JianFeeeee 637a3a3d3f refactor(agent): R4 工作式子语义落地 + 清除 R1–R3 遗留的死代码
## 1. 工作式子的工具禁令收成单一事实来源

禁令此前写了两遍:定义侧(把工具从 childTools 滤掉)与执行侧
(模型硬调时拒绝)。两处名单必须逐字一致,任何一边落后就是真实缺口:

  定义侧漏滤 ⇒ 模型看得见但不该能用(白耗 token,还会反复试)
  执行侧漏拒 ⇒ 模型绕过定义直接调用**就能生效**

现在只有 workerForbidden 一张表,每条禁令把"匹配方式 + 类别 + 解释"
绑在一个结构体里;定义侧 workerToolAllowed、执行侧 workerToolReject
都从它派生。

上一版我用 reason 字符串 + 下标猜分类 + hint 查表做了三处间接,
属于新造的技术债,已重写为单表直查。

判据(均经变异验证):
  TestWorkerToolDenyListIsSingleSource  长出第二份名单 ⇒ 红(实测确认)
  TestWorkerToolAllowedMatchesReject    两侧判据漂移 ⇒ 红
  TestWorkerToolRejectExplainsWhy       拒绝文案不可执行 ⇒ 红

## 2. 删除零使用的抽象(不留技术债)

R1–R3 引入了 ChildKind / Host / Deliverer / DeviceResolver / ToolSpec /
ToolResult / DeclaredKinds / KindWorker / State / SetState / BumpRound /
ChannelDisposition,实现过程中发现它们是假抽象:

  · 各类型要用载体 Agent 的大半能力,要满足接口就得在实现里类型断言回 *Agent
  · 接口比被抽象的东西还大 ⇒ 只是把复杂度换个地方放
  · 实测:26 个导出符号里 20 个零使用、零实现

已删除 host.go 与 kind.go,并把"四种类型清单"和"转投驻留子为何不是类型"
这两个有价值的结论移进 kinds.go 的文档注释(知识保留,死代码删除)。

child 包现在只剩实际被用的 9 个符号:Kind / Child / Entry / Registry /
StopDeps / ErrChildExists / ErrChildNotFound(+ 2 个 Kind 常量)。

## 3. 修掉误导性签名

Entry.Dispose(policy ResidualPolicy) 里 policy **两个实现都不读** ——
残余处置实际走 ApplyResidual / FinishResidentWith,在 Dispose 之前就
已经完成。看签名会以为这里处理残余,是误导。已去掉该参数,
并删掉 child 包里重复定义的 ResidualPolicy(core 包已有一份,且多一个 stash)。

## 验证

  go build ./...                                  PASS
  go vet ./...                                    PASS
  gofmt -l                                        干净
  go test ./internal/agent/core/ -count=1         ok 15.300s
  go test ./internal/agent/core/ -count=1 -race   ok 18.040s
  干净检出(git worktree)单独 build + vet + test  PASS
2026-11-04 08:35:23 +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.

HologramAgent

中文: README.md

Self-hosted agent kernel. Runs on your own hardware; plugins attach as separate processes.

make build build-cli
./build/homed -data /tmp/ha

API keys go in the web UI at http://localhost:8080. Requires Linux.

The main difference from typical agent frameworks is context handling: instead of truncating on overflow or asking the model to summarize, it scores history by relevance and sinks the low-scoring events into cold context, then distills those into a graph. Two other things differ: startup order is resolved at build time, and plugins launch as soon as their facilities are ready.

Architecture

                    homed (kernel)
        LLM orchestration · memory · retrieval
                       │
        ┌──────────────┼──────────────┐
        │              │              │
   stdio RPC       shared mem     event ring
     control       bulk data      notify
        │              │              │
        └──────────────┼──────────────┘
                       │
              plugins (separate processes)
   web UI · QQ · CLI · files · browser

The kernel process handles orchestration, memory and retrieval; HTTP, files and devices belong to plugins (internal/plugin). A crashed plugin is restarted with backoff 1s / 2s / 3s; the 4th crash within 5 minutes stops automatic restarting pending human intervention (cmd/homed/kmod_runtime.go).

Context window

internal/agent/core/context.go

Each event gets two vectors on entry: a dense vector sharing one space with media and cold context, and a TF-IDF word vector as fallback. Pruning scores history against the current input and keeps topK, with the most recent N events exempt from scoring.

