- Extract create/edit modal into ChannelEditModal.vue (defineAsyncComponent),
shrinking Channels.vue from 1438 to 370 lines and dropping ~30KB from the
initial route chunk.
- Move side-effect logic into composables: useWeixinQrcodePoll (QR + 2s status
poll, auto-cleanup) and useWecomBotAuth (lazy SDK script with module-level
promise dedupe). Pure config-JSON helpers move to utils/channelConfigJson.ts.
- Switch i18n locales from static imports to dynamic import keyed by current
locale; applyLocale becomes async to avoid first-render flicker.
- /channels route opts into keep-alive (meta.keepAlive=true). Channels.vue
pauses status polling in onDeactivated and resumes in onActivated, with an
isActive guard to prevent late-resolving timers from leaking after navigation.
- Initial load goes from serial 3-RTT to Promise.all + 4-card el-skeleton.
When SSE setup fails (e.g. workspace permission denied for shared channel
conversations opened from the web console), the failed turn is never
persisted on the backend. Two issues made the failure invisible to the user:
- The fallback errorInfo dropped data.message, so the inline retry card fell
back to the generic "请求过程中遇到了意外问题" template instead of the
actual reason. Carry rawMessage through, and lower the MessageBubble
display threshold from >8 to >3 chars so short-but-informative messages
(7-char Chinese / "Forbidden") aren't filtered out.
- The status-poll loop in useChat overwrote the local-only failed turn
with the server's "no message" view, erasing the inline retry card.
Skip the merge for turns that exist only locally and are in error state,
so the user can still see the failure and retry.
Issue #24: tools selected in the agent binding UI had no effect at runtime.
mate_tool.name stores the Java class name (e.g. "BrowserUseTool") and was
written into mate_agent_tool.tool_name, but AgentToolSet.withAllowedToolsOnly
matched by the @Tool function name (e.g. "browser_use") — so every binding
was silently filtered out.
Fix: AgentToolSet builds an alias index per ToolCallback indexed by every
equivalent identifier — function name, Spring bean name, and Java class
simple name. withAllowedToolsOnly / withDeniedToolsFiltered / excluding
all accept any of these aliases, mirroring how Spring's BeanFactory accepts
bean names + aliases.
ToolRegistry.getEnabledToolSet now threads a bean→beanName resolver into
the new AgentToolSet.fromCallbacks(...) overload. Existing two-arg callers
keep working; tests pass without changes.
Zero data migration: stale mate_agent_tool rows that previously had no
effect now resolve correctly via the class-name alias.
- Reconcile approval status atomically: DB row, message metadata, in-memory store
- Approve and deny both flip the tool-call card + timeline segment to a terminal
state on the gate message — no more orange spinner stuck after a decision
- Frontend hydrate matches by pendingId and reverse-converges to expired so a
refresh after server-side timeout / consume clears the banner without restart
- Stop sweep, GC timeout, and JVM restart all close the loop with consistent
state
- Remove the dead REST /approve endpoint + matching frontend client export so
there is only one resolve path to maintain
Some self-hosted OpenAI-compatible serving frameworks return a 400 Bad Request
with a generic Pydantic "body=None / Field required" error when the outbound
request carries tool_choice="auto" but the server was launched without an
auto-tool-choice opt-in flag. The error message hides the real cause: the
request is rejected at validation time before the body is parsed, so the
upstream client sees only the generic body-missing error.
Per the OpenAI spec, omitting tool_choice when tools is non-empty is
functionally equivalent to "auto" — the server defaults to auto-pick.
Adding a stripAutoToolChoice patcher to the buildOpenAiApi chain:
- changes nothing on compliant servers (OpenAI / DashScope / DeepSeek / Kimi
default to auto when tools are present)
- unblocks strict OpenAI-compatible self-hosted endpoints
Explicit values other than "auto" ({"none", "required", or a function
descriptor}) are passed through unchanged.
Run on both chatCompletionEntity and chatCompletionStream paths so both
buffered and streaming calls benefit.
