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## 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/` ✓
116 lines
8.5 KiB
Markdown
116 lines
8.5 KiB
Markdown
**中文** | [English](../en/OVERVIEW.md)
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# HologramAgent — Project Overview
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## What Is This
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HologramAgent is a continuously-running personal intelligent Agent framework.
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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.
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### Design Highlights
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**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:
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- Plugins register tools (Tool) with the kernel for LLM invocation
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- Plugins hook into the processing pipeline (Stage) to intercept/rewrite message flow at various phases
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- Plugins subscribe/publish events (Event) for loosely-coupled communication
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- Plugins queue or interrupt input delivery through IO API
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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.
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**Business semantics stay in plugins** — the kernel does not define business
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objects: terminals, command history, device state and media libraries all belong to
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the plugin domain. Take terminals: the PTY, session lifecycle and output buffering
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all live in `agentcli`; when WebUI or CLI needs a terminal panel it **subscribes to
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the event bus** (`EventTerminalOutput` + `EventToolCall`) and builds its own view
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instead of reading a state component inside the kernel. The kernel offers only the
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event bus and the plugin registration surface — adding a new capability does not
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require touching the kernel, and no second version of business truth accumulates there.
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**Three-Layer Memory Architecture** — Manages information retention across long agent runtimes through a tiered storage strategy:
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- **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
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- **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
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- **Stablemem Layer**: SQLite graph database, persists entities and relations, BFS traversal recall, distillation pipeline extracts triples from conversations
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Three progressive layers — context, cold archive, long-term stable memory — form an information decay and consolidation pipeline from short-term to persistent storage.
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**Media Memory (first-class memory blocks since v1.2.0)** — Images and audio are not attachments; they are first-class nodes of memory:
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- **Content-addressed store (CAS)**: addressed by digest, metadata in SQLite and blobs on disk (two-level
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bucketing), identical bytes stored once. Every `Get` re-verifies the digest (silently returning corrupt
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data is worse than an error).
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- **Blocks carry their own multimodal vector and fingerprint**, and are retrieved directly — there is no
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media marker in the body text any more.
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- **No separate GC, no reference counting, no keep-set**: blocks follow the single-layer invariant —
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Context → Cold Context → Graph is a **migration** of a block, not a copy, and nothing is kept alive by
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references; **deleting a block deletes its content.**
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- **Reaches the plugin boundary since v1.1.1**: plugins read and write media through `InsertWithMedia` /
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`InjectInputMedia`; the model attaches media via the `media_digests` argument of `memory_commit` / `coldcontext_commit`.
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- **The old mechanism was removed entirely**: the **descriptive index** — writing the vision model's
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description into the body text as a `[<mime> <short digest>] <description>` marker and retrieving by it —
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together with `media_refs` reference counting, was deleted in v1.2.0. A description is second-hand
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information produced by a model; retrieving "someone else's rendering of the image" is worse than
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retrieving the image's own vector.
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## What It Actually Does
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Code is in the project root, implemented in Go.
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**Kernel** (`internal/agent/core/`):
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- `eventloop.go` — Message loop (`eventLoop`), queuing input from the IO layer
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- `process.go` / `stages.go` — Processing pipeline: memory recall → persona injection → LLM call → tool execution → output delivery, 7 stage hooks
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- `toolcall.go` — Tool scheduling and execution
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- `context.go` — Context management (pretrained word embedding scoring StaticEmbedder → CosineSimilarity, TF-IDF fallback), automatic pruning of low-relevance events
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- LLM calls abstracted through the Provider interface, with multi-source automatic fallback
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**Memory System** (`internal/memory/`):
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- **GraphDB** (`graph.go`) — SQLite, entities + relations tables, BFS traversal
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- **Cold Context Store** (`internal/memory/coldcontext/`) — cold memory with two-phase retrieval (Peek, then Remove)
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- **Text Memory** (`text/text.go`) — Raw conversation logs, JSONL file rotation
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- **Social Store** (`social/social.go`) — Persona traits + relationship network, wraps GraphDB
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- **Memory Indexer** (`indexer.go`) — Auto-vectorizes GraphDB entities, recalls and injects into system prompt on user input
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**Knowledge Base** (`internal/knowledge/knowledge.go`):
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- File system directory `knowledge/<name>/content.md`
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- TF-IDF vector search, independent index instance from the memory system
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- LLM operates via three tools: `knowledge_search` / `knowledge_create` / `knowledge_list`
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**Plugin System** (`internal/plugin/`):
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- Built-in plugins: Go `init()` self-registration, compiled into kernel
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- External plugins (since v1.0.0): compiled to an ordinary Go binary `plugin.bin`, spawned by the
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kernel as an **independent subprocess**, communicating over stdio JSON-RPC (control plane) +
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a shared memory segment (data plane) + an event ring (notification plane); Lua script plugins are
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also supported (the C ABI shared-library channel, `-buildmode=c-shared`, was removed entirely in v1.0.0)
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- PluginSDK (`internal/sdk/`) defines four channels: RegisterTool / RegisterStage / Subscribe / RegisterOutputChannel
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- 7 stage hooks: on_input → pre_action → post_action → before_toolcall → after_toolcall → before_output → after_output
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**LLM Provider** (`internal/agent/api/provider.go`):
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- Provider interface: Name / Chat / ChatStream / MaxContextTokens
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- Single implementation, `LuaAdaptedProvider`: every source goes through a Lua adapter script that
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transforms requests/responses; adapter scripts live in `internal/lua/adapters/`, one `.lua` per protocol
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- 10 built-in adapters: deepseek / openai / anthropic / gemini / mistral / groq / github / kimicode / ollama / server
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- Sources (`core.llm.sources.<name>.*`) are configured at deploy time — the count is deployment-specific
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and is not tied to the number of built-in adapters
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**WebUI** (`internal/plugins/webui/`):
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- Embedded SPA dashboard (`dashboard.html` packaged via `//go:embed`)
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- REST API: status query, configuration management, memory operations, knowledge management, plugin management
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- OpenAI API-compatible `/v1/chat/completions` endpoint
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- SSE event stream `/api/v1/chat/events`
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**ClawHub Adapter** (`internal/plugins/clawhubadapter/`):
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- Unified loader for OC plugins (Node.js), Python sidecar, JS sidecar, and SKILL plugins
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- RegistryDispatcher pattern: routes registration notifications to Tool/Provider/Channel/Stage registries
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- ClawHub marketplace search and install: `clawhubadapter_search` / `clawhubadapter_npm_install`
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- 9 provider types mapped to LLM-accessible tools (image generation, web search, speech, etc.)
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- OC channels auto-registered as IO devices with text/file/image/audio capability flags
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## Project Status
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Core functionality is operational. Plugin system and SDK are ready for independent external plugin development.
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- Built-in plugins (13): webui / cli / agentcli / cfgmgr / healthcheck / kbtree / multimodal / pluginmgr / clawhubadapter / remotedevice / skillmgr / seemedia / seq
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- Criterion: **a plugin stays built-in only if it requires internal-SDK-only capabilities**; everything else ships as an .hmap external plugin (see ARCHITECTURE)
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- External plugin examples ([hologramagentsdk](https://github.com/JianFeeeee/hologramagentsdk) repo `example/`, both Go and Lua types): qq / files / a2a / ai_image / bili / browser / calendar / editdoc / memo / music / ocr / rss / sanitizer / weather / luademo
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- Distribution: `.hmap` plugin package format, installable via WebUI
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