## 问题 README 与两份 ARCHITECTURE / OVERVIEW 仍在用旧称「Document 层」, 而第二层早已改名 cold context(工具名 `coldcontext_query` / `coldcontext_commit`)。 不止是层名。文档里引用的四个符号在代码里**一个都不存在**: | 文档里写的 | 代码里实际 | |---|---| | `docStore.ContextToDoc` | `coldcontextStore.ContextToColdContext` | | `FindColdDocs` | `FindColdContexts` | | `docToTriples` | `coldDocToTriples` | | `docStore.SetVectorizer` | (已无此调用,embedder 构造期注入) | 四处都用 `grep -rn "\b名字\b" --include=*.go` 确认过:旧名 0 处,新名各自 4 处。 ## 改了什么 - `assets/docs/zh/ARCHITECTURE.md` 13 处、`en/ARCHITECTURE.md` 15 处 - `assets/docs/zh|en/OVERVIEW.md` 各 3 处 - README 两版:「文档层」→「冷上下文层」 - `assets/branding/mascot-xiaozhai-guide.md` 的丝带配色表(三色分别对应三层) ## 顺带修正层号 ARCHITECTURE 用的是 **L1 Context / L2 Cold Context / L3 Stable**, 我上一版 README 写成了 L0/L1/L2 —— 少了一层,且与架构文档对不上。已改为 L1/L2/L3。 ## 顺带修掉断掉的交叉引用 `internal/agent/core/toolcall.go` 与 `recallcoldcontext_test.go` 的注释写 「ARCHITECTURE「记忆流转」② Document 层的读取分支」,指的正是刚改名的节。 不改就成了悬空引用。三个测试函数名(`TestContextToDoc` 等)指向已删函数,一并改名。 ## 验证 - 全仓 `grep` 旧名:`*.md` / `*.go` 均 0 处(排除 build/third_party/.pi) - `go build ./...` ✓ - `go test ./internal/memory/coldcontext/ ./internal/agent/core/` ✓
8.5 KiB
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
- Cold Context Layer (L2): JSON-file-backed cold memory with dense + TF-IDF retrieval, 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 → Cold Context → 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 - Cold Context Store (
internal/memory/coldcontext/) — cold memory with two-phase retrieval (Peek, then Remove) - 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