Three bugs surfaced when a non-admin workspace member opened the channel
admin page:
- vue-i18n "Invalid linked format" when '@' appeared in message strings
without the linked-format escape. Replaced literal '@' with vue-i18n v9
literal interpolation {'@'} in both zh-CN.ts and en-US.ts (6 strings:
QQ guide step3, accessControl requireMention/Tooltip).
- 403 from WorkspaceAccessInterceptor was being treated as 401 by the
axios interceptor and the chat SSE handler, clearing the token and
redirecting to /login. Split the two:
* 401 = authentication failure -> handleAuthFailure (logout)
* 403 = authorization failure -> keep session, surface to caller
Now a member who lacks workspace permission sees a toast instead of
being silently logged out.
- Two backend exception sites threw with the default code=500 for what
is semantically an auth/authz event, contradicting the codes returned
elsewhere for the same business event:
* AuthService.login() bad credentials 500 -> 401
* WorkspaceService.requirePermission() 500 -> 403
This aligns service-layer denials with SecurityConfig (401 for missing
JWT) and WorkspaceAccessInterceptor (403 for permission denied), so
the same business event always produces the same code.
Foundation for the ghost-approval root-cause fix.
Adds ResolveOutcome / MetadataDecision; rewrites ApprovalWorkflowService so
every resolve / consume / timeout / supersede transitions through one
two-phase contract: snapshot → DB UPDATE conditional on status=PENDING →
metadata reconciliation → afterCommit memory mutation. ChatController,
ChannelMessageRouter, and ApprovalController all switch to the workflow;
ApprovalService.resolve / resolveAndConsume / consumeApproved /
cancelStalePending / denyAllByConversation are physically removed so
DB-bypass is no longer reachable at compile time.
Specific fixes:
- recoverFromDb preserves DB pendingId + createdAt (was generating fresh
random ids, breaking every later DB sync)
- effectiveExpireAt = expireAt ?? createdAt + PENDING_TTL: legacy rows
with NULL expireAt no longer resurrect as live PENDING after restart
- markPendingApprovalsResolved flips pendingApproval.status + currentPhase
+ MessageEntity.status atomically (was only flipping the first field;
message.status uses existing completed/stopped, not approved/denied,
to stay within the frontend Message.status union)
- GC scheduler moves to ApprovalWorkflowService; timeouts and overflow
evictions now sync DB + metadata + memory through markTimeout
- DB UPDATE rows=0 returns alreadyResolved (concurrent-resolve safe);
exception propagates so @Transactional rolls back; memory stays untouched
- expireRecoveredRow gates metadata write on DB success (was writing
metadata even when DB update failed, producing the worst-case ghost)
- Mockito JDK 21 agent attach fixed via maven-dependency-plugin properties
+ surefire argLine (no more flaky self-attach across machines)
Tests: 34 new across 4 classes (recovery, resolve, GC, metadata sync).
Full suite: 788 / 788.
The two tools-sync scripts ran on every startup and used H2 MERGE INTO
... KEY(id), which overwrites every column on existing rows. That
silently reverted UI-toggled `enabled` and was the proximate cause of
a recent WriteFileTool/EditFileTool outage.
They were also a strict subset of the fresh-install seed (data-zh.sql /
data-en.sql register all 19 builtins; the sync scripts only 16) and out
of date. Per-tool Flyway migrations (V3, V31) are already the canonical
'register a new builtin' path, so the sync layer was duplicated and
error-prone.
Delete both files and the runToolSyncScript() loader. Tool descriptions
shown to the LLM come from @Tool annotations in code, not the DB row,
so removing per-startup metadata refresh has no functional impact.
Two follow-up improvements on top of renderDocxFromFile so the docx
pipeline can handle real long-form deliverables instead of just
prose-only memos.
Image embedding (P1).
MarkdownDocxRenderer now recognizes single-line  markdown
and embeds the referenced file via POI's XWPFRun.addPicture():
- PNG / JPG / GIF / BMP read straight from disk
- SVG rasterized via Apache Batik (PNGTranscoder, target width 1400px)
before embedding — OOXML stores raster images, so any vector source
needs conversion. Batik runs in-JVM, no rsvg-convert / cairo on host.
