mirror of
https://github.com/JefferyHcool/BiliNote.git
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41f17592c2
- whisper: model.bin 截断/损坏时删目录重下重试一次，修「Unable to
open file model.bin」死循环；mlx 同样按 config.json 判完整性
- /generate_note 加就绪门禁：本地转写引擎模型没下好直接拦截，返回
reason=transcriber_model_not_ready，不让任务静默卡在首次下载
- 全局代理：新增 ProxyConfigManager（JSON 配置 + HTTP_PROXY env 兜底）
+ build_openai_client，统一注入代理到 LLM/Groq 客户端；yt-dlp 与
youtube-transcript-api 也走代理
- build_openai_client 校验 api_key 非空，空 key 给「xxx 的 API Key
未配置」而不是天书般的 Illegal header value b'Bearer '
- universal_gpt: 模型拒绝自定义 temperature（o1/o3/gpt-5 系列）时
就地去掉参数重试，不消耗重试预算
- connect_test 改用真实 chat completion 而非 /v1/models 探测
- main.py: lifespan 拆 [startup 1/5..5/5] 分段日志 + 异常清晰定位
- /sys_health 重构为结构化返回 {backend,ffmpeg,db,whisper_model}
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
60 lines
2.1 KiB
Python
60 lines
2.1 KiB
Python
from typing import List
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from app.gpt.base import GPT
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from app.utils.openai_client import build_openai_client
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from app.gpt.prompt import BASE_PROMPT, AI_SUM, SCREENSHOT
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from app.gpt.utils import fix_markdown
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from app.models.gpt_model import GPTSource
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from app.models.transcriber_model import TranscriptSegment
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from datetime import timedelta
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class DeepSeekGPT(GPT):
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def __init__(self):
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from os import getenv
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self.api_key = getenv("DEEP_SEEK_API_KEY")
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self.base_url = getenv("DEEP_SEEK_API_BASE_URL")
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self.model=getenv('DEEP_SEEK_MODEL')
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print(self.model)
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self.client = build_openai_client(self.api_key, self.base_url, key_label="DeepSeek 的 API Key")
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self.screenshot = False
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def _format_time(self, seconds: float) -> str:
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return str(timedelta(seconds=int(seconds)))[2:] # e.g., 03:15
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def _build_segment_text(self, segments: List[TranscriptSegment]) -> str:
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return "\n".join(
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f"{self._format_time(seg.start)} - {seg.text.strip()}"
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for seg in segments
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)
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def ensure_segments_type(self, segments) -> List[TranscriptSegment]:
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return [
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TranscriptSegment(**seg) if isinstance(seg, dict) else seg
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for seg in segments
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]
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def create_messages(self, segments: List[TranscriptSegment], title: str,tags:str):
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content = BASE_PROMPT.format(
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video_title=title,
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segment_text=self._build_segment_text(segments),
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tags=tags
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)
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if self.screenshot:
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print(":需要截图")
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content += SCREENSHOT
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print(content)
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return [{"role": "user", "content": content + AI_SUM}]
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def summarize(self, source: GPTSource) -> str:
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self.screenshot = source.screenshot
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source.segment = self.ensure_segments_type(source.segment)
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messages = self.create_messages(source.segment, source.title,source.tags)
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response = self.client.chat.completions.create(
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model=self.model,
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messages=messages,
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temperature=0.7
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)
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return response.choices[0].message.content.strip()
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