Expose the LLM token-level streaming deltas (EventReasoningDelta /
EventContentDelta) to every client channel and add user-initiated
interrupt (cancel generation / send interrupt message) to all three
frontends, preserving the existing interrupt-injection semantics.
SDK/events:
- EventReasoningDelta, EventContentDelta constants exported in the
public/internal SDK event alias tables.
CLI plugin:
- handleChat subscribes to both delta events and forwards
reasoning_delta / content_delta JSON frames (channel-filtered);
aggregated reasoning/tool_call/response frames still fire as before.
- New /stop (alias /interrupt) builtin injects an interrupt via
InjectInterrupt(cliSource, cliChannel) - matches interceptLoop
semantics: cancels an active stream and re-injects the message as
a [中断消息] for a restarted turn; with no active LLM it behaves
as a plain input.
Waiter client (line mode + TUI):
- streamRender accumulates delta chunks and redraws the current line;
a reset frame (stream abandoned, e.g. user interrupt) flushes the
partial buffer so the next turn does not concatenate onto stale
content. Aggregated frames terminate the delta line and render the
final text (old servers without deltas behave exactly as before).
- TUI merges content_delta into the in-flight agent message and seals
it (final flag) on response/tool_call/error so subsequent deltas
never append to a finished message.
WebUI:
- SSE handler subscribes to the two delta events but does NOT record
them into the replay ring - reconnection replays only aggregated
events (the final truth), avoiding duplicate delta accumulation.
- POST /api/v1/chat/interrupt calls InjectInterrupt(webui, webui)
with optional message; fronted by a Stop button shown only while
a generation is in flight.
dashboard.html / GUI app.js:
- Stop button next to Send (hidden until chatLoading); interruptChat
POSTs /chat/interrupt. Delta listeners append incrementally;
agent_output (aggregated) now replaces (not appends) the in-flight
content and marks _final; reset frames finalize the partial message.
process.go:
- chatStreamWithFallback preserves the context.Canceled/
DeadlineExceeded contract: a user interrupt returns the canceled
error (never a partial-content success) so the existing continue
branch restarts the turn with the [中断消息]. A reset
EventContentDelta is published so connected clients drop stale
partial renderings before the new turn begins.
Verified: /stop 'msg' via waiter triggers 'interrupt from cli/cli' in
interceptLoop; unit TestChatStreamCancelPreservesInterrupt confirms the
canceled error propagates instead of being swallowed.
Replace the blocking Chat() call in process() with
chatStreamWithFallback: ChatStream first, accumulate chunks, fall back
to non-stream Chat on connect failure or empty-stream failure.
Why: the non-streaming path blocked for the ENTIRE LLM generation (up
to the 180s HTTP timeout). Reasoning models thinking 60-120s plus AUTO
chain failover regularly exceeded it -> context canceled -> full turn
wasted. With streaming the first chunk arrives in ~1-3s and any
flowing token keeps the connection alive; total generation time is no
longer bounded by an overall timeout.
Compatibility (external behavior unchanged):
- process() signature/return values unchanged
- Aggregated events (EventReasoning / EventAgentLLMChain) still fire
once per turn with full text after stream completion - existing
plugin subscribers see identical payloads as before
- New incremental events EventReasoningDelta / EventContentDelta are
additive; old subscribers ignore unknown event types
- Tool execution loop, memory pipeline, stage pipeline untouched
Streaming details:
- Tool call fragments accumulated per OpenAI streaming convention:
id/name arrive on the first fragment, arguments as raw JSON string
shards across fragments; merged and parsed once at stream end
- normalizeStreamToolCalls keeps nameless argument shards (the
non-stream normalizer drops them); ToolCall gains RawArguments to
carry shard text
- Interrupt mid-stream returns partial content instead of discarding
the whole generation
Verified end-to-end against llmsproxy: plain chat streams correctly;
curl confirms tool-call shard wire format ({" + command" + :"date"}
-> {"command":"date"}); unit tests cover shard merging and
content/reasoning accumulation.
Rewrite LuaAdaptedProvider.ChatStream to match the maturity of
llmsproxy's streaming implementation:
HTTP layer:
- Dedicated stream HTTP client with no overall timeout (SSE must not
be cut by the 180s Chat timeout); only a 30s dial timeout
- Uses applyAdapterHeaders (supports build_headers dynamic signing
hook), matching the non-streaming Chat path
Non-200 response handling:
- New TransformError Lua hook (adapter.transform_error) for per-source
protocol knowledge in error messages
- Safe fallback truncation of raw error bodies (prevents HTML dump
leakage to clients)
SSE parsing enhancements:
- parseOpenAICompatibleStreamChunkFull: handles token usage in the
final chunk (prompt_tokens/prompt, total_tokens/total dual keys),
prompt cache detail fields, and empty-string finish_reason filtering
(sensenova sends "" on every chunk)
- Replaced old SSEScanner with bufio.Scanner (larger buffer, fewer
allocations)
Stream integrity:
- errorOnlyChunk detection: holds back the first chunk to reject
degenerate streams (e.g. zen free pool's finish_reason:"network_error"
with empty content) before any byte reaches the caller
- [DONE] dedup: adapters that already emit a terminating done chunk
with the real finish_reason don't get a second reason-less done
- Clean EOF sends a final Done:true if no done was seen
Struct changes:
- StreamChunk: added FinishReason and Usage fields for callers
- LuaAdaptedProvider: added streamClient (lazy) + streamMu
Tested: curl against llmsproxy SSE confirms reasoning_content parsing
is correct (delta.reasoning_content), usage chunk handling works, and
[DONE] termination is properly emitted.
