mirror of
https://github.com/JefferyHcool/BiliNote.git
synced 2026-05-06 20:42:52 +08:00
1ebf236f4f
- 新增 logger 模块，用于全局日志记录 - 在关键位置添加日志输出，包括事件处理、文件清理、FFmpeg 检查等 - 优化数据库操作，增加日志记录 - 在主程序启动时添加日志输出
207 lines
7.7 KiB
Python
207 lines
7.7 KiB
Python
import os
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from typing import Union
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from pydantic import HttpUrl
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from app.db.video_task_dao import insert_video_task, delete_task_by_video
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from app.downloaders.base import Downloader
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from app.downloaders.bilibili_downloader import BilibiliDownloader
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from app.downloaders.douyin_downloader import DouyinDownloader
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from app.downloaders.youtube_downloader import YoutubeDownloader
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from app.gpt.base import GPT
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from app.gpt.deepseek_gpt import DeepSeekGPT
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from app.gpt.openai_gpt import OpenaiGPT
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from app.gpt.qwen_gpt import QwenGPT
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from app.models.gpt_model import GPTSource
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from app.models.notes_model import NoteResult
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from app.models.notes_model import AudioDownloadResult
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from app.enmus.note_enums import DownloadQuality
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from app.models.transcriber_model import TranscriptResult
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from app.transcriber.base import Transcriber
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from app.transcriber.transcriber_provider import get_transcriber
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from app.transcriber.whisper import WhisperTranscriber
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import re
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from app.utils.note_helper import replace_content_markers
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from app.utils.video_helper import generate_screenshot
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# from app.services.whisperer import transcribe_audio
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# from app.services.gpt import summarize_text
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from dotenv import load_dotenv
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from app.utils.logger import get_logger
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logger = get_logger(__name__)
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load_dotenv()
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BACKEND_BASE_URL = os.getenv("API_BASE_URL", "http://localhost:8000")
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output_dir = os.getenv('OUT_DIR')
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image_base_url = os.getenv('IMAGE_BASE_URL')
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logger.info("starting up")
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class NoteGenerator:
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def __init__(self):
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self.model_size: str = 'base'
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self.device: Union[str, None] = None
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self.transcriber_type = 'fast-whisper'
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self.transcriber = self.get_transcriber()
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# TODO 需要更换为可调节
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self.provider = os.getenv('MODEl_PROVIDER','openai')
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self.video_path = None
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logger.info("初始化NoteGenerator")
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def get_gpt(self) -> GPT:
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if self.provider == 'openai':
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logger.info("使用OpenAI")
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return OpenaiGPT()
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elif self.provider == 'deepSeek':
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logger.info("使用DeepSeek")
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return DeepSeekGPT()
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elif self.provider == 'qwen':
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logger.info("使用Qwen")
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return QwenGPT()
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else:
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logger.warning("不支持的AI提供商")
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raise ValueError(f"不支持的AI提供商：{self.provider}")
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def get_downloader(self, platform: str) -> Downloader:
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if platform == "bilibili":
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logger.info("下载 Bilibili 平台视频")
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return BilibiliDownloader()
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elif platform == "youtube":
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logger.info("下载 YouTube 平台视频")
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return YoutubeDownloader()
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elif platform == 'douyin':
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logger.info("下载 Douyin 平台视频")
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return DouyinDownloader()
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else:
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logger.warning("不支持的平台")
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raise ValueError(f"不支持的平台：{platform}")
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def get_transcriber(self) -> Transcriber:
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'''
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:param transcriber: 选择的转义器
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:return:
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'''
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if self.transcriber_type == 'fast-whisper':
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logger.info("使用Whisper")
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return get_transcriber()
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else:
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logger.warning("不支持的转义器")
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raise ValueError(f"不支持的转义器：{self.transcriber}")
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def save_meta(self, video_id, platform, task_id):
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logger.info(f"记录已经生成的数据信息")
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insert_video_task(video_id=video_id, platform=platform, task_id=task_id)
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def insert_screenshots_into_markdown(self, markdown: str, video_path: str, image_base_url: str,
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output_dir: str) -> str:
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"""