- Pictures are pinned to roughly the printable page width (≈ 5.77 in
for A4 minus default 1800-twip margins) and given a 4:3 height
fallback. Mixing images inline with other paragraph text is not
supported by design — the markdown subset assumes one image per
block paragraph. Inline images would require splitting paragraphs
across runs with explicit positioning, well beyond what this
renderer covers.
- Failure modes (missing file, unsupported format, Batik blowing up)
emit an italicised "[image: alt — reason]" placeholder so the rest
of the document still renders; the agent can read its own log to
see why the picture didn't make it.
- Adds two transitive deps via pom: batik-transcoder + batik-codec at
1.18, ~10 MB combined. Worth it given the alternative is shelling
out to system tooling.
Multi-file render (P2-lite).
New tool renderDocxFromFiles(List<String> filePaths, filename, pageSize)
reads several markdown files in order and renders one combined docx.
Lets the agent split a 30-page proposal into cover.md / ch1.md /
ch2.md / appendix.md and produce a single deliverable in one tool
call. Each path goes through WorkspacePathGuard.validatePath; any
empty or unreadable file aborts with a typed error so the agent
fixes its file list before retrying. Files are joined with a blank
line — no separator markup is injected, headings carry over cleanly.
I deliberately did NOT build the heavier mutable-docx state
("appendDocxChapter / finalizeDocx") flavor of P2: the multi-file
form covers the same workflow with no per-conversation state to
clean up, and the agent can iterate by rewriting the chapter file
and re-running the tool. Stateful append can come later if a
streaming use case actually shows up.
renderDocx and renderDocxFromFile @Tool descriptions updated to point
the agent at renderDocxFromFile for >5 KB markdown and to advertise
the new image-embedding capability.
renderDocx requires the markdown body to flow through the LLM as a
tool argument. For an 80 KB project proposal that's ≈ 20 K tokens of
streaming output spent just to repeat back content the model already
wrote to disk a turn earlier — multi-minute generation, real money.
renderDocxFromFile takes a file path instead. The agent uses
write_file / edit_file to assemble the markdown locally, then calls
this tool with just the path. JVM reads the file in one IO syscall
and feeds it to the existing MarkdownDocxRenderer. Token cost drops
from ≈ 20 K to ≈ 50 (the path string).
Behavior:
- Path resolution honors WorkspacePathGuard, same boundary as
read_file / write_file. No path traversal.
- UTF-8 read; rejects empty / missing / non-regular paths with
typed error messages so the agent can recover.
- Output cached in GeneratedFileCache and returned as a relative
/api/v1/files/generated/{id} link, with the same anti-host-
hallucination instruction renderDocx already carries.
- Same supported markdown subset (headings, bold, lists, tables).
Image references () still render as raw text — full
image embedding (P1) and SVG → PNG conversion (also P1) need
Apache Batik plus image-rendering plumbing in MarkdownDocxRenderer
and is tracked separately. Chapter-mode merge (P2) likewise needs
its own plumbing.
The @Tool description tells the agent to prefer this path when
markdown exceeds ~5 KB and shows the full write_file →
renderDocxFromFile workflow inline.
Three small but high-impact fixes that all surfaced together while
verifying the long-form generation flow.
1. ChatConsole onBeforeUnmount no longer kills the backend turn.
Previously, switching tabs / route navigation / any cause that
unmounted the chat view called stopChatGeneration(), which POSTs
/chat/{cid}/stop and aborts the in-flight LLM call. The user
reported a turn dying mid-generation just from switching pages.
Replaced with resetForNewConversation() — front-end SSE disconnect
only, no /stop. Backend keeps running; pollActivity / status probe
reconnects on return. Aligns with the existing comment in
selectConversation: "let A's backend agent run continue running."
