mirror of
https://github.com/JefferyHcool/BiliNote.git
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refactor(backend): 重构后端异常处理和模型管理
- 新增自定义异常类 BizException、NoteError 和 ProviderError - 优化了模型管理相关的逻辑，包括加载、删除和测试连接等功能 - 改进了 Douyin 下载器的错误处理 - 调整了任务重试逻辑和笔记生成的异常处理- 更新了相关组件和页面以适应新的异常处理机制
This commit is contained in:
JefferyHcool
@@ -1,75 +1,63 @@
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import json
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from dataclasses import asdict
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from fastapi import HTTPException
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from app.downloaders.local_downloader import LocalDownloader
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from app.enmus.task_status_enums import TaskStatus
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import logging
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import os
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from typing import Union, Optional
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import re
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from dataclasses import asdict
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from pathlib import Path
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from typing import List, Optional, Tuple, Union, Any
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from pydantic import HttpUrl
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from dotenv import load_dotenv
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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.services.constant import SUPPORT_PLATFORM_MAP
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from app.enmus.task_status_enums import TaskStatus
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from app.enmus.exception import NoteErrorEnum, ProviderErrorEnum
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from app.exceptions.note import NoteError
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from app.exceptions.provider import ProviderError
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from app.db.video_task_dao import delete_task_by_video, insert_video_task
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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.gpt_factory import GPTFactory
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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.audio_model import AudioDownloadResult
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from app.models.gpt_model import GPTSource
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from app.models.model_config import ModelConfig
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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, TranscriptSegment
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from app.services.constant import SUPPORT_PLATFORM_MAP
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from app.services.provider import ProviderService
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from app.transcriber.base import Transcriber
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from app.transcriber.transcriber_provider import get_transcriber, _transcribers
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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.status_code import StatusCode
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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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from app.utils.video_reader import VideoReader
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from events import transcription_finished
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from app.utils.video_helper import generate_screenshot
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from app.utils.note_helper import replace_content_markers
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from app.enmus.note_enums import DownloadQuality
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logger = get_logger(__name__)
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# 环境变量
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load_dotenv()
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api_path = os.getenv("API_BASE_URL", "http://localhost")
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BACKEND_PORT = os.getenv("BACKEND_PORT", 8000)
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NOTE_OUTPUT_DIR = Path(os.getenv("NOTE_OUTPUT_DIR", "note_results"))
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NOTE_OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
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IMAGE_BASE_URL = os.getenv("IMAGE_BASE_URL", "/static/screenshots")
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IMAGE_OUTPUT_DIR = os.getenv("OUT_DIR", "images")
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BACKEND_BASE_URL = f"{api_path}:{BACKEND_PORT}"
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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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NOTE_OUTPUT_DIR = "note_results"
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logger = logging.getLogger(__name__)
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logger.setLevel(logging.INFO)
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class NoteGenerator:
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class States:
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INIT = 'INIT'
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PARSING = 'PARSING'
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DOWNLOADING = 'DOWNLOADING'
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TRANSCRIBING = 'TRANSCRIBING'
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SUMMARIZING = 'SUMMARIZING'
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SAVING = 'SAVING'
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SUCCESS = 'SUCCESS'
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FAILED = 'FAILED'
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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 = os.getenv('TRANSCRIBER_TYPE', 'fast-whisper')
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self.transcriber = self.get_transcriber()
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self.video_path = None
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logger.info("初始化NoteGenerator")
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import logging
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logger = logging.getLogger(__name__)
