Hundao
589c5b06fe
- Auto-fixed 70 lint errors (import sorting, aliased errors, datetime.UTC)
- Fixed 85 remaining errors manually:
- E501: wrapped long lines in queen_profiles, catalog, routes_credentials
- F821: added missing TYPE_CHECKING imports for AgentHost, ToolRegistry,
HookContext, HookResult; added runtime imports where needed
- F811: removed duplicate method definitions in queen_lifecycle_tools
- F841/B007: removed unused variables in discovery.py
- W291: removed trailing whitespace in queen nodes
- E402: moved import to top of queen_memory_v2.py
- Fixed AgentRuntime -> AgentHost in example template type annotations
- Reformatted 343 files with ruff format
99 lines
3.4 KiB
Python
99 lines
3.4 KiB
Python
"""Prompt composition for agent loops.
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Builds canonical system prompts from AgentContext fields.
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Extracted from the former orchestrator/prompting module.
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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from datetime import datetime
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from typing import Any
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@dataclass(frozen=True)
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class PromptSpec:
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identity_prompt: str = ""
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focus_prompt: str = ""
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narrative: str = ""
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accounts_prompt: str = ""
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skills_catalog_prompt: str = ""
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protocols_prompt: str = ""
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memory_prompt: str = ""
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agent_type: str = "event_loop"
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output_keys: tuple[str, ...] = ()
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def stamp_prompt_datetime(prompt: str) -> str:
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local = datetime.now().astimezone()
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stamp = f"Current date and time: {local.strftime('%Y-%m-%d %H:%M %Z (UTC%z)')}"
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return f"{prompt}\n\n{stamp}" if prompt else stamp
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def build_prompt_spec(
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ctx: Any,
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*,
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focus_prompt: str | None = None,
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narrative: str | None = None,
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memory_prompt: str | None = None,
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) -> PromptSpec:
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from framework.skills.tool_gating import augment_catalog_for_tools
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resolved_memory = memory_prompt
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if resolved_memory is None:
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resolved_memory = getattr(ctx, "memory_prompt", "") or ""
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dynamic = getattr(ctx, "dynamic_memory_provider", None)
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if dynamic is not None:
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try:
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resolved_memory = dynamic() or ""
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except Exception:
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resolved_memory = getattr(ctx, "memory_prompt", "") or ""
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# Tool-gated pre-activation: inject full body of default skills whose
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# trigger tools are present in this agent's tool list (e.g. browser_*
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# pulls in hive.browser-automation). Keeps non-browser agents lean.
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tool_names = [getattr(t, "name", "") for t in (getattr(ctx, "available_tools", None) or [])]
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skills_catalog_prompt = augment_catalog_for_tools(ctx.skills_catalog_prompt or "", tool_names)
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return PromptSpec(
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identity_prompt=ctx.identity_prompt or "",
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focus_prompt=focus_prompt if focus_prompt is not None else (ctx.agent_spec.system_prompt or ""),
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narrative=narrative if narrative is not None else (ctx.narrative or ""),
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accounts_prompt=ctx.accounts_prompt or "",
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skills_catalog_prompt=skills_catalog_prompt,
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protocols_prompt=ctx.protocols_prompt or "",
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memory_prompt=resolved_memory,
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agent_type=ctx.agent_spec.agent_type,
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output_keys=tuple(ctx.agent_spec.output_keys or ()),
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)
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def build_system_prompt(spec: PromptSpec) -> str:
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parts: list[str] = []
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if spec.identity_prompt:
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parts.append(spec.identity_prompt)
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if spec.accounts_prompt:
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parts.append(f"\n{spec.accounts_prompt}")
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if spec.skills_catalog_prompt:
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parts.append(f"\n{spec.skills_catalog_prompt}")
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if spec.protocols_prompt:
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parts.append(f"\n{spec.protocols_prompt}")
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if spec.memory_prompt:
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parts.append(f"\n{spec.memory_prompt}")
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if spec.focus_prompt:
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parts.append(f"\n{spec.focus_prompt}")
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if spec.narrative:
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parts.append(f"\n{spec.narrative}")
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return "\n".join(parts)
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def build_system_prompt_for_context(
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ctx: Any,
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*,
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focus_prompt: str | None = None,
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narrative: str | None = None,
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memory_prompt: str | None = None,
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) -> str:
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spec = build_prompt_spec(ctx, focus_prompt=focus_prompt, narrative=narrative, memory_prompt=memory_prompt)
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return build_system_prompt(spec)
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