JianFeeeee 2b2707cb89 test(agent): 让 rt 跨进程 e2e 真正跑起来 + 策略撤销改为行为判据
## 一、e2e 一直 SKIP,等于从未验证

`TestExternalRTChild_*` 4 条判据长期 SKIP(缺插件产物)。本次用
`third_party/hologramagentsdk/example/rtvoice/build/plugin.bin`
实跑,立刻暴露两处**测试与插件不同步**:

  rtvoice_inject  插件已改名为 <name>_say     ⇒ 注入失败
  rtvoice_dump    插件从来没有这个工具        ⇒ 观测失败

改名发生在插件侧,而判据长期不运行,所以没人发现。这正是
"SKIP 判据等于没有判据"的实证。

修法:
  · 注入改用 `rtvoice-e2e_say`(插件当前唯一调试入口,走与麦克风
    完全相同的 p.Push → InjectInterruptTextOpts 路径)
  · 输出观测改为对 outputch 设备做一次**跨进程 RPC**(channelDevice
    句柄 → 插件进程 → 拿回执),不依赖插件内部私有状态

## 二、策略撤销判据从源码扫描改为行为断言

`TestChildTeardownRevokesPolicy` 原先扫源码文本,找停止函数体里有没有
`revokeChildPolicy`。R2/R3 把撤销移进骨架 Cleanup 后文本匹配失效 ——
但行为是对的,判据自己变红。

这暴露出它抓不住的真实风险:`StopDeps.RevokePolicy` 是**注入**的,
漏填时 Cleanup 里的 nil 检查会静默跳过,而字符串仍在别处,源码扫描照样绿。

现在分两层:
  · kernelmod/all  保留源码断言,但钉**两个环节成对**:
                   ① Cleanup 真的调用 deps.RevokePolicy
                   ② 各类型真的注入它
                   并增加"单数与复数必须共用骨架 Stop"的结构护栏
  · agent/core     新增行为判据 childpolicy_test.go:
                   声明策略 → 走真实停止路径 → 主体表里必须消失

## 三、验证

    go build ./...                                  PASS
    go vet ./...                                    PASS
    gofmt -l                                        干净
    go test ./... -count=1        62 包全过,0 FAIL
    go test ./... -count=1 -race  0 FAIL

    rt 跨进程 e2e(4 条,不再 SKIP):
      TestExternalRTChild_FullChain                    PASS(rtchild 跑了 1 轮)
      TestExternalRTChild_ReuseDoesNotLeakTranscript   PASS
      TestExternalRTChild_BulkStopUnregistersInbound   PASS
      TestExternalRTChild_RepeatedCyclesDoNotAccumulate PASS

    变异验证:断开 routeInputByOwner 的 rt 分支 ⇒
      FullChain 立即红,并准确报出"输入没有到达 rtSlot"

    干净检出(git worktree)单独 build + vet + test + e2e  PASS
2026-11-04 08:56:47 +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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