1. 术语统一:
- doc_query / doc_commit → coldcontext_query / coldcontext_commit
- 「图记忆 / Graph 层」→「稳定记忆 / Stablemem 层(L3)」
- 分层命名补上 L1/L2/L3 语义:Context(热) / Cold-context(冷) / Stablemem(持久)
涉及 README.md、README_EN.md、assets/docs/{zh,en}/{ARCHITECTURE,OVERVIEW}.md
2. 补上本次最大的结构变化(文档里此前完全没有):
- 安全防火墙作为**独立内核模块**:凭据闸门、工具黑白名单+沙箱、
敏感词与提示词注入预警、按主体授权与插件命名限式;显式代理而非 monkey patch
- device 数据面作为**独立内核模块**:工具注册与路由、inputch/outputch、设备登记;
路由表在 internal/toolroute 以避免 core ↔ kernelboot 成环
3. 历史计划文档(memory-*.md / context-overflow-l4-design / entities-retirement /
git-branching)加**归档说明**:明确术语已过时、现行口径以 ARCHITECTURE.md 为准。
刻意不改写历史正文 —— 那是决策记录,改写等于伪造。
剩余旧词只出现在归档文档与 scripts/capability-bench/PLAN.md(评测历史记录)。
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中文 | English
HologramAgent — Project Overview
What Is This
HologramAgent is a continuously-running personal intelligent Agent framework.
Core architecture: a long-running kernel process (homed) that connects to various IO channels (QQ, Web, CLI, etc.) through a plugin system. The kernel handles LLM orchestration, memory management, and knowledge retrieval; plugins handle all external IO — sending/receiving messages, file operations, web search, etc.
Design Highlights
Separation of Core Domain and Application Domain — The kernel (core domain) performs no IO operations; all IO capabilities belong to plugins (application domain). The boundary is defined through PluginSDK:
- Plugins register tools (Tool) with the kernel for LLM invocation
- Plugins hook into the processing pipeline (Stage) to intercept/rewrite message flow at various phases
- Plugins subscribe/publish events (Event) for loosely-coupled communication
- Plugins queue or interrupt input delivery through IO API
The significance lies in clear responsibility boundaries: the kernel focuses on orchestration and memory management, while plugins handle IO implementation — the two are not coupled.
Business semantics stay in plugins — the kernel does not define business
objects: terminals, command history, device state and media libraries all belong to
the plugin domain. Take terminals: the PTY, session lifecycle and output buffering
all live in agentcli; when WebUI or CLI needs a terminal panel it subscribes to
the event bus (EventTerminalOutput + EventToolCall) and builds its own view
instead of reading a state component inside the kernel. The kernel offers only the
event bus and the plugin registration surface — adding a new capability does not
require touching the kernel, and no second version of business truth accumulates there.
Three-Layer Memory Architecture — Manages information retention across long agent runtimes through a tiered storage strategy:
- Context Layer: In-memory pretrained word embedding scored event window (StaticEmbedder word vectors → CosineSimilarity, TF-IDF fallback), maintains recent context in real-time, low-relevance events automatically sink to the next layer
- Document Layer: JSON files + TF-IDF vector-indexed temporary memory, supports explicit submission and implicit archival, cold data distills to Graph
- Stablemem Layer: SQLite graph database, persists entities and relations, BFS traversal recall, distillation pipeline extracts triples from conversations
Three progressive layers — context, cold archive, long-term stable memory — form an information decay and consolidation pipeline from short-term to persistent storage.
Media Memory (first-class memory blocks since v1.2.0) — Images and audio are not attachments; they are first-class nodes of memory:
- Content-addressed store (CAS): addressed by digest, metadata in SQLite and blobs on disk (two-level
bucketing), identical bytes stored once. Every
Getre-verifies the digest (silently returning corrupt data is worse than an error). - Blocks carry their own multimodal vector and fingerprint, and are retrieved directly — there is no media marker in the body text any more.
- No separate GC, no reference counting, no keep-set: blocks follow the single-layer invariant — Context → Document → Graph is a migration of a block, not a copy, and nothing is kept alive by references; deleting a block deletes its content.
- Reaches the plugin boundary since v1.1.1: plugins read and write media through
InsertWithMedia/InjectInputMedia; the model attaches media via themedia_digestsargument ofmemory_commit/coldcontext_commit. - The old mechanism was removed entirely: the descriptive index — writing the vision model's
description into the body text as a
[<mime> <short digest>] <description>marker and retrieving by it — together withmedia_refsreference counting, was deleted in v1.2.0. A description is second-hand information produced by a model; retrieving "someone else's rendering of the image" is worse than retrieving the image's own vector.
