Mirrors the feishu one-click flow: scan a QR with the DingTalk app,
approve, and the bot's client_id / client_secret get auto-filled instead
of forcing the user through the open-dev console. Saves about seven
manual steps per channel setup.
Backend
- Bump dingtalk-stream from 1.3.5 to 1.3.12. Diff against the classes we
depend on (OpenDingTalkStreamClient, ChatbotMessage, MessageContent,
GenericEventListener) is empty — pure point-release bumps, no API churn.
- New DingTalkAppRegistrationService: synchronously runs init + begin
against /app/registration/{init,begin} on oapi.dingtalk.com to obtain
the device_code and verification URL, then spawns a daemon worker that
polls /app/registration/poll every 5s until SUCCESS / FAIL / EXPIRED is
returned. Sessions evict after 7 minutes, worker has a 6-minute hard
runtime cap, transient HTTP errors do not terminate the loop. Same
shape as the feishu service, but written from scratch because the
dingtalk-stream SDK doesn't wrap this OAuth device flow.
- Two new endpoints under /api/v1/channels/webhook:
POST /dingtalk/register/begin returns session_id;
GET /dingtalk/register/status returns status + qrcode_img (data URI
PNG, ZXing-encoded from the verification URL, matching the feishu and
weixin flows). Status surface: waiting / confirmed / expired / denied.
Frontend
- channelApi.dingtalkRegisterBegin / dingtalkRegisterStatus.
- New useDingTalkAppRegister composable, structurally identical to
useFeishuAppRegister minus the domain argument. Stops polling on
terminal status, fires onConfirmed with {clientId, clientSecret}.
- ChannelEditModal: dingtalk-register-card rendered when channelType is
dingtalk, scoped DingTalk blue (#1f79ff) to differentiate from feishu's
indigo. onConfirmed writes channelConfig.client_id / client_secret so
the existing form fields update reactively.
- i18n: channels.dingtalkRegister.* keys for title / hint / button states
/ scan / confirmed / expired / denied / startFailed.
Saves the user the entire 'go to the open platform -> create an enterprise
app -> copy App ID and Secret' detour. Click a button in the channel form,
scan the QR code, confirm authorization, credentials are auto-filled.
Backend
- Bump com.larksuite.oapi:oapi-sdk from 2.5.3 to 2.6.1, which adds the
scene/registration package wrapping the device-code flow.
- New FeishuAppRegistrationService: each begin() creates a sessionId,
spawns a worker thread, runs the SDK's blocking RegisterApp.register
with onQRCode and onStatusChange wired into a per-session state machine
(PENDING -> WAITING -> CONFIRMED / EXPIRED / DENIED / ERROR). The
session caches the QR data URI so ZXing only encodes once per attempt.
Sessions evict after 5 minutes so closed browsers don't leak the map.
- Two new webhook endpoints under /api/v1/channels/webhook/feishu:
POST /register/begin returns session_id, GET /register/status returns
status + qrcode_img (data URI base64 PNG, ZXing-encoded from the SDK's
verification URL — the raw URL would render as a broken image, so the
encoding step matches the WeCom flow).
- SDK detail caught the hard way: don't pass .domain() or .larkDomain().
The SDK defaults are accounts.feishu.cn / accounts.larksuite.com (the
registration endpoints). open.feishu.cn is the open-API endpoint, a
completely different service. Passing the wrong one makes the SDK parse
HTML as JSON and emit invalid_response.
Frontend
- channelApi: feishuRegisterBegin / feishuRegisterStatus.
- New useFeishuAppRegister composable: state machine that begins the
session, polls status every 2s, prefers qrcode_img over qrcode_url for
the <img> src, stops on terminal status, fires onConfirmed with
{appId, appSecret}.
- ChannelEditModal: a new feishu-register-card above the wecom one. The
composable's onConfirmed writes channelConfig.app_id / app_secret, so
the existing form fields update reactively.
- i18n: channels.feishuRegister.* keys for title / hint / button states /
scan / confirmed / expired / denied / error.
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.
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.
Full-stack AI assistant built on Spring AI Alibaba.
Features: ReAct Agent, Plan-and-Execute, MCP Protocol, Multi-Model, Multi-Channel.
Apache-2.0 License
