JianFeeeee 81a0f5f598 feat(security): 插件按工具声明内容策略 + 目录名统一
## 一、插件声明层(用户裁定)

> 「敏感词策略也应该是插件声明啊,每个插件声明自己轮次以及自己工具的
>   敏感词策略」

SecurityProfile 新增两个字段:

  ToolSensitiveWords map[string][]string  // key=工具名模式(尾 *),value=词表
  DetectInjection    bool                 // 开启内核内置注入迹象识别

语义是**追加不覆盖**:整轮 SensitiveWords 仍然生效。
取宽不取窄的理由:当前处置是 B 档(标记+警示,不阻断),
多标一条只是多一句警示,漏标则是安全缺口。

## 二、修掉我自己造的「莲藕式分层」

前一版把 *security.Round 从 runInputTask 一路搬到工具链
(prepareInputTask(evt, round) → TaskFrame.SecRound →
executeToolCallOutcomeWithRound),并在 rtchild 里另补一条。

那是把**分层策略实现成跨层传参**:每多一条工具执行路径就要求调用方
多传一次句柄。profileActivator 的设计注释早就写明了正路:

> 工具调用发生在 LLM 决定之后,此时插件已不在调用栈上。
> 唯一可靠的传递方式是**内核在输入进来时记住**,在该轮的工具判定里使用。

改为 security 自取:

  Runtime.ScanContentForAgent(agentID, isChild, ins, text)
    → ForAgent(agentID, isChild)   // per-agent 视图,天然不串档
    → EffectiveProfile()           // session > longtime
    → 合并 全局词表 + 档位词表 + 工具词表 + DetectInjection

core 只递交**事实**(我是谁 / 哪个工具 / 什么文本),不认识 Round。
与 CheckToolForAgent 同一套身份推断,不引入第二个入口语义。
TaskFrame.SecRound / executeToolCallOutcomeWithRound 全部撤除。

## 三、目录名统一

third_party/homeagent-sdk → third_party/hologramagentsdk

module 与远端仓早已是 hologramagentsdk,只剩物理目录是遗留名。
同步改了 go.mod replace、构建/打包/部署脚本、5 处测试里的分段路径。
注意:这里改的是**主仓 vendored 的 SDK 源码路径**,example/ 由 SDK
独立仓自己跟踪,主仓不涉及。

## 判据

TestToolSensitiveWordsAppendOnlyForThatTool   词表只对目标工具生效 + 追加语义
TestToolSensitiveWordsUseAgentScope           security 按 agent scope 自取生效
(变异验证:删掉 ForAgent 查询 → 红)

## 验证

	go build ./...                 → 0
	go vet ./...                   → 0
	go test ./... -count=1 -race   → 62 ok / 0 FAIL / 0 DATA RACE
	gofmt -l internal/             → 干净
2026-11-03 09:51:11 +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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