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self.transcriber_type = os.getenv("TRANSCRIBER_TYPE", "fast-whisper")
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self.transcriber: Transcriber = self._init_transcriber()
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self.video_img_urls = []
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@staticmethod
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def update_task_status(task_id: str, status: Union[str, TaskStatus], message: Optional[str] = None):
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@@ -81,310 +69,179 @@ class NoteGenerator:
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with open(path, "w", encoding="utf-8") as f:
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json.dump(content, f, ensure_ascii=False, indent=2)
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def get_gpt(self, model_name: str = None, provider_id: str = None) -> GPT:
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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: Optional[str] = None,
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model_name: Optional[str] = None,
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provider_id: Optional[str] = None,
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link: bool = False,
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screenshot: bool = False,
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_format: Optional[List[str]] = None,
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style: Optional[str] = None,
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extras: Optional[str] = None,
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output_path: Optional[str] = None,
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video_understanding: bool = False,
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video_interval: int = 0,
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grid_size: Optional[List[int]] = None,
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) -> NoteResult | None:
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self.task_id = task_id
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self._change_state(self.States.INIT)
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try:
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self._change_state(self.States.PARSING)
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downloader = self._get_downloader(platform)
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gpt = self._get_gpt(model_name, provider_id)
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self.audio_cache_file = NOTE_OUTPUT_DIR / f"{task_id}_audio.json"
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self.transcript_cache_file = NOTE_OUTPUT_DIR / f"{task_id}_transcript.json"
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self.markdown_cache_file = NOTE_OUTPUT_DIR / f"{task_id}_markdown.md"
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self.audio_meta = self._download_audio_video(
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downloader, video_url, quality, output_path,
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screenshot, video_understanding, video_interval, grid_size or []
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)
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self.transcript = self._transcribe_audio()
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self.markdown = self._summarize_text(
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gpt, link, screenshot, _format or [], style, extras
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)
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self.markdown = self._post_process_markdown(
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self.markdown, self.video_path, _format or [], self.audio_meta, platform
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)
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self._change_state(self.States.SAVING)
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self._save_metadata(self.audio_meta.video_id, platform, task_id)
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self._change_state(self.States.SUCCESS)
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return NoteResult(markdown=self.markdown, transcript=self.transcript, audio_meta=self.audio_meta)
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except Exception as e:
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logger.exception(f"任务 {self.task_id} 失败: {e}")
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self._change_state(self.States.FAILED, str(e))
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return None
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def _change_state(self, state: str, message: Optional[str] = None):
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if not self.task_id:
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return
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NOTE_OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
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status_file = NOTE_OUTPUT_DIR / f"{self.task_id}.status.json"
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data = {"status": state}
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if message:
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data["message"] = message
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temp_file = status_file.with_suffix('.tmp')
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with temp_file.open('w', encoding='utf-8') as f:
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json.dump(data, f, ensure_ascii=False, indent=2)
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temp_file.replace(status_file)
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def _init_transcriber(self) -> Transcriber:
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if self.transcriber_type not in _transcribers:
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raise Exception(f"不支持的转写器：{self.transcriber_type}")
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return get_transcriber(self.transcriber_type)
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def _get_gpt(self, model_name: Optional[str], provider_id: Optional[str]) -> GPT:
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provider = ProviderService.get_provider_by_id(provider_id)
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if not provider:
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logger.error(f"[get_gpt] 未找到对应的模型供应商: provider_id={provider_id}")
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raise ValueError(f"未找到对应的模型供应商: provider_id={provider_id}")
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gpt = GPTFactory().from_config(
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ModelConfig(
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api_key=provider.get('api_key'),
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base_url=provider.get('base_url'),
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model_name=model_name,
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provider=provider.get('type'),
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name=provider.get('name')
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)
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raise ProviderError(code=ProviderErrorEnum.NOT_FOUND, message=ProviderErrorEnum.NOT_FOUND.message)
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config = ModelConfig(
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api_key=provider["api_key"], base_url=provider["base_url"],
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model_name=model_name, provider=provider["type"], name=provider["name"]
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)
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return gpt
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return GPTFactory().from_config(config)
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def get_downloader(self, platform: str) -> Downloader:
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downloader = SUPPORT_PLATFORM_MAP[platform]
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if downloader:
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logger.info(f"使用{downloader}下载器")
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return downloader
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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_downloader(self, platform: str) -> Downloader:
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downloader_cls = SUPPORT_PLATFORM_MAP.get(platform)
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if not downloader_cls:
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raise NoteError(code=NoteErrorEnum.PLATFORM_NOT_SUPPORTED.code,
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message=NoteErrorEnum.PLATFORM_NOT_SUPPORTED.message)
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return downloader_cls
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def get_transcriber(self) -> Transcriber:
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'''
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def _download_audio_video(self, downloader, video_url, quality, output_path,
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screenshot, video_understanding, video_interval, grid_size):
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self._change_state(self.States.DOWNLOADING)
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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 in _transcribers.keys():
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logger.info(f"使用{self.transcriber_type}转义器")
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return get_transcriber(transcriber_type=self.transcriber_type)
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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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need_video = screenshot or video_understanding
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if need_video:
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self.video_path = Path(downloader.download_video(video_url, output_path))
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if grid_size:
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self.video_img_urls = VideoReader(
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video_path=str(self.video_path),
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grid_size=tuple(grid_size),
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frame_interval=video_interval,
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unit_width=1280, unit_height=720,
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save_quality=90,
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).run()
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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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if self.audio_cache_file.exists():
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with open(self.audio_cache_file, "r", encoding="utf-8") as f:
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data = json.load(f)
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return AudioDownloadResult(**data)
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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, _format: list) -> 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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audio = downloader.download(
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video_url=video_url, quality=quality, output_dir=output_path, need_video=need_video
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)
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with open(self.audio_cache_file, "w", encoding="utf-8") as f:
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json.dump(asdict(audio), f, ensure_ascii=False, indent=2)
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return audio
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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"/static/screenshots/{os.path.basename(image_path)}"
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replacement = f""
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new_markdown = new_markdown.replace(marker, replacement, 1)
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def _transcribe_audio(self):
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self._change_state(self.States.TRANSCRIBING)
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if self.transcript_cache_file.exists():
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with open(self.transcript_cache_file, "r", encoding="utf-8") as f:
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data = json.load(f)
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segments = [TranscriptSegment(**seg) for seg in data.get("segments", [])]
