Superpowers：超能力 AI Agent 框架 2026 版

pip install superpowers

from superpowers import Agent

agent = Agent(
    name="知识助手",
    role="研究员",
    goals=["找资料", "总结", "提问"]
)

from superpowers.skill import Skill

class WebSearchSkill(Skill):
    name = "web_search"
    description = "搜索互联网信息"
    
    async def execute(self, query: str) -> dict:
        return await search_engine.search(query)

from superpowers.plugin import Plugin

class CalculatorPlugin(Plugin):
    name = "calculator"
    skills = [ArithmeticSkill, MathSkill]

agent = Agent.from_config("agent.yaml")

# agent.yaml
skills:
  - name: web_search
    source: superpowers.skills.web
  - name: calculator
    source: local_plugins.calculator
  - name: memory
    source: superpowers.skills.memory

result = agent.run("查询 AI 近三年发展趋势")
# Agent 自动调用 web_search, memory 等技能

# 当前对话上下文
agent.memory.short_term.add({
    "question": "解释 AI 的定义",
    "answer": "..."
})

# 持久化存储
agent.memory.long_term.store(
    user_id="user_123",
    knowledge="喜欢使用 GPT 模型"
)

result = agent.run("描述这张图片的情绪")
# 通过 VisionSkill 分析图像

result = agent.run("摘要这份 PDF 报告")
# 通过 PDFReaderSkill 解析

from superpowers.planner import Planner

planner = Planner()
plan = planner.create_plan("构建一个博客系统")
# 自动分解：前端 → 后端 → 数据库 → 部署

tasks = [
    agent.run("分析用户数据"),
    agent.run("生成报告"),
    agent.run("更新仪表盘")
]
results = await asyncio.gather(*tasks)

from superpowers.cache import Cache

cache = Cache(ttl=3600)
result = cache.get(key) or agent.run(query)
cache.set(key, result)

# 多个 Skill 并行执行
skills = [search_skill, calc_skill, recall_skill]
results = await asyncio.gather(*[s.run(data) for s in skills])

from langchain.agents import Tool
from superpowers import SkillRegistry

registry = SkillRegistry()
tools = [
    Tool(
        name=skill.name,
        func=skill.run,
        description=skill.description
    )
    for skill in registry.get_all()
]

from superpowers.backends import VLLMBackend

backend = VLLMBackend(model="llama3:8b")
agent.llm_backend = backend