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50 lines
1.8 KiB
Python
50 lines
1.8 KiB
Python
"""LLM helper 与 provider 实现之间的运行时端口。"""
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from collections.abc import Callable
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from typing import Any, Protocol
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class LLMProviderRuntimePort(Protocol):
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"""声明 LLM helper 所需的最小 provider 运行时能力。"""
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def resolve_cached_model_metadata(self, **kwargs: Any) -> dict[str, Any] | None:
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"""从本地目录缓存解析模型元数据。"""
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...
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async def resolve_runtime(self, **kwargs: Any) -> dict[str, Any]:
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"""解析创建模型客户端所需的统一运行时参数。"""
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...
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def create_bedrock_client(self, *args: Any, **kwargs: Any) -> Any:
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"""创建带统一认证和网络配置的 Bedrock 客户端。"""
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...
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async def list_models(self, **kwargs: Any) -> list[dict[str, Any]]:
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"""返回 provider 可用的模型目录。"""
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...
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def resolve_model_list_base_url(self, **kwargs: Any) -> str | None:
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"""解析兼容接口用于查询模型列表的基础地址。"""
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...
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LLMProviderRuntimeFactory = Callable[[], LLMProviderRuntimePort]
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_provider_runtime_factory: LLMProviderRuntimeFactory | None = None
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def register_llm_provider_runtime(
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factory: LLMProviderRuntimeFactory | None,
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) -> LLMProviderRuntimeFactory | None:
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"""注册 provider 运行时工厂，并返回先前工厂供隔离测试恢复。"""
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global _provider_runtime_factory
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previous = _provider_runtime_factory
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_provider_runtime_factory = factory
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return previous
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def resolve_llm_provider_runtime() -> LLMProviderRuntimePort:
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"""解析已组装的 provider 运行时，未注册时给出明确边界错误。"""
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if _provider_runtime_factory is None:
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raise RuntimeError("LLM provider 运行时尚未由启动层完成组装")
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return _provider_runtime_factory()
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