145 lines
5.5 KiB
Python
145 lines
5.5 KiB
Python
# -*- coding: utf-8 -*-
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"""
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音视频处理适配器
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复用MaxKB的模型系统，保持模块独立性
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"""
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import os
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import json
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import tempfile
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from typing import Dict, List, Optional, Any
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from concurrent.futures import ThreadPoolExecutor
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class MediaAdapter:
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"""
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音视频处理适配器
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复用MaxKB的模型系统，保持模块独立性
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"""
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def __init__(self, logger=None):
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self.logger = logger or self._get_default_logger()
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from .config import MediaConfig
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self.config = MediaConfig()
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def _get_default_logger(self):
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"""获取默认logger"""
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try:
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from common.utils.logger import maxkb_logger
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from .logger import MediaLogger
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return MediaLogger(maxkb_logger)
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except:
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import logging
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from .logger import MediaLogger
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return MediaLogger(logging.getLogger('MediaAdapter'))
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def process_media(self,
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file_content: bytes,
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file_name: str,
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stt_model_id: Optional[str] = None,
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llm_model_id: Optional[str] = None,
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workspace_id: Optional[str] = None,
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options: Dict[str, Any] = None) -> Dict:
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"""
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处理音视频文件
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Args:
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file_content: 文件内容
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file_name: 文件名
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stt_model_id: STT模型ID（MaxKB系统中的）
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llm_model_id: LLM模型ID（用于文本优化，可选）
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workspace_id: 工作空间ID
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options: 其他选项
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- language: 语言（zh/en/auto）
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- segment_duration: 分段时长（秒）
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- enable_punctuation: 是否添加标点
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- enable_summary: 是否生成摘要
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Returns:
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{
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'status': 'success',
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'media_type': 'audio/video',
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'duration': 120.5,
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'segments': [
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{
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'index': 0,
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'start_time': 0,
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'end_time': 60,
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'text': '转写文本',
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'enhanced_text': '优化后的文本',
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'summary': '段落摘要'
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}
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],
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'full_text': '完整文本',
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'metadata': {
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'stt_model': 'model_name',
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'language': 'zh',
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'processing_time': 10.5
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}
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}
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"""
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options = options or {}
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self.logger.info(f"开始处理媒体文件: {file_name}")
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self.logger.info(f"接收到的参数:")
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self.logger.info(f" - stt_model_id: {stt_model_id}")
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self.logger.info(f" - workspace_id: {workspace_id}")
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self.logger.info(f" - llm_model_id: {llm_model_id}")
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self.logger.info(f" - options: {options}")
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self.logger.info(f" - enable_summary in options: {options.get('enable_summary')}")
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try:
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# 判断媒体类型
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media_type = self._detect_media_type(file_name)
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# 获取STT模型实例
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stt_model = None
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if stt_model_id and workspace_id:
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try:
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from models_provider.tools import get_model_instance_by_model_workspace_id
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stt_model = get_model_instance_by_model_workspace_id(stt_model_id, workspace_id)
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self.logger.info(f"成功获取STT模型实例: {stt_model}")
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except Exception as e:
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self.logger.error(f"获取STT模型失败: {str(e)}")
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else:
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self.logger.warning(f"STT模型未配置 - stt_model_id: {stt_model_id}, workspace_id: {workspace_id}")
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# 获取LLM模型实例（可选）
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llm_model = None
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if llm_model_id and workspace_id:
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try:
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from models_provider.tools import get_model_instance_by_model_workspace_id
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llm_model = get_model_instance_by_model_workspace_id(llm_model_id, workspace_id)
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self.logger.info(f"使用LLM模型: {llm_model_id}")
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except Exception as e:
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self.logger.warning(f"获取LLM模型失败: {str(e)}")
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# 处理文件
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if media_type == 'video':
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from .processors.video_processor import VideoProcessor
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processor = VideoProcessor(self.config, self.logger)
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else:
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from .processors.audio_processor import AudioProcessor
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processor = AudioProcessor(self.config, self.logger)
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result = processor.process(
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file_content=file_content,
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file_name=file_name,
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stt_model=stt_model,
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llm_model=llm_model,
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options=options
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)
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self.logger.info(f"媒体文件处理成功: {file_name}")
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return result
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except Exception as e:
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self.logger.error(f"处理媒体文件失败: {str(e)}")
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raise
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def _detect_media_type(self, file_name: str) -> str:
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"""检测媒体类型"""
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file_ext = file_name.lower().split('.')[-1]
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video_exts = {'mp4', 'avi', 'mov', 'mkv', 'webm', 'flv', 'wmv'}
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if file_ext in video_exts:
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return 'video'
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return 'audio' |