# 日志即代理：ActiveGraph--事件溯源反应图实现可审计可分叉的智能体系统

- 来源：Hacker News 热门（buzzing.cc 中文翻译）
- 作者：iacguy
- 发布时间：2026-07-06 05:27
- AIHOT 分数：54
- AIHOT 链接：https://aihot.virxact.com/items/cmr8bwrdk00ujsl0d34ucbdl1
- 原文链接：https://arxiv.org/abs/2605.21997

## AI 摘要

ActiveGraph 是一个反转传统代理框架的运行时，将只追加的事件日志作为真相来源，工作图是日志的确定性投影。普通函数、类或 LLM 支持的例程等行为对图变化做出反应并发出新事件，组件间完全通过共享图协调，无需直接指令。该设计实现三个特性：从日志确定性重放任意运行、在任意事件低成本分叉运行且不重复共享前缀、以及从高层目标到单个模型调用的端到端溯源。项目以 Apache-2.0 开源，附带快速启动演示、确定性重放、分叉对比和溯源追踪功能。

## 正文

Computer Science > Artificial Intelligence

[Submitted on 21 May 2026]

Title:The Log is the Agent: Event-Sourced Reactive Graphs for Auditable, Forkable Agentic Systems

Authors:Yohei Nakajima

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Abstract:Most agent frameworks are built around the language model: a conversation loop comes first, then tools, then rules, and finally a logging layer bolted on for observability, with state persisted as retrievable "memory." We describe ActiveGraph, a runtime that inverts this arrangement. The append-only event log is the source of truth; the working graph is a deterministic projection of that log; and behaviors--ordinary functions, classes, LLM-backed routines, or logic attached to typed edges--react to changes in the graph and emit new events. No component instructs another; coordination happens entirely through the shared graph. This single design decision yields three properties that retrieval-and-summarization memory systems do not provide: deterministic replay of any run from its log, cheap forking that branches a run at any event without re-executing the shared prefix, and end-to-end lineage from a high-level goal down to the individual model call that produced each artifact. We present the architecture, a determinism contract that makes replay sound, and a worked diligence example whose full causal structure is reconstructable from the log alone. We discuss--without claiming to demonstrate--why this substrate is unusually well suited to self-improving agents, and how it extends the BabyAGI lineage and prior graph-memory research.

Comments:

Subjects: Artificial Intelligence (cs.AI); Multiagent Systems (cs.MA)

Cite as: arXiv:2605.21997 [cs.AI]

(or arXiv:2605.21997v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2605.21997

arXiv-issued DOI via DataCite

Submission history

From: Yohei Nakajima [view email]
[v1] Thu, 21 May 2026 04:55:38 UTC (55 KB)

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