Files
deer-flow/backend/packages/harness/deerflow/config/skills_config.py
T
greatmengqi edf345cd72 refactor(config): eliminate global mutable state, wire DeerFlowContext into runtime
- Freeze all config models (AppConfig + 15 sub-configs) with frozen=True
- Purify from_file() — remove 9 load_*_from_dict() side-effect calls
- Replace mtime/reload/push/pop machinery with single ContextVar + init_app_config()
- Delete 10 sub-module globals and their getters/setters/loaders
- Migrate 50+ consumers from get_*_config() to get_app_config().xxx

- Expand DeerFlowContext: app_config + thread_id + agent_name (frozen dataclass)
- Wire into Gateway runtime (worker.py) and DeerFlowClient via context= parameter
- Remove sandbox_id from runtime.context — flows through ThreadState.sandbox only
- Middleware/tools access runtime.context directly via Runtime[DeerFlowContext] generic
- resolve_context() retained at server entry points for LangGraph Server fallback
2026-04-14 01:18:19 +08:00

57 lines
1.8 KiB
Python

from pathlib import Path
from pydantic import BaseModel, ConfigDict, Field
def _default_repo_root() -> Path:
"""Resolve the repo root without relying on the current working directory."""
return Path(__file__).resolve().parents[5]
class SkillsConfig(BaseModel):
"""Configuration for skills system"""
model_config = ConfigDict(frozen=True)
path: str | None = Field(
default=None,
description="Path to skills directory. If not specified, defaults to ../skills relative to backend directory",
)
container_path: str = Field(
default="/mnt/skills",
description="Path where skills are mounted in the sandbox container",
)
def get_skills_path(self) -> Path:
"""
Get the resolved skills directory path.
Returns:
Path to the skills directory
"""
if self.path:
# Use configured path (can be absolute or relative)
path = Path(self.path)
if not path.is_absolute():
# If relative, resolve from the repo root for deterministic behavior.
path = _default_repo_root() / path
return path.resolve()
else:
# Default: ../skills relative to backend directory
from deerflow.skills.loader import get_skills_root_path
return get_skills_root_path()
def get_skill_container_path(self, skill_name: str, category: str = "public") -> str:
"""
Get the full container path for a specific skill.
Args:
skill_name: Name of the skill (directory name)
category: Category of the skill (public or custom)
Returns:
Full path to the skill in the container
"""
return f"{self.container_path}/{category}/{skill_name}"