JianFeeeee 7ac40811e7 feat(memory): 媒体 GC 与描述生成两条后台循环
补齐媒体记忆的最后两块:容量上限真正生效,描述文本成为持久语义记忆。

## mediaGCLoop:让容量上限不再形同虚设

CAS 的 GC 只在被显式调用时执行,Put 路径不触发它。此前配置项
core.memory.media.max_mb 注册了却没有任何调用方——一次 see_video 抽 10 帧,
帧本身在工具结果被 Prune 后就没人引用了,若无人清理会一直堆在磁盘上。

现在按 gc_interval(默认 6h)周期调 GC(gc_min_age)。两个不变量:
  - 有引用的内容永不删除,即使超容量(宁可超限也不断引用)
  - gc_min_age(默认 1h)保护刚 Put 还没来得及 AddRef 的项——它们
    refcount 也是 0

## mediaDescribeLoop:描述才是能活过 GC 的那部分

blob 会被容量 GC 淘汰,而描述留在 media 表里,并经 mediaSummaryForEvent
写进 L0 事件、随归档进 L2 文档、经蒸馏进 L3 图库。于是「那张紫蓝红三色
带图」在原始字节早已被清掉之后仍然可被检索到。

复用既有的视觉回退链(resolveModalFallback + chatModalFallbackBatch),
不新造一套模型调用。

三个刻意的决定:

  - **走后台而非入库时同步**:视觉模型一次调用生产实测 9.6s。放在对话
    路径上会让每张图都给回复加十几秒,而描述的价值是几个月后还能检索到,
    不是这一轮——这一轮模型本来就直接看着图。
  - **逐条而非批量**:批量拿回来是一整段文字,无法可靠切分回各自的
    digest(模型未必按序号输出,也可能把两张图合并成一句)。宁可多几次
    往返也要保证「描述 ↔ digest」的对应关系确定。
  - **默认关闭**(describe_on_ingest=false):它消耗视觉模型配额。开启后
    每 30s 最多处理 4 条,不跟对话抢额度。

失败处理分三类:
  - 网络抖动/配额 → 不标记,下轮重试
  - 空回复 → 视作失败(上游剥离媒体时通常回空,与 modalfallback 同理)
  - 不可描述(kind=other、blob 已丢失)→ 标记 described_by=unsupported/
    content-missing,退出队列

## 顺带修掉 Pending 的一个真缺陷

测试写出来才发现:Pending 原先只看 `description = ''`,于是被标记为
described_by=unsupported 但 description 仍空的项**每轮都会被重新取出来
重试**,永久占着 LIMIT 的名额,真正需要描述的新项永远轮不到。
改为同时要求 described_by 也为空。

这是「先写断言再看它是否成立」抓到的——原本我以为标记一下就够了。

## 测试

medialoop_test.go 7 例:两条循环在禁用时立即返回(nil store / 零间隔 /
describe 关闭三种形态,不留空转 goroutine)、GC 清孤儿保留有引用项、
minAge 保护新项、无可用源时不误标记、不可描述大类被标记后退出队列。
media_test.go 补 1 例专测 Pending 的排除逻辑。

全仓 go build / go vet / go test 通过,SDK 冻结 diff = 0。
2026-09-04 22:00:03 +08:00
2026-07-29 15:45:24 +08:00

⚠️ AI-Assisted Programming Notice: Parts of this project's code, documentation, and commit history were generated or modified with AI assistance. Key changes have been human-reviewed, but please evaluate and verify before use.

HomeAgent

中文: README.md

An Agent framework designed around separation of core domain and application domain. The kernel enforces a zero-IO policy — all external interaction (WebUI, QQ, CLI, file operations, web search, memos, etc.) is handled by the plugin layer; the kernel performs no direct IO operations.

Combined with a three-layer memory architecture (Context → Document → Graph), it maintains contextual coherence across long-running single-conversation sessions through tiered storage and automated archival.

homed (kernel, zero IO) ← PluginSDK → plugins (all IO capabilities)

Since v1.0.0 external plugins are independent subprocesses, communicating with the kernel over stdio JSON-RPC (control plane) + a shared memory segment (data plane) + an event ring (notification plane). A plugin crash cannot take down the kernel and it restarts automatically; swapping plugin.bin gives true hot-reload.

Design Principles

Separation of Core Domain and Application Domain — The kernel's responsibilities are limited to LLM orchestration, memory management, and knowledge retrieval; all IO capabilities (message send/receive, file read/write, network requests, hardware interaction, etc.) are implemented by plugins. This separation defines domain boundaries at the Agent framework level, with distinct responsibility scopes for the kernel and plugins.

