_content: Dict[str, Any]) -> List[Dict[str, Any]]:
- """处理音频识别的主函数,返回 [{url, asr_content}]"""
- try:
- audio_urls = self.extract_audio_urls(formatted_content)
- if not audio_urls:
- return []
- return self.analyze_audios_with_gemini(audio_urls)
- finally:
- # 触发一次缓存清理(若到时间)
- self.cleanup_cache()
- def main():
- """测试函数"""
- test_content = {
- "audio_url_list": [
- {"audio_url": "http://rescdn.yishihui.com/pipeline/audio/09417cf6-60ec-4b62-8ee1-06f9268b13b1.mp3"}
- ]
- }
- identifier = AudioIdentifier()
- result = identifier.process_audios(test_content)
- print(json.dumps(result, ensure_ascii=False, indent=2))
- if __name__ == '__main__':
- main()
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