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return TranscriptResult(language=data["language"], full_text=data["full_text"], segments=segments)
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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 HTTPException(
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status_code=500,
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detail={
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"code": StatusCode.DOWNLOAD_ERROR,
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"msg": f"截图生成失败",
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"error": str(e)
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}
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)
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transcript = self.transcriber.transcript(self.audio_meta.file_path)
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with open(self.transcript_cache_file, "w", encoding="utf-8") as f:
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json.dump(asdict(transcript), f, ensure_ascii=False, indent=2)
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return transcript
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def _summarize_text(self, gpt, link, screenshot, formats, style, extras):
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self._change_state(self.States.SUMMARIZING)
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source = GPTSource(
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title=self.audio_meta.title,
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segment=self.transcript.segments,
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tags=self.audio_meta.raw_info.get("tags", []),
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screenshot=screenshot,
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video_img_urls=self.video_img_urls,
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link=link, _format=formats, style=style, extras=extras
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)
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markdown = gpt.summarize(source)
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with open(self.markdown_cache_file, "w", encoding="utf-8") as f:
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f.write(markdown)
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return markdown
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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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def _post_process_markdown(self, markdown, video_path, formats, audio_meta, platform):
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if "screenshot" in formats and video_path:
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markdown = self._insert_screenshots(markdown, video_path)
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if "link" in formats:
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markdown = replace_content_markers(markdown, video_id=audio_meta.video_id, platform=platform)
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return markdown
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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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def _insert_screenshots(self, markdown, video_path):
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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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matches = []
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for match in re.finditer(pattern, markdown):
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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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matches.append((match.group(0), int(mm)*60+int(ss)))
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for idx, (marker, ts) in enumerate(matches):
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img_path = generate_screenshot(str(video_path), str(IMAGE_OUTPUT_DIR), ts, idx)
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filename = Path(img_path).name
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img_url = f"{IMAGE_BASE_URL.rstrip('/')}/{filename}"
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markdown = markdown.replace(marker, f"", 1)
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return markdown
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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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model_name: str = None,
|
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provider_id: str = None,
|
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link: bool = False,
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screenshot: bool = False,
|
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_format: list = None,
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style: str = None,
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extras: str = None,
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path: Union[str, None] = None,
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video_understanding: bool = False,
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video_interval=0,
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grid_size=[]
|
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) -> NoteResult:
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def _save_metadata(self, video_id: str, platform: str, task_id: str):
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insert_video_task(video_id=video_id, platform=platform, task_id=task_id)
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|
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try:
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logger.info(f"🎯 开始解析并生成笔记，task_id={task_id}")
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self.update_task_status(task_id, TaskStatus.PARSING)
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downloader = self.get_downloader(platform)
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gpt = self.get_gpt(model_name=model_name, provider_id=provider_id)
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video_img_urls = []
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audio_cache_path = os.path.join(NOTE_OUTPUT_DIR, f"{task_id}_audio.json")
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transcript_cache_path = os.path.join(NOTE_OUTPUT_DIR, f"{task_id}_transcript.json")
|
||||
markdown_cache_path = os.path.join(NOTE_OUTPUT_DIR, f"{task_id}_markdown.md")
|
||||
|
||||
# -------- 1. 下载音频 --------
|
