此前三段式拆分后 ONNX 路径从未从 Go 侧跑通:embedder_onnx_test.go 仍引用 分段前的 API(e.renderInput、TextTower.onnx、旧目录),go vet -tags onnxruntime 直接编译失败。导出脚本只在 /tmp 且硬编码本机路径、从第三个目录拷贝固定形状的 Vision.onnx,完全不可复现。音频会被视觉塔编码,静默往统一空间灌入错误坐标。 本提交补齐这些缺口: 一、可复现导出脚本(scripts/export_qwen3vl_embedding_onnx.py) - 自动拉取模型(HuggingFace 优先,失败回落 ModelScope,支持 HF_ENDPOINT 镜像); - 导出 TokenEmbedding + Transformer + Vision 三段图,图文共用同一 token embedding、28 层 Transformer、last-token 池化与 fingerprint; - 双重自检(不可省):分段 PyTorch vs 完整模型 + 导出后的 ONNX vs 完整模型, cos < 0.999999 即非零退出——「能加载」不等于「算得对」; - 默认把 L2 归一化后的冻结参考向量写入产物目录(qwen_reference.json)—— Go 测试据此做逐维冻结回归,且「该目录是哪次导出的」从文件本身可追溯; - --verify-only 校验既有产物不重新导出,可用来确认线上在用的图没坏。 关键实测结论(已写入 docs/zh/multimodal-space.md 与长期记忆): 原生多帧视频不可行——Qwen3-VL 视觉塔把 grid_thw 当 Python 值消费 (grid_thw.tolist()),legacy tracer 固化为常量,导出后图中根本没有 grid_thw 输入,换帧数调用直接 Invalid input name: grid_thw。故视觉塔固定 (1,48,48), 视频由上层抽帧后逐帧按图像编码(同模型/同维度/同 fingerprint),音频明确 unsupported。 二、模态边界(vector.ErrModalityUnsupported) - 新增 vector.ErrModalityUnsupported:表示「该模态不在本统一空间的原生覆盖 范围内」,与普通错误语义不同——调用方应把它当「永远不会有向量」而非 「本次失败、下次重试」; - qwen.EmbedImageDense 按 mime 拒绝 audio/* 与 video/*:此前它会拿视觉塔 去解音频字节,往统一空间灌入语义错误的坐标且静默; - reembedStaleMedia 对 ErrModalityUnsupported 不计失败、不重试、不用别的 模型向量顶替(TestReembedStaleMedia_SkipsUnsupportedWithoutFaking 守住)。 三、Go ONNX 测试首次完整通过 - 重写 embedder_onnx_test.go:修复编译 + 文本冻结回归 + 图像冻结回归 + 两条阴性对照(不同输入必须不同、图像与文本必须不同)+ 不支持模态断言; - 参考值从产物目录的 qwen_reference.json 读取(不在测试里硬编码浮点); - 用线上部署产物实测全部通过(text cos=0.999999940, image cos=0.999999762)。 四、.gitignore 修复 - /scripts/ 此前被列在「运行时产物」下,但它是作者维护的工具目录 (模型导出、侧车、部署校验),deploy/systemd/embed-sidecar.service 直接 引用 scripts/embed_sidecar.py,忽略它会让那份 unit 在别人的机器上指向 不存在的文件。改为只忽略 __pycache__。 五、文档(docs/zh/multimodal-space.md) - 获取/启用/产物契约/模态边界/验证/资源成本/与现有部署产物的等价性。 验证:go build ./...、go vet ./...、go vet -tags onnxruntime ./...、 go test -short 全部通过;ONNX 标签测试对线上部署产物全部通过。
⚠️ 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 v1.1.1 media reaches the plugin boundary: plugins and the model can both read and
write images/audio in memory (InsertWithMedia, InjectInputMedia). Media lives in plain-text
memory as a [<mime> <short digest>] <description> marker — the description is the searchable
semantic memory, the digest is the key back to the bytes.
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
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
v1.1.1 — Multimodal reaches the plugin boundary. v1.1.0 gave the memory system binary
multimedia nodes, but that path was open only to the kernel itself; this release opens it to
plugins and the model. The public SDK gains media fields and three media injection methods
(paired with SDK v1.1.0,
shared by the whole 1.1.x line), and the kernel implements the four matching RPCs. The bridge
layer had been silently dropping fields: Confidence/types/SentenceText handed in by a
plugin were discarded, Doc kept only three fields, and Remove never released references
(media stayed "referenced" forever, so GC could never reclaim it). processTextInput and
processMediaInput were unified into a single processInput, which finally gives the media
path the dedup, no_memory, channel Cleaner, interrupt semantics and correct EventRawInput
it had always lacked. Three real defects fixed: user-sent images never appeared in the WebUI
chat log (the media path published a map while the subscriber asserted a string),
memory_commit's sentence_text had never been exposed to the model (though it is the
mandatory link in the media binding chain), and two data races in PluginSDK (11 reported
by -race; in production this showed up as sporadic nil-dereference crashes during plugin reload).
v1.1.0 — Memory system supports binary multimedia nodes. Content-addressed media store
(CAS + SQLite metadata + on-disk blobs, Get always re-verifies the digest) wired through L0
(context events) / L2 (documents) / L3 (graph sentences), with reference-counted GC (referenced
items are never deleted). The description text produced by the vision model is the durable
semantic memory; the blob is only a cache that capacity GC may evict.
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
- Project Overview | 中文
- Technical Architecture | 中文
- Plugin Development Guide | 中文
- Lua Adapter | 中文
- Knowledge Base Demo
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_v1.1.1_{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.