What It Actually Does
Code is in the project root, implemented in Go.
Kernel (internal/agent/core/):
eventloop.go— Message loop (eventLoop), queuing input from the IO layerprocess.go/stages.go— Processing pipeline: memory recall → persona injection → LLM call → tool execution → output delivery, 7 stage hookstoolcall.go— Tool scheduling and executioncontext.go— Context management (pretrained word embedding scoring StaticEmbedder → CosineSimilarity, TF-IDF fallback), automatic pruning of low-relevance events- LLM calls abstracted through the Provider interface, with multi-source automatic fallback
Memory System (internal/memory/):
- GraphDB (
graph.go) — SQLite, entities + relations tables, BFS traversal - Document Store (
document/document.go) — Temporary memory, JSON files + TF-IDF vector index, consume-on-read - Text Memory (
text/text.go) — Raw conversation logs, JSONL file rotation - Social Store (
social/social.go) — Persona traits + relationship network, wraps GraphDB - Memory Indexer (
indexer.go) — Auto-vectorizes GraphDB entities, recalls and injects into system prompt on user input
Knowledge Base (internal/knowledge/knowledge.go):
- File system directory
knowledge/<name>/content.md - TF-IDF vector search, independent index instance from the memory system
- LLM operates via three tools:
knowledge_search/knowledge_create/knowledge_list
Plugin System (internal/plugin/):
- Built-in plugins: Go
init()self-registration, compiled into kernel - External plugins (since v1.0.0): compiled to an ordinary Go binary
plugin.bin, spawned by the kernel as an independent subprocess, communicating over stdio JSON-RPC (control plane) + a shared memory segment (data plane) + an event ring (notification plane); Lua script plugins are also supported (the C ABI shared-library channel,-buildmode=c-shared, was removed entirely in v1.0.0) - PluginSDK (
internal/sdk/) defines four channels: RegisterTool / RegisterStage / Subscribe / RegisterOutputChannel - 7 stage hooks: on_input → pre_action → post_action → before_toolcall → after_toolcall → before_output → after_output
LLM Provider (internal/agent/api/provider.go):
- Provider interface: Name / Chat / ChatStream / MaxContextTokens
- Single implementation,
LuaAdaptedProvider: every source goes through a Lua adapter script that transforms requests/responses; adapter scripts live ininternal/lua/adapters/, one.luaper protocol - 10 built-in adapters: deepseek / openai / anthropic / gemini / mistral / groq / github / kimicode / ollama / server
- Sources (
core.llm.sources.<name>.*) are configured at deploy time — the count is deployment-specific and is not tied to the number of built-in adapters
WebUI (internal/plugins/webui/):
- Embedded SPA dashboard (
dashboard.htmlpackaged via//go:embed) - REST API: status query, configuration management, memory operations, knowledge management, plugin management
- OpenAI API-compatible
/v1/chat/completionsendpoint - SSE event stream
/api/v1/chat/events
ClawHub Adapter (internal/plugins/clawhubadapter/):
- Unified loader for OC plugins (Node.js), Python sidecar, JS sidecar, and SKILL plugins
- RegistryDispatcher pattern: routes registration notifications to Tool/Provider/Channel/Stage registries
- ClawHub marketplace search and install:
clawhubadapter_search/clawhubadapter_npm_install - 9 provider types mapped to LLM-accessible tools (image generation, web search, speech, etc.)
- OC channels auto-registered as IO devices with text/file/image/audio capability flags
Project Status
Core functionality is operational. Plugin system and SDK are ready for independent external plugin development.
- Built-in plugins (13): webui / cli / agentcli / cfgmgr / healthcheck / kbtree / multimodal / pluginmgr / clawhubadapter / remotedevice / skillmgr / seemedia / seq
- Criterion: a plugin stays built-in only if it requires internal-SDK-only capabilities; everything else ships as an .hmap external plugin (see ARCHITECTURE)
- External plugin examples (hologramagentsdk repo
example/, both Go and Lua types): qq / files / a2a / ai_image / bili / browser / calendar / editdoc / memo / music / ocr / rss / sanitizer / weather / luademo - Distribution:
.hmapplugin package format, installable via WebUI