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扫描 markdown 中的 *Screenshot-xx:xx，生成截图并插入 markdown 图片
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:param markdown:
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:param image_base_url: 最终返回给前端的路径前缀（如 /static/screenshots）
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"""
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matches = self.extract_screenshot_timestamps(markdown)
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new_markdown = markdown
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logger.info(f"开始为笔记生成截图")
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try:
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for idx, (marker, ts) in enumerate(matches):
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image_path = generate_screenshot(video_path, output_dir, ts, idx)
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image_relative_path = os.path.join(image_base_url, os.path.basename(image_path)).replace("\\", "/")
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image_url = f"{BACKEND_BASE_URL.rstrip('/')}/{image_relative_path.lstrip('/')}"
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replacement = f""
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new_markdown = new_markdown.replace(marker, replacement, 1)
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return new_markdown
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except Exception as e:
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logger.error(f"截图生成失败：{e}")
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raise e
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@staticmethod
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def delete_note(video_id: str, platform: str):
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logger.info(f"删除生成的笔记记录")
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return delete_task_by_video(video_id, platform)
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import re
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def extract_screenshot_timestamps(self, markdown: str) -> list[tuple[str, int]]:
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"""
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从 Markdown 中提取 Screenshot 时间标记（如 *Screenshot-03:39 或 Screenshot-[03:39]），
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并返回匹配文本和对应时间戳（秒）
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"""
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logger.info(f"开始提取截图时间标记")
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pattern = r"(?:\*Screenshot-(\d{2}):(\d{2})|Screenshot-\[(\d{2}):(\d{2})\])"
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matches = list(re.finditer(pattern, markdown))
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results = []
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for match in matches:
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mm = match.group(1) or match.group(3)
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ss = match.group(2) or match.group(4)
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total_seconds = int(mm) * 60 + int(ss)
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results.append((match.group(0), total_seconds))
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return results
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def generate(
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self,
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video_url: Union[str, HttpUrl],
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platform: str,
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quality: DownloadQuality = DownloadQuality.medium,
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task_id: Union[str, None] = None,
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link: bool = False,
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screenshot: bool = False,
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path: Union[str, None] = None
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) -> NoteResult:
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logger.info(f"开始解析并生成笔记")
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# 1. 选择下载器
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downloader = self.get_downloader(platform)
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gpt = self.get_gpt()
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logger.info(f'使用{downloader.__class__.__name__}下载器\n'
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f'使用{gpt.__class__.__name__}GPT\n'
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f'视频地址：{video_url}')
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if screenshot:
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video_path = downloader.download_video(video_url)
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self.video_path = video_path
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print(video_path)
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# 2. 下载音频
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audio: AudioDownloadResult = downloader.download(
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video_url=video_url,
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quality=quality,
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output_dir=path,
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need_video=screenshot
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)
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logger.info(f"下载音频成功，文件路径：{audio.file_path}")
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# 3. Whisper 转写
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transcript: TranscriptResult = self.transcriber.transcript(file_path=audio.file_path)
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logger.info(f"Whisper 转写成功，转写结果：{transcript.full_text}")
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# 4. GPT 总结
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source = GPTSource(
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title=audio.title,
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segment=transcript.segments,
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tags=audio.raw_info.get('tags'),
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screenshot=screenshot,
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link=link
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)
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logger.info(f"GPT 总结完成，总结结果：{source}")
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markdown: str = gpt.summarize(source)
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print("markdown结果", markdown)
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markdown = replace_content_markers(markdown=markdown, video_id=audio.video_id, platform=platform)
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if self.video_path:
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markdown = self.insert_screenshots_into_markdown(markdown, self.video_path, image_base_url, output_dir)
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self.save_meta(video_id=audio.video_id, platform=platform, task_id=task_id)
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# 5. 返回结构体
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return NoteResult(
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markdown=markdown,
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transcript=transcript,
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audio_meta=audio
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)
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