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* fix(skills): scope allowed-tools to active skills * fix(skills): tolerate stale active skill paths * chore: retrigger CI * fix(skills): document policy activation limits * perf(skills): reuse per-step tool policy decisions * fix(skills): harden runtime tool policy contracts * fix(skills): redact cached policy decisions * fix(skills): make slash tool policy authoritative * fix(skills): preserve policy-safe discovery tools * test(skills): cover explicit task delegation policy
382 lines
17 KiB
Python
382 lines
17 KiB
Python
"""Configuration and loaders for custom agents.
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Custom agents are stored per-user under ``{base_dir}/users/{user_id}/agents/{name}/``.
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A legacy shared layout at ``{base_dir}/agents/{name}/`` is still readable so that
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installations that pre-date user isolation continue to work until they run the
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``scripts/migrate_user_isolation.py`` migration. New writes always target the
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per-user layout.
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"""
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import logging
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import re
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from pathlib import Path
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from typing import Any
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import yaml
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from pydantic import BaseModel, Field, field_validator, model_validator
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from deerflow.config.paths import get_paths
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from deerflow.runtime.user_context import get_effective_user_id
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logger = logging.getLogger(__name__)
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SOUL_FILENAME = "SOUL.md"
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AGENT_NAME_PATTERN = re.compile(r"^[A-Za-z0-9-]+$")
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def _blank_to_none(value: str | None) -> str | None:
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"""Normalize a whitespace-only string to ``None``; leave real values untouched.
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A whitespace-only string (e.g. ``" "``) is truthy in Python, so an
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unstripped ``value or fallback`` expression never falls through to the
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fallback. The ``require_mention`` precedence chain (``trigger.mention_login``
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-> ``github.bot_login`` -> ``channels.github.default_mention_login`` ->
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``agent.name``, see AGENTS.md) relies on exactly that fallthrough, so both
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of the config-sourced links are normalized here, once, at the model layer
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— every reader downstream (today's and any future one) sees an honest
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"unset" instead of a literal whitespace string that can never match a
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real ``@mention``.
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"""
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if value is None:
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return None
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stripped = value.strip()
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return stripped or None
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class GitHubTriggerConfig(BaseModel):
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"""Per-event trigger filter inside a :class:`GitHubBinding`."""
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# If set, only these GitHub action values fire the agent. None means "any
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# action allowed". Example: ["opened"] for pull_request restricts the agent
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# to only respond to brand-new PRs.
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actions: list[str] | None = None
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# If True, comment events only fire when the bot login is @-mentioned in
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# the comment body. Ignored on non-comment events.
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require_mention: bool = False
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# GitHub logins whose events bypass require_mention. Lets a repo owner
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# talk to the bot without typing the handle every time.
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allow_authors: list[str] = Field(default_factory=list)
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# Override the global default bot mention login for this trigger only.
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# Useful when one agent answers as @bot-a and another as @bot-b. A
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# whitespace-only value is normalized to None (see ``_blank_to_none``) so
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# it is treated as unset and falls through to ``github.bot_login`` instead
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# of being compared against literally.
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mention_login: str | None = None
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@field_validator("mention_login")
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@classmethod
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def _normalize_mention_login(cls, value: str | None) -> str | None:
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return _blank_to_none(value)
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class GitHubBinding(BaseModel):
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"""One (agent, repo) binding with per-event trigger overrides."""
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# GitHub "owner/name" string.
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repo: str
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# Event name → trigger override. Missing keys fall back to the dispatcher's
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# default trigger for that event.
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triggers: dict[str, GitHubTriggerConfig] = Field(default_factory=dict)
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class GitHubAgentConfig(BaseModel):
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"""Top-level ``github:`` block on a custom agent's ``config.yaml``."""
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# GitHub App installation id used to mint per-repo access tokens. The
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# ``ChannelManager`` mints a 1h installation token from this and injects it
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# into ``run_context["github_token"]``, which the ``bash`` tool exposes to
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# the agent's sandbox as ``GH_TOKEN`` / ``GITHUB_TOKEN``. The agent then
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# uses ``gh`` to read repo state, push branches, and post comments itself.
