AI 记忆

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  • 记录 UAIX-MEMR-1296
  • 小路 /zh-cn/ai-memory/canonical-ai-memory/
  • 使用 规范公共记录

文件状态

公共标准页面 作为当前公共标准记录的一部分在 UAIX 上发布
代码
UAIX-MEMR-1296
表面
AI 记忆
使用权
公开且可链接

如何使用本页

此处说明当前公开记录、证据路径和支持边界。

公开记录项

AI 记忆数据包向导公开记录项项目交接公开记录项

公开记录项

此处说明当前公开记录、证据路径和支持边界。

此处说明当前公开记录、证据路径和支持边界。

公开记录项

公开记录项

此处说明当前公开记录、证据路径和支持边界。

公开记录项

公开记录项

此处说明当前公开记录、证据路径和支持边界。

公开记录项

公开记录项

此处说明当前公开记录、证据路径和支持边界。

公开记录项

AI 记忆数据包向导此处说明当前公开记录、证据路径和支持边界。公开记录项此处说明当前公开记录、证据路径和支持边界。项目交接此处说明当前公开记录、证据路径和支持边界。公开记录项此处说明当前公开记录、证据路径和支持边界。路线图此处说明当前公开记录、证据路径和支持边界。

证明路径

公开记录项

此处说明当前公开记录、证据路径和支持边界。

  1. 1公开记录项此处说明当前公开记录、证据路径和支持边界。
  2. 2公开记录项此处说明当前公开记录、证据路径和支持边界。
  3. 3公开记录项此处说明当前公开记录、证据路径和支持边界。
  4. 4此处说明当前公开记录、证据路径和支持边界。此处说明当前公开记录、证据路径和支持边界。
公开记录项公开记录项
A source becomes Canonical AI Memory only after review promotes its accepted slice into current project memory, durable docs, code, tests, release notes, roadmap state, machine artifacts, or long-memory evidence.

此处说明当前公开记录、证据路径和支持边界。

What Canonical AI 记忆 Means

Canonical AI 记忆 is the reviewed memory record an AI can rely on for a bounded project. It is not every chat, dropped report, wiki page, graph edge, or generated summary. It is the current, source-backed operating layer that says what is true enough to act on, what is only background, and what still needs review.

当前 UAIX support is template-driven and file-based: public guidance pages, starter bundle templates, local AGENTS.md, readme.human, typed .uai records, wizard-generated files, and targeted checks. It is practical project memory, not a hosted memory service.

The Layer Model

Layer Role 边界
Raw sources Original reports, docs, logs, exports, intake files, and source snapshots. Preserve for provenance and later review; do not treat as instructions merely because an agent can read them.
LLM Wiki LLM Wiki is the durable source memory for reviewed summaries, long rationale, source-linked pages, contradictions, indexes, and logs. 可选 for UAIX. Wiki memory stays background until promoted into accepted project surfaces.
Derived knowledge graph 可选 read-only projection over reviewed wiki and handoff records for routing, retrieval, contradiction discovery, and provenance navigation. GraphRAG is retrieval assistance over governed evidence, not a new authority layer.
AI 记忆 AI 记忆 is the compact portable operating packet: current facts, constraints, decisions, owners, next actions, checks, and pointers to deeper sources. Keep it small enough to load before work; route bulky history back to durable memory.
项目交接 项目交接 is the transfer packet for repository, project, team, vendor, or agent takeover. It tells the next actor what to read, what not to assume, what may change, and which checks matter.
Execution agent The human or AI doing the work through local tools and repository rules. Execution is not authority. The agent must cite loaded memory, obey constraints, and report blockers.

Build Order

  1. Preserve raw source material with source path, date, owner, sensitivity, and disposition.
  2. Compile reviewed LLM Wiki or documentation pages when the project needs durable background memory.
  3. Derive graph IDs, claim nodes, source spans, contradiction links, and retrieval indexes only from reviewed records.
  4. Export the compact AI 记忆 packet with current truth, constraints, owners, next actions, and targeted checks.
  5. Use 项目交接 when responsibility or execution moves to another person, team, vendor, or agent.
  6. After work completes, promote only reviewed conclusions back into hot memory, docs, code, tests, release notes, roadmap state, machine artifacts, or long-memory evidence.

Review And Promotion Rules

A source becomes canonical AI 记忆 only after it survives review. Dropped files, generated summaries, old chats, LLM Wiki pages, AIWikis archives, and graph results are source leads until a human or project rule promotes their accepted slice into current project state.

  • Keep source provenance attached when a claim moves between layers.
  • Mark sensitivity, owner, review state, freshness, and promotion target.
  • Preserve contradictions instead of hiding them in a clean summary.
  • Abstain when the reviewed source does not support an answer or action.
  • Update the smallest current memory surface that future workers actually need.

Where Knowledge Graphs Fit

Knowledge graphs can make canonical AI 记忆 easier to navigate when they are derived from reviewed pages and handoff records. Stable IDs, claim nodes, source spans, review events, contradiction states, and release snapshots help retrieval systems cite why a fact is usable.

That graph layer is optional. 当前 UAIX does not provide a hosted graph database, public graph API, public SPARQL endpoint, automatic repository writes, automatic LLM Wiki sync, certification, endorsement, SDK, CLI, official adapter, or UAI-1 conformance evidence for graph exports.

当前 Support 边界

  • 当前: public guidance, generated starter templates, local files, package manifests, wizard outputs, support-boundary copy, and targeted local checks.
  • 当前: optional LLM Wiki 计划ning fields and optional knowledge graph planning fields when they help preserve source routing and review boundaries.
  • Not current: hosted memory import, automatic site or repository writes, automatic wiki sync, hosted graph services, official adapters, SDKs, CLIs, certification, endorsement, or repo-local .uai conformance profiles.

Wizard Guidance

The AI 记忆数据包向导 should be used to create the compact operating packet after the project chooses its memory layers. Select the LLM Wiki path when durable source memory exists or is being planned. Select 文件交接 when dropped-file intake must be reviewed before project work. Select the combined path only when the receiver must complete real project work plus hot-memory and long-memory/archive outcomes.

For Canonical AI 记忆, wizard answers should name the raw source path, durable memory path, graph and retrieval policy if any, promotion owner, evidence log, source boundary, workspace routing rule, targeted checks, and blocked actions.