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A microkernel-style agent framework

Project description

psi-agent

English

用 Python socket 拼装 AI agent 的微框架。

你只需要写 Python 函数和 Markdown——剩下的 socket 通信、tool calling、SSE 流式、定时任务框架全替你做了。

为什么选它

  • 简单组合:ai、session、channel 三个独立进程,socket 对插即用。没有中心配置,不依赖数据库
  • Workspace 即 Agent:在 workspace/ 下丢几个 Python 函数就是 tools,写个 system prompt 就是 agent 人格,加个 cron 就是定时任务
  • 流式交互:REPL 实时显示 AI 思考过程(dim 样式)和最终回复,所见即所得

架构

用户 ←→ Channel (REPL/CLI) ──Unix socket── Session ──Unix socket── AI (OpenAI/Anthropic)

快速开始

需要 Python >= 3.14

三个终端,三步跑起来:

# 安装
uv sync

# 终端 1:启动 AI 后端(--api-key 可选,不传则读 PSI_AI_API_KEY 环境变量)
uv run psi-agent ai \
  --provider openai \
  --session-socket ./ai.sock \
  --model gpt-4o-mini \
  --api-key $OPENAI_API_KEY \
  --base-url https://api.openai.com/v1

# 终端 2:启动 Session
uv run psi-agent session \
  --workspace ./examples/a-simple-bash-only-workspace \
  --channel-socket ./channel.sock \
  --ai-socket ./ai.sock

# 终端 3:REPL 交互
uv run psi-agent channel repl --session-socket ./channel.sock

REPL 操作:Enter 换行,Alt+Enter 发送,Ctrl+D 退出。

也可以一句命令搞定:

uv run psi-agent channel cli \
  --session-socket ./channel.sock \
  --message "列出当前目录的文件"

CLI 一览

psi-agent
├── ai                        # 统一 AI 后端(支持 50+ provider)
├── session                    # Session + workspace 管理
└── channel
    ├── repl                   # 交互式 REPL
    └── cli                    # 单次消息

定义你自己的 Agent

一个 workspace 就是一个 agent:

my-workspace/
├── tools/                    # 每个 .py 文件定义一个 tool
│   └── bash.py               # async def bash(command: str) -> str
├── skills/                   # */SKILL.md 技能文档(system_prompt_builder 自行遍历)
├── schedules/                # 定时任务
│   └── daily-report/
│       └── TASK.md           # YAML 头 (name, cron) + Markdown body
└── systems/
    └── system.py             # async def system_prompt_builder() -> str

Tool 就是一个 async 函数,函数名 = 文件名,参数类型自动映射为 JSON Schema:

# tools/bash.py
import anyio

async def bash(command: str) -> str:
    """Execute a bash command.
    Args:
        command: The command to run.
    """
    result = await anyio.run_process(["/bin/bash", "-c", command])
    return result.stdout.decode().strip()

定时任务的 body 会在 cron 触发时作为消息发送给 AI:

---
name: daily-report
cron: "0 12 * * *"
---
请生成一份项目进展日报。

更多细节见 examples/a-simple-bash-only-workspace/

开发

uv run ruff check .          # lint
uv run ruff format --check . # 格式
uv run ty check              # 类型
uv run pytest -v             # 测试

作者

Hao Zhang hzhangxyz@outlook.com

许可

MIT License. 详见 LICENSE

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