mirror of
https://github.com/JefferyHcool/BiliNote.git
synced 2026-06-12 19:20:00 +08:00
- 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>
183 lines
6.6 KiB
Python
183 lines
6.6 KiB
Python
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from app.db.model_dao import insert_model, get_all_models, get_model_by_provider_and_name, delete_model
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from app.db.provider_dao import get_enabled_providers
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from app.enmus.exception import ProviderErrorEnum
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from app.exceptions.provider import ProviderError
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from app.gpt.gpt_factory import GPTFactory
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from app.gpt.provider.OpenAI_compatible_provider import OpenAICompatibleProvider
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from app.models.model_config import ModelConfig
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from app.services.provider import ProviderService
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from app.utils.logger import get_logger
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logger=get_logger(__name__)
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class ModelService:
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@staticmethod
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def _build_model_config(provider: dict) -> ModelConfig:
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return ModelConfig(
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api_key=provider["api_key"],
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base_url=provider["base_url"],
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provider=provider["name"],
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model_name='',
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name=provider["name"],
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)
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@staticmethod
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def get_model_list(provider_id: int, verbose: bool = False):
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provider = ProviderService.get_provider_by_id(provider_id)
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if not provider:
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return []
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try:
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config = ModelService._build_model_config(provider)
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gpt = GPTFactory().from_config(config)
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models = gpt.list_models()
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if verbose:
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print(f"[{provider['name']}] 模型列表: {models}")
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return models
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except Exception as e:
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print(f"[{provider['name']}] 获取模型失败: {e}")
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return []
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@staticmethod
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def get_all_models(verbose: bool = False):
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try:
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raw_models = get_all_models()
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if verbose:
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print(f"所有模型列表: {raw_models}")
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return ModelService._format_models(raw_models)
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except Exception as e:
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print(f"获取所有模型失败: {e}")
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return []
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@staticmethod
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def get_all_models_safe(verbose: bool = False):
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try:
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raw_models = get_all_models()
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if verbose:
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print(f"所有模型列表: {raw_models}")
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return ModelService._format_models(raw_models)
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except Exception as e:
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print(f"获取所有模型失败: {e}")
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return []
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@staticmethod
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def _format_models(raw_models: list) -> list:
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"""
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格式化模型列表
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"""
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formatted = []
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for model in raw_models:
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formatted.append({
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"id": model.get("id"),
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"provider_id": model.get("provider_id"),
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"model_name": model.get("model_name"),
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"created_at": model.get("created_at", None), # 如果有created_at字段
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})
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return formatted
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@staticmethod
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def get_enabled_models_by_provider( provider_id: str|int,):
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from app.db.model_dao import get_models_by_provider
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all_models = get_models_by_provider(provider_id)
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enabled_models = all_models
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return enabled_models
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@staticmethod
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def get_all_models_by_id(provider_id: str, verbose: bool = False):
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try:
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provider = ProviderService.get_provider_by_id(provider_id)
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models = ModelService.get_model_list(provider["id"], verbose=verbose)
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print(type(models))
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serializable_models = [m.dict() for m in models.data]
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model_list = {
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"models": serializable_models
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}
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logger.info(f"[{provider['name']}] 获取模型成功")
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return model_list
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except Exception as e:
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# print(f"[{provider_id}] 获取模型失败: {e}")
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logger.error(f"[{provider_id}] 获取模型失败: {e}")
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return []
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@staticmethod
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def connect_test(id: str, model: str | None = None) -> bool:
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"""连通性测试:发一条最小化 chat completion。
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model 优先级:
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1. 调用方显式传入(前端可在「模型选择」UI 里挑一个再测)
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2. DB 中该 provider 已保存的第一个模型
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3. 都没有 → 抛错让用户先加一个模型
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"""
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provider = ProviderService.get_provider_by_id(id)
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if not provider:
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raise ProviderError(
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code=ProviderErrorEnum.NOT_FOUND.code,
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message=ProviderErrorEnum.NOT_FOUND.message,
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)
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if not provider.get('api_key'):
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raise ProviderError(
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code=ProviderErrorEnum.NOT_FOUND.code,
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message=ProviderErrorEnum.NOT_FOUND.message,
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)
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if not model:
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saved_models = ModelService.get_enabled_models_by_provider(provider["id"])
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if not saved_models:
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raise ProviderError(
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code=ProviderErrorEnum.WRONG_PARAMETER.code,
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message="请先为该供应商添加至少一个模型再测试连通性",
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)
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model = saved_models[0]["model_name"]
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ok = OpenAICompatibleProvider.test_connection(
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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=model,
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)
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if ok:
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return True
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raise ProviderError(
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code=ProviderErrorEnum.WRONG_PARAMETER.code,
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message=ProviderErrorEnum.WRONG_PARAMETER.message,
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)
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@staticmethod
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def delete_model_by_id( model_id: int) -> bool:
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try:
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delete_model(model_id)
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return True
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except Exception as e:
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print(f"[{model_id}] <UNK>: {e}")
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return False
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@staticmethod
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def add_new_model(provider_id: int, model_name: str) -> bool:
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try:
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# 先查供应商是否存在
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provider = ProviderService.get_provider_by_id(provider_id)
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if not provider:
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print(f"供应商ID {provider_id} 不存在,无法添加模型")
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return False
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# 查询是否已存在同名模型
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existing = get_model_by_provider_and_name(provider_id, model_name)
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if existing:
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print(f"模型 {model_name} 已存在于供应商ID {provider_id} 下,跳过插入")
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return False
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# 插入模型
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insert_model(provider_id=provider_id, model_name=model_name)
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print(f"模型 {model_name} 已成功添加到供应商ID {provider_id}")
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return True
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except Exception as e:
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print(f"添加模型失败: {e}")
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return False
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if __name__ == '__main__':
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# 单个 Provider 测试
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print(ModelService.get_model_list(1, verbose=True))
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# 所有 Provider 模型测试
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# print(ModelService.get_all_models(verbose=True))
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