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# None means no token is minted: the agent still runs but cannot push or
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# post (effectively read-only via unauthenticated ``gh`` for public repos,
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# or fully blind for private ones).
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installation_id: int | None = None
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# GitHub App login this agent posts as (e.g. ``llm-gateway-ai`` for the
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# ``llm-gateway-ai[bot]`` App identity, without the ``[bot]`` suffix).
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# The dispatcher's self-event gate uses this to recognize webhook
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# deliveries triggered by this agent's own activity, regardless of what
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# ``mention_login`` the agent uses for trigger matching. None means
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# "fall back to mention_login / agent name", which is fine when those
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# match the bot identity, but should be set explicitly when they differ.
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# A whitespace-only value is normalized to None (see ``_blank_to_none``)
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# so it is treated as unset and falls through the rest of the chain.
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bot_login: str | None = None
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# Override the default github-channel ``recursion_limit`` (250). GitHub
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# runs are autonomous and long-running by nature — clone, explore, edit,
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# test, push, comment — but the right ceiling varies a lot by workload:
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# a review-only agent might be happy at 50, a multi-file refactor agent
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# might need 500+. Setting None means "use the channel default (250)".
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# Any positive integer is honored verbatim — including values below the
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# channel default and below the global 100-step floor — so an explicit
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# safety setting like ``recursion_limit: 50`` halts the agent at 50
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# super-steps as configured. Values <=0 are ignored (treated as None)
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# — a negative/zero limit would halt the agent before the first step.
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recursion_limit: int | None = None
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# Repos this agent is bound to. Empty list = bound to nothing = the agent
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# never fires from a webhook, even if it has a ``github:`` block.
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bindings: list[GitHubBinding] = Field(default_factory=list)
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@field_validator("bot_login")
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@classmethod
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def _normalize_bot_login(cls, value: str | None) -> str | None:
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return _blank_to_none(value)
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@model_validator(mode="after")
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def _unique_binding_repos(self) -> "GitHubAgentConfig":
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"""Reject duplicate ``repo`` values across ``bindings``.
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At most one binding per repo is allowed. The per-event ``triggers``
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map on a single binding already expresses "this agent listens to N
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events on this repo", so multiple bindings for the same repo would
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either duplicate events (silent first-wins / double-registration —
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see PR feedback R3) or fragment them across rows for no benefit.
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Since this is the initial implementation and no existing operator
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config relies on duplicate-repo bindings, we fail loudly at config
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load instead of papering over the ambiguity at dispatch time.
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"""
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seen: set[str] = set()
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dupes: set[str] = set()
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for binding in self.bindings:
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if binding.repo in seen:
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dupes.add(binding.repo)
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seen.add(binding.repo)
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if dupes:
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raise ValueError(f"Agent github.bindings has duplicate repos {sorted(dupes)}. Each repo must appear at most once — merge their `triggers:` maps into a single binding.")
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return self
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def validate_agent_name(name: str | None) -> str | None:
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"""Validate a custom agent name before using it in filesystem paths."""
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if name is None:
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return None
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if not isinstance(name, str):
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raise ValueError("Invalid agent name. Expected a string or None.")
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if not AGENT_NAME_PATTERN.fullmatch(name):
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raise ValueError(f"Invalid agent name '{name}'. Must match pattern: {AGENT_NAME_PATTERN.pattern}")
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return name
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class AgentConfig(BaseModel):
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"""Configuration for a custom agent."""
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name: str
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description: str = ""
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model: str | None = None
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tool_groups: list[str] | None = None
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# skills controls which skills are discoverable and may be activated by the
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# agent. It does not activate their allowed-tools policies at construction:
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# - None (or omitted): load all enabled skills (default fallback behavior)
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# - [] (explicit empty list): disable all skills
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# - ["skill1", "skill2"]: load only the specified skills
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skills: list[str] | None = None
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# Optional binding to GitHub repositories so this agent can respond to
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# webhook events from the gateway dispatcher. None means "no GitHub
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# integration", which is the case for every existing agent.