2. Agent max_iterations raised 25 → 100 with a hard ceiling.
The previous 25-step ceiling caused LimitExceededNode to fire on
substantive multi-tool tasks (document generation + image conversion
+ retry loops). 100 matches QwenPaw's _MAX_MAX_ITERATIONS upper
bound. New plumbing:
- BaseAgent.MAX_ITERATIONS_HARD_CEILING = 100 public constant
- BaseAgent default field 25 → 100 (Java-side fallback)
- AgentGraphBuilder clamps any per-agent DB override to the
ceiling at runtime; if the row holds 200, runtime sees 100 and
a WARN is logged with the original value.
- V47 migration (h2 + mysql) idempotently bumps the three default
seeded agents (1000000001, 1000000002, 1000000003) only if they
still hold the old defaults (25 / 20). User-customized values
are not touched.
- data-en/zh/-mysql-en/-mysql-zh seed files updated to 100 for
fresh installs.
3. DocxRenderTool tells the LLM not to prepend a host to the URL.
DeepSeek and Claude have both been observed wrapping the
/api/v1/files/generated/{id} relative path returned by renderDocx
into an absolute URL with a hallucinated domain (e.g.
https://ai-tools-system.com/...), breaking the download link in
the rendered chat bubble. The tool's return string now appends an
explicit "must use the relative path verbatim, do not add any
https:// or http:// prefix" instruction, which Claude and
DeepSeek both honor.
A bundle of stability fixes that all surfaced together while running
the same long-form generation task across multiple turns. Each one
addresses a distinct way the previous behavior silently dropped
content the user had already seen on screen.
1. Mid-turn narrative persistence (StateGraphReActAgent +
SummarizingNode). Intermediate ReasoningNode rounds and
SummarizingNode broadcast their content_delta directly to the
SSE channel for live display, but the StreamAccumulator only
received the final answer. After refresh the assistant message
showed only tool_call cards with no body text.
StateGraphReActAgent now also forwards STREAMED_CONTENT (already
set per round) as a persistOnly StreamDelta whenever it changes,
so every narrative chunk lands in the accumulator's content
buffer and gets written to mate_message. SummarizingNode now
writes its summary into the same key so summarize narratives
persist too.
2. Follow-up message queue, not dispose (ChatController#interruptStream).
Sending a new message while a turn was running called
requestInterrupt, which dispose()d the active Reactor chain mid
LLM call. That cancelled the in-flight generation, lost partial
tokens, and left the user staring at a half-finished bubble.
The endpoint now uses enqueueMessage in all paths, matching
the "wait for current turn, then run" behavior. The old
requestInterrupt API is kept for any future force-replace UI
but no caller routes to it.
3. Queued user message ordering (ChatStreamTracker.QueuedInput +
ChatController.startQueuedMessage). interruptStream used to save
the queued user message immediately, before the in-flight
assistant message finalized in doOnError. listMessages orders
by create_time ASC, so the queued user message ended up above
the assistant reply it was supposed to follow. QueuedInput now
carries contentParts; persistence is delayed to startQueuedMessage,
which runs only after Asst-N is on disk.
4. JVM shutdown flush (ChatStreamTracker @PreDestroy +
emergencySaveAccumulator). A mvn spring-boot:run restart used to
wipe in-flight turns: SSE emitter timed out, ShutdownHook fired,
HikariPool closed before doOnError could save. ChatStreamTracker
now exposes an emergency-save callback per RunState; ChatController
registers one per stream that snapshots the accumulator and
writes status="interrupted_shutdown". @PreDestroy walks active
runs, invokes the callback, then disposes. Spring's reverse-order
bean teardown keeps ConversationService and Hikari alive long
enough for the save to complete.
5. Observation thresholds for summarize (GraphObservationProperties +
application.yml). The previous total-chars threshold of 12 KB
triggered summarize after one or two RFC reads, costing a 40 to
80 second compaction LLM call per loop. Tuned to: total 200 KB,
single 16 KB, large-result 32 KB, rounds safety net 25. Java
field defaults reverted to the conservative original values so
application.yml stays the source of truth.
6. Frontend thinking segmentation (useChat.ts thinking_delta +
phase). Multi-round ReAct turns merged every reasoning + summarize
round's thinking into one segment, accumulating to 9 KB+ in a
single bubble. thinking_delta now uses findLast(running) so a
tool_call_started or phase transition closes the previous segment
and the next delta opens a fresh one. phase event also closes
running thinking/content segments.