The selfInputCh previously treated ALL internal messages as memory
consolidation tasks (hardcoded _consolidation_ output channel), which
silently discarded child-agent completion notifications:
- processConsolidation never appends to conversation context, so the
parent agent could not see that its child had finished
- it also discards the LLM response without emitting to any output
channel, so nothing reached the user
- net effect: notifications vanished; parent never called child_result
Restore the intended design: each self-input message now carries a
target output channel. Only consolidation tasks (_consolidation_) go
through the no-memory path (no context write, no emit). Child
notifications carry the parent's original output channel and are
processed as normal input: appended to context, LLM sees them and can
call child_result, and the response is emitted back to the user.
Changes:
- new selfInputMsg{text, channel} type + channelConsolidation const
- selfInputCh: chan string -> chan selfInputMsg
- injectSelf (consolidation) keeps _consolidation_; new
injectSelfChannel for flagged messages
- handleSelfInput routes on msg.channel instead of hardcoding
- executeSpawnChild captures a.currentOutputChannel and passes it to
runChildTask so the notification returns to the originating channel
(falls back to "cli" when unset or consolidation)
- executeChildResultTool: remove dead double-lock/re-check block
Verified end-to-end with tmux PTY against llmsproxy:
spawn_child -> child done -> notification processed via normal path
(log shows 'input from system -> response, tools=[child_result]'),
parent agent retrieved the child result successfully.
The local llmsproxy AUTO chain tries 6+ slots across 3 tiers sequentially.
Each failed tier incurs busyWait (2s) + upstream timeout, so a full chain
exhaustion can exceed 120s. The llmsproxy logs showed 143 'context canceled'
errors for the homeagent key — the client gave up before the chain finished.
180s gives the chain enough room to complete before the client timeout fires.
Also remove stale backup files under /usr/local/bin/.
- C ABI invoke_stage 增加 result 输出参数，外部插件 stage 回调可将修改后的
StageContext(RawMessage/LLMText/FinalText/Response/ToolResults) 写回内核
- ABI 标识版本改为字符串 semver 与核心 Version 对齐(ABIVersion="0.9.0")，
C 层协商用派生整数 CABINum=900(major*100+minor)，不再使用独立数字编码
- version_min 保证 v0.8.x(800) 旧插件向后兼容可加载
- 修复工具循环 zen 兼容补位误伤首轮 system 上下文(仅尾部为 assistant/tool 时补位)
- 更新 README 项目状态说明
- Drop skill.NewManager from homed bootstrap; skills dir no longer core-managed
- Remove GetInjectedPrompt system-prompt injection (skills are not first-class)
- Delete internal/skill package, SkillAPI, webui /api/v1/skills, status skills block
- ConfigRegistry: plugin config tables now created only via RegisterDef; arbitrary
scope Set/Get no longer implicitly creates config_<name> tables (fixes stray
config_today_task table from SKILL directory name being used as a scope)
- Six-phase plan complete: webui/cli/healthcheck/pluginmgr/clawhubadapter
now interact with the kernel exclusively via internal/sdk interfaces;
all Configure() calls and package-level global injection removed
- buildSDK in internal/plugin/registry.go is the single assembly point
- Add internal/sdk/events.go exporting event types/constants
- Fix ProviderManager cooldown sharing: LuaAdaptedProvider.Name() now
returns the source name instead of lua_<adapter>, so multiple sources
sharing an adapter (single script load via shared VM AdapterCache) no
longer share failure-cooldown state
- Verified: build/vet/tests green, deployed to homeagent.service with
full plugin capability testing via local OpenAI-compatible mock
- process.go: attach resp.ReasoningContent when building assistant messages
- deepseek.lua v2.1.0: remove last_reasoning closure hack; rely on
core-provided reasoning_content in messages
- openai.lua: strip reasoning_content from messages in transform_request
(not supported by OpenAI API)
- process.go: only emit resp.Content on the first tool call per batch,
subsequent assistant messages use empty content (serialized as null)
- provider.go: MarshalJSON outputs null content when empty with tool_calls
to comply with DeepSeek/OpenAI expected format
- output.go: update parameter interface (payload/type/meta) to match
tool definitions (uncommitted from previous refactor)
- Redesign output_send__ tools: content JSON string -> structured
payload/meta/type params for LLM reliability
- executeOutputSendTool: route by type with capability check
- executeOutputSendHelp: show meta format + type enum
- Updated system prompt rules for new interface
- docToTriples: use jieba exact mode adjacent co-occurrence
- Unify vector space: Doc.Vector field, ContextToDoc vectorizer,
ReindexWithVectorizer on startup
- StaticEmbedder: pre-trained ConceptNet Numberbatch/fastText word embeddings,
auto-download with TF-IDF fallback, comma-separated multi-model paths
- CleanTemplateText: regex stripping of QQ tool call templates and noise
- textForVector: per-source vector strategy (agent→Response, user→Input,
cold_storage→both)
- Indexer.BuildContext and ExtractKeywords now clean input before vectorization
- Protect recent 10 events in Prune (regression fix: use local var not const)
- Output channels generate per-channel tools: output_send__{name} (type=output) + output_send__{name}_help
- content is JSON string transparently passed to plugin handler for routing
- EventAgentLLMChain: full LLM response forwarded after each turn for webui/logs
- sdk.New refactored to SDKConfig struct (no more 13 positional args)
- RegisterOutputChannel adds desc param for JSON format documentation
- channelDevice simplified (no Tools method), desc field added
- Child agent permission updated for output_send__ prefix
- System prompt: output gates, multi-call, long messages split
- WebUI: subscribes to EventAgentLLMChain in SSE, no output channel
- Tests updated for new naming convention
Root node items (items without category) were skipped by depth>0 check,
causing knowledge_list to always return '(空)'. Also simplified formatTree
to avoid redundant child item rendering.
