3 个文件全部在 `<module>/test/`,源码目录仍零 `_test.go`。
共 17 条判据,只调导出接口,输入 → 可观察输出。
`internal/kernelmod/pluginhost` 本批跳过:它的 PluginCatalog 只有
`newCatalog` 这个未导出构造,没有对外入口。按「不为测试导出内部」的
规矩,不为它造壳。
## internal/plugins/seq —— Parse / Store
TestParseValidSequence 合法 JSON → 名字/Boot/Groups
TestParseRejectsUnknownField 拼错字段必须报 unknown field
TestParseRejectsInvalidJSON 坏 JSON 报错
TestStoreRoundTrip Save → List/Load → Delete
TestLoadMissingReportsError
TestCheckNewRejectsSelfRecursion #self 调用被拒
TestCheckNewAcceptsValidCall 合法 group 调用通过
**判据写错过三次,都按真实输入契约修正**:
① group 的工具字段叫 `tools` 不叫 `steps`;
② `tools` 在 JSON 里是字符串(若干以 `;` 分隔的 JSON 对象),不是数组;
③ 最后一个工具末尾必须有 `;`。
`CheckNew` 守的是 seq_call 的 target 校验,不是"同名重复",判据按此改。
**还发现一条假绿并修掉**:`TestParseRejectsUnknownField` 第一版只断言
`err != nil`,但输入没带 group —— "没有任何 group"同样会报错,
去掉 `DisallowUnknownFields` 后判据仍绿。改成带合法 group
且断言错误里含 `unknown field`,变异才真红。
## internal/nlp —— 配置 / Extractor
TestDefaultExtractorConfig 默认权重可用
TestSetFusionWeightsRoundTrip 设入 → FusionConfig 读回
TestSetDefaultParserRoundTrip SetDefaultParser → GetDefaultParser
TestExtractEmptyTextReturnsEmptySet
TestExtractNonEmptyTextDoesNotPanic
不带 ONNX 模型时默认 parser 为 nil、`NewExtractor(nil)` 走 fallback,
这是真实契约;判据不要求它非 nil,而是用 stub 验证 Set/Get 往返。
## internal/memory/pipeline —— Distiller
TestAppendThenRecentRecords Append → GetRecentRecords
TestGetRecentRecordsRespectsLimit limit + 取最新 N 条
TestPauseResumeStopped 暂停/恢复可观察
TestStatsIsUsable
TestRawPathIsUnderDataDir
## 变异验证(改回旧实现必须红)
seq 去掉 DisallowUnknownFields → ★ 未知字段被静默接受
nlp SetFusionWeights 丢 alpha → ★ FusionConfig 不符
pipeline Append 不记录 → ★ GetRecentRecords = 0 条
全部还原后复跑全绿。
## 验证
go build ./... PASS
go vet ./... PASS
gofmt -l 干净
python3 .github/scripts/check-ci-gates.py PASS
go test ./... -count=1 35 个测试包 / 100 包无测试 / 0 FAIL
3 个新包 -race 全绿
源码目录 _test.go 0
⚠️ 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 v1.2.0homedno 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.
homedrequires Linux (it relies on fd inheritance and intra-segment offset dereferencing of the shared memory region; seecmd/homed/platform_windows.go). On Windows onlywaiter.exeis built andhomedruns under WSL2 (see Downloads). macOS can buildwaiter/initconfig;homedmust 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.