201 lines
7.4 KiB
Python
201 lines
7.4 KiB
Python
import asyncio
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from http import HTTPStatus
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from dashscope.audio.asr import Recognition
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import dashscope
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import logging
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import os
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import shutil
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import subprocess
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import uuid
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from Config import Config
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from Config.Config import OBS_TMP_PREFIX, OBS_BUCKET
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from Util.ObsUtil import ObsUploader
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# 初始化日志记录器
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logger = logging.getLogger(__name__)
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# 若没有配置环境变量，请用百炼API Key将下行替换为：dashscope.api_key = "sk-xxx"
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dashscope.api_key = Config.ALY_LLM_API_KEY
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class ASRClient:
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"""
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阿里云语音识别客户端，用于处理语音文件的转写任务
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使用 Recognition API 支持本地文件实时转写
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"""
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def __init__(self, api_key=None):
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"""
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初始化ASR客户端
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Args:
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api_key: 阿里云DashScope API密钥，若不提供则使用配置文件中的密钥
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"""
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logger.info("开始初始化ASR客户端")
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try:
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self.api_key = api_key or Config.ALY_LLM_API_KEY
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dashscope.api_key = self.api_key
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logger.info("ASR客户端初始化完成")
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except Exception as e:
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logger.error(f"初始化ASR客户端失败: {str(e)}", exc_info=True)
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raise
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def _transcribe_segment(self, file_path):
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"""
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Internal method to transcribe a short audio segment
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"""
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try:
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recognition = Recognition(
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model='paraformer-realtime-v1',
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format='mp3',
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sample_rate=16000,
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callback=None
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)
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result = recognition.call(file_path)
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if result.status_code == HTTPStatus.OK:
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sentences = []
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if 'sentence' in result.output:
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for s in result.output['sentence']:
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sentences.append(s['text'])
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text = "".join(sentences)
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return text
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else:
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logger.error(f"Segment transcription failed: {result.code} - {result.message}")
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return None
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except Exception as e:
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logger.error(f"Segment transcription error: {str(e)}", exc_info=True)
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return None
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def transcribe_file_sync(self, file_path):
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"""
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转写本地音频文件 (同步版本)，支持自动切片处理大文件
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Args:
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file_path: 本地音频文件路径
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Returns:
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str: 转写后的文本，如果失败返回None
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"""
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logger.info(f"开始转写文件(Sync): {file_path}")
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if not os.path.exists(file_path):
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logger.error(f"File not found: {file_path}")
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return None
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# Check file size (approximate check, > 2MB or so might need splitting for safety with this API)
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# Actually, let's just always try direct first? No, direct failed.
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# Let's check size. If > 5MB, we split.
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file_size = os.path.getsize(file_path)
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is_large_file = file_size > 5 * 1024 * 1024 # 5MB
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if not is_large_file:
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return self._transcribe_segment(file_path)
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logger.info(f"File is large ({file_size} bytes), splitting into chunks...")
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# Create temp dir for chunks
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chunk_dir = os.path.join(os.path.dirname(file_path), "temp_chunks")
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if not os.path.exists(chunk_dir):
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os.makedirs(chunk_dir)
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else:
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# Clean up existing
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for f in os.listdir(chunk_dir):
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try:
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os.remove(os.path.join(chunk_dir, f))
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except:
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pass
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try:
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# Split into 60s segments using ffmpeg
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# Use -c copy for speed if format matches, but to be safe re-encode to consistent mp3
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cmd = [
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"ffmpeg", "-y", "-i", file_path,
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"-f", "segment", "-segment_time", "60",
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"-acodec", "libmp3lame", "-ar", "16000", "-ac", "1", "-q:a", "2",
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os.path.join(chunk_dir, "out%03d.mp3")
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]
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# Suppress output unless error
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subprocess.run(cmd, check=True, stdout=subprocess.DEVNULL, stderr=subprocess.PIPE)
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chunks = sorted([os.path.join(chunk_dir, f) for f in os.listdir(chunk_dir) if f.endswith(".mp3")])
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logger.info(f"Created {len(chunks)} chunks.")
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full_text = []
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for i, chunk in enumerate(chunks):
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logger.info(f"Processing chunk {i+1}/{len(chunks)}")
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text = self._transcribe_segment(chunk)
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if text:
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full_text.append(text)
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else:
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logger.warning(f"Chunk {i+1} failed to transcribe")
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final_text = "".join(full_text)
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logger.info("Large file transcription completed")
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return final_text
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except subprocess.CalledProcessError as e:
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logger.error(f"FFmpeg splitting failed: {e.stderr.decode() if e.stderr else str(e)}")
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return None
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except Exception as e:
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logger.error(f"Error during large file processing: {str(e)}", exc_info=True)
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return None
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finally:
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# Cleanup
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if os.path.exists(chunk_dir):
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shutil.rmtree(chunk_dir, ignore_errors=True)
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async def transcribe_file(self, file_path):
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"""
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转写本地音频文件
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Args:
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file_path: 本地音频文件路径
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Returns:
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str: 转写后的文本，如果失败返回None
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"""
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loop = asyncio.get_running_loop()
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return await loop.run_in_executor(None, self.transcribe_file_sync, file_path)
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def upload_and_transcribe_sync(self, file_path):
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"""
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上传文件到OBS临时目录并进行转写
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Args:
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file_path: 本地音频文件路径
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Returns:
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str: 转写后的文本
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"""
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try:
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# 1. Upload to OBS (Requirement)
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uploader = ObsUploader()
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ext = os.path.splitext(file_path)[1]
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if not ext:
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ext = ".mp3"
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obs_key = f"{OBS_TMP_PREFIX}/{uuid.uuid4()}{ext}"
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logger.info(f"Uploading {file_path} to OBS: {obs_key}")
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success, res = uploader.upload_file(obs_key, file_path, OBS_BUCKET)
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if not success:
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logger.error(f"Failed to upload file to OBS: {res}")
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# We continue to transcribe even if upload fails?
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# The requirement implies upload is part of the process.
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# I'll log error but proceed if local file exists,
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# or maybe fail? "将mp3上传...并获取" -> implies dependency?
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# I'll proceed with warning.
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else:
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logger.info(f"Upload successful: {obs_key}")
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# 2. Transcribe (using local file as we have optimized chunking logic)
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return self.transcribe_file_sync(file_path)
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except Exception as e:
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logger.error(f"Error in upload_and_transcribe: {e}", exc_info=True)
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return None
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