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oliver
dbbe3add6a
同时收敛启动与运维脚本默认行为（含 wiki worker）、更新 Admin 可观测性与相关测试，降低首轮时延并提高运行稳定性。 Made-with: Cursor
141 lines
4 KiB
Python
141 lines
4 KiB
Python
from __future__ import annotations
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from dataclasses import dataclass
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import json
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from typing import Any
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from oclaw.runtime.agent_context import build_role_system_context
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from oclaw.runtime.workspaces.experts import discover_specialist_ids_from_workspaces
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SpecialistId = str
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AgentRoleId = str
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MANAGER_AGENT_ID: AgentRoleId = "manager"
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AGENT_PROFILE_BINDINGS_KEY = "agent_profile_bindings"
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@dataclass(frozen=True)
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class SpecialistConfig:
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specialist_id: SpecialistId
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expert_name: str
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default_tool_tags: frozenset[str] | None
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SPECIALISTS: dict[SpecialistId, SpecialistConfig] = {
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"ops": SpecialistConfig(
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specialist_id="ops",
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expert_name="network_ops",
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default_tool_tags=None,
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),
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"generalist": SpecialistConfig(
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specialist_id="generalist",
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expert_name="generalist+workspace+productivity",
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default_tool_tags=None,
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),
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"image": SpecialistConfig(
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specialist_id="image",
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# image specialist currently reuses generalist expert tool registry,
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# including image_edit tool.
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expert_name="generalist",
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default_tool_tags=None,
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),
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"memory": SpecialistConfig(
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specialist_id="memory",
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expert_name="memory",
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default_tool_tags=None,
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),
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}
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def discover_specialist_ids() -> tuple[SpecialistId, ...]:
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return discover_specialist_ids_from_workspaces(base_order=("generalist", "ops", "image", "memory"))
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SPECIALIST_IDS: tuple[SpecialistId, ...] = discover_specialist_ids()
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AGENT_ROLE_IDS: tuple[AgentRoleId, ...] = (MANAGER_AGENT_ID, *SPECIALIST_IDS)
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def expert_name_for_specialist(specialist_id: SpecialistId) -> str:
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sid = normalize_specialist_id(specialist_id)
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cfg = SPECIALISTS.get(sid) or SPECIALISTS["generalist"]
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return cfg.expert_name
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def default_tool_tags_for_specialist(specialist_id: SpecialistId) -> frozenset[str] | None:
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sid = normalize_specialist_id(specialist_id)
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cfg = SPECIALISTS.get(sid) or SPECIALISTS["generalist"]
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return cfg.default_tool_tags
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def default_system_prefix_for_specialist(specialist_id: SpecialistId, lang: str = "zh") -> str:
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sid = normalize_specialist_id(specialist_id)
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_ = (lang or "zh").strip().lower()
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return build_role_system_context(sid)
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def model_role_for_specialist(specialist_id: SpecialistId) -> AgentRoleId:
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sid = normalize_specialist_id(specialist_id)
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if sid in SPECIALIST_IDS:
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return sid
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return "generalist"
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def normalize_specialist_id(specialist_id: SpecialistId | None) -> SpecialistId:
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sid = (specialist_id or "").strip().lower()
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if sid in SPECIALISTS:
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return sid
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if sid in discover_specialist_ids():
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return sid
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return "generalist"
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def empty_agent_profile_bindings() -> dict[AgentRoleId, str]:
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return {rid: "" for rid in AGENT_ROLE_IDS}
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def parse_agent_profile_bindings(raw: str | None) -> dict[AgentRoleId, str]:
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out = empty_agent_profile_bindings()
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text = (raw or "").strip()
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if not text:
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return out
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try:
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obj = json.loads(text)
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except Exception:
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return out
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if not isinstance(obj, dict):
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return out
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for rid in AGENT_ROLE_IDS:
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v = obj.get(rid)
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if v is None:
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continue
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s = str(v).strip()
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out[rid] = s
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return out
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def dump_agent_profile_bindings(bindings: dict[AgentRoleId, Any]) -> str:
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raw = {}
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for rid in AGENT_ROLE_IDS:
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v = bindings.get(rid) if isinstance(bindings, dict) else None
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raw[rid] = str(v).strip() if v is not None else ""
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return json.dumps(raw, ensure_ascii=False)
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__all__ = [
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"AGENT_PROFILE_BINDINGS_KEY",
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"AGENT_ROLE_IDS",
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"AgentRoleId",
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"dump_agent_profile_bindings",
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"empty_agent_profile_bindings",
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"MANAGER_AGENT_ID",
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"SpecialistConfig",
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"SpecialistId",
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"SPECIALISTS",
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"SPECIALIST_IDS",
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"default_system_prefix_for_specialist",
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"default_tool_tags_for_specialist",
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"discover_specialist_ids",
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"expert_name_for_specialist",
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"model_role_for_specialist",
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"normalize_specialist_id",
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"parse_agent_profile_bindings",
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]
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