7. Other small things bundled: removed a debug metadata-keys log
that flooded the log file with one line per stream chunk; fixed
three stale tests that didn't compile after earlier constructor
changes (WikiLogServiceTest, WikiOverviewSpliceTest,
WikiProcessingServiceLazyTest); added rfc-066 documenting the
unified message queue + priority refactor as the next logical
step on top of these stabilizations.
Verified end-to-end with multiple full sessions: a four-minute
generation that produced the expected docx and a follow-up enqueue
that ran cleanly after the previous turn naturally completed,
without the old "Disposable unavailable" interrupt path.
Same bug as the prior queue-drop fix in doOnComplete, but in the
sister branch that fires when the agent's reactive stream errors
out (CancellationException from a user stop). The guard
cr.queuedInput() != null && !(isUserStop && !isInterruptFollowup)
mis-classified "user stopped, no interrupt-with-followup, but a
message is in the queue" as an explicit abort and silently dropped
the freshly-typed follow-up.
The frontend's enqueue path never sets interruptType — it just
calls requestStop + offers to messageQueue. Whoever puts a message
in the queue means it; just run it. Aligns with doOnComplete and
the four other queue-launch sites in this controller.
A series of cross-cutting stability fixes that surfaced together
during a long debugging session.
reasoning_content / Claude prefill self-replicating 400:
- ChatController persists typed errors (content starts with '[错误] ')
with status='error', so the failure text stops being re-sent as
multi-turn context — DeepSeek thinking 400 ('reasoning_content
must be passed back') and Claude 400 ('does not support assistant
message prefill') used to recursively re-create themselves every
retry by polluting history.
- BaseAgent.sanitizeForLlm filters status='error' / '[错误] ' prefix
assistant messages from history before LLM dispatch.
- BaseAgent.fetchHistoryMessages defensively drops trailing
AssistantMessages — Claude rejects assistant-tail prompts.
- NodeStreamingChatHelper.dropTrailingAssistant runs the same
defense at every doStreamCall pre-egress, so the in-turn
summarizing→reasoning transition (which leaves an assistant
scaffold at the tail) doesn't trip Claude either.
- AgentGraphBuilder.FallbackPolicy.DEEPSEEK switched (null,true,true)
→ (' ',false,true), aligning with KIMI/OPENAI's tolerant ' '
fallback. The previous 'force explicit 400' design was the
self-replicating loop's prime mover.
narration + tool args truncation:
- ReasoningNode.DEFAULT_MAX_OUTPUT_TOKENS 4096 → 16384. The 4k cap
was decapitating renderDocx tool_call args mid-stream when the
model emitted a long content field on top of thinking content;
the resulting 'invalid JSON' aborted execution silently.
- ReasoningNode appends a hermes-style TOOL_USE_ENFORCEMENT clause
to every system prompt: 'when you say you will perform an action,
call the tool now in the same response — narration is a protocol
violation'. Treats 'now I will generate the docx' (and never
actually calling renderDocx) as a forbidden pattern.
- ToolExecutionExecutor.normalizeToolExecutionError reframes the
JSON-truncated error as actionable instructions: 're-call the
same tool now with shorter content or split into multiple
sequential calls; do NOT describe the result as text'.
side fixes from the same evening:
- ChatController doOnComplete skips completionPublisher.publish
when isError=true, keeping memory extraction off the garbage path.
- ChatController doOnComplete queued-message guard simplified to
'cr.queuedInput() != null', matching the other 4 sites in the
controller. The previous 'isInterruptFollowup || !wasStopped'
guard silently dropped queued messages when the user did
Stop-then-Enqueue (wasStopped=true && interruptType=null), losing
the freshly-typed follow-up message.
- prompts/graph/summarize-system.txt now distinguishes 'single
task' (default; output one cohesive summary) from 'multiple
independent sub-tasks' (use the子任务 N format). Stops the
summarizer from inventing '子任务 1: PRO-027' decomposition for
unitary requests like 'write me a project proposal'.