Three-Layer Memory Architecture — Manages information retention in long-running agents through a tiered storage strategy:

  • Context Layer: Pretrained word embedding / TF-IDF fallback relevance-scored event window, protects last 10 entries, maintains topK context entries
  • Document Layer: Temporary memory with automatic cold data sinking, also supports user-initiated submissions
  • Graph Layer: SQLite graph database, persists entity relationships and semantic memory, supports distillation pipelines to extract triples from conversations

Architecture Diagrams

1. Message Processing Sequence

sequenceDiagram
    participant U as User/Plugin
    participant IO as IOManager
    participant EV as eventLoop
    participant CTX as RelevanceContext
    participant LLM as LLM+Tool Loop
    participant ST as StageHost
    participant MEM as Three-Layer Memory

    U->>IO: InjectInput(type, payload)
    IO->>EV: inputCh
    rect lavender
        Note over EV: processTextInput
        EV->>ST: StageOnInput  Plugin can rewrite/short-circuit
        EV->>CTX: Prune(input,topK)  StaticEmbedder/TF-IDF cosine pruning
        CTX->>MEM: Low-score events archived to Document (original timestamp)
        EV->>CTX: Append(input)  CleanTemplateText→three-branch vector→5s write
    end
    rect lightgreen
        Note over EV,LLM: process()
        EV->>MEM: buildMemoryContext  Indexer recalls from Graph (vector+jieba→BFS depth=2)
        EV->>MEM: buildSystemPrompt  DocQuery summary+Graph memory index+Persona+Skills
        EV->>ST: StagePreAction  Plugin can pre-intercept
        loop Tool loop
            LLM->>LLM: drainInterrupts
            LLM->>LLM: LLM Chat
            LLM->>ST: StagePostAction  Plugin can modify/short-circuit
            alt No tool call
                LLM-->>EV: Returns response
            else
                loop Each tool
                    ST->>ST: StageBeforeToolcall  Plugin can reject
                    LLM->>LLM: executeToolCall
                    ST->>ST: StageAfterToolcall
                end
            end
        end
    end
    rect lightpink
        Note over EV: emitResponse
        CTX->>CTX: Append(response)
        ST->>ST: StageBeforeOutput  Plugin can rewrite
        EV-->>U: ResponseCh CLI sync
        EV-->>EV: Event bus WebUI SSE
        ST->>ST: StageAfterOutput  Read-only
        EV->>MEM: emitMemoryCandidate
    end

2. Stage Pipeline

flowchart LR
    S1[① on_input] --> S2[② pre_action]
    S2 --> S3[③ post_action]
    S3 --> Q{Has tool?}
    Q -->|Yes| S4[④ before_toolcall]
    S4 --> T[executeToolCall]
    T --> S5[⑤ after_toolcall]
    S5 --> S3
    Q -->|No| S6[⑥ before_output]
    S6 --> S7[⑦ after_output]
    style S1 fill:#e1f5fe
    style S3 fill:#fff3e0
    style S6 fill:#e8f5e9

3. Three-Layer Memory

flowchart TB
    subgraph C[① Context Working Window]
        RC[RelevanceContext]
        A[Append] -->|CleanTemplateText→three-branch vector| RC
        P[Prune StaticEmbedder/TF-IDF Cosine] -->|Low score original timestamp| D
        P -->|Keep| TL[timeline→chronological→system prompt]
    end
    subgraph D[② Document File Memory]
        DS[DocStore JSON+TF-IDF]
        Q1[Query summary auto-inject] -->|[Related Memory Docs]| SP
        Q2[doc_query LLM active recall] -->|Consume+delete source| DS
        Q2 -->|Original timestamp write to context| RC
        CD[FindColdDocs 72h] -->|docToTriples| G
    end
    subgraph G[③ Graph Database]
        DB[(SQLite)]
        IDX[Indexer vector+jieba→BFS depth=2] -->|[Memory Index]| SP
        MEM[memory_recall/commit/merge/purge/edit]
        SOC[person_query/set_trait]
    end
    subgraph H[④ Heartbeat Distillation]
        REORG -->|Step3 Cold docs| CD
        REORG -->|Step4 Bigram Jaccard| CONS[consolidation]
        PIPE[Pipeline regex] -->|Name/Address/Likes/Age/Job| DB
    end
    SP[System Prompt] -->|Sequential assembly| LLM
    LLM[LLM] -->|doc_query| Q2
    LLM -->|memory_recall| MEM

See assets/docs/en/ARCHITECTURE.md for details.

