Huixin615 65afc9b1d2
fix(skills): apply allowed-tools only to active skills (#4098)
* 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
2026-07-16 14:12:02 +08:00

382 lines
17 KiB
Python

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