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github: GitHubAgentConfig | None = None
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# Fields explicitly managed by the agent-update surfaces (the
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# ``update_agent`` harness tool and the HTTP ``PATCH /api/agents/{name}``
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# route). Anything else declared on :class:`AgentConfig` — currently
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# ``github``, and any future field — is preserved verbatim by
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# :func:`preserve_non_managed_fields` so neither surface can silently
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# drop hand-authored configuration. ``name`` is included because the
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# updaters always re-emit it from the directory name (it must never come
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# from the request body).
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MANAGED_AGENT_CONFIG_FIELDS: frozenset[str] = frozenset({"name", "description", "model", "tool_groups", "skills"})
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def preserve_non_managed_fields(existing_cfg: AgentConfig) -> dict[str, object]:
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"""Return every top-level field on ``existing_cfg`` not in :data:`MANAGED_AGENT_CONFIG_FIELDS`.
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Used by the two surfaces that rewrite a custom agent's ``config.yaml``
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(the ``update_agent`` harness tool and the HTTP ``PATCH /api/agents/{name}``
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route) to carry forward any hand-authored field — currently ``github``,
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and any field added to :class:`AgentConfig` in the future — that the
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update API does not expose as an argument. Without this, operators who
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hand-author a ``github:`` block on a custom agent would silently lose
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it the next time the agent or a UI editor touched ``description`` /
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``model`` / ``tool_groups`` / ``skills``.
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``exclude_unset=True`` is recursive in Pydantic v2, so a sub-field the
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user did not write (and that defaulted to a Pydantic default) is not
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materialized into the dict — the file round-trips visually intact.
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"""
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return existing_cfg.model_dump(exclude_unset=True, exclude=MANAGED_AGENT_CONFIG_FIELDS)
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def resolve_agent_dir(name: str, *, user_id: str | None = None) -> Path:
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"""Return the on-disk directory for an agent, preferring the per-user layout.
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Resolution order:
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1. ``{base_dir}/users/{user_id}/agents/{name}/`` (per-user, current layout).
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2. ``{base_dir}/agents/{name}/`` (legacy shared layout — read-only fallback).
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If neither exists, the per-user path is returned so callers that intend to
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create the agent write into the new layout.
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Args:
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name: Validated agent name.
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user_id: Owner of the agent. Defaults to the effective user from the
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request context (or ``"default"`` in no-auth mode).
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"""
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paths = get_paths()
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effective_user = user_id or get_effective_user_id()
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user_path = paths.user_agent_dir(effective_user, name)
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# Require config.yaml to confirm this is a genuine agent directory,
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# not a leftover from memory/storage writes (see #3390).
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if user_path.exists() and (user_path / "config.yaml").exists():
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return user_path
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legacy_path = paths.agent_dir(name)
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if legacy_path.exists() and (legacy_path / "config.yaml").exists():
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return legacy_path
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return user_path
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def load_agent_config(name: str | None, *, user_id: str | None = None) -> AgentConfig | None:
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"""Load the custom or default agent's config from its directory.
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Reads from the per-user layout first; falls back to the legacy shared layout
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for installations that have not yet been migrated.
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Args:
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name: The agent name.
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user_id: Owner of the agent. Defaults to the effective user from the
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current request context.
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Returns:
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AgentConfig instance, or ``None`` if ``name`` is ``None``.
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Raises:
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FileNotFoundError: If the agent directory or config.yaml does not exist.
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ValueError: If config.yaml cannot be parsed.