N defaults to 10, bounded by budget: min(configured, ContextTokens / avg tokens per event).

That bound came from a measurement. At a 50k window with 5800 tokens per event and a 40000 budget, pinning 10 events needed 58k, more than the budget itself. Every prune met its target without freeing space; the budget was gone after two rounds and the task terminated, with recall falling from 44% to 22%. Small windows now tighten automatically; a 1M window uses the configured value.

Pruned events move to the cold-context layer together with the media blocks they hold. Block IDs stay the same; only the holding layer changes. Retrieval uses coldcontext_query: Peek to confirm, then Remove the source copy. There is no fetch-and-delete path, since deletion follows confirmation.

Three layers

internal/agent/core/context.go · internal/memory/coldcontext/ · internal/memory/graph.go

Layer Holds Reaches the model Cooling
L1 Context events + blocks directly, in the system prompt low relevance sinks
L2 Cold Context events + blocks (same shape as L1) inserted back into L1 order on recall ≤2 accesses and 72h idle, then distilled
L3 Stable triples, nodes are blocks on recall never leaves

A block has exactly one holder at any layer, with no reference counting. Images and audio are blocks in L2/L3 with their own vectors, searched in the same space as text.

Scenes

internal/memory/scene_emerge.go

A scene is built from five weighted features: channel 1.0, conversation partner 1.0, tools 0.8, topic 0.4, time of day 0.2. A scene is created on the second occurrence of the same fingerprint (minSceneEvidence = 2); one-off interactions don't create one. Join threshold 0.5, recall 0.35. Recurrence adds 1 to strength; scenes that stop recurring decay by half-life.

Two entry points run in parallel: a plugin declares the scene at an injection point (e.g. chan:qq/peer:group_1), or fingerprints cluster on their own. A declared scene derives features only from its own key and does not absorb the full fingerprint. Absorbing it would make the declared scene match nearly every later turn of that kind at close to 1.0 similarity, and the clustering path could never grow narrower scenes.

Seven stages

internal/agent/core/stages.go

Stage When Plugins can
on_input message arrives blocklist, rate limit, short-circuit reply
pre_action context ready, before LLM inject external data
post_action LLM returns text and tool calls filter, force redirect
before_toolcall before one tool runs audit, deny, rewrite args
after_toolcall after one tool runs redact, sort results
before_output final text ready format adaptation
after_output after sending statistics

The inner loop is post_action → [before_toolcall → run → after_toolcall] → post_action. It exits when the model stops calling tools, all calls are denied, or the limit is reached.

Everything else

  • Channels: web UI, CLI, QQ groups and DMs, A2A, ACP in your IDE
  • Tools: files, shell, code, browser (real Chrome), calendar, notes, RSS, music
  • Modalities: images, video, voice, screenshots, web pages

28 built-in plugins, 89 model-callable tools. External plugins live one per repo under github.com/HologramAgent.

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 HologramAgent
  • Linux: .deb (amd64/arm64), .rpm (x86_64), .tar.gz
  • Windows: HologramAgent_v1.2.0_{Full,Server,Client}_win64.exe (NSIS installer, includes the AGPL license page). Since v1.2.0 homed no longer supports native Windows (it relies on fd inheritance and in-segment offset dereferencing), so the installer bootstraps WSL2 and installs the Linux packages inside the distribution the same way a Linux host would.
  • 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.

homed requires Linux (it relies on fd inheritance and intra-segment offset dereferencing of the shared memory region; see cmd/homed/platform_windows.go). On Windows only waiter.exe is built and homed runs under WSL2 (see Downloads). macOS can build waiter/initconfig; homed must be built on native macOS.

License

AGPL-3.0-only. See LICENSE.

Bundled third-party components keep their own licenses; full texts ship in /usr/share/doc/hologramagent/licenses/.

Third-party components shipped with the packages

Component License Location
Chinese-CLIP ViT-B/16 (ONNX artifacts) Apache-2.0 /usr/lib/hologram/models/chinese-clip-vit-b16-onnx/
ONNX Runtime (libonnxruntime.so) MIT /usr/lib/hologram/onnxruntime/
jieba dictionary (embedded in the binary) MIT internal/memory/jiebadict/
Go dependencies (go-sqlite3, gojieba, bubbletea, …) MIT / BSD-3 / Apache-2.0 permissive, AGPL-3.0-compatible

The package metadata declares this package as AGPL-3.0-only.

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