skills/INTEGRATION_GUIDE.md
本文档说明如何将 SKILL 机制集成到现有的 DB-GPT agent 中。
在需要使用 SKILL 的文件中添加导入：
from dbgpt.agent.skill import (
Skill,
SkillBuilder,
SkillLoader,
SkillManager,
SkillType,
get_skill_manager,
initialize_skill,
)
在你的 Agent 类中添加 Skill 支持：
from dbgpt.agent.expand.tool_assistant_agent import ToolAssistantAgent
from dbgpt.agent.skill import Skill
class SkillEnabledAgent(ToolAssistantAgent):
def __init__(self, skill: Optional[Skill] = None, **kwargs):
super().__init__(**kwargs)
self._skill = skill
if self._skill:
self._apply_skill_to_profile()
@property
def skill(self) -> Optional[Skill]:
return self._skill
def _apply_skill_to_profile(self):
"""应用 Skill 配置到 Agent profile。"""
if self.skill.prompt_template:
self.bind_prompt = self.skill.prompt_template
if self.profile:
self.profile.goal = self.skill.metadata.description
async def load_resource(self, question: str, is_retry_chat: bool = False):
"""加载 Skill 所需的资源。"""
if self.skill:
await self._load_skill_resources()
return await super().load_resource(question, is_retry_chat)
async def _load_skill_resources(self):
"""加载 Skill 所需的工具和知识。"""
if not self.resource:
return
# 检查必需的工具
if self.skill.required_tools:
available_tools = self.resource.get_resource_by_type("tool")
available_tool_names = [t.name for t in available_tools]
for required_tool in self.skill.required_tools:
if required_tool not in available_tool_names:
raise ValueError(
f"Required tool '{required_tool}' not found. "
f"Available tools: {available_tool_names}"
)
# 检查必需的知识库
if self.skill.required_knowledge:
available_knowledge = self.resource.get_resource_by_type("knowledge")
available_knowledge_names = [k.name for k in available_knowledge]
for required_knowledge in self.skill.required_knowledge:
if required_knowledge not in available_knowledge_names:
raise ValueError(
f"Required knowledge '{required_knowledge}' not found. "
f"Available knowledge: {available_knowledge_names}"
)
在应用启动时初始化 Skill Manager：
from dbgpt.component import SystemApp
def initialize_app():
system_app = SystemApp()
initialize_skill(system_app)
return system_app
from dbgpt.agent.skill import get_skill_manager
def register_my_skills(system_app):
skill_manager = get_skill_manager(system_app)
# 创建并注册 Skill
skill = (
SkillBuilder(name="my_skill", description="My skill description")
.with_skill_type(SkillType.Chat)
.with_prompt_template("You are a helpful assistant.")
.build()
)
skill_manager.register_skill(
skill_instance=skill,
name="my_skill",
)
from dbgpt.agent import AgentContext, LLMConfig, AgentMemory
async def create_agent_with_skill():
# 获取 Skill
skill_manager = get_skill_manager()
skill = skill_manager.get_skill(name="my_skill")
# 创建 Agent
agent = SkillEnabledAgent(skill=skill)
# 绑定配置
context = AgentContext(conv_id="test_conv")
llm_config = LLMConfig()
memory = AgentMemory()
await agent.bind(context).bind(llm_config).bind(memory).build()
return agent
原始文件：packages/dbgpt-serve/src/dbgpt_serve/agent/agents/expand/intent_recognition_agent.py
import logging
from dbgpt.agent import ConversableAgent, get_agent_manager
from dbgpt.agent.core.profile import DynConfig, ProfileConfig
from dbgpt.agent.skill import Skill
from dbgpt_serve.agent.agents.expand.actions.intent_recognition_action import (
IntentRecognitionAction,
)
class IntentRecognitionAgent(ConversableAgent):
profile: ProfileConfig = ProfileConfig(...)
def __init__(self, skill: Optional[Skill] = None, **kwargs):
super().__init__(**kwargs)
self._skill = skill
self._init_actions([IntentRecognitionAction])
if self._skill:
self._apply_skill_to_profile()
@property
def skill(self) -> Optional[Skill]:
return self._skill
def _apply_skill_to_profile(self):
if self.skill and self.skill.prompt_template:
self.bind_prompt = self.skill.prompt_template
agent_manage = get_agent_manager()
agent_manage.register_agent(IntentRecognitionAgent)
{
"metadata": {
"name": "intent_recognition",
"description": "Intent recognition skill for user queries",
"version": "1.0.0",
"author": "DB-GPT Team",
"skill_type": "custom",
"tags": ["intent", "recognition", "nlp"]
},
"prompt_template": "You are an intent recognition expert. Analyze user queries and identify their intents.",
"required_tools": [],
"required_knowledge": [],
"config": {
"max_intents": 10,
"enable_slot_filling": true
}
}
from dbgpt.agent.skill import Skill, SkillMetadata, SkillType
from dbgpt.core import PromptTemplate
class IntentRecognitionSkill(Skill):
def __init__(self):
metadata = SkillMetadata(
name="intent_recognition",
description="Intent recognition skill",
version="1.0.0",
skill_type=SkillType.Custom,
tags=["intent", "recognition"],
)
prompt = PromptTemplate.from_template(
"You are an intent recognition expert."
)
super().__init__(
metadata=metadata,
prompt_template=prompt,
config={"max_intents": 10},
)
import pytest
from dbgpt.agent.skill import SkillBuilder, SkillType
def test_skill_integration():
# 创建 Skill
skill = (
SkillBuilder(name="test_skill", description="Test skill")
.build()
)
# 创建 Agent
agent = SkillEnabledAgent(skill=skill)
# 验证
assert agent.skill is not None
assert agent.skill.metadata.name == "test_skill"
A: 在 Agent 中添加 switch_skill 方法：
def switch_skill(self, skill: Skill):
self._skill = skill
self._apply_skill_to_profile()
A: 可以，使用 with_required_tool 多次添加：
skill = (
SkillBuilder(name="multi_tool", description="Multi tool skill")
.with_required_tool("tool1")
.with_required_tool("tool2")
.with_required_tool("tool3")
.build()
)
A: 使用 SkillLoader：
from dbgpt.agent.skill import SkillLoader
loader = SkillLoader()
skill = loader.load_skill_from_file("path/to/skill.json")