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"""
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if name is None:
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return None
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name = validate_agent_name(name)
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agent_dir = resolve_agent_dir(name, user_id=user_id)
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config_file = agent_dir / "config.yaml"
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if not agent_dir.exists():
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raise FileNotFoundError(f"Agent directory not found: {agent_dir}")
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if not config_file.exists():
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raise FileNotFoundError(f"Agent config not found: {config_file}")
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try:
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with open(config_file, encoding="utf-8") as f:
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data: dict[str, Any] = yaml.safe_load(f) or {}
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except yaml.YAMLError as e:
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raise ValueError(f"Failed to parse agent config {config_file}: {e}") from e
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# Ensure name is set from directory name if not in file
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if "name" not in data:
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data["name"] = name
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# Strip unknown fields before passing to Pydantic (e.g. legacy prompt_file)
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known_fields = set(AgentConfig.model_fields.keys())
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data = {k: v for k, v in data.items() if k in known_fields}
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return AgentConfig(**data)
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def load_agent_soul(agent_name: str | None, *, user_id: str | None = None) -> str | None:
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"""Read the SOUL.md file for a custom agent, if it exists.
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SOUL.md defines the agent's personality, values, and behavioral guardrails.
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It is injected into the lead agent's system prompt as additional context.
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Args:
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agent_name: The name of the agent or None for the default agent.
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user_id: Owner of the agent. Defaults to the effective user from the
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current request context.
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Returns:
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The SOUL.md content as a string, or None if the file does not exist.
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"""
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if agent_name:
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agent_dir = resolve_agent_dir(agent_name, user_id=user_id)
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soul_path = agent_dir / SOUL_FILENAME
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# Fallback: resolve_agent_dir requires config.yaml to be present
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# (see #3390), but SOUL.md loading does not depend on config.yaml.
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# If the resolved dir doesn't have config.yaml (meaning the resolver
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# returned its default path because no agent dir qualified) and also
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# lacks SOUL.md, check the per-user and legacy directories directly
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# so that agents configured via DEER_FLOW_CONFIG_PATH (or any setup
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# where the agent dir has SOUL.md but no config.yaml) can still load
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# their soul (#4135). The config.yaml guard ensures this fallback
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# only fires for dirs the resolver couldn't resolve, not for a
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# properly-resolved per-user agent that simply lacks SOUL.md -
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# preserving the "per-user entries fully shadow legacy entries"
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# invariant (agents_config.py:3-7, list_custom_agents).
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if not soul_path.exists() and not (agent_dir / "config.yaml").exists():
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paths = get_paths()
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effective_user = user_id or get_effective_user_id()
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for candidate in (
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paths.user_agent_dir(effective_user, agent_name),
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paths.agent_dir(agent_name),
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):
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if (candidate / SOUL_FILENAME).exists():
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soul_path = candidate / SOUL_FILENAME
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break
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else:
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agent_dir = get_paths().base_dir
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soul_path = agent_dir / SOUL_FILENAME
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if not soul_path.exists():
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return None
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content = soul_path.read_text(encoding="utf-8").strip()
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return content or None
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def list_custom_agents(*, user_id: str | None = None) -> list[AgentConfig]:
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"""Scan the agents directory and return all valid custom agents.
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Returns the union of agents in the per-user layout and the legacy shared
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layout, so that pre-migration installations remain visible until they are
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migrated. Per-user entries shadow legacy entries with the same name.
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Args:
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user_id: Owner whose agents to list. Defaults to the effective user
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from the current request context.
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Returns:
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List of AgentConfig for each valid agent directory found.
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"""
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paths = get_paths()
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effective_user = user_id or get_effective_user_id()
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seen: set[str] = set()
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agents: list[AgentConfig] = []
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user_root = paths.user_agents_dir(effective_user)
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legacy_root = paths.agents_dir
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for root in (user_root, legacy_root):
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if not root.exists():
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continue
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for entry in sorted(root.iterdir()):
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if not entry.is_dir():
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continue
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if entry.name in seen:
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continue
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config_file = entry / "config.yaml"
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if not config_file.exists():
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logger.debug(f"Skipping {entry.name}: no config.yaml")
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continue
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try:
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agent_cfg = load_agent_config(entry.name, user_id=effective_user)
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if agent_cfg is None:
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continue
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agents.append(agent_cfg)
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seen.add(entry.name)
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except Exception as e:
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logger.warning(f"Skipping agent '{entry.name}': {e}")
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agents.sort(key=lambda a: a.name)
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return agents
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