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## 翻案依据（逐方法对照公开 SDK，非方法名 grep） 初判把 kbtree/multimodal 归入"只用公开 SDK"，错了。两边的 s.Knowledge() / s.LLM() **同名但接口面不同**： - kbtree 需要 KnowledgeAPI.Subtree/CategoryCounts/SearchIn/Categories 与 KnowledgeTreeView/KnowledgeCategoryCount 类型 —— 公开 KnowledgeAPI 只有 Search/Add/List，树视图类型公开面根本没有 - multimodal 需要 LLMAPI.Chat + LLMMessage/LLMContentBlock —— 公开 LLMAPI 只有 ListSources/SetSource/CurrentSource，没有 Chat 外置它们 = OCR/看图/转写、知识树浏览静默失效。 ## 最终内置 13 个 cli webui agentcli healthcheck pluginmgr seq remotedevice clawhubadapter kbtree multimodal cfgmgr skillmgr seemedia 外置 5 个（SDK 仓 example/ 已提供工程并已部署验证）： cmd localuse mcp（本轮）+ ai_image files（此前）+ timer（更早） ## 文档同步（中英 6 份） 数量 11 → 13；判定标准小节补「终审翻案」与教训： **判外置与否必须逐方法对照公开接口，同名方法不等于同面。** 验证：go build/vet/test 全绿；生产实例已部署新内核 + 新插件包， 四个按需插件经 plugin_start 拉起、工具全部注册（cmd_run / local_screensee / mcp_* / files_edit_line 实核）。
107 lines
7.8 KiB
Markdown
107 lines
7.8 KiB
Markdown
**中文** | [English](../en/OVERVIEW.md)
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# HomeAgent — Project Overview
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## What Is This
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HomeAgent 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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**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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- **Document Layer**: JSON files + TF-IDF vector-indexed temporary memory, supports explicit submission and implicit archival, cold data distills to Graph
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- **Graph 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 graph 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 → Document → 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` / `doc_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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- **Document Store** (`document/document.go`) — Temporary memory, JSON files + TF-IDF vector index, consume-on-read
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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 ([homeagent-sdk](https://github.com/JianFeeeee/homeagentsdk) 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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