Skip to main content

RootEngine AI Agent Framework Core

Project description

RootEngine Core

AI Agent 框架的底层组件库。

这是什么

RootEngine Core 是一个用于构建 Agent 框架的框架。它提供:

  • REIF 格式 - 结构化的 Agent 信息交换格式,统一对话、工具调用、结果的规范
  • 核心组件 - 对话管理、工具系统、LLM 适配器
  • 可组合 - 自由组合这些组件来构建你自己的 Agent

如果你想从零搭建一个 Agent 系统,这是一个不错的起点。如果你想要一个开箱即用的 Agent,可能还不适合你。

安装

pip install rootengine-core

要求:Python >= 3.8

REIF 是什么

REIF(RootEngine Information Format)是一套信息格式规范,定义了 Agent 内部和组件之间如何交换数据:

  • conversation - 对话历史
  • tool_registry - 工具注册表
  • tool_call - 工具调用请求
  • tool_result - 工具执行结果

使用统一格式的好处是:组件之间接口稳定,方便替换和扩展。

快速开始

对话管理

from rootengine_core import BaseConversation

conv = BaseConversation()
conv.append("system", "你是一个有帮助的助手")
conv.append("user", "你好")

print(conv.messages)
# [
#   {"role": "system", "content": "你是一个有帮助的助手", "created_at": "..."},
#   {"role": "user", "content": "你好", "created_at": "..."}
# ]

工具调用

from rootengine_core import Tool
from rootengine_core.utils import create_reif

# 定义一个工具
def greeting(name, agent=None):
    return f"Hello, {name}!"

# 工具注册表(REIF 格式)
registry = create_reif({"category": "tool_registry"})
registry["reif_content"] = {
    "a1b2c3d4e5f6789012345678abcdef01": {
        "name": "greeting",
        "type": "function",
        "function": {
            "name": "greeting",
            "description": "打招呼",
            "parameters": {
                "type": "object",
                "properties": {"name": {"type": "string"}},
                "required": ["name"]
            }
        }
    }
}

# 初始化工具
tool = Tool(
    tool_registry_entry=registry,
    agent=None,
    tool_func_map={"a1b2c3d4e5f6789012345678abcdef01": greeting}
)

# 执行工具调用
result = tool.execute({
    "id": "call_001",
    "type": "function",
    "function": {
        "registry_id": "a1b2c3d4e5f6789012345678abcdef01",
        "arguments": {"name": "Alice"}
    },
    "created_at": "2024-01-01T00:00:00Z"
})

print(result)
# {"call_id": "call_001", "type": "function",
#  "function": {"result_content": "Hello, Alice!", "status": "success"},
#  "created_at": "..."}

LLM 适配器

from rootengine_core import OpenAIAdapter

adapter = OpenAIAdapter(model="gpt-4o-mini")
# adapter.from_provider(llm_response)  # 解析 LLM 返回

状态

这是一个早期项目,核心组件可用,但:

  • 文档还不完整
  • 工具系统示例较少
  • 尚未经过大规模生产验证

模块一览

模块 说明
conversation 对话管理
tool 工具注册与执行
llm LLM 适配器
utils/reif_func REIF 格式创建与验证

其他

  • utils 里有很多好玩的东西

许可证

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

rootengine_core-0.5.8.tar.gz (23.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

rootengine_core-0.5.8-py3-none-any.whl (31.6 kB view details)

Uploaded Python 3

File details

Details for the file rootengine_core-0.5.8.tar.gz.

File metadata

  • Download URL: rootengine_core-0.5.8.tar.gz
  • Upload date:
  • Size: 23.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.4

File hashes

Hashes for rootengine_core-0.5.8.tar.gz
Algorithm Hash digest
SHA256 c2e4e5769551b24274773b063999390379fa0ae71a38f4562674dc2abc296e55
MD5 32adc4f07731974fafb16f5a4310f581
BLAKE2b-256 321b0d32084477155b24bb79ebf31315cff6670180147d83689f4e460d45d251

See more details on using hashes here.

File details

Details for the file rootengine_core-0.5.8-py3-none-any.whl.

File metadata

File hashes

Hashes for rootengine_core-0.5.8-py3-none-any.whl
Algorithm Hash digest
SHA256 9df56c99c8b63ea98898c289c96b5e56df366a8e215c7d3fab1468455c6a0a29
MD5 b826e585ec399c680732a47a3413ceeb
BLAKE2b-256 0cb7313b3b5da8f324166de51b774ccd0620926ea37f997c6a45ec1297704059

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page