66 lines
2.8 KiB
Python
66 lines
2.8 KiB
Python
"""🤖 Agent Core — role registry.
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Cowork Local runs one engine per surface (Cowork tab, Schedule Task,
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GraphRAG codebase-memory chat) rather than a hand-off pipeline between
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separate agent processes. This registry gives each already-existing
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behavior one of the reference role names, purely so audit-log entries
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and the Monitoring Dashboard can group activity by role — it introduces
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no new orchestration logic.
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PLANNER — the ``update_plan`` tool call inside ``chat_agent.run_cowork``'s
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loop.
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REASONING — the model's streamed ``on_reasoning`` output (chat_agent /
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code_agent). Deliberately NOT written to the audit log (that
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would be one entry per streamed token) — the Monitoring
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Dashboard's Agent Status panel instead reads live AgentWorker
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state, which already reflects a run in progress.
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CODE — ``code_agent.run_code``'s tool-execution loop.
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KNOWLEDGE — GraphRAG's codebase-memory "Ask" (``_ask`` in
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``structure_graph_view.py``).
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TASK — Schedule Task's unattended ``_run_agent`` loop.
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COWORK — the Cowork tab's own interactive tool-use loop — the same
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engine TASK's ``cowork``-type tasks run, but ``run_cowork``'s
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default role when no override is given.
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"""
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from __future__ import annotations
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from typing import Dict, NamedTuple
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PLANNER = "planner"
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REASONING = "reasoning"
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CODE = "code"
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KNOWLEDGE = "knowledge"
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TASK = "task"
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COWORK = "cowork"
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SECURITY = "security"
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HELP = "help"
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class AgentRole(NamedTuple):
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key: str
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label: str
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description: str
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ROLES: Dict[str, AgentRole] = {
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PLANNER: AgentRole(PLANNER, "Planner Agent", "Builds/updates the step plan (update_plan)."),
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REASONING: AgentRole(REASONING, "Reasoning Agent", "The model's streamed reasoning output."),
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CODE: AgentRole(CODE, "Code Agent", "Sandboxed run_code tool-execution loop."),
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KNOWLEDGE: AgentRole(KNOWLEDGE, "Knowledge Agent", "GraphRAG codebase-memory Ask / feature management."),
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TASK: AgentRole(TASK, "Task Agent", "Schedule Task's unattended run."),
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COWORK: AgentRole(COWORK, "Cowork Agent", "The Cowork tab's interactive tool-use loop."),
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SECURITY: AgentRole(SECURITY, "Security Agent",
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"System-management agent: Agent Security's prompt/attachment/command "
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"validation (core/agent_security.py). Runs inline on the active turn's "
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"provider before a request/command is allowed."),
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HELP: AgentRole(HELP, "Help Agent",
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"The floating in-app assistant (ui/help_agent_widget.py): answers "
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"how-to-use-the-app questions only, no tools, replies in the user's "
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"own language."),
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}
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def label_for(role_key: str) -> str:
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role = ROLES.get(role_key)
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return role.label if role else (role_key or "—")
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