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https://github.com/willmiao/ComfyUI-Lora-Manager.git
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Introduce an agent skill framework for LLM-driven metadata enrichment: - AgentCLI (py/agent_cli/): in-process wrappers around internal services using standard relative imports, eliminating the need for sys.path hacks - LLMService: centralized BYOK (bring-your-own-key) LLM client supporting OpenAI, Ollama, and custom OpenAI-compatible endpoints - PostProcessor: deterministic engine that applies LLM output via AgentCLI (replaces old handler.py + _BASE_MODEL_ALIASES approach) - SkillRegistry: filesystem-based skill discovery (skill.yaml + prompt.md) - AgentService: orchestrates skill execution with WebSocket progress - Frontend AgentManager: WebSocket listeners, skill execution, config UI - Context menu entries (single + bulk) for "Enrich Metadata (Agent)" - Settings UI for AI Provider configuration (BYOK) - Full i18n support across 9 locales Bug fixes found during review: - aiohttp.web.json_response: status_code= -> status= - settings_modal cancelEditApiKey: wrong argument position - AgentManager.isLlmConfigured: allow Ollama without API key - PostProcessor._merge_tags: lowercase all tags to match TagUpdateService
185 lines
6.7 KiB
Python
185 lines
6.7 KiB
Python
"""Discovery and loading of agent skills.
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Skills live in ``py/services/agent/skills/<name>/`` directories. Each
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directory must contain:
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- ``skill.yaml`` — metadata (name, title, description, schemas, permissions)
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- ``prompt.md`` — LLM system prompt template (Jinja2-style ``{{variable}}`` placeholders)
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- ``handler.py`` — async ``prepare`` and ``post_process`` functions
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The registry scans the skills directory on first access and caches results.
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"""
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from __future__ import annotations
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import asyncio
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import importlib
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import importlib.util
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import logging
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import os
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from pathlib import Path
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from typing import Any, Callable, Dict, List, Optional
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import yaml
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from .skill_definition import SkillDefinition, SkillPermissions
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logger = logging.getLogger(__name__)
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# Directory where built-in skills are stored
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_SKILLS_DIR = Path(__file__).parent / "skills"
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class SkillRegistry:
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"""Discover and load agent skills from the filesystem."""
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_instance: Optional["SkillRegistry"] = None
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_lock: asyncio.Lock = asyncio.Lock()
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def __init__(self, skills_dir: Path = _SKILLS_DIR) -> None:
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self._skills_dir = skills_dir
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self._skills: Dict[str, SkillDefinition] = {}
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self._loaded: bool = False
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# ------------------------------------------------------------------
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# Singleton access
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# ------------------------------------------------------------------
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@classmethod
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async def get_instance(cls) -> "SkillRegistry":
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"""Return the lazily-initialised global ``SkillRegistry``."""
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if cls._instance is None:
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async with cls._lock:
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if cls._instance is None:
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registry = cls()
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registry._discover()
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cls._instance = registry
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return cls._instance
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@classmethod
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def reset_instance(cls) -> None:
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"""Reset the cached singleton — primarily for tests."""
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cls._instance = None
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# ------------------------------------------------------------------
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# Discovery
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# ------------------------------------------------------------------
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def _discover(self) -> None:
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"""Scan the skills directory and load all valid skill definitions."""
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self._skills.clear()
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if not self._skills_dir.is_dir():
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logger.warning("Skills directory does not exist: %s", self._skills_dir)
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self._loaded = True
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return
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for entry in sorted(self._skills_dir.iterdir()):
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if not entry.is_dir():
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continue
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skill_yaml = entry / "skill.yaml"
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if not skill_yaml.exists():
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continue
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try:
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definition = self._load_skill_yaml(skill_yaml)
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if definition is not None:
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self._skills[definition.name] = definition
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logger.debug("Loaded skill: %s", definition.name)
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except Exception as exc:
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logger.warning("Failed to load skill from %s: %s", skill_yaml, exc)
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self._loaded = True
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logger.info("Discovered %d agent skills", len(self._skills))
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def _load_skill_yaml(self, path: Path) -> Optional[SkillDefinition]:
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"""Parse a skill.yaml file into a :class:`SkillDefinition`."""
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with open(path, "r", encoding="utf-8") as f:
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data = yaml.safe_load(f)
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if not data or "name" not in data:
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logger.warning("skill.yaml missing required 'name' field: %s", path)
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return None
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# Parse permissions
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perm_data = data.get("permissions", {})
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permissions = SkillPermissions(
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write_metadata=perm_data.get("write_metadata", True),
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write_previews=perm_data.get("write_previews", True),
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network_domains=tuple(perm_data.get("network_domains", [])),
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)
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return SkillDefinition(
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name=data["name"],
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title=data.get("title", data["name"]),
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description=data.get("description", ""),
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llm_required=data.get("llm_required", False),
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input_schema=data.get("input_schema", {}),
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output_schema=data.get("output_schema", {}),
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model_type_filter=data.get("model_type_filter"),
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permissions=permissions,
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)
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# ------------------------------------------------------------------
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# Public API
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# ------------------------------------------------------------------
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def list_skills(self) -> List[SkillDefinition]:
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"""Return all discovered skill definitions."""
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if not self._loaded:
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self._discover()
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return list(self._skills.values())
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def get_skill(self, name: str) -> Optional[SkillDefinition]:
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"""Return the skill definition for ``name``, or ``None`` if not found."""
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if not self._loaded:
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self._discover()
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return self._skills.get(name)
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def load_prompt(self, name: str) -> str:
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"""Load and return the prompt template for a skill."""
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skill_dir = self._skills_dir / name
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prompt_path = skill_dir / "prompt.md"
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if not prompt_path.exists():
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raise FileNotFoundError(f"Prompt template not found: {prompt_path}")
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with open(prompt_path, "r", encoding="utf-8") as f:
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return f.read()
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def load_handler(self, name: str) -> Dict[str, Callable]:
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"""Dynamically import a skill's handler module and return its functions.
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Returns a dict with ``prepare`` and ``post_process`` callables.
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``prepare`` may be absent (the skill doesn't need pre-LLM data gathering).
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"""
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skill_dir = self._skills_dir / name
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handler_path = skill_dir / "handler.py"
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if not handler_path.exists():
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raise FileNotFoundError(f"Handler not found: {handler_path}")
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# Use importlib to load the module by file path
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# Important: use a fully-qualified module name so that absolute imports
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# (e.g. ``from py.utils.metadata_manager import MetadataManager``) resolve correctly.
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module_name = f"py.services.agent.skills.{name}.handler"
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spec = importlib.util.spec_from_file_location(module_name, handler_path)
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if spec is None or spec.loader is None:
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raise ImportError(f"Cannot load handler module from {handler_path}")
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module = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(module)
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result: Dict[str, Callable] = {}
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if hasattr(module, "prepare"):
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result["prepare"] = module.prepare
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if hasattr(module, "post_process"):
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result["post_process"] = module.post_process
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else:
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raise AttributeError(
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f"Skill handler {name} is missing required 'post_process' function"
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)
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return result
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