【问题】 1. 入站请求用 InjectInterruptText 抢占打断当前对话,立即回 202 submitted, agent 的回复 emit 到未注册的 channel(a2a/acp)→ 请求方永远拿不到回复文本, 只能干等超时。(acp 的 session.Replying 从未被填真回复 → SSE 永远 "(未收到回复)") 2. 无法指定/延续 session:a2a 无 session 概念;acp session/new 每次新建、 不接受调用方 session_id,多轮上下文断裂。 3. a2a/acp 通道未注册为输出设备 → emitResponse 的回复无落点, output_list_channels 也不可见 → agent 困惑"回复该发到哪"。 【修复】 - 入站改用 SDK InjectInputSync 同步注入:阻塞等待 agent 处理完成, 直接把最终回复文本返回给 HTTP 请求方(不再回 202)。 这是 A2A/ACP 协议的合理形态——客户端控制超时,服务端同步返回。 - session 支持:a2a tasks.send 与 acp session/new 均接受 params.session_id, 指定则延续已有会话(拼上下文前缀),不指定则新建并返回 session_id。 单会话保留最多 10 轮历史防膨胀;30min GC 清理 2h 未用会话。 - a2a/acp 注册为输出通道(RegisterOutputChannel):回复有落点, output_list_channels 可见,agent 可主动 output_send 推消息。 - 注入提示词明确"直接以文本回复即可,无需调 output_send"—— agent 不再把回复走 queued 入队而返回干净文本。 端到端验证: 单轮:status=completed, reply=真实回复文本(非 submitted) 多轮:同 session_id 第二轮准确复述第一轮问题(上下文生效) a2a v1.2.0 / acp v1.1.0 安装 config_kept=true
⚠️ 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)
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 + .so/.dll dynamic loader
├── 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
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).
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
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.