Web Mascot

HomeAgent Web Mascot Xiaozhai

Xiaozhai — HomeAgent Web Mascot

Quick Start

make build build-cli
./build/homed -data /tmp/ha
# Interactive mode
./build/waiter

# Or single message
echo "Hello, remember that I like coffee" | ./build/waiter

API keys are configured via WebUI http://localhost:8080 settings page, persisted in SQLite.

Code Structure

cmd/homed/          Daemon entry, assembles all subsystems
cmd/waiter/         CLI client (Unix socket)
internal/
├── agent/core/     Agent core: event loop, LLM tool loop, 7-stage pipeline
├── agent/api/      LLM Provider + 8 Lua adapters
├── memory/         Three-layer memory: Graph(SQLite) / Document(JSON+TF-IDF) / Text(JSONL) + StaticEmbedder(pretrained word embedding/TF-IDF fallback) + CleanTemplateText(de-template)
├── knowledge/      Knowledge base (filesystem + TF-IDF)
├── plugin/         Plugin registry + subprocess loader (stdio RPC + shared memory segment + event ring)
├── plugins/        11 built-in plugins (webui/cli/timer/cmd/mcp/clawhubadapter/agentcli/healthcheck/pluginmgr/files/cfgmgr)
├── sdk/            PluginSDK (Tool/Stage/Event three channels)
├── config/         SQLite config center
├── events/         Event bus
└── internal/lua/adapters/   8 LLM protocol adapter scripts
External plugin development: see [homeagent-sdk](https://gitcode.com/JianFeeeee/homeagent-sdk) repo, use `plugindev` toolchain, refer to Go and Lua examples in `example/`

Project Status

v1.0.0 — External plugins moved from C ABI shared libraries to subprocess + shared memory. The first release that no longer loads .so/.dll, and it is incompatible with 0.9.x (existing plugins must be rebuilt into plugin.bin with the new plugindev, though business code needs zero changes). Eliminates 6 classes of defects that had caused production incidents: hot-reload silently failing (DF_1_NODELETE making dlclose a no-op), no crash isolation (a plugin panic took down homed), stage lost updates (35.8~36.8% loss under the copy model), uncancellable cgo timeouts (linear OS-thread leaks), output_send reporting false success (the model was told "sent" while the message never went out), and Windows capability degradation (only 3 stage fields visible, no write-back). Three communication planes: stdio JSON-RPC (control) + shared memory segment (data) + event ring (notification); the privilege gradient is now enforced by three explicit gates. RPC round-trip p50 24.1µs; crash-to-recovery under 1s.

v0.9.0 — C ABI v2: external plugin Stage callbacks can now write back (invoke_stage gained a result out-param; plugins may mutate RawMessage/LLMText/ToolResults etc. in OnInput/AfterToolcall/PostAction and have them synced to the core). ABI version now tracks core minor releases (v0.9.x → ABIVersion=2, version_min=1 keeps old plugins loadable). Also fixes the tool-loop zen-compat placeholder that wrongly fired on first-turn system context tail. The SDK ships an enhanced sanitizer example (bad-UTF-8 / U+FFFD / ANSI-escape scrub across the whole pipeline). This ABI retired with v1.0.0.

v0.8.0 — Core is functional, plugin system enhanced. 20+ built-in plugins. External plugin development via homeagent-sdk repo. Added input channel NoMemory/Cleaner, ChannelDef, plugin disable/enable system (CLI + WebUI), plugindev toolchain C ABI ChannelDef support.

Documentation

Downloads

Releases ship three variants:

Variant Contents For
full homed + waiter + desktop GUI + systemd unit Single-machine, everything
server homed + waiter + systemd unit Servers (no desktop environment)
client waiter + desktop GUI Connecting to a remote HomeAgent
  • Linux: .deb (amd64/arm64), .rpm (x86_64), .tar.gz
  • Windows: HomeAgent_v1.0.0_{Full,Server,Client}_win64.exe (NSIS installer)
  • Portable: homeagent-bin-<os>_<arch>.tar.gz (homed/waiter/initconfig)
  • Verification: SHA256SUMS

The macOS homed requires a native macOS build (CGO + sqlite3), so release packages ship only waiter/initconfig.

Build

make build build-cli    # Build daemon + CLI
make test               # go test ./...
make install            # Install to system

Dependencies: Go 1.25+, CGo (go-sqlite3), Linux/Windows.

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