mirror of
https://github.com/jxxghp/MoviePilot.git
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132 lines
4.9 KiB
Python
132 lines
4.9 KiB
Python
"""Agent 编排服务门面。
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chain 层需要触发 Agent 后台任务、渲染提示词、查询模型能力时统一经本模块调用。
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具体实现由 startup 组合根注册，形成依赖倒置：
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chain -> application.agent <- startup -> agent
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门面保存 provider 而非重量级实现对象，注册本身不会物化 Agent、LLM 或工具树。
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本模块禁止静态或函数内导入 app.agent，否则会重新形成跨层循环依赖。
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"""
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from typing import Any, Callable, Optional
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Provider = Callable[[], Any]
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# provider 注册表由 startup/initializers/agent.py 在组合根装配。
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_agent_manager_provider: Optional[Provider] = None
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_running_agent_manager_provider: Optional[Provider] = None
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_prompt_manager_provider: Optional[Provider] = None
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_agent_capability_manager_provider: Optional[Provider] = None
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_llm_helper_provider: Optional[Provider] = None
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_manual_redo_prompt_builder_provider: Optional[Provider] = None
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def register_agent_service_providers(
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*,
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agent_manager_provider: Provider,
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running_agent_manager_provider: Provider,
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prompt_manager_provider: Provider,
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capability_manager_provider: Provider,
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llm_helper_provider: Provider,
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manual_redo_prompt_builder_provider: Provider,
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) -> None:
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"""注册 Agent 服务 provider，保持组合根装配阶段零重量实现导入。"""
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global _agent_manager_provider, _running_agent_manager_provider
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global _prompt_manager_provider, _agent_capability_manager_provider
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global _llm_helper_provider, _manual_redo_prompt_builder_provider
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_agent_manager_provider = agent_manager_provider
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_running_agent_manager_provider = running_agent_manager_provider
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_prompt_manager_provider = prompt_manager_provider
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_agent_capability_manager_provider = capability_manager_provider
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_llm_helper_provider = llm_helper_provider
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_manual_redo_prompt_builder_provider = manual_redo_prompt_builder_provider
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def register_agent_services(
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agent_manager: Any,
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prompt_manager: Any,
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capability_manager: Any,
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llm_helper: Any,
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manual_redo_prompt_builder: Optional[Callable[[Any], str]] = None,
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) -> None:
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"""兼容直接对象注入；生产组合根应注册惰性 provider。"""
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register_agent_service_providers(
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agent_manager_provider=lambda: agent_manager,
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running_agent_manager_provider=lambda: agent_manager,
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prompt_manager_provider=lambda: prompt_manager,
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capability_manager_provider=lambda: capability_manager,
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llm_helper_provider=lambda: llm_helper,
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manual_redo_prompt_builder_provider=lambda: manual_redo_prompt_builder,
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)
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def _resolve(provider: Optional[Provider], service_name: str) -> Any:
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"""解析已注册服务；缺少组合根装配时给出稳定错误。"""
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if provider is None:
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raise RuntimeError(
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f"Agent 服务 {service_name} 未注册："
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"请先导入 app.startup.initializers.agent 完成组合根装配"
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)
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return provider()
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def get_agent_manager() -> Any:
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"""返回 canonical AgentManager；调用可能触发实现物化。"""
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return _resolve(_agent_manager_provider, "agent_manager")
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def get_running_agent_manager() -> Any | None:
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"""返回已进入 RUNNING 的 AgentManager，不触发实现物化。"""
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return _resolve(_running_agent_manager_provider, "running_agent_manager")
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def get_prompt_manager() -> Any:
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"""按需返回提示词管理器。"""
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return _resolve(_prompt_manager_provider, "prompt_manager")
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def supports_image_input(
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provider: Optional[str] = None,
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model: Optional[str] = None,
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base_url: Optional[str] = None,
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base_url_preset: Optional[str] = None,
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) -> bool:
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"""判断当前模型是否启用了图片输入能力。"""
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llm_helper = _resolve(_llm_helper_provider, "llm_helper")
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return llm_helper.supports_image_input(
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provider=provider,
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model=model,
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base_url=base_url,
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base_url_preset=base_url_preset,
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)
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def is_audio_input_available() -> bool:
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"""判断语音输入能力是否可用。"""
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capability_manager = _resolve(
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_agent_capability_manager_provider,
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"agent_capability_manager",
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)
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return capability_manager.is_audio_input_available()
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def transcribe_audio(content: bytes, filename: str = "input.ogg") -> Optional[str]:
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"""把音频内容转写为文本。"""
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capability_manager = _resolve(
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_agent_capability_manager_provider,
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"agent_capability_manager",
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)
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return capability_manager.transcribe_audio(content, filename=filename)
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def build_manual_redo_prompt(history: Any) -> str:
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"""构造整理记录 AI 重新整理提示词（builder 由 agent 层注册）。"""
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builder = _resolve(
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_manual_redo_prompt_builder_provider,
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"manual_redo_prompt_builder",
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)
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if builder is None:
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raise RuntimeError("整理记录重新整理提示词构建器未注册")
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return builder(history)
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