||||
try:
|
||||
self.update_task_status(task_id, TaskStatus.DOWNLOADING)
|
||||
|
||||
# 加载音频缓存（如果存在）
|
||||
audio = None
|
||||
if os.path.exists(audio_cache_path):
|
||||
logger.info(f"检测到已有音频缓存，直接读取，task_id={task_id}")
|
||||
with open(audio_cache_path, "r", encoding="utf-8") as f:
|
||||
audio_data = json.load(f)
|
||||
audio = AudioDownloadResult(**audio_data)
|
||||
|
||||
# 需要视频的情况（截图 or 视频理解）
|
||||
need_video = 'screenshot' in _format or video_understanding
|
||||
if need_video:
|
||||
try:
|
||||
video_path = downloader.download_video(video_url)
|
||||
self.video_path = video_path
|
||||
logger.info(f"成功下载视频文件: {video_path}")
|
||||
|
||||
video_img_urls = VideoReader(
|
||||
video_path=video_path,
|
||||
grid_size=tuple(grid_size),
|
||||
frame_interval=video_interval,
|
||||
unit_width=1280,
|
||||
unit_height=720,
|
||||
save_quality=90,
|
||||
).run()
|
||||
except Exception as e:
|
||||
logger.error(f"Error 下载视频失败，task_id={task_id}，错误信息：{e}")
|
||||
self.update_task_status(task_id, TaskStatus.FAILED, message=f"下载音频失败：{e}")
|
||||
raise HTTPException(
|
||||
status_code=500,
|
||||
detail={
|
||||
"code": StatusCode.DOWNLOAD_ERROR,
|
||||
"msg": f"下载视频失败，task_id={task_id}",
|
||||
"error": str(e)
|
||||
}
|
||||
)
|
||||
|
||||
# 没有音频缓存就下载音频（可能同时也带上视频）
|
||||
if audio is None:
|
||||
audio = downloader.download(
|
||||
video_url=video_url,
|
||||
quality=quality,
|
||||
output_dir=path,
|
||||
need_video='screenshot' in _format, # 注意这里只为了截图需要
|
||||
)
|
||||
with open(audio_cache_path, "w", encoding="utf-8") as f:
|
||||
json.dump(asdict(audio), f, ensure_ascii=False, indent=2)
|
||||
logger.info(f"音频下载并缓存成功，task_id={task_id}")
|
||||
except Exception as e:
|
||||
logger.error(f"Error 下载音频失败，task_id={task_id}，错误信息：{e}")
|
||||
self.update_task_status(task_id, TaskStatus.FAILED, message=f"下载音频失败：{e}")
|
||||
|
||||
raise HTTPException(
|
||||
status_code=500,
|
||||
detail={
|
||||
"code": StatusCode.DOWNLOAD_ERROR,
|
||||
"msg": f"下载音频失败，task_id={task_id}",
|
||||
"error": str(e)
|
||||
}
|
||||
)
|
||||
|
||||
# -------- 2. 转写文字 --------
|
||||
try:
|
||||
self.update_task_status(task_id, TaskStatus.TRANSCRIBING)
|
||||
if os.path.exists(transcript_cache_path):
|
||||
logger.info(f"检测到已有转写缓存，直接读取，task_id={task_id}")
|
||||
try:
|
||||
with open(transcript_cache_path, "r", encoding="utf-8") as f:
|
||||
transcript_data = json.load(f)
|
||||
transcript = TranscriptResult(
|
||||
language=transcript_data["language"],
|
||||
full_text=transcript_data["full_text"],
|
||||
segments=[TranscriptSegment(**seg) for seg in transcript_data["segments"]]
|
||||
)
|
||||
except (json.JSONDecodeError, KeyError) as e:
|
||||
logger.warning(f"Warning 读取转录缓存失败，重新转录，task_id={task_id}，错误信息：{e}")
|
||||
transcript: TranscriptResult = self.transcriber.transcript(file_path=audio.file_path)
|
||||
with open(transcript_cache_path, "w", encoding="utf-8") as f:
|
||||
json.dump(asdict(transcript), f, ensure_ascii=False, indent=2)
|
||||
else:
|
||||
transcript: TranscriptResult = self.transcriber.transcript(file_path=audio.file_path)
|
||||
with open(transcript_cache_path, "w", encoding="utf-8") as f:
|
||||
json.dump(asdict(transcript), f, ensure_ascii=False, indent=2)
|
||||
logger.info(f"文字转写并缓存成功，task_id={task_id}")
|
||||
except Exception as e:
|
||||
logger.error(f"Error 转写文字失败，task_id={task_id}，错误信息：{e}")
|
||||
self.update_task_status(task_id, TaskStatus.FAILED, message=f"转写文字失败：{e}")
|
||||
raise HTTPException(
|
||||
status_code=500,
|
||||
detail={
|
||||
"code": StatusCode.GENERATE_ERROR, # =1003
|
||||
"msg": f"转写文字失败，task_id={task_id}",
|
||||
"error": str(e)
|
||||
}
|
||||
)
|
||||
|
||||
# -------- 3. 总结内容 --------
|
||||
try:
|
||||
self.update_task_status(task_id, TaskStatus.SUMMARIZING)
|
||||
# if os.path.exists(markdown_cache_path):
|
||||
# logger.info(f"检测到已有总结缓存，直接读取，task_id={task_id}")
|
||||
# with open(markdown_cache_path, "r", encoding="utf-8") as f:
|
||||
# markdown = f.read()
|
||||
# else:
|
||||
source = GPTSource(
|
||||
title=audio.title,
|
||||
segment=transcript.segments,
|
||||
tags=audio.raw_info.get('tags'),
|
||||
screenshot=screenshot,
|
||||
video_img_urls=video_img_urls,
|
||||
link=link,
|
||||
_format=_format,
|
||||
style=style,
|
||||
extras=extras
|
||||
)
|
||||
|
||||
markdown: str = gpt.summarize(source)
|
||||
with open(markdown_cache_path, "w", encoding="utf-8") as f:
|
||||
f.write(markdown)
|
||||
logger.info(f"GPT总结并缓存成功，task_id={task_id}")
|
||||
except Exception as e:
|
||||
logger.error(f"Error 总结内容失败，task_id={task_id}，错误信息：{e}")
|
||||
self.update_task_status(task_id, TaskStatus.FAILED, message=f"总结内容失败：{e}")
|
||||
raise HTTPException(
|
||||
status_code=500,
|
||||
detail={
|
||||
"code": StatusCode.GENERATE_ERROR, # =1003
|
||||
"msg": f"总结内容失败，task_id={task_id}",
|
||||
"error": str(e)
|
||||
}
|
||||
)
|
||||
|
||||
# -------- 4. 插入截图 --------
|
||||
if _format and 'screenshot' in _format:
|
||||
try:
|
||||
markdown = self.insert_screenshots_into_markdown(markdown, self.video_path, image_base_url,
|
||||
output_dir, _format)
|
||||
except Exception as e:
|
||||
logger.warning(f"Warning 插入截图失败，跳过处理，task_id={task_id}，错误信息：{e}")
|
||||
if _format and 'link' in _format:
|
||||
try:
|
||||
markdown = replace_content_markers(markdown, video_id=audio.video_id, platform=platform)
|
||||
except Exception as e:
|
||||
logger.warning(f"Warning 插入链接失败，跳过处理，task_id={task_id}，错误信息：{e}")
|
||||
# 注意：截图失败不终止整体流程
|
||||
|
||||
# -------- 5. 保存数据库记录 --------
|
||||
self.update_task_status(task_id, TaskStatus.SAVING)
|
||||
self.save_meta(video_id=audio.video_id, platform=platform, task_id=task_id)
|
||||
|
||||
# -------- 6. 完成 --------
|
||||
self.update_task_status(task_id, TaskStatus.SUCCESS)
|
||||
logger.info(f"succeed 笔记生成成功，task_id={task_id}")
|
||||
# TODO :改为前端一键清除缓存
|
||||
# if platform != 'local':
|
||||
# transcription_finished.send({
|
||||
# "file_path": audio.file_path,
|
||||
# })
|
||||
return NoteResult(
|
||||
markdown=markdown,
|
||||
transcript=transcript,
|
||||
audio_meta=audio
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error 笔记生成流程异常终止，task_id={task_id}，错误信息：{e}")
|
||||
self.update_task_status(task_id, TaskStatus.FAILED, message=str(e))
|
||||
|
||||
# 返回结构化错误信息给前端（可以用于日志 + 显示 + 错误定位）
|
||||
raise HTTPException(
|
||||
status_code=500,
|
||||
detail={
|
||||
"code": StatusCode.FAIL,
|
||||
"msg": f"笔记生成流程异常终止，task_id={task_id}",
|
||||
"error": str(e)
|
||||
}
|
||||
)
|
||||
@staticmethod
|
||||
def delete_note(video_id: str, platform: str) -> int:
|
||||
return delete_task_by_video(video_id, platform)
|
||||
Reference in New Issue
Block a user